Simulation of pseudo-CT images based on deformable image registration of ultrasound images: A proof of concept for transabdominal ultrasound imaging of the prostate during radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meer, Skadi van der; Camps, Saskia M.; Oncology Solutions Department, Philips Research, High Tech Campus 34, Eindhoven 5656 AE

Purpose: Imaging of patient anatomy during treatment is a necessity for position verification and for adaptive radiotherapy based on daily dose recalculation. Ultrasound (US) image guided radiotherapy systems are currently available to collect US images at the simulation stage (US{sub sim}), coregistered with the simulation computed tomography (CT), and during all treatment fractions. The authors hypothesize that a deformation field derived from US-based deformable image registration can be used to create a daily pseudo-CT (CT{sub ps}) image that is more representative of the patients’ geometry during treatment than the CT acquired at simulation stage (CT{sub sim}). Methods: The three prostatemore » patients, considered to evaluate this hypothesis, had coregistered CT and US scans on various days. In particular, two patients had two US–CT datasets each and the third one had five US–CT datasets. Deformation fields were computed between pairs of US images of the same patient and then applied to the corresponding US{sub sim} scan to yield a new deformed CT{sub ps} scan. The original treatment plans were used to recalculate dose distributions in the simulation, deformed and ground truth CT (CT{sub gt}) images to compare dice similarity coefficients, maximum absolute distance, and mean absolute distance on CT delineations and gamma index (γ) evaluations on both the Hounsfield units (HUs) and the dose. Results: In the majority, deformation did improve the results for all three evaluation methods. The change in gamma failure for dose (γ{sub Dose}, 3%, 3 mm) ranged from an improvement of 11.2% in the prostate volume to a deterioration of 1.3% in the prostate and bladder. The change in gamma failure for the CT images (γ{sub CT}, 50 HU, 3 mm) ranged from an improvement of 20.5% in the anus and rectum to a deterioration of 3.2% in the prostate. Conclusions: This new technique may generate CT{sub ps} images that are more representative of the actual patient anatomy than the CT{sub sim} scan.« less

A computed tomography-based spatial normalization for the analysis of [18F] fluorodeoxyglucose positron emission tomography of the brain.

PubMed

Cho, Hanna; Kim, Jin Su; Choi, Jae Yong; Ryu, Young Hoon; Lyoo, Chul Hyoung

2014-01-01

We developed a new computed tomography (CT)-based spatial normalization method and CT template to demonstrate its usefulness in spatial normalization of positron emission tomography (PET) images with [(18)F] fluorodeoxyglucose (FDG) PET studies in healthy controls. Seventy healthy controls underwent brain CT scan (120 KeV, 180 mAs, and 3 mm of thickness) and [(18)F] FDG PET scans using a PET/CT scanner. T1-weighted magnetic resonance (MR) images were acquired for all subjects. By averaging skull-stripped and spatially-normalized MR and CT images, we created skull-stripped MR and CT templates for spatial normalization. The skull-stripped MR and CT images were spatially normalized to each structural template. PET images were spatially normalized by applying spatial transformation parameters to normalize skull-stripped MR and CT images. A conventional perfusion PET template was used for PET-based spatial normalization. Regional standardized uptake values (SUV) measured by overlaying the template volume of interest (VOI) were compared to those measured with FreeSurfer-generated VOI (FSVOI). All three spatial normalization methods underestimated regional SUV values by 0.3-20% compared to those measured with FSVOI. The CT-based method showed slightly greater underestimation bias. Regional SUV values derived from all three spatial normalization methods were correlated significantly (p < 0.0001) with those measured with FSVOI. CT-based spatial normalization may be an alternative method for structure-based spatial normalization of [(18)F] FDG PET when MR imaging is unavailable. Therefore, it is useful for PET/CT studies with various radiotracers whose uptake is expected to be limited to specific brain regions or highly variable within study population.

Evaluation of portable CT scanners for otologic image-guided surgery

PubMed Central

Balachandran, Ramya; Schurzig, Daniel; Fitzpatrick, J Michael; Labadie, Robert F

2011-01-01

Purpose Portable CT scanners are beneficial for diagnosis in the intensive care unit, emergency room, and operating room. Portable fixed-base versus translating-base CT systems were evaluated for otologic image-guided surgical (IGS) applications based on geometric accuracy and utility for percutaneous cochlear implantation. Methods Five cadaveric skulls were fitted with fiducial markers and scanned using both a translating-base, 8-slice CT scanner (CereTom®) and a fixed-base, flat-panel, volume-CT (fpVCT) scanner (Xoran xCAT®). Images were analyzed for: (a) subjective quality (i.e. noise), (b) consistency of attenuation measurements (Hounsfield units) across similar tissue, and (c) geometric accuracy of fiducial marker positions. The utility of these scanners in clinical IGS cases was tested. Results Five cadaveric specimens were scanned using each of the scanners. The translating-base, 8-slice CT scanner had spatially consistent Hounsfield units, and the image quality was subjectively good. However, because of movement variations during scanning, the geometric accuracy of fiducial marker positions was low. The fixed-base, fpVCT system had high spatial resolution, but the images were noisy and had spatially inconsistent attenuation measurements; while the geometric representation of the fiducial markers was highly accurate. Conclusion Two types of portable CT scanners were evaluated for otologic IGS. The translating-base, 8-slice CT scanner provided better image quality than a fixed-base, fpVCT scanner. However, the inherent error in three-dimensional spatial relationships by the translating-based system makes it suboptimal for otologic IGS use. PMID:21779768

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Shuai; Yu, Lifeng; Wang, Jia

Purpose: Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Methods: Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i)more » numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. Results: The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Conclusions: Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.« less

Optimization of the scan protocols for CT-based material extraction in small animal PET/CT studies

NASA Astrophysics Data System (ADS)

Yang, Ching-Ching; Yu, Jhih-An; Yang, Bang-Hung; Wu, Tung-Hsin

2013-12-01

We investigated the effects of scan protocols on CT-based material extraction to minimize radiation dose while maintaining sufficient image information in small animal studies. The phantom simulation experiments were performed with the high dose (HD), medium dose (MD) and low dose (LD) protocols at 50, 70 and 80 kVp with varying mA s. The reconstructed CT images were segmented based on Hounsfield unit (HU)-physical density (ρ) calibration curves and the dual-energy CT-based (DECT) method. Compared to the (HU;ρ) method performed on CT images acquired with the 80 kVp HD protocol, a 2-fold improvement in segmentation accuracy and a 7.5-fold reduction in radiation dose were observed when the DECT method was performed on CT images acquired with the 50/80 kVp LD protocol, showing the possibility to reduce radiation dose while achieving high segmentation accuracy.

A combined learning algorithm for prostate segmentation on 3D CT images.

PubMed

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei

2017-11-01

Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentation method is proposed for the prostate on three-dimensional (3D) CT images. We combine population-based and patient-based learning methods for segmenting the prostate on CT images. Population data can provide useful information to guide the segmentation processing. Because of inter-patient variations, patient-specific information is particularly useful to improve the segmentation accuracy for an individual patient. In this study, we combine a population learning method and a patient-specific learning method to improve the robustness of prostate segmentation on CT images. We train a population model based on the data from a group of prostate patients. We also train a patient-specific model based on the data of the individual patient and incorporate the information as marked by the user interaction into the segmentation processing. We calculate the similarity between the two models to obtain applicable population and patient-specific knowledge to compute the likelihood of a pixel belonging to the prostate tissue. A new adaptive threshold method is developed to convert the likelihood image into a binary image of the prostate, and thus complete the segmentation of the gland on CT images. The proposed learning-based segmentation algorithm was validated using 3D CT volumes of 92 patients. All of the CT image volumes were manually segmented independently three times by two, clinically experienced radiologists and the manual segmentation results served as the gold standard for evaluation. The experimental results show that the segmentation method achieved a Dice similarity coefficient of 87.18 ± 2.99%, compared to the manual segmentation. By combining the population learning and patient-specific learning methods, the proposed method is effective for segmenting the prostate on 3D CT images. The prostate CT segmentation method can be used in various applications including volume measurement and treatment planning of the prostate. © 2017 American Association of Physicists in Medicine.

Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

PubMed

Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

2012-01-01

Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images. Copyright © 2011 Elsevier Ltd. All rights reserved.

A registration-based segmentation method with application to adiposity analysis of mice microCT images

NASA Astrophysics Data System (ADS)

Bai, Bing; Joshi, Anand; Brandhorst, Sebastian; Longo, Valter D.; Conti, Peter S.; Leahy, Richard M.

2014-04-01

Obesity is a global health problem, particularly in the U.S. where one third of adults are obese. A reliable and accurate method of quantifying obesity is necessary. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) are two measures of obesity that reflect different associated health risks, but accurate measurements in humans or rodent models are difficult. In this paper we present an automatic, registration-based segmentation method for mouse adiposity studies using microCT images. We co-register the subject CT image and a mouse CT atlas. Our method is based on surface matching of the microCT image and an atlas. Surface-based elastic volume warping is used to match the internal anatomy. We acquired a whole body scan of a C57BL6/J mouse injected with contrast agent using microCT and created a whole body mouse atlas by manually delineate the boundaries of the mouse and major organs. For method verification we scanned a C57BL6/J mouse from the base of the skull to the distal tibia. We registered the obtained mouse CT image to our atlas. Preliminary results show that we can warp the atlas image to match the posture and shape of the subject CT image, which has significant differences from the atlas. We plan to use this software tool in longitudinal obesity studies using mouse models.

Automated movement correction for dynamic PET/CT images: evaluation with phantom and patient data.

PubMed

Ye, Hu; Wong, Koon-Pong; Wardak, Mirwais; Dahlbom, Magnus; Kepe, Vladimir; Barrio, Jorge R; Nelson, Linda D; Small, Gary W; Huang, Sung-Cheng

2014-01-01

Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers.

Automated Movement Correction for Dynamic PET/CT Images: Evaluation with Phantom and Patient Data

PubMed Central

Ye, Hu; Wong, Koon-Pong; Wardak, Mirwais; Dahlbom, Magnus; Kepe, Vladimir; Barrio, Jorge R.; Nelson, Linda D.; Small, Gary W.; Huang, Sung-Cheng

2014-01-01

Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers. PMID:25111700

Development of CT and 3D-CT Using Flat Panel Detector Based Real-Time Digital Radiography System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ravindran, V. R.; Sreelakshmi, C.; Vibin

2008-09-26

The application of Digital Radiography in the Nondestructive Evaluation (NDE) of space vehicle components is a recent development in India. A Real-time DR system based on amorphous silicon Flat Panel Detector has been developed for the NDE of solid rocket motors at Rocket Propellant Plant of VSSC in a few years back. The technique has been successfully established for the nondestructive evaluation of solid rocket motors. The DR images recorded for a few solid rocket specimens are presented in the paper. The Real-time DR system is capable of generating sufficient digital X-ray image data with object rotation for the CTmore » image reconstruction. In this paper the indigenous development of CT imaging based on the Realtime DR system for solid rocket motor is presented. Studies are also carried out to generate 3D-CT image from a set of adjacent CT images of the rocket motor. The capability of revealing the spatial location and characterisation of defect is demonstrated by the CT and 3D-CT images generated.« less

Carbon nanotube based respiratory gated micro-CT imaging of a murine model of lung tumors with optical imaging correlation

NASA Astrophysics Data System (ADS)

Burk, Laurel M.; Lee, Yueh Z.; Heathcote, Samuel; Wang, Ko-han; Kim, William Y.; Lu, Jianping; Zhou, Otto

2011-03-01

Current optical imaging techniques can successfully measure tumor load in murine models of lung carcinoma but lack structural detail. We demonstrate that respiratory gated micro-CT imaging of such models gives information about structure and correlates with tumor load measurements by optical methods. Four mice with multifocal, Kras-induced tumors expressing firefly luciferase were imaged against four controls using both optical imaging and respiratory gated micro-CT. CT images of anesthetized animals were acquired with a custom CNT-based system using 30 ms x-ray pulses during peak inspiration; respiration motion was tracked with a pressure sensor beneath each animal's abdomen. Optical imaging based on the Luc+ signal correlating with tumor load was performed on a Xenogen IVIS Kinetix. Micro-CT images were post-processed using Osirix, measuring lung volume with region growing. Diameters of the largest three tumors were measured. Relationships between tumor size, lung volumes, and optical signal were compared. CT images and optical signals were obtained for all animals at two time points. In all lobes of the Kras+ mice in all images, tumors were visible; the smallest to be readily identified measured approximately 300 microns diameter. CT-derived tumor volumes and optical signals related linearly, with r=0.94 for all animals. When derived for only tumor bearing animals, r=0.3. The trend of each individual animal's optical signal tracked correctly based on the CT volumes. Interestingly, lung volumes also correlated positively with optical imaging data and tumor volume burden, suggesting active remodeling.

Noise reduction in spectral CT: reducing dose and breaking the trade-off between image noise and energy bin selection.

PubMed

Leng, Shuai; Yu, Lifeng; Wang, Jia; Fletcher, Joel G; Mistretta, Charles A; McCollough, Cynthia H

2011-09-01

Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i) numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.

Blind CT image quality assessment via deep learning strategy: initial study

NASA Astrophysics Data System (ADS)

Li, Sui; He, Ji; Wang, Yongbo; Liao, Yuting; Zeng, Dong; Bian, Zhaoying; Ma, Jianhua

2018-03-01

Computed Tomography (CT) is one of the most important medical imaging modality. CT images can be used to assist in the detection and diagnosis of lesions and to facilitate follow-up treatment. However, CT images are vulnerable to noise. Actually, there are two major source intrinsically causing the CT data noise, i.e., the X-ray photo statistics and the electronic noise background. Therefore, it is necessary to doing image quality assessment (IQA) in CT imaging before diagnosis and treatment. Most of existing CT images IQA methods are based on human observer study. However, these methods are impractical in clinical for their complex and time-consuming. In this paper, we presented a blind CT image quality assessment via deep learning strategy. A database of 1500 CT images is constructed, containing 300 high-quality images and 1200 corresponding noisy images. Specifically, the high-quality images were used to simulate the corresponding noisy images at four different doses. Then, the images are scored by the experienced radiologists by the following attributes: image noise, artifacts, edge and structure, overall image quality, and tumor size and boundary estimation with five-point scale. We trained a network for learning the non-liner map from CT images to subjective evaluation scores. Then, we load the pre-trained model to yield predicted score from the test image. To demonstrate the performance of the deep learning network in IQA, correlation coefficients: Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are utilized. And the experimental result demonstrate that the presented deep learning based IQA strategy can be used in the CT image quality assessment.

Prediction of CT Substitutes from MR Images Based on Local Diffeomorphic Mapping for Brain PET Attenuation Correction.

PubMed

Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

2016-10-01

Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no image segmentation or accurate registration is required. Our method demonstrates superior performance in CT prediction and PET reconstruction compared with competing methods. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: a digital phantom study.

PubMed

Bernatowicz, K; Keall, P; Mishra, P; Knopf, A; Lomax, A; Kipritidis, J

2015-01-01

Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CT can significantly reduce lung imaging artifacts. Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) "conventional" 4D CT that uses a constant imaging and couch-shift frequency, (ii) "beam paused" 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) "respiratory-gated" 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm(3) spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10(-19)). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%-1.4%), false positives (4.0%-2.6%), and false negatives (2.7%-1.3%). These percentage reductions correspond to gating reducing image artifacts by 24-90 cm(3) of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm(3) of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

PubMed

Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

2017-07-01

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

PubMed

Han, Dongfeng; Bayouth, John; Song, Qi; Taurani, Aakant; Sonka, Milan; Buatti, John; Wu, Xiaodong

2011-01-01

Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we have proposed a general framework to use both PET and CT images simultaneously for tumor segmentation. Our method utilizes the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Markov Random Field (MRF) based segmentation of the image pair with a regularized term that penalizes the segmentation difference between PET and CT. Our method simulates the clinical practice of delineating tumor simultaneously using both PET and CT, and is able to concurrently segment tumor from both modalities, achieving globally optimal solutions in low-order polynomial time by a single maximum flow computation. The method was evaluated on clinically relevant tumor segmentation problems. The results showed that our method can effectively make use of both PET and CT image information, yielding segmentation accuracy of 0.85 in Dice similarity coefficient and the average median hausdorff distance (HD) of 6.4 mm, which is 10% (resp., 16%) improvement compared to the graph cuts method solely using the PET (resp., CT) images.

SU-E-J-240: The Impact On Clinical Dose-Distributions When Using MR-Images Registered with Stereotactic CT-Images in Gamma Knife Radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benmakhlouf, H; Kraepelien, T; Forander, P

2014-06-01

Purpose: Most Gamma knife treatments are based solely on MR-images. However, for fractionated treatments and to implement TPS dose calculations that require electron densities, CT image data is essential. The purpose of this work is to assess the dosimetric effects of using MR-images registered with stereotactic CT-images in Gamma knife treatments. Methods: Twelve patients treated for vestibular schwannoma with Gamma Knife Perfexion (Elekta Instruments, Sweden) were selected for this study. The prescribed doses (12 Gy to periphery) were delivered based on the conventional approach of using stereotactic MR-images only. These plans were imported into stereotactic CT-images (by registering MR-images withmore » stereotactic CT-images using the Leksell gamma plan registration software). The dose plans, for each patient, are identical in both cases except for potential rotations and translations resulting from the registration. The impact of the registrations was assessed by an algorithm written in Matlab. The algorithm compares the dose-distributions voxel-by-voxel between the two plans, calculates the full dose coverage of the target (treated in the conventional approach) achieved by the CT-based plan, and calculates the minimum dose delivered to the target (treated in the conventional approach) achieved by the CT-based plan. Results: The mean dose difference between the plans was 0.2 Gy to 0.4 Gy (max 4.5 Gy) whereas between 89% and 97% of the target (treated in the conventional approach) received the prescribed dose, by the CT-plan. The minimum dose to the target (treated in the conventional approach) given by the CT-based plan was between 7.9 Gy and 10.7 Gy (compared to 12 Gy in the conventional treatment). Conclusion: The impact of using MR-images registered with stereotactic CT-images has successfully been compared to conventionally delivered dose plans showing significant differences between the two. Although CTimages have been implemented clinically; the effect of the registration has not been fully investigated.« less

Comparison of 3D bone models of the knee joint derived from CT and 3T MR imaging.

PubMed

Neubert, Aleš; Wilson, Katharine J; Engstrom, Craig; Surowiec, Rachel K; Paproki, Anthony; Johnson, Nicholas; Crozier, Stuart; Fripp, Jurgen; Ho, Charles P

2017-08-01

To examine whether magnetic resonance (MR) imaging can offer a viable alternative to computed tomography (CT) based 3D bone modeling. CT and MR (SPACE, TrueFISP, VIBE) images were acquired from the left knee joint of a fresh-frozen cadaver. The distal femur, proximal tibia, proximal fibula and patella were manually segmented from the MR and CT examinations. The MR bone models obtained from manual segmentations of all three sequences were compared to CT models using a similarity measure based on absolute mesh differences. The average absolute distance between the CT and the various MR-based bone models were all below 1mm across all bones. The VIBE sequence provided the best agreement with the CT model, followed by the SPACE, then the TrueFISP data. The most notable difference was for the proximal tibia (VIBE 0.45mm, SPACE 0.82mm, TrueFISP 0.83mm). The study indicates that 3D MR bone models may offer a feasible alternative to traditional CT-based modeling. A single radiological examination using the MR imaging would allow simultaneous assessment of both bones and soft-tissues, providing anatomically comprehensive joint models for clinical evaluation, without the ionizing radiation of CT imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Algorithm for lung cancer detection based on PET/CT images

NASA Astrophysics Data System (ADS)

Saita, Shinsuke; Ishimatsu, Keita; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Ohtsuka, Hideki; Nishitani, Hiromu; Ohmatsu, Hironobu; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2009-02-01

The five year survival rate of the lung cancer is low with about twenty-five percent. In addition it is an obstinate lung cancer wherein three out of four people die within five years. Then, the early stage detection and treatment of the lung cancer are important. Recently, we can obtain CT and PET image at the same time because PET/CT device has been developed. PET/CT is possible for a highly accurate cancer diagnosis because it analyzes quantitative shape information from CT image and FDG distribution from PET image. However, neither benign-malignant classification nor staging intended for lung cancer have been established still enough by using PET/CT images. In this study, we detect lung nodules based on internal organs extracted from CT image, and we also develop algorithm which classifies benignmalignant and metastatic or non metastatic lung cancer using lung structure and FDG distribution(one and two hour after administering FDG). We apply the algorithm to 59 PET/CT images (malignant 43 cases [Ad:31, Sq:9, sm:3], benign 16 cases) and show the effectiveness of this algorithm.

Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information

NASA Astrophysics Data System (ADS)

Lee, Duhgoon; Nam, Woo Hyun; Lee, Jae Young; Ra, Jong Beom

2011-01-01

In order to utilize both ultrasound (US) and computed tomography (CT) images of the liver concurrently for medical applications such as diagnosis and image-guided intervention, non-rigid registration between these two types of images is an essential step, as local deformation between US and CT images exists due to the different respiratory phases involved and due to the probe pressure that occurs in US imaging. This paper introduces a voxel-based non-rigid registration algorithm between the 3D B-mode US and CT images of the liver. In the proposed algorithm, to improve the registration accuracy, we utilize the surface information of the liver and gallbladder in addition to the information of the vessels inside the liver. For an effective correlation between US and CT images, we treat those anatomical regions separately according to their characteristics in US and CT images. Based on a novel objective function using a 3D joint histogram of the intensity and gradient information, vessel-based non-rigid registration is followed by surface-based non-rigid registration in sequence, which improves the registration accuracy. The proposed algorithm is tested for ten clinical datasets and quantitative evaluations are conducted. Experimental results show that the registration error between anatomical features of US and CT images is less than 2 mm on average, even with local deformation due to different respiratory phases and probe pressure. In addition, the lesion registration error is less than 3 mm on average with a maximum of 4.5 mm that is considered acceptable for clinical applications.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Metal artifact reduction through MVCBCT and kVCT in radiotherapy

NASA Astrophysics Data System (ADS)

Liugang, Gao; Hongfei, Sun; Xinye, Ni; Mingming, Fang; Zheng, Cao; Tao, Lin

2016-11-01

This study proposes a new method for removal of metal artifacts from megavoltage cone beam computed tomography (MVCBCT) and kilovoltage CT (kVCT) images. Both images were combined to obtain prior image, which was forward projected to obtain surrogate data and replace metal trace in the uncorrected kVCT image. The corrected image was then reconstructed through filtered back projection. A similar radiotherapy plan was designed using the theoretical CT image, the uncorrected kVCT image, and the corrected image. The corrected images removed most metal artifacts, and the CT values were accurate. The corrected image also distinguished the hollow circular hole at the center of the metal. The uncorrected kVCT image did not display the internal structure of the metal, and the hole was misclassified as metal portion. Dose distribution calculated based on the corrected image was similar to that based on the theoretical CT image. The calculated dose distribution also evidently differed between the uncorrected kVCT image and the theoretical CT image. The use of the combined kVCT and MVCBCT to obtain the prior image can distinctly improve the quality of CT images containing large metal implants.

Assessment of body fat based on potential function clustering segmentation of computed tomography images

NASA Astrophysics Data System (ADS)

Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong

2005-01-01

In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.

MRI for the detection of calcific features of vertebral haemangioma.

PubMed

Bender, Y Y; Böker, S M; Diederichs, G; Walter, T; Wagner, M; Fallenberg, E; Liebig, T; Rickert, M; Hamm, B; Makowski, M R

2017-08-01

To evaluate the diagnostic performance of susceptibility-weighted-magnetic-resonance imaging (SW-MRI) for the detection of vertebral haemangiomas (VHs) compared to T1/T2-weighted MRI sequences, radiographs, and computed tomography (CT). The study was approved by the local ethics review board. An SW-MRI sequence was added to the clinical spine imaging protocol. The image-based diagnosis of 56 VHs in 46 patients was established using T1/T2 MRI in combination with radiography/CT as the reference standard. VHs were assessed based on T1/T2-weighted MRI images alone and in combination with SW-MRI, while radiographs/CT images were excluded from the analysis. Fifty-one of 56 VHs could be identified on T1/T2 MRI images alone, if radiographs/CT images were excluded from analysis. In five cases (9.1%), additional radiographs/CT images were required for the imaging-based diagnosis. If T1/T2 and SW-MRI images were used in combination, all VHs could be diagnosed, without the need for radiography/CT. Size measurements revealed a close correlation between CT and SW-MRI (R 2 =0.94; p<0.05). This study demonstrates that SW-MRI enables reliable detection of the typical calcified features of VHs. This is of importance for routine MRI of the spine, as the use of additional CT/radiography can be minimized. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Determination of CT number and density profile of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using computed tomography imaging and electron density phantom

NASA Astrophysics Data System (ADS)

Yusof, Mohd Fahmi Mohd; Hamid, Puteri Nor Khatijah Abdul; Bauk, Sabar; Hashim, Rokiah; Tajuddin, Abdul Aziz

2015-04-01

Plug density phantoms were constructed in accordance to CT density phantom model 062M CIRS using binderless, pre-treated and tannin-based Rhizophora Spp. particleboards. The Rhizophora Spp. plug phantoms were scanned along with the CT density phantom using Siemens Somatom Definition AS CT scanner at three CT energies of 80, 120 and 140 kVp. 15 slices of images with 1.0 mm thickness each were taken from the central axis of CT density phantom for CT number and CT density profile analysis. The values were compared to water substitute plug phantom from the CT density phantom. The tannin-based Rhizophora Spp. gave the nearest value of CT number to water substitute at 80 and 120 kVp CT energies with χ2 value of 0.011 and 0.014 respectively while the binderless Rhizphora Spp. gave the nearest CT number to water substitute at 140 kVp CT energy with χ2 value of 0.023. The tannin-based Rhizophora Spp. gave the nearest CT density profile to water substitute at all CT energies. This study indicated the suitability of Rhizophora Spp. particleboard as phantom material for the use in CT imaging studies.

Determination of CT number and density profile of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using computed tomography imaging and electron density phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yusof, Mohd Fahmi Mohd, E-mail: mfahmi@usm.my; Hamid, Puteri Nor Khatijah Abdul; Tajuddin, Abdul Aziz

2015-04-29

Plug density phantoms were constructed in accordance to CT density phantom model 062M CIRS using binderless, pre-treated and tannin-based Rhizophora Spp. particleboards. The Rhizophora Spp. plug phantoms were scanned along with the CT density phantom using Siemens Somatom Definition AS CT scanner at three CT energies of 80, 120 and 140 kVp. 15 slices of images with 1.0 mm thickness each were taken from the central axis of CT density phantom for CT number and CT density profile analysis. The values were compared to water substitute plug phantom from the CT density phantom. The tannin-based Rhizophora Spp. gave the nearest valuemore » of CT number to water substitute at 80 and 120 kVp CT energies with χ{sup 2} value of 0.011 and 0.014 respectively while the binderless Rhizphora Spp. gave the nearest CT number to water substitute at 140 kVp CT energy with χ{sup 2} value of 0.023. The tannin-based Rhizophora Spp. gave the nearest CT density profile to water substitute at all CT energies. This study indicated the suitability of Rhizophora Spp. particleboard as phantom material for the use in CT imaging studies.« less

Registration of PET and CT images based on multiresolution gradient of mutual information demons algorithm for positioning esophageal cancer patients.

PubMed

Jin, Shuo; Li, Dengwang; Wang, Hongjun; Yin, Yong

2013-01-07

Accurate registration of 18F-FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from (18)F-FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information-based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application.

Registration of PET and CT images based on multiresolution gradient of mutual information demons algorithm for positioning esophageal cancer patients

PubMed Central

Jin, Shuo; Li, Dengwang; Yin, Yong

2013-01-01

Accurate registration of  18F−FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from  18F−FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information‐based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application. PACS numbers: 87.57.nj, 87.57.Q‐, 87.57.uk PMID:23318381

A minimum spanning forest based classification method for dedicated breast CT images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei, E-mail: bfei@emory.edu

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting modelmore » used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.« less

Investigation of four-dimensional computed tomography-based pulmonary ventilation imaging in patients with emphysematous lung regions

NASA Astrophysics Data System (ADS)

Yamamoto, Tokihiro; Kabus, Sven; Klinder, Tobias; Lorenz, Cristian; von Berg, Jens; Blaffert, Thomas; Loo, Billy W., Jr.; Keall, Paul J.

2011-04-01

A pulmonary ventilation imaging technique based on four-dimensional (4D) computed tomography (CT) has advantages over existing techniques. However, physiologically accurate 4D-CT ventilation imaging has not been achieved in patients. The purpose of this study was to evaluate 4D-CT ventilation imaging by correlating ventilation with emphysema. Emphysematous lung regions are less ventilated and can be used as surrogates for low ventilation. We tested the hypothesis: 4D-CT ventilation in emphysematous lung regions is significantly lower than in non-emphysematous regions. Four-dimensional CT ventilation images were created for 12 patients with emphysematous lung regions as observed on CT, using a total of four combinations of two deformable image registration (DIR) algorithms: surface-based (DIRsur) and volumetric (DIRvol), and two metrics: Hounsfield unit (HU) change (VHU) and Jacobian determinant of deformation (VJac), yielding four ventilation image sets per patient. Emphysematous lung regions were detected by density masking. We tested our hypothesis using the one-tailed t-test. Visually, different DIR algorithms and metrics yielded spatially variant 4D-CT ventilation images. The mean ventilation values in emphysematous lung regions were consistently lower than in non-emphysematous regions for all the combinations of DIR algorithms and metrics. VHU resulted in statistically significant differences for both DIRsur (0.14 ± 0.14 versus 0.29 ± 0.16, p = 0.01) and DIRvol (0.13 ± 0.13 versus 0.27 ± 0.15, p < 0.01). However, VJac resulted in non-significant differences for both DIRsur (0.15 ± 0.07 versus 0.17 ± 0.08, p = 0.20) and DIRvol (0.17 ± 0.08 versus 0.19 ± 0.09, p = 0.30). This study demonstrated the strong correlation between the HU-based 4D-CT ventilation and emphysema, which indicates the potential for HU-based 4D-CT ventilation imaging to achieve high physiologic accuracy. A further study is needed to confirm these results.

Body-wide anatomy recognition in PET/CT images

NASA Astrophysics Data System (ADS)

Wang, Huiqian; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Zhao, Liming; Torigian, Drew A.

2015-03-01

With the rapid growth of positron emission tomography/computed tomography (PET/CT)-based medical applications, body-wide anatomy recognition on whole-body PET/CT images becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem and seldom studied due to unclear anatomy reference frame and low spatial resolution of PET images as well as low contrast and spatial resolution of the associated low-dose CT images. We previously developed an automatic anatomy recognition (AAR) system [15] whose applicability was demonstrated on diagnostic computed tomography (CT) and magnetic resonance (MR) images in different body regions on 35 objects. The aim of the present work is to investigate strategies for adapting the previous AAR system to low-dose CT and PET images toward automated body-wide disease quantification. Our adaptation of the previous AAR methodology to PET/CT images in this paper focuses on 16 objects in three body regions - thorax, abdomen, and pelvis - and consists of the following steps: collecting whole-body PET/CT images from existing patient image databases, delineating all objects in these images, modifying the previous hierarchical models built from diagnostic CT images to account for differences in appearance in low-dose CT and PET images, automatically locating objects in these images following object hierarchy, and evaluating performance. Our preliminary evaluations indicate that the performance of the AAR approach on low-dose CT images achieves object localization accuracy within about 2 voxels, which is comparable to the accuracies achieved on diagnostic contrast-enhanced CT images. Object recognition on low-dose CT images from PET/CT examinations without requiring diagnostic contrast-enhanced CT seems feasible.

Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: A digital phantom study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernatowicz, K., E-mail: kingab@student.ethz.ch; Knopf, A.; Lomax, A.

Purpose: Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CTmore » can significantly reduce lung imaging artifacts. Methods: Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) “conventional” 4D CT that uses a constant imaging and couch-shift frequency, (ii) “beam paused” 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) “respiratory-gated” 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm{sup 3} spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Results: Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10{sup −19}). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%–1.4%), false positives (4.0%–2.6%), and false negatives (2.7%–1.3%). These percentage reductions correspond to gating reducing image artifacts by 24–90 cm{sup 3} of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. Conclusions: For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm{sup 3} of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.« less

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, C; Qi, H; Chen, Z

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using meanmore » filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.« less

MR and CT image fusion for postimplant analysis in permanent prostate seed implants.

PubMed

Polo, Alfredo; Cattani, Federica; Vavassori, Andrea; Origgi, Daniela; Villa, Gaetano; Marsiglia, Hugo; Bellomi, Massimo; Tosi, Giampiero; De Cobelli, Ottavio; Orecchia, Roberto

2004-12-01

To compare the outcome of two different image-based postimplant dosimetry methods in permanent seed implantation. Between October 1999 and October 2002, 150 patients with low-risk prostate carcinoma were treated with (125)I and (103)Pd in our institution. A CT-MRI image fusion protocol was used in 21 consecutive patients treated with exclusive brachytherapy. The accuracy and reproducibility of the method was calculated, and then the CT-based dosimetry was compared with the CT-MRI-based dosimetry using the dose-volume histogram (DVH) related parameters recommended by the American Brachytherapy Society and the American Association of Physicists in Medicine. Our method for CT-MRI image fusion was accurate and reproducible (median shift <1 mm). Differences in prostate volume were found, depending on the image modality used. Quality assurance DVH-related parameters strongly depended on the image modality (CT vs. CT-MRI): V(100) = 82% vs. 88%, p < 0.05. D(90) = 96% vs. 115%, p < 0.05. Those results depend on the institutional implant technique and reflect the importance of lowering inter- and intraobserver discrepancies when outlining prostate and organs at risk for postimplant dosimetry. Computed tomography-MRI fused images allow accurate determination of prostate size, significantly improving the dosimetric evaluation based on DVH analysis. This provides a consistent method to judge a prostate seed implant's quality.

Generating patient specific pseudo-CT of the head from MR using atlas-based regression

NASA Astrophysics Data System (ADS)

Sjölund, J.; Forsberg, D.; Andersson, M.; Knutsson, H.

2015-01-01

Radiotherapy planning and attenuation correction of PET images require simulation of radiation transport. The necessary physical properties are typically derived from computed tomography (CT) images, but in some cases, including stereotactic neurosurgery and combined PET/MR imaging, only magnetic resonance (MR) images are available. With these applications in mind, we describe how a realistic, patient-specific, pseudo-CT of the head can be derived from anatomical MR images. We refer to the method as atlas-based regression, because of its similarity to atlas-based segmentation. Given a target MR and an atlas database comprising MR and CT pairs, atlas-based regression works by registering each atlas MR to the target MR, applying the resulting displacement fields to the corresponding atlas CTs and, finally, fusing the deformed atlas CTs into a single pseudo-CT. We use a deformable registration algorithm known as the Morphon and augment it with a certainty mask that allows a tailoring of the influence certain regions are allowed to have on the registration. Moreover, we propose a novel method of fusion, wherein the collection of deformed CTs is iteratively registered to their joint mean and find that the resulting mean CT becomes more similar to the target CT. However, the voxelwise median provided even better results; at least as good as earlier work that required special MR imaging techniques. This makes atlas-based regression a good candidate for clinical use.

Magnetic resonance imaging versus computed tomography to plan hemilaminectomies in chondrodystrophic dogs with intervertebral disc extrusion.

PubMed

Noyes, Julie A; Thomovsky, Stephanie A; Chen, Annie V; Owen, Tina J; Fransson, Boel A; Carbonneau, Kira J; Matthew, Susan M

2017-10-01

To determine the influence of preoperative computed tomography (CT) versus magnetic resonance (MR) on hemilaminectomies planned to treat thoracolumbar (TL) intervertebral disc (IVD) extrusions in chondrodystrophic dogs. Prospective clinical study. Forty chondrodystrophic dogs with TL IVD extrusion and preoperative CT and MR studies. MR and CT images were randomized and reviewed by 4 observers masked to the dog's identity and corresponding imaging studies. Observers planned the location along the spine, side, and extent (number of articular facets to be removed) based on individual reviews of CT and MR studies. Intra-observer agreement was determined between overall surgical plan, location, side, and size of the hemilaminectomy planned on CT versus MR of the same dog. Similar surgical plans were developed based on MR versus CT in 43.5%-66.6% of dogs, depending on the observer. Intra-observer agreement in location, side, and size of the planned hemilaminectomy based on CT versus MR ranged between 48.7%-66.6%, 87%-92%, and 51.2%-71.7% of dogs, respectively. Observers tended to plan larger laminectomy defects based on MR versus CT of the same dog. Findings from this study indicated considerable differences in hemilaminectomies planned on preoperative MR versus CT imaging. Surgical location and size varied the most; the side of planned hemilaminectomies was most consistent between imaging modalities. © 2017 The American College of Veterinary Surgeons.

Precision analysis of a quantitative CT liver surface nodularity score.

PubMed

Smith, Andrew; Varney, Elliot; Zand, Kevin; Lewis, Tara; Sirous, Reza; York, James; Florez, Edward; Abou Elkassem, Asser; Howard-Claudio, Candace M; Roda, Manohar; Parker, Ellen; Scortegagna, Eduardo; Joyner, David; Sandlin, David; Newsome, Ashley; Brewster, Parker; Lirette, Seth T; Griswold, Michael

2018-04-26

To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images. An anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test-retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC. There was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100-140, mA 200-400, and auto-mA, section thickness 1.25-5.0 mm, field of view 35-50 cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test-retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%). The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability.

Modeling respiratory motion for reducing motion artifacts in 4D CT images.

PubMed

Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei

2013-04-01

Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a lung cancer patient by comparing the synthesized images and the original images at different phases. The synthesized images matched well with the original images. The motion model was used to reduce irregular motion artifacts in the 4D CT images of three lung cancer patients. Visual assessment indicated that the proposed approach could reduce severe image artifacts. The shape distortions around the diaphragm and tumor regions were mitigated in the synthesized 4D CT images. The authors have derived a mathematical model to represent the regular respiratory motion from a patient-specific 4D CT set and have demonstrated its application in reducing irregular motion artifacts in 4D CT images. The authors' approach can mitigate shape distortions of anatomy caused by irregular breathing motion during 4D CT acquisition.

A denoising algorithm for CT image using low-rank sparse coding

NASA Astrophysics Data System (ADS)

Lei, Yang; Xu, Dong; Zhou, Zhengyang; Wang, Tonghe; Dong, Xue; Liu, Tian; Dhabaan, Anees; Curran, Walter J.; Yang, Xiaofeng

2018-03-01

We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously construct the dictionary and achieve sparse representation through clustering similar image patches. A variable-splitting scheme and a quadratic optimization are used to reconstruct CT image based on achieved sparse coefficients. We tested this denoising technology using phantom, brain and abdominal CT images. The experimental results showed that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

Comparison of analytical and numerical approaches for CT-based aberration correction in transcranial passive acoustic imaging

NASA Astrophysics Data System (ADS)

Jones, Ryan M.; Hynynen, Kullervo

2016-01-01

Computed tomography (CT)-based aberration corrections are employed in transcranial ultrasound both for therapy and imaging. In this study, analytical and numerical approaches for calculating aberration corrections based on CT data were compared, with a particular focus on their application to transcranial passive imaging. Two models were investigated: a three-dimensional full-wave numerical model (Connor and Hynynen 2004 IEEE Trans. Biomed. Eng. 51 1693-706) based on the Westervelt equation, and an analytical method (Clement and Hynynen 2002 Ultrasound Med. Biol. 28 617-24) similar to that currently employed by commercial brain therapy systems. Trans-skull time delay corrections calculated from each model were applied to data acquired by a sparse hemispherical (30 cm diameter) receiver array (128 piezoceramic discs: 2.5 mm diameter, 612 kHz center frequency) passively listening through ex vivo human skullcaps (n  =  4) to emissions from a narrow-band, fixed source emitter (1 mm diameter, 516 kHz center frequency). Measurements were taken at various locations within the cranial cavity by moving the source around the field using a three-axis positioning system. Images generated through passive beamforming using CT-based skull corrections were compared with those obtained through an invasive source-based approach, as well as images formed without skull corrections, using the main lobe volume, positional shift, peak sidelobe ratio, and image signal-to-noise ratio as metrics for image quality. For each CT-based model, corrections achieved by allowing for heterogeneous skull acoustical parameters in simulation outperformed the corresponding case where homogeneous parameters were assumed. Of the CT-based methods investigated, the full-wave model provided the best imaging results at the cost of computational complexity. These results highlight the importance of accurately modeling trans-skull propagation when calculating CT-based aberration corrections. Although presented in an imaging context, our results may also be applicable to the problem of transmit focusing through the skull.

Accuracy of radiotherapy dose calculations based on cone-beam CT: comparison of deformable registration and image correction based methods

NASA Astrophysics Data System (ADS)

Marchant, T. E.; Joshi, K. D.; Moore, C. J.

2018-03-01

Radiotherapy dose calculations based on cone-beam CT (CBCT) images can be inaccurate due to unreliable Hounsfield units (HU) in the CBCT. Deformable image registration of planning CT images to CBCT, and direct correction of CBCT image values are two methods proposed to allow heterogeneity corrected dose calculations based on CBCT. In this paper we compare the accuracy and robustness of these two approaches. CBCT images for 44 patients were used including pelvis, lung and head & neck sites. CBCT HU were corrected using a ‘shading correction’ algorithm and via deformable registration of planning CT to CBCT using either Elastix or Niftyreg. Radiotherapy dose distributions were re-calculated with heterogeneity correction based on the corrected CBCT and several relevant dose metrics for target and OAR volumes were calculated. Accuracy of CBCT based dose metrics was determined using an ‘override ratio’ method where the ratio of the dose metric to that calculated on a bulk-density assigned version of the same image is assumed to be constant for each patient, allowing comparison to the patient’s planning CT as a gold standard. Similar performance is achieved by shading corrected CBCT and both deformable registration algorithms, with mean and standard deviation of dose metric error less than 1% for all sites studied. For lung images, use of deformed CT leads to slightly larger standard deviation of dose metric error than shading corrected CBCT with more dose metric errors greater than 2% observed (7% versus 1%).

Variation in the human ribs geometrical properties and mechanical response based on X-ray computed tomography images resolution.

PubMed

Perz, Rafał; Toczyski, Jacek; Subit, Damien

2015-01-01

Computational models of the human body are commonly used for injury prediction in automobile safety research. To create these models, the geometry of the human body is typically obtained from segmentation of medical images such as computed tomography (CT) images that have a resolution between 0.2 and 1mm/pixel. While the accuracy of the geometrical and structural information obtained from these images depend greatly on their resolution, the effect of image resolution on the estimation of the ribs geometrical properties has yet to be established. To do so, each of the thirty-four sections of ribs obtained from a Post Mortem Human Surrogate (PMHS) was imaged using three different CT modalities: standard clinical CT (clinCT), high resolution clinical CT (HRclinCT), and microCT. The images were processed to estimate the rib cross-section geometry and mechanical properties, and the results were compared to those obtained from the microCT images by computing the 'deviation factor', a metric that quantifies the relative difference between results obtained from clinCT and HRclinCT to those obtained from microCT. Overall, clinCT images gave a deviation greater than 100%, and were therefore deemed inadequate for the purpose of this study. HRclinCT overestimated the rib cross-sectional area by 7.6%, the moments of inertia by about 50%, and the cortical shell area by 40.2%, while underestimating the trabecular area by 14.7%. Next, a parametric analysis was performed to quantify how the variations in the estimate of the geometrical properties affected the rib predicted mechanical response under antero-posterior loading. A variation of up to 45% for the predicted peak force and up to 50% for the predicted stiffness was observed. These results provide a quantitative estimate of the sensitivity of the response of the FE model to the resolution of the images used to generate it. They also suggest that a correction factor could be derived from the comparison between microCT and HRclinCT images to improve the response of the model developed based on HRclinCT images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Technical Note: Quantitative accuracy evaluation for spectral images from a detector-based spectral CT scanner using an iodine phantom.

PubMed

Duan, Xinhui; Arbique, Gary; Guild, Jeffrey; Xi, Yin; Anderson, Jon

2018-05-01

The purpose of this study was to evaluate the quantitative accuracy of spectral images from a detector-based spectral CT scanner using a phantom with iodine-loaded inserts. A 40-cm long-body phantom with seven iodine inserts (2-20 mg/ml of iodine) was used in the study. The inserts could be placed at 5.5 or 10.5 cm from the phantom axis. The phantom was scanned five times for each insert configuration using 120 kVp tube voltage. A set of iodine, virtual noncontrast, effective atomic number, and virtual monoenergetic spectral CT images were generated and measurements were made for all the iodine rods. Measured values were compared with reference values calculated from the chemical composition information provided by the phantom manufacturer. Radiation dose from the spectral CT was compared to a conventional CT using a CTDI (32 cm) phantom. Good agreement between measurements and reference values was achieved for all types of spectral images. The differences ranged from -0.46 to 0.1 mg/ml for iodine concentration, -9.95 to 6.41 HU for virtual noncontrast images, 0.12 to 0.35 for effective Z images, and -17.7 to 55.7 HU for virtual monoenergetic images. For a similar CTDIvol, image noise from the conventional CT was 10% lower than the spectral CT. The detector-based spectral CT can achieve accurate spectral measurements on iodine concentration, virtual non-contrast images, effective atomic numbers, and virtual monoenergetic images. © 2018 American Association of Physicists in Medicine.

Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT

NASA Astrophysics Data System (ADS)

Robins, Marthony; Solomon, Justin; Sahbaee, Pooyan; Sedlmair, Martin; Choudhury, Kingshuk Roy; Pezeshk, Aria; Sahiner, Berkman; Samei, Ehsan

2017-09-01

Virtual nodule insertion paves the way towards the development of standardized databases of hybrid CT images with known lesions. The purpose of this study was to assess three methods (an established and two newly developed techniques) for inserting virtual lung nodules into CT images. Assessment was done by comparing virtual nodule volume and shape to the CT-derived volume and shape of synthetic nodules. 24 synthetic nodules (three sizes, four morphologies, two repeats) were physically inserted into the lung cavity of an anthropomorphic chest phantom (KYOTO KAGAKU). The phantom was imaged with and without nodules on a commercial CT scanner (SOMATOM Definition Flash, Siemens) using a standard thoracic CT protocol at two dose levels (1.4 and 22 mGy CTDIvol). Raw projection data were saved and reconstructed with filtered back-projection and sinogram affirmed iterative reconstruction (SAFIRE, strength 5) at 0.6 mm slice thickness. Corresponding 3D idealized, virtual nodule models were co-registered with the CT images to determine each nodule’s location and orientation. Virtual nodules were voxelized, partial volume corrected, and inserted into nodule-free CT data (accounting for system imaging physics) using two methods: projection-based Technique A, and image-based Technique B. Also a third Technique C based on cropping a region of interest from the acquired image of the real nodule and blending it into the nodule-free image was tested. Nodule volumes were measured using a commercial segmentation tool (iNtuition, TeraRecon, Inc.) and deformation was assessed using the Hausdorff distance. Nodule volumes and deformations were compared between the idealized, CT-derived and virtual nodules using a linear mixed effects regression model which utilized the mean, standard deviation, and coefficient of variation (Mea{{n}RHD} , ST{{D}RHD} and C{{V}RHD}{) }~ of the regional Hausdorff distance. Overall, there was a close concordance between the volumes of the CT-derived and virtual nodules. Percent differences between them were less than 3% for all insertion techniques and were not statistically significant in most cases. Correlation coefficient values were greater than 0.97. The deformation according to the Hausdorff distance was also similar between the CT-derived and virtual nodules with minimal statistical significance in the (C{{V}RHD} ) for Techniques A, B, and C. This study shows that both projection-based and image-based nodule insertion techniques yield realistic nodule renderings with statistical similarity to the synthetic nodules with respect to nodule volume and deformation. These techniques could be used to create a database of hybrid CT images containing nodules of known size, location and morphology.

Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT

PubMed Central

Robins, Marthony; Solomon, Justin; Sahbaee, Pooyan; Sedlmair, Martin; Choudhury, Kingshuk Roy; Pezeshk, Aria; Sahiner, Berkman; Samei, Ehsan

2017-01-01

Virtual nodule insertion paves the way towards the development of standardized databases of hybrid CT images with known lesions. The purpose of this study was to assess three methods (an established and two newly developed techniques) for inserting virtual lung nodules into CT images. Assessment was done by comparing virtual nodule volume and shape to the CT-derived volume and shape of synthetic nodules. 24 synthetic nodules (three sizes, four morphologies, two repeats) were physically inserted into the lung cavity of an anthropomorphic chest phantom (KYOTO KAGAKU). The phantom was imaged with and without nodules on a commercial CT scanner (SOMATOM Definition Flash, Siemens) using a standard thoracic CT protocol at two dose levels (1.4 and 22 mGy CTDIvol). Raw projection data were saved and reconstructed with filtered back-projection and sinogram affirmed iterative reconstruction (SAFIRE, strength 5) at 0.6 mm slice thickness. Corresponding 3D idealized, virtual nodule models were co-registered with the CT images to determine each nodule’s location and orientation. Virtual nodules were voxelized, partial volume corrected, and inserted into nodule-free CT data (accounting for system imaging physics) using two methods: projection-based Technique A, and image-based Technique B. Also a third Technique C based on cropping a region of interest from the acquired image of the real nodule and blending it into the nodule-free image was tested. Nodule volumes were measured using a commercial segmentation tool (iNtuition, TeraRecon, Inc.) and deformation was assessed using the Hausdorff distance. Nodule volumes and deformations were compared between the idealized, CT-derived and virtual nodules using a linear mixed effects regression model which utilized the mean, standard deviation, and coefficient of variation (MeanRHD, and STDRHD CVRHD) of the regional Hausdorff distance. Overall, there was a close concordance between the volumes of the CT-derived and virtual nodules. Percent differences between them were less than 3% for all insertion techniques and were not statistically significant in most cases. Correlation coefficient values were greater than 0.97. The deformation according to the Hausdorff distance was also similar between the CT-derived and virtual nodules with minimal statistical significance in the (CVRHD) for Techniques A, B, and C. This study shows that both projection-based and image-based nodule insertion techniques yield realistic nodule renderings with statistical similarity to the synthetic nodules with respect to nodule volume and deformation. These techniques could be used to create a database of hybrid CT images containing nodules of known size, location and morphology. PMID:28786399

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

Accuracy of Dual-Energy Virtual Monochromatic CT Numbers: Comparison between the Single-Source Projection-Based and Dual-Source Image-Based Methods.

PubMed

Ueguchi, Takashi; Ogihara, Ryota; Yamada, Sachiko

2018-03-21

To investigate the accuracy of dual-energy virtual monochromatic computed tomography (CT) numbers obtained by two typical hardware and software implementations: the single-source projection-based method and the dual-source image-based method. A phantom with different tissue equivalent inserts was scanned with both single-source and dual-source scanners. A fast kVp-switching feature was used on the single-source scanner, whereas a tin filter was used on the dual-source scanner. Virtual monochromatic CT images of the phantom at energy levels of 60, 100, and 140 keV were obtained by both projection-based (on the single-source scanner) and image-based (on the dual-source scanner) methods. The accuracy of virtual monochromatic CT numbers for all inserts was assessed by comparing measured values to their corresponding true values. Linear regression analysis was performed to evaluate the dependency of measured CT numbers on tissue attenuation, method, and their interaction. Root mean square values of systematic error over all inserts at 60, 100, and 140 keV were approximately 53, 21, and 29 Hounsfield unit (HU) with the single-source projection-based method, and 46, 7, and 6 HU with the dual-source image-based method, respectively. Linear regression analysis revealed that the interaction between the attenuation and the method had a statistically significant effect on the measured CT numbers at 100 and 140 keV. There were attenuation-, method-, and energy level-dependent systematic errors in the measured virtual monochromatic CT numbers. CT number reproducibility was comparable between the two scanners, and CT numbers had better accuracy with the dual-source image-based method at 100 and 140 keV. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Objective image characterization of a spectral CT scanner with dual-layer detector

NASA Astrophysics Data System (ADS)

Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David

2018-01-01

This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.

Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

PubMed

Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

2014-12-01

To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers (n = 100) scored overall image quality as sufficient or good with MBIR model-based iterative reconstruction in 99% (99 of 100). Liver SNR signal-to-noise ratio was significantly greater for MBIR model-based iterative reconstruction (10.8 ± 2.5 [standard deviation] vs 7.7 ± 1.4, P < .001); there was no difference for CNR contrast-to-noise ratio (2.5 ± 1.4 vs 2.4 ± 1.4, P = .45). For ASIR adaptive statistical iterative reconstruction and MBIR model-based iterative reconstruction , respectively, volume CT dose index was 15.2 mGy ± 7.6 versus 6.2 mGy ± 3.6; SSDE size-specific dose estimate was 16.4 mGy ± 6.6 versus 6.7 mGy ± 3.1 (P < .001). Liver CT images reconstructed with MBIR model-based iterative reconstruction may allow up to 59% radiation dose reduction compared with the dose with ASIR adaptive statistical iterative reconstruction , without compromising depiction of findings or image quality. © RSNA, 2014.

Image-based metal artifact reduction in x-ray computed tomography utilizing local anatomical similarity

NASA Astrophysics Data System (ADS)

Dong, Xue; Yang, Xiaofeng; Rosenfield, Jonathan; Elder, Eric; Dhabaan, Anees

2017-03-01

X-ray computed tomography (CT) is widely used in radiation therapy treatment planning in recent years. However, metal implants such as dental fillings and hip prostheses can cause severe bright and dark streaking artifacts in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. In this work, a metal artifact reduction method is proposed based on the intrinsic anatomical similarity between neighboring CT slices. Neighboring CT slices from the same patient exhibit similar anatomical features. Exploiting this anatomical similarity, a gamma map is calculated as a weighted summation of relative HU error and distance error for each pixel in an artifact-corrupted CT image relative to a neighboring, artifactfree image. The minimum value in the gamma map for each pixel is used to identify an appropriate pixel from the artifact-free CT slice to replace the corresponding artifact-corrupted pixel. With the proposed method, the mean CT HU error was reduced from 360 HU and 460 HU to 24 HU and 34 HU on head and pelvis CT images, respectively. Dose calculation accuracy also improved, as the dose difference was reduced from greater than 20% to less than 4%. Using 3%/3mm criteria, the gamma analysis failure rate was reduced from 23.25% to 0.02%. An image-based metal artifact reduction method is proposed that replaces corrupted image pixels with pixels from neighboring CT slices free of metal artifacts. This method is shown to be capable of suppressing streaking artifacts, thereby improving HU and dose calculation accuracy.

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

PubMed Central

Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

2017-01-01

The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

Denoising of polychromatic CT images based on their own noise properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Ji Hye; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr

Purpose: Because of high diagnostic accuracy and fast scan time, computed tomography (CT) has been widely used in various clinical applications. Since the CT scan introduces radiation exposure to patients, however, dose reduction has recently been recognized as an important issue in CT imaging. However, low-dose CT causes an increase of noise in the image and thereby deteriorates the accuracy of diagnosis. In this paper, the authors develop an efficient denoising algorithm for low-dose CT images obtained using a polychromatic x-ray source. The algorithm is based on two steps: (i) estimation of space variant noise statistics, which are uniquely determinedmore » according to the system geometry and scanned object, and (ii) subsequent novel conversion of the estimated noise to Gaussian noise so that an existing high performance Gaussian noise filtering algorithm can be directly applied to CT images with non-Gaussian noise. Methods: For efficient polychromatic CT image denoising, the authors first reconstruct an image with the iterative maximum-likelihood polychromatic algorithm for CT to alleviate the beam-hardening problem. We then estimate the space-variant noise variance distribution on the image domain. Since there are many high performance denoising algorithms available for the Gaussian noise, image denoising can become much more efficient if they can be used. Hence, the authors propose a novel conversion scheme to transform the estimated space-variant noise to near Gaussian noise. In the suggested scheme, the authors first convert the image so that its mean and variance can have a linear relationship, and then produce a Gaussian image via variance stabilizing transform. The authors then apply a block matching 4D algorithm that is optimized for noise reduction of the Gaussian image, and reconvert the result to obtain a final denoised image. To examine the performance of the proposed method, an XCAT phantom simulation and a physical phantom experiment were conducted. Results: Both simulation and experimental results show that, unlike the existing denoising algorithms, the proposed algorithm can effectively reduce the noise over the whole region of CT images while preventing degradation of image resolution. Conclusions: To effectively denoise polychromatic low-dose CT images, a novel denoising algorithm is proposed. Because this algorithm is based on the noise statistics of a reconstructed polychromatic CT image, the spatially varying noise on the image is effectively reduced so that the denoised image will have homogeneous quality over the image domain. Through a simulation and a real experiment, it is verified that the proposed algorithm can deliver considerably better performance compared to the existing denoising algorithms.« less

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning

NASA Astrophysics Data System (ADS)

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L.

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multiatlas- based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning.

PubMed

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multi-atlas-based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

Generative Adversarial Networks for Noise Reduction in Low-Dose CT.

PubMed

Wolterink, Jelmer M; Leiner, Tim; Viergever, Max A; Isgum, Ivana

2017-12-01

Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained to distinguish the output of the generator from routine-dose CT images. The performance of this discriminator was used as an adversarial loss for the generator. Experiments were performed using CT images of an anthropomorphic phantom containing calcium inserts, as well as patient non-contrast-enhanced cardiac CT images. The phantom and patients were scanned at 20% and 100% routine clinical dose. Three training strategies were compared: the first used only voxelwise loss, the second combined voxelwise loss and adversarial loss, and the third used only adversarial loss. The results showed that training with only voxelwise loss resulted in the highest peak signal-to-noise ratio with respect to reference routine-dose images. However, CNNs trained with adversarial loss captured image statistics of routine-dose images better. Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels. Testing took less than 10 s per CT volume. CNN-based low-dose CT noise reduction in the image domain is feasible. Training with an adversarial network improves the CNNs ability to generate images with an appearance similar to that of reference routine-dose CT images.

SU-E-J-219: A Dixon Based Pseudo-CT Generation Method for MR-Only Radiotherapy Treatment Planning of the Pelvis and Head and Neck

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maspero, M.; Meijer, G.J.; Lagendijk, J.J.W.

2015-06-15

Purpose: To develop an image processing method for MRI-based generation of electron density maps, known as pseudo-CT (pCT), without usage of model- or atlas-based segmentation, and to evaluate the method in the pelvic and head-neck region against CT. Methods: CT and MRI scans were obtained from the pelvic region of four patients in supine position using a flat table top only for CT. Stratified CT maps were generated by classifying each voxel based on HU ranges into one of four classes: air, adipose tissue, soft tissue or bone.A hierarchical region-selective algorithm, based on automatic thresholding and clustering, was used tomore » classify tissues from MR Dixon reconstructed fat, In-Phase (IP) and Opposed-Phase (OP) images. First, a body mask was obtained by thresholding the IP image. Subsequently, an automatic threshold on the Dixon fat image differentiated soft and adipose tissue. K-means clustering on IP and OP images resulted in a mask that, via a connected neighborhood analysis, allowing the user to select the components corresponding to bone structures.The pCT was estimated through assignment of bulk HU to the tissue classes. Bone-only Digital Reconstructed Radiographs (DRR) were generated as well. The pCT images were rigidly registered to the stratified CT to allow a volumetric and voxelwise comparison. Moreover, pCTs were also calculated within the head-neck region in two volunteers using the same pipeline. Results: The volumetric comparison resulted in differences <1% for each tissue class. A voxelwise comparison showed a good classification, ranging from 64% to 98%. The primary misclassified classes were adipose/soft tissue and bone/soft tissue. As the patients have been imaged on different table tops, part of the misclassification error can be explained by misregistration. Conclusion: The proposed approach does not rely on an anatomy model providing the flexibility to successfully generate the pCT in two different body sites. This research is founded by ZonMw IMDI Programme, project name: “RASOR sharp: MRI based radiotherapy planning using a single MRI sequence”, project number: 10-104003010.« less

90Y Liver Radioembolization Imaging Using Amplitude-Based Gated PET/CT.

PubMed

Osborne, Dustin R; Acuff, Shelley; Neveu, Melissa; Kaman, Austin; Syed, Mumtaz; Fu, Yitong

2017-05-01

The usage of PET/CT to monitor patients with hepatocellular carcinoma following Y radioembolization has increased; however, image quality is often poor because of low count efficiency and respiratory motion. Motion can be corrected using gating techniques but at the expense of additional image noise. Amplitude-based gating has been shown to improve quantification in FDG PET, but few have used this technique in Y liver imaging. The patients shown in this work indicate that amplitude-based gating can be used in Y PET/CT liver imaging to provide motion-corrected images with higher estimates of activity concentration that may improve posttherapy dosimetry.

Calibration free beam hardening correction for cardiac CT perfusion imaging

NASA Astrophysics Data System (ADS)

Levi, Jacob; Fahmi, Rachid; Eck, Brendan L.; Fares, Anas; Wu, Hao; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2016-03-01

Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration's BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12+/-2HU to 1+/-1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48+/-6HU to 1+/-5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28+/-6 HU to less than 4+/-4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.

An Adaptive MR-CT Registration Method for MRI-guided Prostate Cancer Radiotherapy

PubMed Central

Zhong, Hualiang; Wen, Ning; Gordon, James; Elshaikh, Mohamed A; Movsas, Benjamin; Chetty, Indrin J.

2015-01-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ/cm3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for development of high-quality MRI-guided radiation therapy. PMID:25775937

An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

NASA Astrophysics Data System (ADS)

Zhong, Hualiang; Wen, Ning; Gordon, James J.; Elshaikh, Mohamed A.; Movsas, Benjamin; Chetty, Indrin J.

2015-04-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm-3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy.

Generation of synthetic CT data using patient specific daily MR image data and image registration

NASA Astrophysics Data System (ADS)

Melanie Kraus, Kim; Jäkel, Oliver; Niebuhr, Nina I.; Pfaffenberger, Asja

2017-02-01

To fully exploit the advantages of magnetic resonance imaging (MRI) for radiotherapy (RT) treatment planning, a method is required to overcome the problem of lacking electron density information. We aim to establish and evaluate a new method for computed tomography (CT) data generation based on MRI and image registration. The thereby generated CT data is used for dose accumulation. We developed a process flow based on an initial pair of rigidly co-registered CT and T2-weighted MR image representing the same anatomical situation. Deformable image registration using anatomical landmarks is performed between the initial MRI data and daily MR images. The resulting transformation is applied to the initial CT, thus fractional CT data is generated. Furthermore, the dose for a photon intensity modulated RT (IMRT) or intensity modulated proton therapy (IMPT) plan is calculated on the generated fractional CT and accumulated on the initial CT via inverse transformation. The method is evaluated by the use of phantom CT and MRI data. Quantitative validation is performed by evaluation of the mean absolute error (MAE) between the measured and the generated CT. The effect on dose accumulation is examined by means of dose-volume parameters. One patient case is presented to demonstrate the applicability of the method introduced here. Overall, CT data derivation lead to MAEs with a median of 37.0 HU ranging from 29.9 to 66.6 HU for all investigated tissues. The accuracy of image registration showed to be limited in the case of unexpected air cavities and at tissue boundaries. The comparisons of dose distributions based on measured and generated CT data agree well with the published literature. Differences in dose volume parameters kept within 1.6% and 3.2% for photon and proton RT, respectively. The method presented here is particularly suited for application in adaptive RT in current clinical routine, since only minor additional technical equipment is required.

Prostate CT segmentation method based on nonrigid registration in ultrasound-guided CT-based HDR prostate brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaofeng, E-mail: xyang43@emory.edu; Rossi, Peter; Ogunleye, Tomi

2014-11-01

Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approachmore » that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7.28% ± 0.86%, and the prostate volume Dice overlap coefficient was 91.89% ± 1.19%. Conclusions: The authors have developed a novel approach to improve prostate contour utilizing intraoperative TRUS-based prostate volume in the CT-based prostate HDR treatment planning, demonstrated its clinical feasibility, and validated its accuracy with MRIs. The proposed segmentation method would improve prostate delineations, enable accurate dose planning and treatment delivery, and potentially enhance the treatment outcome of prostate HDR brachytherapy.« less

Prostate CT segmentation method based on nonrigid registration in ultrasound-guided CT-based HDR prostate brachytherapy

PubMed Central

Yang, Xiaofeng; Rossi, Peter; Ogunleye, Tomi; Marcus, David M.; Jani, Ashesh B.; Mao, Hui; Curran, Walter J.; Liu, Tian

2014-01-01

Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approach that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7.28% ± 0.86%, and the prostate volume Dice overlap coefficient was 91.89% ± 1.19%. Conclusions: The authors have developed a novel approach to improve prostate contour utilizing intraoperative TRUS-based prostate volume in the CT-based prostate HDR treatment planning, demonstrated its clinical feasibility, and validated its accuracy with MRIs. The proposed segmentation method would improve prostate delineations, enable accurate dose planning and treatment delivery, and potentially enhance the treatment outcome of prostate HDR brachytherapy. PMID:25370648

TU-AB-BRA-02: An Efficient Atlas-Based Synthetic CT Generation Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, X

2016-06-15

Purpose: A major obstacle for MR-only radiotherapy is the need to generate an accurate synthetic CT (sCT) from MR image(s) of a patient for the purposes of dose calculation and DRR generation. We propose here an accurate and efficient atlas-based sCT generation method, which has a computation speed largely independent of the number of atlases used. Methods: Atlas-based sCT generation requires a set of atlases with co-registered CT and MR images. Unlike existing methods that align each atlas to the new patient independently, we first create an average atlas and pre-align every atlas to the average atlas space. When amore » new patient arrives, we compute only one deformable image registration to align the patient MR image to the average atlas, which indirectly aligns the patient to all pre-aligned atlases. A patch-based non-local weighted fusion is performed in the average atlas space to generate the sCT for the patient, which is then warped back to the original patient space. We further adapt a PatchMatch algorithm that can quickly find top matches between patches of the patient image and all atlas images, which makes the patch fusion step also independent of the number of atlases used. Results: Nineteen brain tumour patients with both CT and T1-weighted MR images are used as testing data and a leave-one-out validation is performed. Each sCT generated is compared against the original CT image of the same patient on a voxel-by-voxel basis. The proposed method produces a mean absolute error (MAE) of 98.6±26.9 HU overall. The accuracy is comparable with a conventional implementation scheme, but the computation time is reduced from over an hour to four minutes. Conclusion: An average atlas space patch fusion approach can produce highly accurate sCT estimations very efficiently. Further validation on dose computation accuracy and using a larger patient cohort is warranted. The author is a full time employee of Elekta, Inc.« less

Evaluation of motion-correction methods for dual-gated cardiac positron emission tomography/computed tomography imaging.

PubMed

Klén, Riku; Noponen, Tommi; Koikkalainen, Juha; Lötjönen, Jyrki; Thielemans, Kris; Hoppela, Erika; Sipilä, Hannu; Teräs, Mika; Knuuti, Juhani

2016-09-01

Dual gating is a method of dividing the data of a cardiac PET scan into smaller bins according to the respiratory motion and the ECG of the patient. It reduces the undesirable motion artefacts in images, but produces several images for interpretation and decreases the quality of single images. By using motion-correction techniques, the motion artefacts in the dual-gated images can be corrected and the images can be combined into a single motion-free image with good statistics. The aim of the present study is to develop and evaluate motion-correction methods for cardiac PET studies. We have developed and compared two different methods: computed tomography (CT)/PET-based and CT-only methods. The methods were implemented and tested with a cardiac phantom and three patient datasets. In both methods, anatomical information of CT images is used to create models for the cardiac motion. In the patient study, the CT-only method reduced motion (measured as the centre of mass of the myocardium) on average 43%, increased the contrast-to-noise ratio on average 6.0% and reduced the target size on average 10%. Slightly better figures (51, 6.9 and 28%) were obtained with the CT/PET-based method. Even better results were obtained in the phantom study for both the CT-only method (57, 68 and 43%) and the CT/PET-based method (61, 74 and 52%). We conclude that using anatomical information of CT for motion correction of cardiac PET images, both respiratory and pulsatile motions can be corrected with good accuracy.

Evaluation of non-rigid registration parameters for atlas-based segmentation of CT images of human cochlea

NASA Astrophysics Data System (ADS)

Elfarnawany, Mai; Alam, S. Riyahi; Agrawal, Sumit K.; Ladak, Hanif M.

2017-02-01

Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient's hearing. Clinical computed tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10% and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively, the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828+/-0.021 and 0.25+/-0.09mm respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage: moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear structures in clinical CT images.

Evaluation of Atlas-Based Attenuation Correction for Integrated PET/MR in Human Brain: Application of a Head Atlas and Comparison to True CT-Based Attenuation Correction.

PubMed

Sekine, Tetsuro; Buck, Alfred; Delso, Gaspar; Ter Voert, Edwin E G W; Huellner, Martin; Veit-Haibach, Patrick; Warnock, Geoffrey

2016-02-01

Attenuation correction (AC) for integrated PET/MR imaging in the human brain is still an open problem. In this study, we evaluated a simplified atlas-based AC (Atlas-AC) by comparing (18)F-FDG PET data corrected using either Atlas-AC or true CT data (CT-AC). We enrolled 8 patients (median age, 63 y). All patients underwent clinically indicated whole-body (18)F-FDG PET/CT for staging, restaging, or follow-up of malignant disease. All patients volunteered for an additional PET/MR of the head (additional tracer was not injected). For each patient, 2 AC maps were generated: an Atlas-AC map registered to a patient-specific liver accelerated volume acquisition-Flex MR sequence and using a vendor-provided head atlas generated from multiple CT head images and a CT-based AC map. For comparative AC, the CT-AC map generated from PET/CT was superimposed on the Atlas-AC map. PET images were reconstructed from the list-mode raw data from the PET/MR imaging scanner using each AC map. All PET images were normalized to the SPM5 PET template, and (18)F-FDG accumulation was quantified in 67 volumes of interest (VOIs; automated anatomic labeling atlas). Relative difference (%diff) between images based on Atlas-AC and CT-AC was calculated, and averaged difference images were generated. (18)F-FDG uptake in all VOIs was compared using Bland-Altman analysis. The range of error in all 536 VOIs was -3.0%-7.3%. Whole-brain (18)F-FDG uptake based on Atlas-AC was slightly underestimated (%diff = 2.19% ± 1.40%). The underestimation was most pronounced in the regions below the anterior/posterior commissure line, such as the cerebellum, temporal lobe, and central structures (%diff = 3.69% ± 1.43%, 3.25% ± 1.42%, and 3.05% ± 1.18%), suggesting that Atlas-AC tends to underestimate the attenuation values of the skull base bone. When compared with the gold-standard CT-AC, errors introduced using Atlas-AC did not exceed 8% in any brain region investigated. Underestimation of (18)F-FDG uptake was minor (<4%) but significant in regions near the skull base. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

TH-CD-206-09: Learning-Based MRI-CT Prostate Registration Using Spare Patch-Deformation Dictionary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, X; Jani, A; Rossi, P

Purpose: To enable MRI-guided prostate radiotherapy, MRI-CT deformable registration is required to map the MRI-defined tumor and key organ contours onto the CT images. Due to the intrinsic differences in grey-level intensity characteristics between MRI and CT images, the integration of MRI into CT-based radiotherapy is very challenging. We are developing a learning-based registration approach to address this technical challenge. Methods: We propose to estimate the deformation between MRI and CT images in a patch-wise fashion by using the sparse representation technique. Specifically, we assume that two image patches should follow the same deformation if their patch-wise appearance patterns aremore » similar. We first extract a set of key points in the new CT image. Then, for each key point, we adaptively construct a coupled dictionary from the training MRI-CT images, where each coupled element includes both appearance and deformation of the same image patch. After calculating the sparse coefficients in representing the patch appearance of each key point based on the constructed dictionary, we can predict the deformation for this point by applying the same sparse coefficients to the respective deformations in the dictionary. Results: This registration technique was validated with 10 prostate-cancer patients’ data and its performance was compared with the commonly used free-form-deformation-based registration. Several landmarks in both images were identified to evaluate the accuracy of our approach. Overall, the averaged target registration error of the intensity-based registration and the proposed method was 3.8±0.4 mm and 1.9±0.3 mm, respectively. Conclusion: We have developed a novel prostate MR-CT registration approach based on patch-deformation dictionary, demonstrated its clinical feasibility, and validated its accuracy. This technique will either reduce or compensate for the effect of patient-specific treatment variation measured during the course of radiotherapy, is therefore well-suited for a number of MRI-guided adaptive radiotherapy, and potentially enhance prostate radiotherapy treatment outcome.« less

WE-H-207A-07: Image-Based Versus Atlas-Based Internal Dosimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fallahpoor, M; Abbasi, M; Parach, A

Purpose: Monte Carlo (MC) simulation is known as the gold standard method for internal dosimetry. It requires radionuclide distribution from PET or SPECT and body structure from CT for accurate dose calculation. The manual or semi-automatic segmentation of organs from CT images is a major obstacle. The aim of this study is to compare the dosimetry results based on patient’s own CT and a digital humanoid phantom as an atlas with pre-specified organs. Methods: SPECT-CT images of a 50 year old woman who underwent bone pain palliation with Samarium-153 EDTMP for osseous metastases from breast cancer were used. The anatomicalmore » date and attenuation map were extracted from SPECT/CT and three XCAT digital phantoms with different BMIs (i.e. matched (38.8) and unmatched (35.5 and 36.7) with patient’s BMI that was 38.3). Segmentation of patient’s organs in CT image was performed using itk-SNAP software. GATE MC Simulator was used for dose calculation. Specific absorbed fractions (SAFs) and S-values were calculated for the segmented organs. Results: The differences between SAFs and S-values are high using different anatomical data and range from −13% to 39% for SAF values and −109% to 79% for S-values in different organs. In the spine, the clinically important target organ for Samarium Therapy, the differences in the S-values and SAF values are higher between XCAT phantom and CT when the phantom with identical BMI is employed (53.8% relative difference in S-value and 26.8% difference in SAF). However, the whole body dose values were the same between the calculations based on the CT and XCAT with different BMIs. Conclusion: The results indicated that atlas-based dosimetry using XCAT phantom even with matched BMI for patient leads to considerable errors as compared to image-based dosimetry that uses the patient’s own CT Patient-specific dosimetry using CT image is essential for accurate results.« less

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

A limited-angle CT reconstruction method based on anisotropic TV minimization.

PubMed

Chen, Zhiqiang; Jin, Xin; Li, Liang; Wang, Ge

2013-04-07

This paper presents a compressed sensing (CS)-inspired reconstruction method for limited-angle computed tomography (CT). Currently, CS-inspired CT reconstructions are often performed by minimizing the total variation (TV) of a CT image subject to data consistency. A key to obtaining high image quality is to optimize the balance between TV-based smoothing and data fidelity. In the case of the limited-angle CT problem, the strength of data consistency is angularly varying. For example, given a parallel beam of x-rays, information extracted in the Fourier domain is mostly orthogonal to the direction of x-rays, while little is probed otherwise. However, the TV minimization process is isotropic, suggesting that it is unfit for limited-angle CT. Here we introduce an anisotropic TV minimization method to address this challenge. The advantage of our approach is demonstrated in numerical simulation with both phantom and real CT images, relative to the TV-based reconstruction.

Low-dose CT image reconstruction using gain intervention-based dictionary learning

NASA Astrophysics Data System (ADS)

Pathak, Yadunath; Arya, K. V.; Tiwari, Shailendra

2018-05-01

Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.

High-resolution three-dimensional visualization of the rat spinal cord microvasculature by synchrotron radiation micro-CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Jianzhong; Cao, Yong; Wu, Tianding

2014-10-15

Purpose: Understanding the three-dimensional (3D) morphology of the spinal cord microvasculature has been limited by the lack of an effective high-resolution imaging technique. In this study, synchrotron radiation microcomputed tomography (SRµCT), a novel imaging technique based on absorption imaging, was evaluated with regard to the detection of the 3D morphology of the rat spinal cord microvasculature. Methods: Ten Sprague-Dawley rats were used in this ex vivo study. After contrast agent perfusion, their spinal cords were isolated and scanned using conventional x-rays, conventional micro-CT (CµCT), and SRµCT. Results: Based on contrast agent perfusion, the microvasculature of the rat spinal cord wasmore » clearly visualized for the first time ex vivo in 3D by means of SRµCT scanning. Compared to conventional imaging techniques, SRµCT achieved higher resolution 3D vascular imaging, with the smallest vessel that could be distinguished approximately 7.4 μm in diameter. Additionally, a 3D pseudocolored image of the spinal cord microvasculature was generated in a single session of SRµCT imaging, which was conducive to detailed observation of the vessel morphology. Conclusions: The results of this study indicated that SRµCT scanning could provide higher resolution images of the vascular network of the spinal cord. This modality also has the potential to serve as a powerful imaging tool for the investigation of morphology changes in the 3D angioarchitecture of the neurovasculature in preclinical research.« less

TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury

NASA Astrophysics Data System (ADS)

Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo

2010-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.

Automatic co-segmentation of lung tumor based on random forest in PET-CT images

NASA Astrophysics Data System (ADS)

Jiang, Xueqing; Xiang, Dehui; Zhang, Bin; Zhu, Weifang; Shi, Fei; Chen, Xinjian

2016-03-01

In this paper, a fully automatic method is proposed to segment the lung tumor in clinical 3D PET-CT images. The proposed method effectively combines PET and CT information to make full use of the high contrast of PET images and superior spatial resolution of CT images. Our approach consists of three main parts: (1) initial segmentation, in which spines are removed in CT images and initial connected regions achieved by thresholding based segmentation in PET images; (2) coarse segmentation, in which monotonic downhill function is applied to rule out structures which have similar standardized uptake values (SUV) to the lung tumor but do not satisfy a monotonic property in PET images; (3) fine segmentation, random forests method is applied to accurately segment the lung tumor by extracting effective features from PET and CT images simultaneously. We validated our algorithm on a dataset which consists of 24 3D PET-CT images from different patients with non-small cell lung cancer (NSCLC). The average TPVF, FPVF and accuracy rate (ACC) were 83.65%, 0.05% and 99.93%, respectively. The correlation analysis shows our segmented lung tumor volumes has strong correlation ( average 0.985) with the ground truth 1 and ground truth 2 labeled by a clinical expert.

Diagnostic accuracy of a volume-rendered computed tomography movie and other computed tomography-based imaging methods in assessment of renal vascular anatomy for laparoscopic donor nephrectomy.

PubMed

Yamamoto, Shingo; Tanooka, Masao; Ando, Kumiko; Yamano, Toshiko; Ishikura, Reiichi; Nojima, Michio; Hirota, Shozo; Shima, Hiroki

2009-12-01

To evaluate the diagnostic accuracy of computed tomography (CT)-based imaging methods for assessing renal vascular anatomy, imaging studies, including standard axial CT, three-dimensional volume-rendered CT (3DVR-CT), and a 3DVR-CT movie, were performed on 30 patients who underwent laparoscopic donor nephrectomy (10 right side, 20 left side) for predicting the location of the renal arteries and renal, adrenal, gonadal, and lumbar veins. These findings were compared with videos obtained during the operation. Two of 37 renal arteries observed intraoperatively were missed by standard axial CT and 3DVR-CT, whereas all arteries were identified by the 3DVR-CT movie. Two of 36 renal veins were missed by standard axial CT and 3DVR-CT, whereas 1 was missed by the 3DVR-CT movie. In 20 left renal hilar anatomical structures, 20 adrenal, 20 gonadal, and 22 lumbar veins were observed during the operation. Preoperatively, the standard axial CT, 3DVR-CT, and 3DVR-CT movie detected 11, 19, and 20 adrenal veins; 13, 14, and 19 gonadal veins; and 6, 11, and 15 lumbar veins, respectively. Overall, of 135 renal vascular structures, the standard axial CT, 3DVR-CT, and 3DVR-CT movie accurately detected 99 (73.3%), 113 (83.7%), and 126 (93.3%) vessels, respectively, which indicated that the 3DVR-CT movie demonstrated a significantly higher detection rate than other CT-based imaging methods (P < 0.05). The 3DVR-CT movie accurately provides essential information about the renal vascular anatomy before laparoscopic donor nephrectomy.

Qualitative and Quantitative Imaging Evaluation of Renal Cell Carcinoma Subtypes with Grating-based X-ray Phase-contrast CT

NASA Astrophysics Data System (ADS)

Braunagel, Margarita; Birnbacher, Lorenz; Willner, Marian; Marschner, Mathias; De Marco, Fabio; Viermetz, Manuel; Notohamiprodjo, Susan; Hellbach, Katharina; Auweter, Sigrid; Link, Vera; Woischke, Christine; Reiser, Maximilian F.; Pfeiffer, Franz; Notohamiprodjo, Mike; Herzen, Julia

2017-03-01

Current clinical imaging methods face limitations in the detection and correct characterization of different subtypes of renal cell carcinoma (RCC), while these are important for therapy and prognosis. The present study evaluates the potential of grating-based X-ray phase-contrast computed tomography (gbPC-CT) for visualization and characterization of human RCC subtypes. The imaging results for 23 ex vivo formalin-fixed human kidney specimens obtained with phase-contrast CT were compared to the results of the absorption-based CT (gbCT), clinical CT and a 3T MRI and validated using histology. Regions of interest were placed on each specimen for quantitative evaluation. Qualitative and quantitative gbPC-CT imaging could significantly discriminate between normal kidney cortex (54 ± 4 HUp) and clear cell (42 ± 10), papillary (43 ± 6) and chromophobe RCCs (39 ± 7), p < 0.05 respectively. The sensitivity for detection of tumor areas was 100%, 50% and 40% for gbPC-CT, gbCT and clinical CT, respectively. RCC architecture like fibrous strands, pseudocapsules, necrosis or hyalinization was depicted clearly in gbPC-CT and was not equally well visualized in gbCT, clinical CT and MRI. The results show that gbPC-CT enables improved discrimination of normal kidney parenchyma and tumorous tissues as well as different soft-tissue components of RCCs without the use of contrast media.

False dyssynchrony: problem with image-based cardiac functional analysis using x-ray computed tomography

NASA Astrophysics Data System (ADS)

Kidoh, Masafumi; Shen, Zeyang; Suzuki, Yuki; Ciuffo, Luisa; Ashikaga, Hiroshi; Fung, George S. K.; Otake, Yoshito; Zimmerman, Stefan L.; Lima, Joao A. C.; Higuchi, Takahiro; Lee, Okkyun; Sato, Yoshinobu; Becker, Lewis C.; Fishman, Elliot K.; Taguchi, Katsuyuki

2017-03-01

We have developed a digitally synthesized patient which we call "Zach" (Zero millisecond Adjustable Clinical Heart) phantom, which allows for an access to the ground truth and assessment of image-based cardiac functional analysis (CFA) using CT images with clinically realistic settings. The study using Zach phantom revealed a major problem with image-based CFA: "False dyssynchrony." Even though the true motion of wall segments is in synchrony, it may appear to be dyssynchrony with the reconstructed cardiac CT images. It is attributed to how cardiac images are reconstructed and how wall locations are updated over cardiac phases. The presence and the degree of false dyssynchrony may vary from scan-to-scan, which could degrade the accuracy and the repeatability (or precision) of image-based CT-CFA exams.

Lab-based x-ray nanoCT imaging

NASA Astrophysics Data System (ADS)

Müller, Mark; Allner, Sebastian; Ferstl, Simone; Dierolf, Martin; Tuohimaa, Tomi; Pfeiffer, Franz

2017-03-01

Due to the recent development of transmission X-ray tubes with very small focal spot sizes, laboratory-based CT imaging with sub-micron resolutions is nowadays possible. We recently developed a novel X-ray nanoCT setup featuring a prototype nanofocus X-ray source and a single-photon counting detector. The system is based on mere geometrical magnification and can reach resolutions of 200 nm. To demonstrate the potential of the nanoCT system for biomedical applications we show high resolution nanoCT data of a small piece of human tooth comprising coronal dentin. The reconstructed CT data clearly visualize the dentin tubules within the tooth piece.

Accuracy of lung nodule density on HRCT: analysis by PSF-based image simulation.

PubMed

Ohno, Ken; Ohkubo, Masaki; Marasinghe, Janaka C; Murao, Kohei; Matsumoto, Toru; Wada, Shinichi

2012-11-08

A computed tomography (CT) image simulation technique based on the point spread function (PSF) was applied to analyze the accuracy of CT-based clinical evaluations of lung nodule density. The PSF of the CT system was measured and used to perform the lung nodule image simulation. Then, the simulated image was resampled at intervals equal to the pixel size and the slice interval found in clinical high-resolution CT (HRCT) images. On those images, the nodule density was measured by placing a region of interest (ROI) commonly used for routine clinical practice, and comparing the measured value with the true value (a known density of object function used in the image simulation). It was quantitatively determined that the measured nodule density depended on the nodule diameter and the image reconstruction parameters (kernel and slice thickness). In addition, the measured density fluctuated, depending on the offset between the nodule center and the image voxel center. This fluctuation was reduced by decreasing the slice interval (i.e., with the use of overlapping reconstruction), leading to a stable density evaluation. Our proposed method of PSF-based image simulation accompanied with resampling enables a quantitative analysis of the accuracy of CT-based evaluations of lung nodule density. These results could potentially reveal clinical misreadings in diagnosis, and lead to more accurate and precise density evaluations. They would also be of value for determining the optimum scan and reconstruction parameters, such as image reconstruction kernels and slice thicknesses/intervals.

Dual-energy-based metal segmentation for metal artifact reduction in dental computed tomography.

PubMed

Hegazy, Mohamed A A; Eldib, Mohamed Elsayed; Hernandez, Daniel; Cho, Myung Hye; Cho, Min Hyoung; Lee, Soo Yeol

2018-02-01

In a dental CT scan, the presence of dental fillings or dental implants generates severe metal artifacts that often compromise readability of the CT images. Many metal artifact reduction (MAR) techniques have been introduced, but dental CT scans still suffer from severe metal artifacts particularly when multiple dental fillings or implants exist around the region of interest. The high attenuation coefficient of teeth often causes erroneous metal segmentation, compromising the MAR performance. We propose a metal segmentation method for a dental CT that is based on dual-energy imaging with a narrow energy gap. Unlike a conventional dual-energy CT, we acquire two projection data sets at two close tube voltages (80 and 90 kV p ), and then, we compute the difference image between the two projection images with an optimized weighting factor so as to maximize the contrast of the metal regions. We reconstruct CT images from the weighted difference image to identify the metal region with global thresholding. We forward project the identified metal region to designate metal trace on the projection image. We substitute the pixel values on the metal trace with the ones computed by the region filling method. The region filling in the metal trace removes high-intensity data made by the metallic objects from the projection image. We reconstruct final CT images from the region-filled projection image with the fusion-based approach. We have done imaging experiments on a dental phantom and a human skull phantom using a lab-built micro-CT and a commercial dental CT system. We have corrected the projection images of a dental phantom and a human skull phantom using the single-energy and dual-energy-based metal segmentation methods. The single-energy-based method often failed in correcting the metal artifacts on the slices on which tooth enamel exists. The dual-energy-based method showed better MAR performances in all cases regardless of the presence of tooth enamel on the slice of interest. We have compared the MAR performances between both methods in terms of the relative error (REL), the sum of squared difference (SSD) and the normalized absolute difference (NAD). For the dental phantom images corrected by the single-energy-based method, the metric values were 95.3%, 94.5%, and 90.6%, respectively, while they were 90.1%, 90.05%, and 86.4%, respectively, for the images corrected by the dual-energy-based method. For the human skull phantom images, the metric values were improved from 95.6%, 91.5%, and 89.6%, respectively, to 88.2%, 82.5%, and 81.3%, respectively. The proposed dual-energy-based method has shown better performance in metal segmentation leading to better MAR performance in dental imaging. We expect the proposed metal segmentation method can be used to improve the MAR performance of existing MAR techniques that have metal segmentation steps in their correction procedures. © 2017 American Association of Physicists in Medicine.

Attenuation correction of emission PET images with average CT: Interpolation from breath-hold CT

NASA Astrophysics Data System (ADS)

Huang, Tzung-Chi; Zhang, Geoffrey; Chen, Chih-Hao; Yang, Bang-Hung; Wu, Nien-Yun; Wang, Shyh-Jen; Wu, Tung-Hsin

2011-05-01

Misregistration resulting from the difference of temporal resolution in PET and CT scans occur frequently in PET/CT imaging, which causes distortion in tumor quantification in PET. Respiration cine average CT (CACT) for PET attenuation correction has been reported to improve the misalignment effectively by several papers. However, the radiation dose to the patient from a four-dimensional CT scan is relatively high. In this study, we propose a method to interpolate respiratory CT images over a respiratory cycle from inhalation and exhalation breath-hold CT images, and use the average CT from the generated CT set for PET attenuation correction. The radiation dose to the patient is reduced using this method. Six cancer patients of various lesion sites underwent routine free-breath helical CT (HCT), respiration CACT, interpolated average CT (IACT), and 18F-FDG PET. Deformable image registration was used to interpolate the middle phases of a respiratory cycle based on the end-inspiration and end-expiration breath-hold CT scans. The average CT image was calculated from the eight interpolated CT image sets of middle respiratory phases and the two original inspiration and expiration CT images. Then the PET images were reconstructed by these three methods for attenuation correction using HCT, CACT, and IACT. Misalignment of PET image using either CACT or IACT for attenuation correction in PET/CT was improved. The difference in standard uptake value (SUV) from tumor in PET images was most significant between the use of HCT and CACT, while the least significant between the use of CACT and IACT. Besides the similar improvement in tumor quantification compared to the use of CACT, using IACT for PET attenuation correction reduces the radiation dose to the patient.

Quality Assurance Assessment of Diagnostic and Radiation Therapy–Simulation CT Image Registration for Head and Neck Radiation Therapy: Anatomic Region of Interest–based Comparison of Rigid and Deformable Algorithms

PubMed Central

Mohamed, Abdallah S. R.; Ruangskul, Manee-Naad; Awan, Musaddiq J.; Baron, Charles A.; Kalpathy-Cramer, Jayashree; Castillo, Richard; Castillo, Edward; Guerrero, Thomas M.; Kocak-Uzel, Esengul; Yang, Jinzhong; Court, Laurence E.; Kantor, Michael E.; Gunn, G. Brandon; Colen, Rivka R.; Frank, Steven J.; Garden, Adam S.; Rosenthal, David I.

2015-01-01

Purpose To develop a quality assurance (QA) workflow by using a robust, curated, manually segmented anatomic region-of-interest (ROI) library as a benchmark for quantitative assessment of different image registration techniques used for head and neck radiation therapy–simulation computed tomography (CT) with diagnostic CT coregistration. Materials and Methods Radiation therapy–simulation CT images and diagnostic CT images in 20 patients with head and neck squamous cell carcinoma treated with curative-intent intensity-modulated radiation therapy between August 2011 and May 2012 were retrospectively retrieved with institutional review board approval. Sixty-eight reference anatomic ROIs with gross tumor and nodal targets were then manually contoured on images from each examination. Diagnostic CT images were registered with simulation CT images rigidly and by using four deformable image registration (DIR) algorithms: atlas based, B-spline, demons, and optical flow. The resultant deformed ROIs were compared with manually contoured reference ROIs by using similarity coefficient metrics (ie, Dice similarity coefficient) and surface distance metrics (ie, 95% maximum Hausdorff distance). The nonparametric Steel test with control was used to compare different DIR algorithms with rigid image registration (RIR) by using the post hoc Wilcoxon signed-rank test for stratified metric comparison. Results A total of 2720 anatomic and 50 tumor and nodal ROIs were delineated. All DIR algorithms showed improved performance over RIR for anatomic and target ROI conformance, as shown for most comparison metrics (Steel test, P < .008 after Bonferroni correction). The performance of different algorithms varied substantially with stratification by specific anatomic structures or category and simulation CT section thickness. Conclusion Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation. © RSNA, 2014 Online supplemental material is available for this article. PMID:25380454

The relevance of MRI for patient modeling in head and neck hyperthermia treatment planning: a comparison of CT and CT-MRI based tissue segmentation on simulated temperature.

PubMed

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van der Lugt, Aad; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-12-01

In current clinical practice, head and neck (H&N) hyperthermia treatment planning (HTP) is solely based on computed tomography (CT) images. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast over CT. The purpose of the authors' study is to investigate the relevance of using MRI in addition to CT for patient modeling in H&N HTP. CT and MRI scans were acquired for 11 patients in an immobilization mask. Three observers manually segmented on CT, MRI T1 weighted (MRI-T1w), and MRI T2 weighted (MRI-T2w) images the following thermo-sensitive tissues: cerebrum, cerebellum, brainstem, myelum, sclera, lens, vitreous humor, and the optical nerve. For these tissues that are used for patient modeling in H&N HTP, the interobserver variation of manual tissue segmentation in CT and MRI was quantified with the mean surface distance (MSD). Next, the authors compared the impact of CT and CT and MRI based patient models on the predicted temperatures. For each tissue, the modality was selected that led to the lowest observer variation and inserted this in the combined CT and MRI based patient model (CT and MRI), after a deformable image registration. In addition, a patient model with a detailed segmentation of brain tissues (including white matter, gray matter, and cerebrospinal fluid) was created (CT and MRIdb). To quantify the relevance of MRI based segmentation for H&N HTP, the authors compared the predicted maximum temperatures in the segmented tissues (Tmax) and the corresponding specific absorption rate (SAR) of the patient models based on (1) CT, (2) CT and MRI, and (3) CT and MRIdb. In MRI, a similar or reduced interobserver variation was found compared to CT (maximum of median MSD in CT: 0.93 mm, MRI-T1w: 0.72 mm, MRI-T2w: 0.66 mm). Only for the optical nerve the interobserver variation is significantly lower in CT compared to MRI (median MSD in CT: 0.58 mm, MRI-T1w: 1.27 mm, MRI-T2w: 1.40 mm). Patient models based on CT (Tmax: 38.0 °C) and CT and MRI (Tmax: 38.1 °C) result in similar simulated temperatures, while CT and MRIdb (Tmax: 38.5 °C) resulted in significantly higher temperatures. The SAR corresponding to these temperatures did not differ significantly. Although MR imaging reduces the interobserver variation in most tissues, it does not affect simulated local tissue temperatures. However, the improved soft-tissue contrast provided by MRI allows generating a detailed brain segmentation, which has a strong impact on the predicted local temperatures and hence may improve simulation guided hyperthermia.

Model-based iterative reconstruction for reduction of radiation dose in abdominopelvic CT: comparison to adaptive statistical iterative reconstruction.

PubMed

Yasaka, Koichiro; Katsura, Masaki; Akahane, Masaaki; Sato, Jiro; Matsuda, Izuru; Ohtomo, Kuni

2013-12-01

To evaluate dose reduction and image quality of abdominopelvic computed tomography (CT) reconstructed with model-based iterative reconstruction (MBIR) compared to adaptive statistical iterative reconstruction (ASIR). In this prospective study, 85 patients underwent referential-, low-, and ultralow-dose unenhanced abdominopelvic CT. Images were reconstructed with ASIR for low-dose (L-ASIR) and ultralow-dose CT (UL-ASIR), and with MBIR for ultralow-dose CT (UL-MBIR). Image noise was measured in the abdominal aorta and iliopsoas muscle. Subjective image analyses and a lesion detection study (adrenal nodules) were conducted by two blinded radiologists. A reference standard was established by a consensus panel of two different radiologists using referential-dose CT reconstructed with filtered back projection. Compared to low-dose CT, there was a 63% decrease in dose-length product with ultralow-dose CT. UL-MBIR had significantly lower image noise than L-ASIR and UL-ASIR (all p<0.01). UL-MBIR was significantly better for subjective image noise and streak artifacts than L-ASIR and UL-ASIR (all p<0.01). There were no significant differences between UL-MBIR and L-ASIR in diagnostic acceptability (p>0.65), or diagnostic performance for adrenal nodules (p>0.87). MBIR significantly improves image noise and streak artifacts compared to ASIR, and can achieve radiation dose reduction without severely compromising image quality.

Material Separation Using Dual-Energy CT: Current and Emerging Applications.

PubMed

Patino, Manuel; Prochowski, Andrea; Agrawal, Mukta D; Simeone, Frank J; Gupta, Rajiv; Hahn, Peter F; Sahani, Dushyant V

2016-01-01

Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.

Statistical distributions of ultra-low dose CT sinograms and their fundamental limits

NASA Astrophysics Data System (ADS)

Lee, Tzu-Cheng; Zhang, Ruoqiao; Alessio, Adam M.; Fu, Lin; De Man, Bruno; Kinahan, Paul E.

2017-03-01

Low dose CT imaging is typically constrained to be diagnostic. However, there are applications for even lowerdose CT imaging, including image registration across multi-frame CT images and attenuation correction for PET/CT imaging. We define this as the ultra-low-dose (ULD) CT regime where the exposure level is a factor of 10 lower than current low-dose CT technique levels. In the ULD regime it is possible to use statistically-principled image reconstruction methods that make full use of the raw data information. Since most statistical based iterative reconstruction methods are based on the assumption of that post-log noise distribution is close to Poisson or Gaussian, our goal is to understand the statistical distribution of ULD CT data with different non-positivity correction methods, and to understand when iterative reconstruction methods may be effective in producing images that are useful for image registration or attenuation correction in PET/CT imaging. We first used phantom measurement and calibrated simulation to reveal how the noise distribution deviate from normal assumption under the ULD CT flux environment. In summary, our results indicate that there are three general regimes: (1) Diagnostic CT, where post-log data are well modeled by normal distribution. (2) Lowdose CT, where normal distribution remains a reasonable approximation and statistically-principled (post-log) methods that assume a normal distribution have an advantage. (3) An ULD regime that is photon-starved and the quadratic approximation is no longer effective. For instance, a total integral density of 4.8 (ideal pi for 24 cm of water) for 120kVp, 0.5mAs of radiation source is the maximum pi value where a definitive maximum likelihood value could be found. This leads to fundamental limits in the estimation of ULD CT data when using a standard data processing stream

MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Peter C.; Schreibmann, Eduard; Roper, Justin

2015-03-15

Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR.more » Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.« less

Image fusion in craniofacial virtual reality modeling based on CT and 3dMD photogrammetry.

PubMed

Xin, Pengfei; Yu, Hongbo; Cheng, Huanchong; Shen, Shunyao; Shen, Steve G F

2013-09-01

The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface. A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed. Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm. The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.

The CT image standardization based on the verified PSF

NASA Astrophysics Data System (ADS)

Wada, Shinichi; Ohkubo, Masaki; Kunii, Masayuki; Matsumoto, Toru; Murao, Kohei; Awai, Kazuo; Ikeda, Mitsuru

2007-03-01

This study discusses a method of CT image quality standardization that uses a point-spread function (PSF) in MDCT. CT image I(x,y,z) is represented by the following formula: I(x,y,z) = O(x,y,z)***PSF(x,y,z). Standardization was performed by measuring the three-dimensional (3-D) PSFs of two CT images with different image qualities. The image conversion method was constructed and tested using the 3-D PSFs and CT images of the CT scanners of three different manufacturers. The CT scanners used were Lightspeed QX/i, Somatom Volume Zoom, and Brilliance-40. To obtain the PSF(x,y) of these CT scanners, the line spread functions of the respective reconstruction kernels were measured using a phantom described by J.M. Boone. The kernels for each scanner were: soft, standard, lung, bone, and bone plus (GE); B20f, B40f, B41f, B50f, and B60f (Siemens); and B, C, D, E, and L (Philips). Slice sensitivity profile (SSP) were measured using a micro-disk phantom (50 μm* φ1 mm) with 5 mm slice thickness and beam pitch of 1.5 (GE, Siemens) and 0.626 (Philips). 3-D PSF was verified using an MDCT QA phantom. Real chest CT images were converted to images with contrasting standard image quality. Comparison between the converted CT image and the original standard image showed good agreement. The usefulness of the image conversion method is discussed using clinical CT images acquired by CT scanners produced by different manufacturers.

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, H; Xing, L; Liang, Z

Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern formore » each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal

Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance andmore » diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.« less

Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging.

PubMed

Kolb, Christoph; Wetscherek, Andreas; Buzan, Maria Teodora; Werner, René; Rank, Christopher M; Kachelrie, Marc; Kreuter, Michael; Dinkel, Julien; Heuel, Claus Peter; Maier-Hein, Klaus

We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.

Stereotactic ultrasound for target volume definition in a patient with prostate cancer and bilateral total hip replacement.

PubMed

Boda-Heggemann, Judit; Haneder, Stefan; Ehmann, Michael; Sihono, Dwi Seno Kuncoro; Wertz, Hansjörg; Mai, Sabine; Kegel, Stefan; Heitmann, Sigrun; von Swietochowski, Sandra; Lohr, Frank; Wenz, Frederik

2015-01-01

Target-volume definition for prostate cancer in patients with bilateral metal total hip replacements (THRs) is a challenge because of metal artifacts in the planning computed tomography (CT) scans. Magnetic resonance imaging (MRI) can be used for matching and prostate delineation; however, at a spatial and temporal distance from the planning CT, identical rectal and vesical filling is difficult to achieve. In addition, MRI may also be impaired by metal artifacts, even resulting in spatial image distortion. Here, we present a method to define prostate target volumes based on ultrasound images acquired during CT simulation and online-matched to the CT data set directly at the planning CT. A 78-year-old patient with cT2cNxM0 prostate cancer with bilateral metal THRs was referred to external beam radiation therapy. T2-weighted MRI was performed on the day of the planning CT with preparation according to a protocol for reproducible bladder and rectal filling. The planning CT was obtained with the immediate acquisition of a 3-dimensional ultrasound data set with a dedicated stereotactic ultrasound system for online intermodality image matching referenced to the isocenter by ceiling-mounted infrared cameras. MRI (offline) and ultrasound images (online) were thus both matched to the CT images for planning. Daily image guided radiation therapy (IGRT) was performed with transabdominal ultrasound and compared with cone beam CT. Because of variations in bladder and rectal filling and metal-induced image distortion in MRI, soft-tissue-based matching of the MRI to CT was not sufficient for unequivocal prostate target definition. Ultrasound-based images could be matched, and prostate, seminal vesicles, and target volumes were reliably defined. Daily IGRT could be successfully completed with transabdominal ultrasound with good accordance between cone beam CT and ultrasound. For prostate cancer patients with bilateral THRs causing artifacts in planning CTs, ultrasound referenced to the isocenter of the CT simulator and acquired with intermodal online coregistration directly at the planning CT is a fast and easy method to reliably delineate the prostate and target volumes and for daily IGRT. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Translation of Atherosclerotic Plaque Phase-Contrast CT Imaging from Synchrotron Radiation to a Conventional Lab-Based X-Ray Source

PubMed Central

Saam, Tobias; Herzen, Julia; Hetterich, Holger; Fill, Sandra; Willner, Marian; Stockmar, Marco; Achterhold, Klaus; Zanette, Irene; Weitkamp, Timm; Schüller, Ulrich; Auweter, Sigrid; Adam-Neumair, Silvia; Nikolaou, Konstantin; Reiser, Maximilian F.; Pfeiffer, Franz; Bamberg, Fabian

2013-01-01

Objectives Phase-contrast imaging is a novel X-ray based technique that provides enhanced soft tissue contrast. The aim of this study was to evaluate the feasibility of visualizing human carotid arteries by grating-based phase-contrast tomography (PC-CT) at two different experimental set-ups: (i) applying synchrotron radiation and (ii) using a conventional X-ray tube. Materials and Methods Five ex-vivo carotid artery specimens were examined with PC-CT either at the European Synchrotron Radiation Facility using a monochromatic X-ray beam (2 specimens; 23 keV; pixel size 5.4 µm), or at a laboratory set-up on a conventional X-ray tube (3 specimens; 35-40 kVp; 70 mA; pixel size 100 µm). Tomographic images were reconstructed and compared to histopathology. Two independent readers determined vessel dimensions and one reader determined signal-to-noise ratios (SNR) between PC-CT and absorption images. Results In total, 51 sections were included in the analysis. Images from both set-ups provided sufficient contrast to differentiate individual vessel layers. All PCI-based measurements strongly predicted but significantly overestimated lumen, intima and vessel wall area for both the synchrotron and the laboratory-based measurements as compared with histology (all p<0.001 with slope >0.53 per mm2, 95%-CI: 0.35 to 0.70). Although synchrotron-based images were characterized by higher SNRs than laboratory-based images; both PC-CT set-ups had superior SNRs compared to corresponding conventional absorption-based images (p<0.001). Inter-reader reproducibility was excellent (ICCs >0.98 and >0.84 for synchrotron and for laboratory-based measurements; respectively). Conclusion Experimental PC-CT of carotid specimens is feasible with both synchrotron and conventional X-ray sources, producing high-resolution images suitable for vessel characterization and atherosclerosis research. PMID:24039969

[Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images].

PubMed

Zhang, Dongxia; Gan, Yangzhou; Xiong, Jing; Xia, Zeyang

2017-02-01

Complete three-dimensional(3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography(CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs, i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete3 D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.

NEMA image quality phantom measurements and attenuation correction in integrated PET/MR hybrid imaging.

PubMed

Ziegler, Susanne; Jakoby, Bjoern W; Braun, Harald; Paulus, Daniel H; Quick, Harald H

2015-12-01

In integrated PET/MR hybrid imaging the evaluation of PET performance characteristics according to the NEMA standard NU 2-2007 is challenging because of incomplete MR-based attenuation correction (AC) for phantom imaging. In this study, a strategy for CT-based AC of the NEMA image quality (IQ) phantom is assessed. The method is systematically evaluated in NEMA IQ phantom measurements on an integrated PET/MR system. NEMA IQ measurements were performed on the integrated 3.0 Tesla PET/MR hybrid system (Biograph mMR, Siemens Healthcare). AC of the NEMA IQ phantom was realized by an MR-based and by a CT-based method. The suggested CT-based AC uses a template μ-map of the NEMA IQ phantom and a phantom holder for exact repositioning of the phantom on the systems patient table. The PET image quality parameters contrast recovery, background variability, and signal-to-noise ratio (SNR) were determined and compared for both phantom AC methods. Reconstruction parameters of an iterative 3D OP-OSEM reconstruction were optimized for highest lesion SNR in NEMA IQ phantom imaging. Using a CT-based NEMA IQ phantom μ-map on the PET/MR system is straightforward and allowed performing accurate NEMA IQ measurements on the hybrid system. MR-based AC was determined to be insufficient for PET quantification in the tested NEMA IQ phantom because only photon attenuation caused by the MR-visible phantom filling but not the phantom housing is considered. Using the suggested CT-based AC, the highest SNR in this phantom experiment for small lesions (<= 13 mm) was obtained with 3 iterations, 21 subsets and 4 mm Gaussian filtering. This study suggests CT-based AC for the NEMA IQ phantom when performing PET NEMA IQ measurements on an integrated PET/MR hybrid system. The superiority of CT-based AC for this phantom is demonstrated by comparison to measurements using MR-based AC. Furthermore, optimized PET image reconstruction parameters are provided for the highest lesion SNR in NEMA IQ phantom measurements.

Infrared laser transillumination CT imaging system using parallel fiber arrays and optical switches for finger joint imaging

NASA Astrophysics Data System (ADS)

Sasaki, Yoshiaki; Emori, Ryota; Inage, Hiroki; Goto, Masaki; Takahashi, Ryo; Yuasa, Tetsuya; Taniguchi, Hiroshi; Devaraj, Balasigamani; Akatsuka, Takao

2004-05-01

The heterodyne detection technique, on which the coherent detection imaging (CDI) method founds, can discriminate and select very weak, highly directional forward scattered, and coherence retaining photons that emerge from scattering media in spite of their complex and highly scattering nature. That property enables us to reconstruct tomographic images using the same reconstruction technique as that of X-Ray CT, i.e., the filtered backprojection method. Our group had so far developed a transillumination laser CT imaging method based on the CDI method in the visible and near-infrared regions and reconstruction from projections, and reported a variety of tomographic images both in vitro and in vivo of biological objects to demonstrate the effectiveness to biomedical use. Since the previous system was not optimized, it took several hours to obtain a single image. For a practical use, we developed a prototype CDI-based imaging system using parallel fiber array and optical switches to reduce the measurement time significantly. Here, we describe a prototype transillumination laser CT imaging system using fiber-optic based on optical heterodyne detection for early diagnosis of rheumatoid arthritis (RA), by demonstrating the tomographic imaging of acrylic phantom as well as the fundamental imaging properties. We expect that further refinements of the fiber-optic-based laser CT imaging system could lead to a novel and practical diagnostic tool for rheumatoid arthritis and other joint- and bone-related diseases in human finger.

Automatic anatomy partitioning of the torso region on CT images by using multiple organ localizations with a group-wise calibration technique

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Morita, Syoichi; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi

2015-03-01

This paper describes an automatic approach for anatomy partitioning on three-dimensional (3D) computedtomography (CT) images that divide the human torso into several volume-of-interesting (VOI) images based on anatomical definition. The proposed approach combines several individual detections of organ-location with a groupwise organ-location calibration and correction to achieve an automatic and robust multiple-organ localization task. The essence of the proposed method is to jointly detect the 3D minimum bounding box for each type of organ shown on CT images based on intra-organ-image-textures and inter-organ-spatial-relationship in the anatomy. Machine-learning-based template matching and generalized Hough transform-based point-distribution estimation are used in the detection and calibration processes. We apply this approach to the automatic partitioning of a torso region on CT images, which are divided into 35 VOIs presenting major organ regions and tissues required by routine diagnosis in clinical medicine. A database containing 4,300 patient cases of high-resolution 3D torso CT images is used for training and performance evaluations. We confirmed that the proposed method was successful in target organ localization on more than 95% of CT cases. Only two organs (gallbladder and pancreas) showed a lower success rate: 71 and 78% respectively. In addition, we applied this approach to another database that included 287 patient cases of whole-body CT images scanned for positron emission tomography (PET) studies and used for additional performance evaluation. The experimental results showed that no significant difference between the anatomy partitioning results from those two databases except regarding the spleen. All experimental results showed that the proposed approach was efficient and useful in accomplishing localization tasks for major organs and tissues on CT images scanned using different protocols.

Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

NASA Astrophysics Data System (ADS)

Dong, Jian; Kudo, Hiroyuki

2017-03-01

Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

Point spread function modeling and image restoration for cone-beam CT

NASA Astrophysics Data System (ADS)

Zhang, Hua; Huang, Kui-Dong; Shi, Yi-Kai; Xu, Zhe

2015-03-01

X-ray cone-beam computed tomography (CT) has such notable features as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection image degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed first. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection image restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection image restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods. Supported by National Science and Technology Major Project of the Ministry of Industry and Information Technology of China (2012ZX04007021), Young Scientists Fund of National Natural Science Foundation of China (51105315), Natural Science Basic Research Program of Shaanxi Province of China (2013JM7003) and Northwestern Polytechnical University Foundation for Fundamental Research (JC20120226, 3102014KYJD022)

Imaging of cellular spread on a three-dimensional scaffold by means of a novel cell-labeling technique for high-resolution computed tomography.

PubMed

Thimm, Benjamin W; Hofmann, Sandra; Schneider, Philipp; Carretta, Roberto; Müller, Ralph

2012-03-01

Computed tomography (CT) represents a truly three-dimensional (3D) imaging technique that can provide high-resolution images on the cellular level. Thus, one approach to detect single cells is X-ray absorption-based CT, where cells are labeled with a dense, opaque material providing the required contrast for CT imaging. Within the present work, a novel cell-labeling method has been developed showing the feasibility of labeling fixed cells with iron oxide (FeO) particles for subsequent CT imaging and quantitative morphometry. A biotin-streptavidin detection system was exploited to bind FeO particles to its target endothelial cells. The binding of the particles was predominantly close to the cell centers on 2D surfaces as shown by light microscopy, scanning electron microscopy, and CT. When cells were cultured on porous, 3D polyurethane surfaces, significantly more FeO particles were detected compared with surfaces without cells and FeO particle labeling using CT. Here, we report on the implementation and evaluation of a novel cell detection method based on high-resolution CT. This system has potential in cell tracking for 3D in vitro imaging in the future.

Validation of a deformable image registration technique for cone beam CT-based dose verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moteabbed, M., E-mail: mmoteabbed@partners.org; Sharp, G. C.; Wang, Y.

2015-01-15

Purpose: As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (DIR) for prostate treatments. Methods: A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformedmore » CT. The registration quality was assessed as the ability of the DIR method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it’s suitability to be used for dose calculation. PLASTIMATCH, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. Results: The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field lengths decreased from 10.1 to 2.5 mm when CBCT was calibrated prior to registration. The results showed no dependence on the level of bladder filling. In comparison with the dose calculated on the primary deformed CT, differences in mean dose averaged over all organs were 0.2% and 3.9% for dose calculated on the secondary deformed CT with and without CBCT calibration, respectively, and 0.5% for dose calculated directly on the calibrated CBCT, for the full-bladder scenario. Gamma analysis for the distance to agreement of 2 mm and 2% of prescribed dose indicated a pass rate of 100% for both cases involving calibrated CBCT and on average 86% without CBCT calibration. Conclusions: Using deformable registration on the planning CT images to evaluate the IMRT dose based on daily CBCTs was found feasible. The proposed method will provide an accurate dose distribution using planning CT and pretreatment CBCT data, avoiding the additional uncertainties introduced by CBCT inhomogeneity and artifacts. This is a necessary initial step toward future image-guided adaptive radiotherapy of the prostate.« less

Texture-preserved penalized weighted least-squares reconstruction of low-dose CT image via image segmentation and high-order MRF modeling

NASA Astrophysics Data System (ADS)

Han, Hao; Zhang, Hao; Wei, Xinzhou; Moore, William; Liang, Zhengrong

2016-03-01

In this paper, we proposed a low-dose computed tomography (LdCT) image reconstruction method with the help of prior knowledge learning from previous high-quality or normal-dose CT (NdCT) scans. The well-established statistical penalized weighted least squares (PWLS) algorithm was adopted for image reconstruction, where the penalty term was formulated by a texture-based Gaussian Markov random field (gMRF) model. The NdCT scan was firstly segmented into different tissue types by a feature vector quantization (FVQ) approach. Then for each tissue type, a set of tissue-specific coefficients for the gMRF penalty was statistically learnt from the NdCT image via multiple-linear regression analysis. We also proposed a scheme to adaptively select the order of gMRF model for coefficients prediction. The tissue-specific gMRF patterns learnt from the NdCT image were finally used to form an adaptive MRF penalty for the PWLS reconstruction of LdCT image. The proposed texture-adaptive PWLS image reconstruction algorithm was shown to be more effective to preserve image textures than the conventional PWLS image reconstruction algorithm, and we further demonstrated the gain of high-order MRF modeling for texture-preserved LdCT PWLS image reconstruction.

Application of a computed tomography based cystic fibrosis scoring system to chest tomosynthesis

NASA Astrophysics Data System (ADS)

Söderman, Christina; Johnsson, Åse; Vikgren, Jenny; Rystedt, Hans; Ivarsson, Jonas; Rossi Norrlund, Rauni; Nyberg Andersson, Lena; Bâth, Magnus

2013-03-01

In the monitoring of progression of lung disease in patients with cystic fibrosis (CF), recurrent computed tomography (CT) examinations are often used. The relatively new imaging technique chest tomosynthesis (CTS) may be an interesting alternative in the follow-up of these patients due to its visualization of the chest in slices at radiation doses and costs significantly lower than is the case with CT. A first step towards introducing CTS imaging in the diagnostics of CF patients is to establish a scoring system appropriate for evaluating the severity of CF pulmonary disease based on findings in CTS images. Previously, several such CF scoring systems based on CT imaging have been published. The purpose of the present study was to develop a CF scoring system for CTS, by starting from an existing scoring system dedicated for CT images and making modifications regarded necessary to make it appropriate for use with CTS images. In order to determine any necessary changes, three thoracic radiologists independently used a scoring system dedicated for CT on both CT and CTS images from CF patients. The results of the scoring were jointly evaluated by all the observers, which lead to suggestions for changes to the scoring system. Suggested modifications include excluding the scoring of air trapping and doing the scoring of the findings in quadrants of the image instead of in each lung lobe.

Hybrid registration of PET/CT in thoracic region with pre-filtering PET sinogram

NASA Astrophysics Data System (ADS)

Mokri, S. S.; Saripan, M. I.; Marhaban, M. H.; Nordin, A. J.; Hashim, S.

2015-11-01

The integration of physiological (PET) and anatomical (CT) images in cancer delineation requires an accurate spatial registration technique. Although hybrid PET/CT scanner is used to co-register these images, significant misregistrations exist due to patient and respiratory/cardiac motions. This paper proposes a hybrid feature-intensity based registration technique for hybrid PET/CT scanner. First, simulated PET sinogram was filtered with a 3D hybrid mean-median before reconstructing the image. The features were then derived from the segmented structures (lung, heart and tumor) from both images. The registration was performed based on modified multi-modality demon registration with multiresolution scheme. Apart from visual observations improvements, the proposed registration technique increased the normalized mutual information index (NMI) between the PET/CT images after registration. All nine tested datasets show marked improvements in mutual information (MI) index than free form deformation (FFD) registration technique with the highest MI increase is 25%.

FDG-PET/CT imaging for tumor staging and definition of tumor volumes in radiation treatment planning in non-small cell lung cancer.

PubMed

Zheng, Yuanda; Sun, Xiaojiang; Wang, Jian; Zhang, Lingnan; DI, Xiaoyun; Xu, Yaping

2014-04-01

18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) has the potential to improve the staging and radiation treatment (RT) planning of various tumor sites. However, from a clinical standpoint, questions remain with regard to what extent PET/CT changes the target volume and whether PET/CT reduces interobserver variability in target volume delineation. The present study analyzed the use of FDG-PET/CT images for staging and evaluated the impact of FDG-PET/CT on the radiotherapy volume delineation compared with CT in patients with non-small cell lung cancer (NSCLC) who were candidates for radiotherapy. Intraobserver variation in delineating tumor volumes was also observed. In total, 23 patients with stage I-III NSCLC were enrolled and treated with fractionated RT-based therapy with or without chemotherapy. FDG-PET/CT scans were acquired within two weeks prior to RT. PET and CT data sets were sent to the treatment planning system, Pinnacle, through compact discs. The CT and PET images were subsequently fused by means of a dedicated RT planning system. Gross tumor volume (GTV) was contoured by four radiation oncologists on CT (GTV-CT) and PET/CT images (GTV-PET/CT). The resulting volumes were analyzed and compared. For the first phase, two radiation oncologists outlined the contours together, achieving a final consensus. Based on PET/CT, changes in tumor-node-metastasis categories occurred in 8/23 cases (35%). Radiation targeting with fused FDG-PET and CT images resulted in alterations in radiation therapy planning in 12/20 patients (60%) in comparison with CT targeting. The most prominent changes in GTV were observed in cases with atelectasis. For the second phase, the variation in delineating tumor volumes was assessed by four observers. The mean ratio of largest to smallest CT-based GTV was 2.31 (range, 1.01-5.96). The addition of the PET results reduced the mean ratio to 1.46 (range, 1.02-2.27). PET/CT fusion images may have a potential impact on tumor staging and treatment planning. Implementing matched PET/CT results reduced observer variation in delineating tumor volumes significantly with respect to CT only.

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Accuracy of UTE-MRI-based patient setup for brain cancer radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yingli; Cao, Minsong; Kaprealian, Tania

2016-01-15

Purpose: Radiation therapy simulations solely based on MRI have advantages compared to CT-based approaches. One feature readily available from computed tomography (CT) that would need to be reproduced with MR is the ability to compute digitally reconstructed radiographs (DRRs) for comparison against on-board radiographs commonly used for patient positioning. In this study, the authors generate MR-based bone images using a single ultrashort echo time (UTE) pulse sequence and quantify their 3D and 2D image registration accuracy to CT and radiographic images for treatments in the cranium. Methods: Seven brain cancer patients were scanned at 1.5 T using a radial UTEmore » sequence. The sequence acquired two images at two different echo times. The two images were processed using an in-house software to generate the UTE bone images. The resultant bone images were rigidly registered to simulation CT data and the registration error was determined using manually annotated landmarks as references. DRRs were created based on UTE-MRI and registered to simulated on-board images (OBIs) and actual clinical 2D oblique images from ExacTrac™. Results: UTE-MRI resulted in well visualized cranial, facial, and vertebral bones that quantitatively matched the bones in the CT images with geometric measurement errors of less than 1 mm. The registration error between DRRs generated from 3D UTE-MRI and the simulated 2D OBIs or the clinical oblique x-ray images was also less than 1 mm for all patients. Conclusions: UTE-MRI-based DRRs appear to be promising for daily patient setup of brain cancer radiotherapy with kV on-board imaging.« less

SU-F-J-172: Hybrid MR/CT Compatible Phantom for MR-Only Based Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, M; Lee, S; Song, K

2016-06-15

Purpose: Development of hybrid MR/CT compatible phantom was introduced to fully establish MR image only radiation treatment and this suggested technique using in-house developed hybrid MR/CT compatible phantom image would utilize to generate radiation treatment planning and perform dose calculation without multi-modal registration process or generation of pseudo CT. Methods: Fundamental characteristics for “hybrid MR/CT compatible phantom” was established: Relaxation times equivalent to human tissue, dielectric properties, homogeneous relaxation times, sufficient strength to fabricate a torso, ease of handling, a wide variety of density material for calibration, chemical and physical stability over an extended time. For this requirements, chemical componentmore » in each tested plug which would be tissue equivalent to human tissue on MR and CT image and production of phantom body and plug was performed. Chemical component has described below: Agaros, GdCl{sub 3}, NaN{sub 3}, NaCl, K{sub 2}Co{sub 3}, deionized-distilled water. Various mixture of chemical component to simulate human tissue on both MR and CT image was tested by measuring T1, T2 relaxation time and signal intensity (SI) on MR image and Hounsfield unit (HU) on CT and each value was compared. The hybrid MR/CT compatible phantom with 14 plugs was designed and has made. Total height and external diameter was decided by internal size of 32 channel MR head-coil. Results: Tissue-equivalent chemical component materials and hybrid MR/CT compatible phantom was developed. The range of T1, T2 relaxation time and SI on MR image, HU on CT was acquired and could be adjusted to correspond to simulated human tissue. Conclusion: Current result shows its possibility for MR-only based radiotherapy and the best mixing rate of chemical component for tissue-equivalent image on MR and CT was founded. However, additional technical issues remain to be overcome. Conversion of SI on MR image into HU and dose calculation based on converted MRI will be progressing.« less

Investigation of ultra low-dose scans in the context of quantum-counting clinical CT

NASA Astrophysics Data System (ADS)

Weidinger, T.; Buzug, T. M.; Flohr, T.; Fung, G. S. K.; Kappler, S.; Stierstorfer, K.; Tsui, B. M. W.

2012-03-01

In clinical computed tomography (CT), images from patient examinations taken with conventional scanners exhibit noise characteristics governed by electronics noise, when scanning strongly attenuating obese patients or with an ultra-low X-ray dose. Unlike CT systems based on energy integrating detectors, a system with a quantum counting detector does not suffer from this drawback. Instead, the noise from the electronics mainly affects the spectral resolution of these detectors. Therefore, it does not contribute to the image noise in spectrally non-resolved CT images. This promises improved image quality due to image noise reduction in scans obtained from clinical CT examinations with lowest X-ray tube currents or obese patients. To quantify the benefits of quantum counting detectors in clinical CT we have carried out an extensive simulation study of the complete scanning and reconstruction process for both kinds of detectors. The simulation chain encompasses modeling of the X-ray source, beam attenuation in the patient, and calculation of the detector response. Moreover, in each case the subsequent image preprocessing and reconstruction is modeled as well. The simulation-based, theoretical evaluation is validated by experiments with a novel prototype quantum counting system and a Siemens Definition Flash scanner with a conventional energy integrating CT detector. We demonstrate and quantify the improvement from image noise reduction achievable with quantum counting techniques in CT examinations with ultra-low X-ray dose and strong attenuation.

Quality of routine diagnostic abdominal images generated from a novel detector-based spectral CT scanner: a technical report on a phantom and clinical study.

PubMed

Hojjati, Mojgan; Van Hedent, Steven; Rassouli, Negin; Tatsuoka, Curtis; Jordan, David; Dhanantwari, Amar; Rajiah, Prabhakar

2017-11-01

To evaluate the image quality of routine diagnostic images generated from a novel detector-based spectral detector CT (SDCT) and compare it with CT images obtained from a conventional scanner with an energy-integrating detector (Brilliance iCT), Routine diagnostic (conventional/polyenergetic) images are non-material-specific images that resemble single-energy images obtained at the same radiation, METHODS: ACR guideline-based phantom evaluations were performed on both SDCT and iCT for CT adult body protocol. Retrospective analysis was performed on 50 abdominal CT scans from each scanner. Identical ROIs were placed at multiple locations in the abdomen and attenuation, noise, SNR, and CNR were measured. Subjective image quality analysis on a 5-point Likert scale was performed by 2 readers for enhancement, noise, and image quality. On phantom studies, SDCT images met the ACR requirements for CT number and deviation, CNR and effective radiation dose. In patients, the qualitative scores were significantly higher for the SDCT than the iCT, including enhancement (4.79 ± 0.38 vs. 4.60 ± 0.51, p = 0.005), noise (4.63 ± 0.42 vs. 4.29 ± 0.50, p = 0.000), and quality (4.85 ± 0.32, vs. 4.57 ± 0.50, p = 0.000). The SNR was higher in SDCT than iCT for liver (7.4 ± 4.2 vs. 7.2 ± 5.3, p = 0.662), spleen (8.6 ± 4.1 vs. 7.4 ± 3.5, p = 0.152), kidney (11.1 ± 6.3 vs. 8.7 ± 5.0, p = 0.033), pancreas (6.90 ± 3.45 vs 6.11 ± 2.64, p = 0.303), aorta (14.2 ± 6.2 vs. 11.0 ± 4.9, p = 0.007), but was slightly lower in lumbar-vertebra (7.7 ± 4.2 vs. 7.8 ± 4.5, p = 0.937). The CNR of the SDCT was also higher than iCT for all abdominal organs. Image quality of routine diagnostic images from the SDCT is comparable to images of a conventional CT scanner with energy-integrating detectors, making it suitable for diagnostic purposes.

Implementation of an image sharing system significantly reduced repeat computed tomographic imaging in a regional trauma system.

PubMed

Banerjee, Aman; Zosa, Brenda M; Allen, Debra; Wilczewski, Patricia A; Ferguson, Robert; Claridge, Jeffrey A

2016-01-01

The practice of repeating computed tomography (re-CT) is common among trauma patients transferred between hospitals incurring additional cost and radiation exposure. This study sought to evaluate the effectiveness of implementing modern cloud-based technology (lifeIMAGE) across a regional trauma system to reduce the incidence of re-CT imaging. This is a prospective interventional study to evaluate outcomes after implementation of lifeIMAGE in January 2012. Key outcomes were rates of CT imaging, including the rates and costs of re-CT from January 2009 through December 2012. There were 1,081 trauma patients transferred from participating hospitals during the study period (657 patients before and 425 patients after implementation), with the overall re-CT rate of 20.5%. Rates of any CT imaging at referring hospitals decreased (62% vs. 55%, p < 0.05) and also decreased at the accepting regional Level I center (58% vs. 52%, p < 0.05) following system implementation. There were 639 patients (59%) who had CT imaging performed before transfer (404 patients before and 235 patients after implementation). Of these patients, the overall re-CT rate decreased from 38.4% to 28.1% (p = 0.01). Rates of re-CT of the head (21% vs. 11%, p = 0.002), chest (7% vs. 3%, p = 0.05), as well as abdomen and pelvis (12% vs. 5%, p = 0.007) were significantly reduced following system implementation. The cost of repeat imaging per patient was significantly lower following system implementation (mean charges, $1,046 vs. $589; p < 0.001). These results were more pronounced in a subgroup of patients with an Injury Severity Score (ISS) of greater than 14, with a reduction in overall re-CT rate from 51% to 30% (p = 0.03). The implementation of modern cloud-based technology across the regional trauma system resulted in significant reductions in re-CT imaging and cost. Therapeutic/care management study, level IV; economic analysis, level IV.

Automated segmentation of hepatic vessel trees in non-contrast x-ray CT images

NASA Astrophysics Data System (ADS)

Kawajiri, Suguru; Zhou, Xiangrong; Zhang, Xuejin; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki

2007-03-01

Hepatic vessel trees are the key structures in the liver. Knowledge of the hepatic vessel trees is important for liver surgery planning and hepatic disease diagnosis such as portal hypertension. However, hepatic vessels cannot be easily distinguished from other liver tissues in non-contrast CT images. Automated segmentation of hepatic vessels in non-contrast CT images is a challenging issue. In this paper, an approach for automated segmentation of hepatic vessels trees in non-contrast X-ray CT images is proposed. Enhancement of hepatic vessels is performed using two techniques: (1) histogram transformation based on a Gaussian window function; (2) multi-scale line filtering based on eigenvalues of Hessian matrix. After the enhancement of hepatic vessels, candidate of hepatic vessels are extracted by thresholding. Small connected regions of size less than 100 voxels are considered as false-positives and are removed from the process. This approach is applied to 20 cases of non-contrast CT images. Hepatic vessel trees segmented from the contrast-enhanced CT images of the same patient are used as the ground truth in evaluating the performance of the proposed segmentation method. Results show that the proposed method can enhance and segment the hepatic vessel regions in non-contrast CT images correctly.

The segmentation of bones in pelvic CT images based on extraction of key frames.

PubMed

Yu, Hui; Wang, Haijun; Shi, Yao; Xu, Ke; Yu, Xuyao; Cao, Yuzhen

2018-05-22

Bone segmentation is important in computed tomography (CT) imaging of the pelvis, which assists physicians in the early diagnosis of pelvic injury, in planning operations, and in evaluating the effects of surgical treatment. This study developed a new algorithm for the accurate, fast, and efficient segmentation of the pelvis. The proposed method consists of two main parts: the extraction of key frames and the segmentation of pelvic CT images. Key frames were extracted based on pixel difference, mutual information and normalized correlation coefficient. In the pelvis segmentation phase, skeleton extraction from CT images and a marker-based watershed algorithm were combined to segment the pelvis. To meet the requirements of clinical application, physician's judgment is needed. Therefore the proposed methodology is semi-automated. In this paper, 5 sets of CT data were used to test the overlapping area, and 15 CT images were used to determine the average deviation distance. The average overlapping area of the 5 sets was greater than 94%, and the minimum average deviation distance was approximately 0.58 pixels. In addition, the key frame extraction efficiency and the running time of the proposed method were evaluated on 20 sets of CT data. For each set, approximately 13% of the images were selected as key frames, and the average processing time was approximately 2 min (the time for manual marking was not included). The proposed method is able to achieve accurate, fast, and efficient segmentation of pelvic CT image sequences. Segmentation results not only provide an important reference for early diagnosis and decisions regarding surgical procedures, they also offer more accurate data for medical image registration, recognition and 3D reconstruction.

The value of 99mTc-MAA SPECT/CT for lung shunt estimation in 90Y radioembolization: a phantom and patient study.

PubMed

Allred, Jonathan D; Niedbala, Jeremy; Mikell, Justin K; Owen, Dawn; Frey, Kirk A; Dewaraja, Yuni K

2018-06-15

A major toxicity concern in radioembolization therapy of hepatic malignancies is radiation-induced pneumonitis and sclerosis due to hepatopulmonary shunting of 90 Y microspheres. Currently, 99m Tc macroaggregated albumin ( 99m Tc-MAA) imaging is used to estimate the lung shunt fraction (LSF) prior to treatment. The aim of this study was to evaluate the accuracy/precision of LSF estimated from 99m Tc planar and SPECT/CT phantom imaging, and within this context, to compare the corresponding LSF and lung-absorbed dose values from 99m Tc-MAA patient studies. Additionally, LSFs from pre- and post-therapy imaging were compared. A liver/lung torso phantom filled with 99m Tc to achieve three lung shunt values was scanned by planar and SPECT/CT imaging with repeat acquisitions to assess accuracy and precision. To facilitate processing of patient data, a workflow that relies on SPECT and CT-based auto-contouring to define liver and lung volumes for the LSF calculation was implemented. Planar imaging-based LSF estimates for 40 patients, obtained from their medical records, were retrospectively compared with SPECT/CT imaging-based calculations with attenuation and scatter correction. Additionally, in a subset of 20 patients, the pre-therapy estimates were compared with 90 Y PET/CT-based measurements. In the phantom study, improved accuracy in LSF estimation was achieved using SPECT/CT with attenuation and scatter correction (within 13% of the true value) compared with planar imaging (up to 44% overestimation). The results in patients showed a similar trend with planar imaging significantly overestimating LSF compared to SPECT/CT. There was no correlation between lung shunt estimates and the delay between 99m Tc-MAA administration and scanning, but off-target extra hepatic uptake tended to be more likely in patients with a longer delay. The mean lung absorbed dose predictions for the 28 patients who underwent therapy was 9.3 Gy (range 1.3-29.4) for planar imaging and 3.2 Gy (range 0.4-13.4) for SPECT/CT. For the patients with post-therapy imaging, the mean LSF from 90 Y PET/CT was 1.0%, (range 0.3-2.8). This value was not significantly different from the mean LSF estimate from 99m Tc-MAA SPECT/CT (mean 1.0%, range 0.4-1.6; p = 0.968), but was significantly lower than the mean LSF estimate based on planar imaging (mean 4.1%, range 1.2-15.0; p = 0.0002). The improved accuracy demonstrated by the phantom study, agreement with 90 Y PET/CT in patient studies, and the practicality of using auto-contouring for liver/lung definition suggests that 99m Tc-MAA SPECT/CT with scatter and attenuation corrections should be used for lung shunt estimation prior to radioembolization.

TU-G-BRA-02: Can We Extract Lung Function Directly From 4D-CT Without Deformable Image Registration?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kipritidis, J; Woodruff, H; Counter, W

Purpose: Dynamic CT ventilation imaging (CT-VI) visualizes air volume changes in the lung by evaluating breathing-induced lung motion using deformable image registration (DIR). Dynamic CT-VI could enable functionally adaptive lung cancer radiation therapy, but its sensitivity to DIR parameters poses challenges for validation. We hypothesize that a direct metric using CT parameters derived from Hounsfield units (HU) alone can provide similar ventilation images without DIR. We compare the accuracy of Direct and Dynamic CT-VIs versus positron emission tomography (PET) images of inhaled {sup 68}Ga-labelled nanoparticles (‘Galligas’). Methods: 25 patients with lung cancer underwent Galligas 4D-PET/CT scans prior to radiation therapy.more » For each patient we produced three CT- VIs. (i) Our novel method, Direct CT-VI, models blood-gas exchange as the product of air and tissue density at each lung voxel based on time-averaged 4D-CT HU values. Dynamic CT-VIs were produced by evaluating: (ii) regional HU changes, and (iii) regional volume changes between the exhale and inhale 4D-CT phase images using a validated B-spline DIR method. We assessed the accuracy of each CT-VI by computing the voxel-wise Spearman correlation with free-breathing Galligas PET, and also performed a visual analysis. Results: Surprisingly, Direct CT-VIs exhibited better global correlation with Galligas PET than either of the dynamic CT-VIs. The (mean ± SD) correlations were (0.55 ± 0.16), (0.41 ± 0.22) and (0.29 ± 0.27) for Direct, Dynamic HU-based and Dynamic volume-based CT-VIs respectively. Visual comparison of Direct CT-VI to PET demonstrated similarity for emphysema defects and ventral-to-dorsal gradients, but inability to identify decreased ventilation distal to tumor-obstruction. Conclusion: Our data supports the hypothesis that Direct CT-VIs are as accurate as Dynamic CT-VIs in terms of global correlation with Galligas PET. Visual analysis, however, demonstrated that different CT-VI algorithms might have varying accuracy depending on the underlying cause of ventilation abnormality. This research was supported by a National Health and Medical Research Council (NHMRC) Australia Fellowship, an Cancer Institute New South Wales Early Career Fellowship 13-ECF-1/15 and NHMRC scholarship APP1038399. No commercial funding was received for this work.« less

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion.

PubMed

Yang, Y X; Teo, S-K; Van Reeth, E; Tan, C H; Tham, I W K; Poh, C L

2015-08-01

Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors' proposed approach. A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors' proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

Fast 3D registration of multimodality tibial images with significant structural mismatch

NASA Astrophysics Data System (ADS)

Rajapakse, C. S.; Wald, M. J.; Magland, J.; Zhang, X. H.; Liu, X. S.; Guo, X. E.; Wehrli, F. W.

2009-02-01

Recently, micro-magnetic resonance imaging (μMRI) in conjunction with micro-finite element analysis has shown great potential in estimating mechanical properties - stiffness and elastic moduli - of bone in patients at risk of osteoporosis. Due to limited spatial resolution and signal-to-noise ratio achievable in vivo, the validity of estimated properties is often established by comparison to those derived from high-resolution micro-CT (μCT) images of cadaveric specimens. For accurate comparison of mechanical parameters derived from μMR and μCT images, analyzed 3D volumes have to be closely matched. The alignment of the micro structure (and the cortex) is often hampered by the fundamental differences of μMR and μCT images and variations in marrow content and cortical bone thickness. Here we present an intensity cross-correlation based registration algorithm coupled with segmentation for registering 3D tibial specimen images acquired by μMRI and μCT in the context of finite-element modeling to assess the bone's mechanical constants. The algorithm first generates three translational and three rotational parameters required to align segmented μMR and CT images from sub regions with high micro-structural similarities. These transformation parameters are then used to register the grayscale μMR and μCT images, which include both the cortex and trabecular bone. The intensity crosscorrelation maximization based registration algorithm described here is suitable for 3D rigid-body image registration applications where through-plane rotations are known to be relatively small. The close alignment of the resulting images is demonstrated quantitatively based on a voxel-overlap measure and qualitatively using visual inspection of the micro structure.

Volumetric CT-images improve testing of radiological image interpretation skills.

PubMed

Ravesloot, Cécile J; van der Schaaf, Marieke F; van Schaik, Jan P J; ten Cate, Olle Th J; van der Gijp, Anouk; Mol, Christian P; Vincken, Koen L

2015-05-01

Current radiology practice increasingly involves interpretation of volumetric data sets. In contrast, most radiology tests still contain only 2D images. We introduced a new testing tool that allows for stack viewing of volumetric images in our undergraduate radiology program. We hypothesized that tests with volumetric CT-images enhance test quality, in comparison with traditional completely 2D image-based tests, because they might better reflect required skills for clinical practice. Two groups of medical students (n=139; n=143), trained with 2D and volumetric CT-images, took a digital radiology test in two versions (A and B), each containing both 2D and volumetric CT-image questions. In a questionnaire, they were asked to comment on the representativeness for clinical practice, difficulty and user-friendliness of the test questions and testing program. Students' test scores and reliabilities, measured with Cronbach's alpha, of 2D and volumetric CT-image tests were compared. Estimated reliabilities (Cronbach's alphas) were higher for volumetric CT-image scores (version A: .51 and version B: .54), than for 2D CT-image scores (version A: .24 and version B: .37). Participants found volumetric CT-image tests more representative of clinical practice, and considered them to be less difficult than volumetric CT-image questions. However, in one version (A), volumetric CT-image scores (M 80.9, SD 14.8) were significantly lower than 2D CT-image scores (M 88.4, SD 10.4) (p<.001). The volumetric CT-image testing program was considered user-friendly. This study shows that volumetric image questions can be successfully integrated in students' radiology testing. Results suggests that the inclusion of volumetric CT-images might improve the quality of radiology tests by positively impacting perceived representativeness for clinical practice and increasing reliability of the test. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Initial In Vivo Quantification of Tc-99m Sestamibi Uptake as a Function of Tissue Type in Healthy Breasts Using Dedicated Breast SPECT-CT

PubMed Central

Mann, Steve D.; Perez, Kristy L.; McCracken, Emily K. E.; Shah, Jainil P.; Wong, Terence Z.; Tornai, Martin P.

2012-01-01

A pilot study is underway to quantify in vivo the uptake and distribution of Tc-99m Sestamibi in subjects without previous history of breast cancer using a dedicated SPECT-CT breast imaging system. Subjects undergoing diagnostic parathyroid imaging studies were consented and imaged as part of this IRB-approved breast imaging study. For each of the seven subjects, one randomly selected breast was imaged prone-pendant using the dedicated, compact breast SPECT-CT system underneath the shielded patient support. Iteratively reconstructed and attenuation and/or scatter corrected images were coregistered; CT images were segmented into glandular and fatty tissue by three different methods; the average concentration of Sestamibi was determined from the SPECT data using the CT-based segmentation and previously established quantification techniques. Very minor differences between the segmentation methods were observed, and the results indicate an average image-based in vivo Sestamibi concentration of 0.10 ± 0.16 μCi/mL with no preferential uptake by glandular or fatty tissues. PMID:22956950

A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Korhonen, Juha, E-mail: juha.p.korhonen@hus.fi; Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS; Kapanen, Mika

2014-01-15

Purpose: The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents. Methods: T{sub 1}/T{sub 2}*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRImore » intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm. Results: The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from −2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images. Conclusions: This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.« less

CT of the chest with model-based, fully iterative reconstruction: comparison with adaptive statistical iterative reconstruction.

PubMed

Ichikawa, Yasutaka; Kitagawa, Kakuya; Nagasawa, Naoki; Murashima, Shuichi; Sakuma, Hajime

2013-08-09

The recently developed model-based iterative reconstruction (MBIR) enables significant reduction of image noise and artifacts, compared with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP). The purpose of this study was to evaluate lesion detectability of low-dose chest computed tomography (CT) with MBIR in comparison with ASIR and FBP. Chest CT was acquired with 64-slice CT (Discovery CT750HD) with standard-dose (5.7 ± 2.3 mSv) and low-dose (1.6 ± 0.8 mSv) conditions in 55 patients (aged 72 ± 7 years) who were suspected of lung disease on chest radiograms. Low-dose CT images were reconstructed with MBIR, ASIR 50% and FBP, and standard-dose CT images were reconstructed with FBP, using a reconstructed slice thickness of 0.625 mm. Two observers evaluated the image quality of abnormal lung and mediastinal structures on a 5-point scale (Score 5 = excellent and score 1 = non-diagnostic). The objective image noise was also measured as the standard deviation of CT intensity in the descending aorta. The image quality score of enlarged mediastinal lymph nodes on low-dose MBIR CT (4.7 ± 0.5) was significantly improved in comparison with low-dose FBP and ASIR CT (3.0 ± 0.5, p = 0.004; 4.0 ± 0.5, p = 0.02, respectively), and was nearly identical to the score of standard-dose FBP image (4.8 ± 0.4, p = 0.66). Concerning decreased lung attenuation (bulla, emphysema, or cyst), the image quality score on low-dose MBIR CT (4.9 ± 0.2) was slightly better compared to low-dose FBP and ASIR CT (4.5 ± 0.6, p = 0.01; 4.6 ± 0.5, p = 0.01, respectively). There were no significant differences in image quality scores of visualization of consolidation or mass, ground-glass attenuation, or reticular opacity among low- and standard-dose CT series. Image noise with low-dose MBIR CT (11.6 ± 1.0 Hounsfield units (HU)) were significantly lower than with low-dose ASIR (21.1 ± 2.6 HU, p < 0.0005), low-dose FBP CT (30.9 ± 3.9 HU, p < 0.0005), and standard-dose FBP CT (16.6 ± 2.3 HU, p < 0.0005). MBIR shows greater potential than ASIR for providing diagnostically acceptable low-dose CT without compromising image quality. With radiation dose reduction of >70%, MBIR can provide equivalent lesion detectability of standard-dose FBP CT.

Prostate seed implant quality assessment using MR and CT image fusion.

PubMed

Amdur, R J; Gladstone, D; Leopold, K A; Harris, R D

1999-01-01

After a seed implant of the prostate, computerized tomography (CT) is ideal for determining seed distribution but soft tissue anatomy is frequently not well visualized. Magnetic resonance (MR) images soft tissue anatomy well but seed visualization is problematic. We describe a method of fusing CT and MR images to exploit the advantages of both of these modalities when assessing the quality of a prostate seed implant. Eleven consecutive prostate seed implant patients were imaged with axial MR and CT scans. MR and CT images were fused in three dimensions using the Pinnacle 3.0 version of the ADAC treatment planning system. The urethra and bladder base were used to "line up" MR and CT image sets during image fusion. Alignment was accomplished using translation and rotation in the three ortho-normal planes. Accuracy of image fusion was evaluated by calculating the maximum deviation in millimeters between the center of the urethra on axial MR versus CT images. Implant quality was determined by comparing dosimetric results to previously set parameters. Image fusion was performed with a high degree of accuracy. When lining up the urethra and base of bladder, the maximum difference in axial position of the urethra between MR and CT averaged 2.5 mm (range 1.3-4.0 mm, SD 0.9 mm). By projecting CT-derived dose distributions over MR images of soft tissue structures, qualitative and quantitative evaluation of implant quality is straightforward. The image-fusion process we describe provides a sophisticated way of assessing the quality of a prostate seed implant. Commercial software makes the process time-efficient and available to any clinical practice with a high-quality treatment planning system. While we use MR to image soft tissue structures, the process could be used with any imaging modality that is able to visualize the prostatic urethra (e.g., ultrasound).

Iterative CT shading correction with no prior information

NASA Astrophysics Data System (ADS)

Wu, Pengwei; Sun, Xiaonan; Hu, Hongjie; Mao, Tingyu; Zhao, Wei; Sheng, Ke; Cheung, Alice A.; Niu, Tianye

2015-11-01

Shading artifacts in CT images are caused by scatter contamination, beam-hardening effect and other non-ideal imaging conditions. The purpose of this study is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT images (e.g. cone-beam CT, low-kVp CT) without relying on prior information. The method is based on the general knowledge of the relatively uniform CT number distribution in one tissue component. The CT image is first segmented to construct a template image where each structure is filled with the same CT number of a specific tissue type. Then, by subtracting the ideal template from the CT image, the residual image from various error sources are generated. Since forward projection is an integration process, non-continuous shading artifacts in the image become continuous signals in a line integral. Thus, the residual image is forward projected and its line integral is low-pass filtered in order to estimate the error that causes shading artifacts. A compensation map is reconstructed from the filtered line integral error using a standard FDK algorithm and added back to the original image for shading correction. As the segmented image does not accurately depict a shaded CT image, the proposed scheme is iterated until the variation of the residual image is minimized. The proposed method is evaluated using cone-beam CT images of a Catphan©600 phantom and a pelvis patient, and low-kVp CT angiography images for carotid artery assessment. Compared with the CT image without correction, the proposed method reduces the overall CT number error from over 200 HU to be less than 30 HU and increases the spatial uniformity by a factor of 1.5. Low-contrast object is faithfully retained after the proposed correction. An effective iterative algorithm for shading correction in CT imaging is proposed that is only assisted by general anatomical information without relying on prior knowledge. The proposed method is thus practical and attractive as a general solution to CT shading correction.

WE-AB-202-06: Correlating Lung CT HU with Transformation-Based and Xe-CT Derived Ventilation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Du, K; Patton, T; Bayouth, J

Purpose: Regional lung ventilation is useful to reduce radiation-induced function damage during lung cancer radiation therapy. Recently a new direct HU (Hounsfield unit)-based method was proposed to estimate the ventilation potential without image registration. The purpose of this study is to examine if there is a functional dependence between HU values and transformation-based or Xe-CT derived ventilation. Methods: 4DCT images acquired from 13 patients prior to radiation therapy and 4 mechanically ventilated sheep subjects which also have associated Xe-CT images were used for this analysis. Transformation-based ventilation was computed using Jacobian determinant of the transformation field between peak-exhale and peak-inhalemore » 4DCT images. Both transformation and Xe-CT derived ventilation was computed for each HU bin. Color scatter plot and cumulative histogram were used to compare and validate the direct HU-based method. Results: There was little change of the center and shape of the HU histograms between free breathing CT and 4DCT average, with or without smoothing, and between the repeated 4DCT scans. HU of −750 and −630 were found to have the greatest transformation-based ventilation for human and sheep subjects, respectively. Maximum Xe-CT derived ventilation was found to locate at HU of −600 in sheep subjects. The curve between Xe-CT ventilation and HU was noisy for tissue above HU −400, possibly due to less intensity change of Xe gas during wash-out and wash-in phases. Conclusion: Both transformation-based and Xe-CT ventilation demonstrated that lung tissues with HU values in the range of (-750, −600) HU have the maximum ventilation potential. The correlation between HU and ventilation suggests that HU might be used to help guide the ventilation calculation and make it more robust to noise and image registration errors. Research support from NIH grants CA166703 and CA166119 and a gift from Roger Koch.« less

Utility of Dual-Energy CT-based Monochromatic Imaging in the Assessment of Myocardial Delayed Enhancement in Patients with Cardiomyopathy.

PubMed

Chang, Suyon; Han, Kyunghwa; Youn, Jong-Chan; Im, Dong Jin; Kim, Jin Young; Suh, Young Joo; Hong, Yoo Jin; Hur, Jin; Kim, Young Jin; Choi, Byoung Wook; Lee, Hye-Jeong

2018-05-01

Purpose To investigate the diagnostic utility of dual-energy computed tomography (CT)-based monochromatic imaging for myocardial delayed enhancement (MDE) assessment in patients with cardiomyopathy. Materials and Methods The institutional review board approved this prospective study, and informed consent was obtained from all participants who were enrolled in the study. Forty patients (27 men and 13 women; mean age, 56 years ± 15 [standard deviation]; age range, 22-81 years) with cardiomyopathy underwent cardiac magnetic resonance (MR) imaging and dual-energy CT. Conventional (120-kV) and monochromatic (60-, 70-, and 80-keV) images were reconstructed from the dual-energy CT acquisition. Subjective quality score, contrast-to-noise ratio (CNR), and beam-hardening artifacts were compared pairwise with the Friedman test at post hoc analysis. With cardiac MR imaging as the reference standard, diagnostic performance of dual-energy CT in MDE detection and its predictive ability for pattern classification were compared pairwise by using logistic regression analysis with the generalized estimating equation in a per-segment analysis. The Bland-Altman method was used to find agreement between cardiac MR imaging and CT in MDE quantification. Results Among the monochromatic images, 70-keV CT images resulted in higher subjective quality (mean score, 3.38 ± 0.54 vs 3.15 ± 0.43; P = .0067), higher CNR (mean, 4.26 ± 1.38 vs 3.93 ± 1.33; P = .0047), and a lower value for beam-hardening artifacts (mean, 3.47 ± 1.56 vs 4.15 ± 1.67; P < .0001) when compared with conventional CT. When compared with conventional CT, 70-keV CT showed improved diagnostic performance for MDE detection (sensitivity, 94.6% vs 90.4% [P = .0032]; specificity, 96.0% vs 94.0% [P = .0031]; and accuracy, 95.6% vs 92.7% [P < .0001]) and improved predictive ability for pattern classification (subendocardial, 91.5% vs 84.3% [P = .0111]; epicardial, 94.3% vs 73.5% [P = .0001]; transmural, 93.0% vs 77.7% [P = .0018]; mesocardial, 85.4% vs 69.2% [P = .0047]; and patchy. 84.4% vs 78.4% [P = .1514]). For MDE quantification, 70-keV CT showed a small bias 0.1534% (95% limits of agreement: -4.7013, 5.0080). Conclusion Dual-energy CT-based 70-keV monochromatic images improve MDE assessment in patients with cardiomyopathy via improved image quality and CNR and reduced beam-hardening artifacts when compared with conventional CT images. © RSNA, 2017 Online supplemental material is available for this article.

Comparison of quantitative myocardial perfusion imaging CT to fluorescent microsphere-based flow from high-resolution cryo-images

NASA Astrophysics Data System (ADS)

Eck, Brendan L.; Fahmi, Rachid; Levi, Jacob; Fares, Anas; Wu, Hao; Li, Yuemeng; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2016-03-01

Myocardial perfusion imaging using CT (MPI-CT) has the potential to provide quantitative measures of myocardial blood flow (MBF) which can aid the diagnosis of coronary artery disease. We evaluated the quantitative accuracy of MPI-CT in a porcine model of balloon-induced LAD coronary artery ischemia guided by fractional flow reserve (FFR). We quantified MBF at baseline (FFR=1.0) and under moderate ischemia (FFR=0.7) using MPI-CT and compared to fluorescent microsphere-based MBF from high-resolution cryo-images. Dynamic, contrast-enhanced CT images were obtained using a spectral detector CT (Philips Healthcare). Projection-based mono-energetic images were reconstructed and processed to obtain MBF. Three MBF quantification approaches were evaluated: singular value decomposition (SVD) with fixed Tikhonov regularization (ThSVD), SVD with regularization determined by the L-Curve criterion (LSVD), and Johnson-Wilson parameter estimation (JW). The three approaches over-estimated MBF compared to cryo-images. JW produced the most accurate MBF, with average error 33.3+/-19.2mL/min/100g, whereas LSVD and ThSVD had greater over-estimation, 59.5+/-28.3mL/min/100g and 78.3+/-25.6 mL/min/100g, respectively. Relative blood flow as assessed by a flow ratio of LAD-to-remote myocardium was strongly correlated between JW and cryo-imaging, with R2=0.97, compared to R2=0.88 and 0.78 for LSVD and ThSVD, respectively. We assessed tissue impulse response functions (IRFs) from each approach for sources of error. While JW was constrained to physiologic solutions, both LSVD and ThSVD produced IRFs with non-physiologic properties due to noise. The L-curve provided noise-adaptive regularization but did not eliminate non-physiologic IRF properties or optimize for MBF accuracy. These findings suggest that model-based MPI-CT approaches may be more appropriate for quantitative MBF estimation and that cryo-imaging can support the development of MPI-CT by providing spatial distributions of MBF.

Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using {sup 68}Ga-labeled nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kipritidis, John, E-mail: john.kipritidis@sydney.edu.au; Keall, Paul J.; Siva, Shankar

Purpose: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with{sup 68}Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. Methods: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metricsmore » model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (V{sub HU}) or Jacobian determinant of deformation (V{sub Jac}). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρV{sub HU} and ρV{sub Jac}) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σ{sub m} = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d{sub 20} for the (0 − 20)th functional percentile volumes. Results: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρV{sub HU}) with σ{sub m} = 3 mm. This leads to correlation values in the ranges 0.22 ⩽ r ⩽ 0.76 and 0.38 ⩽ d{sub 20} ⩽ 0.68, with r{sup ¯}=0.42±0.16 and d{sup ¯}{sub 20}=0.52±0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant improvements in r{sup ¯} and d{sup ¯}{sub 20} (p < 0.05), with density scaled metrics also showing higher r{sup ¯} than for unscaled versions (p < 0.02). r{sup ¯} and d{sup ¯}{sub 20} were also sensitive to image quality, with statistically significant improvements using standard (as opposed to gated) PET images and with application of median filtering. Conclusions: The use of modified CT ventilation metrics, in conjunction with PET-Galligas and careful application of image filtering has resulted in improved correlation compared to earlier studies using nuclear medicine ventilation. However, CT ventilation and PET-Galligas do not always provide the same functional information. The authors have demonstrated that the agreement can improve for CT ventilation metrics incorporating a tissue density scaling, and also with increasing PET image quality. CT ventilation imaging has clear potential for imaging regional air volume change in the lung, and further development is warranted.« less

A 4DCT imaging-based breathing lung model with relative hysteresis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miyawaki, Shinjiro; Choi, Sanghun; Hoffman, Eric A.

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for bothmore » models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.« less

TU-A-12A-07: CT-Based Biomarkers to Characterize Lung Lesion: Effects of CT Dose, Slice Thickness and Reconstruction Algorithm Based Upon a Phantom Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, B; Tan, Y; Tsai, W

2014-06-15

Purpose: Radiogenomics promises the ability to study cancer tumor genotype from the phenotype obtained through radiographic imaging. However, little attention has been paid to the sensitivity of image features, the image-based biomarkers, to imaging acquisition techniques. This study explores the impact of CT dose, slice thickness and reconstruction algorithm on measuring image features using a thorax phantom. Methods: Twentyfour phantom lesions of known volume (1 and 2mm), shape (spherical, elliptical, lobular and spicular) and density (-630, -10 and +100 HU) were scanned on a GE VCT at four doses (25, 50, 100, and 200 mAs). For each scan, six imagemore » series were reconstructed at three slice thicknesses of 5, 2.5 and 1.25mm with continuous intervals, using the lung and standard reconstruction algorithms. The lesions were segmented with an in-house 3D algorithm. Fifty (50) image features representing lesion size, shape, edge, and density distribution/texture were computed. Regression method was employed to analyze the effect of CT dose, slice of thickness and reconstruction algorithm on these features adjusting 3 confounding factors (size, density and shape of phantom lesions). Results: The coefficients of CT dose, slice thickness and reconstruction algorithm are presented in Table 1 in the supplementary material. No significant difference was found between the image features calculated on low dose CT scans (25mAs and 50mAs). About 50% texture features were found statistically different between low doses and high doses (100 and 200mAs). Significant differences were found for almost all features when calculated on 1.25mm, 2.5mm, and 5mm slice thickness images. Reconstruction algorithms significantly affected all density-based image features, but not morphological features. Conclusions: There is a great need to standardize the CT imaging protocols for radiogenomics study because CT dose, slice thickness and reconstruction algorithm impact quantitative image features to various degrees as our study has shown.« less

A 4D global respiratory motion model of the thorax based on CT images: A proof of concept.

PubMed

Fayad, Hadi; Gilles, Marlene; Pan, Tinsu; Visvikis, Dimitris

2018-05-17

Respiratory motion reduces the sensitivity and specificity of medical images especially in the thoracic and abdominal areas. It may affect applications such as cancer diagnostic imaging and/or radiation therapy (RT). Solutions to this issue include modeling of the respiratory motion in order to optimize both diagnostic and therapeutic protocols. Personalized motion modeling required patient-specific four-dimensional (4D) imaging which in the case of 4D computed tomography (4D CT) acquisition is associated with an increased dose. The goal of this work was to develop a global respiratory motion model capable of relating external patient surface motion to internal structure motion without the need for a patient-specific 4D CT acquisition. The proposed global model is based on principal component analysis and can be adjusted to a given patient anatomy using only one or two static CT images in conjunction with a respiratory synchronized patient external surface motion. It is based on the relation between the internal motion described using deformation fields obtained by registering 4D CT images and patient surface maps obtained either from optical imaging devices or extracted from CT image-based patient skin segmentation. 4D CT images of six patients were used to generate the global motion model which was validated by adapting it on four different patients having skin segmented surfaces and two other patients having time of flight camera acquired surfaces. The reproducibility of the proposed model was also assessed on two patients with two 4D CT series acquired within 2 weeks of each other. Profile comparison shows the efficacy of the global respiratory motion model and an improvement while using two CT images in order to adapt the model. This was confirmed by the correlation coefficient with a mean correlation of 0.9 and 0.95 while using one or two CT images respectively and when comparing acquired to model generated 4D CT images. For the four patients with segmented surfaces, expert validation indicates an error of 2.35 ± 0.26 mm compared to 6.07 ± 0.76 mm when using a simple interpolation between full inspiration (FI) and full expiration (FE) CT only; i.e., without specific modeling of the respiratory motion. For the two patients with acquired surfaces, this error was of 2.48 ± 0.18 mm. In terms of reproducibility, model error changes of 0.12 and 0.17 mm were measured for the two patients concerned. The framework for the derivation of a global respiratory motion model was developed. A single or two static CT images and associated patient surface motion, as a surrogate measure, are only needed to personalize the model. This model accuracy and reproducibility were assessed by comparing acquired vs model generated 4D CT images. Future work will consist of assessing extensively the proposed model for radiotherapy applications. © 2018 American Association of Physicists in Medicine.

The effect of metal artefact reduction on CT-based attenuation correction for PET imaging in the vicinity of metallic hip implants: a phantom study.

PubMed

Harnish, Roy; Prevrhal, Sven; Alavi, Abass; Zaidi, Habib; Lang, Thomas F

2014-07-01

To determine if metal artefact reduction (MAR) combined with a priori knowledge of prosthesis material composition can be applied to obtain CT-based attenuation maps with sufficient accuracy for quantitative assessment of (18)F-fluorodeoxyglucose uptake in lesions near metallic prostheses. A custom hip prosthesis phantom with a lesion-sized cavity filled with 0.2 ml (18)F-FDG solution having an activity of 3.367 MBq adjacent to a prosthesis bore was imaged twice with a chrome-cobalt steel hip prosthesis and a plastic replica, respectively. Scanning was performed on a clinical hybrid PET/CT system equipped with an additional external (137)Cs transmission source. PET emission images were reconstructed from both phantom configurations with CT-based attenuation correction (CTAC) and with CT-based attenuation correction using MAR (MARCTAC). To compare results with the attenuation-correction method extant prior to the advent of PET/CT, we also carried out attenuation correction with (137)Cs transmission-based attenuation correction (TXAC). CTAC and MARCTAC images were scaled to attenuation coefficients at 511 keV using a trilinear function that mapped the highest CT values to the prosthesis alloy attenuation coefficient. Accuracy and spatial distribution of the lesion activity was compared between the three reconstruction schemes. Compared to the reference activity of 3.37 MBq, the estimated activity quantified from the PET image corrected by TXAC was 3.41 MBq. The activity estimated from PET images corrected by MARCTAC was similar in accuracy at 3.32 MBq. CTAC corrected PET images resulted in nearly 40 % overestimation of lesion activity at 4.70 MBq. Comparison of PET images obtained with the plastic and metal prostheses in place showed that CTAC resulted in a marked distortion of the (18)F-FDG distribution within the lesion, whereas application of MARCTAC and TXAC resulted in lesion distributions similar to those observed with the plastic replica. MAR combined with a trilinear CT number mapping for PET attenuation correction resulted in estimates of lesion activity comparable in accuracy to that obtained with (137)Cs transmission-based attenuation correction, and far superior to estimates made without attenuation correction or with a standard CT attenuation map. The ability to use CT images for attenuation correction is a potentially important development because it obviates the need for a (137)Cs transmission source, which entails extra scan time, logistical complexity and expense.

Comparison of Intraoperative Portable CT Scanners in Skull Base and Endoscopic Sinus Surgery: Single Center Case Series

PubMed Central

Conley, David B.; Tan, Bruce; Bendok, Bernard R.; Batjer, H. Hunt; Chandra, Rakesh; Sidle, Douglas; Rahme, Rudy J.; Adel, Joseph G.; Fishman, Andrew J.

2011-01-01

Precise and safe management of complex skull base lesions can be enhanced by intraoperative computed tomography (CT) scanning. Surgery in these areas requires real-time feedback of anatomic landmarks. Several portable CT scanners are currently available. We present a comparison of our clinical experience with three portable scanners in skull base and craniofacial surgery. We present clinical case series and the participants were from the Northwestern Memorial Hospital. Three scanners are studied: one conventional multidetector CT (MDCT), two digital flat panel cone-beam CT (CBCT) devices. Technical considerations, ease of use, image characteristics, and integration with image guidance are presented for each device. All three scanners provide good quality images. Intraoperative scanning can be used to update the image guidance system in real time. The conventional MDCT is unique in its ability to resolve soft tissue. The flat panel CBCT scanners generally emit lower levels of radiation and have less metal artifact effect. In this series, intraoperative CT scanning was technically feasible and deemed useful in surgical decision-making in 75% of patients. Intraoperative portable CT scanning has significant utility in complex skull base surgery. This technology informs the surgeon of the precise extent of dissection and updates intraoperative stereotactic navigation. PMID:22470270

Reducing image noise in computed tomography (CT) colonography: effect of an integrated circuit CT detector.

PubMed

Liu, Yu; Leng, Shuai; Michalak, Gregory J; Vrieze, Thomas J; Duan, Xinhui; Qu, Mingliang; Shiung, Maria M; McCollough, Cynthia H; Fletcher, Joel G

2014-01-01

To investigate whether the integrated circuit (IC) detector results in reduced noise in computed tomography (CT) colonography (CTC). Three hundred sixty-six consecutive patients underwent clinically indicated CTC using the same CT scanner system, except for a difference in CT detectors (IC or conventional). Image noise, patient size, and scanner radiation output (volume CT dose index) were quantitatively compared between patient cohorts using each detector system, with separate comparisons for the abdomen and pelvis. For the abdomen and pelvis, despite significantly larger patient sizes in the IC detector cohort (both P < 0.001), image noise was significantly lower (both P < 0.001), whereas volume CT dose index was unchanged (both P > 0.18). Based on the observed image noise reduction, radiation dose could alternatively be reduced by approximately 20% to result in similar levels of image noise. Computed tomography colonography images acquired using the IC detector had significantly lower noise than images acquired using the conventional detector. This noise reduction can permit further radiation dose reduction in CTC.

The relevance of MRI for patient modeling in head and neck hyperthermia treatment planning: A comparison of CT and CT-MRI based tissue segmentation on simulated temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verhaart, René F., E-mail: r.f.verhaart@erasmusmc.nl; Paulides, Margarethus M.; Fortunati, Valerio

Purpose: In current clinical practice, head and neck (H and N) hyperthermia treatment planning (HTP) is solely based on computed tomography (CT) images. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast over CT. The purpose of the authors’ study is to investigate the relevance of using MRI in addition to CT for patient modeling in H and N HTP. Methods: CT and MRI scans were acquired for 11 patients in an immobilization mask. Three observers manually segmented on CT, MRI T1 weighted (MRI-T1w), and MRI T2 weighted (MRI-T2w) images the following thermo-sensitive tissues: cerebrum, cerebellum, brainstem, myelum, sclera, lens, vitreousmore » humor, and the optical nerve. For these tissues that are used for patient modeling in H and N HTP, the interobserver variation of manual tissue segmentation in CT and MRI was quantified with the mean surface distance (MSD). Next, the authors compared the impact of CT and CT and MRI based patient models on the predicted temperatures. For each tissue, the modality was selected that led to the lowest observer variation and inserted this in the combined CT and MRI based patient model (CT and MRI), after a deformable image registration. In addition, a patient model with a detailed segmentation of brain tissues (including white matter, gray matter, and cerebrospinal fluid) was created (CT and MRI{sub db}). To quantify the relevance of MRI based segmentation for H and N HTP, the authors compared the predicted maximum temperatures in the segmented tissues (T{sub max}) and the corresponding specific absorption rate (SAR) of the patient models based on (1) CT, (2) CT and MRI, and (3) CT and MRI{sub db}. Results: In MRI, a similar or reduced interobserver variation was found compared to CT (maximum of median MSD in CT: 0.93 mm, MRI-T1w: 0.72 mm, MRI-T2w: 0.66 mm). Only for the optical nerve the interobserver variation is significantly lower in CT compared to MRI (median MSD in CT: 0.58 mm, MRI-T1w: 1.27 mm, MRI-T2w: 1.40 mm). Patient models based on CT (T{sub max}: 38.0 °C) and CT and MRI (T{sub max}: 38.1 °C) result in similar simulated temperatures, while CT and MRI{sub db} (T{sub max}: 38.5 °C) resulted in significantly higher temperatures. The SAR corresponding to these temperatures did not differ significantly. Conclusions: Although MR imaging reduces the interobserver variation in most tissues, it does not affect simulated local tissue temperatures. However, the improved soft-tissue contrast provided by MRI allows generating a detailed brain segmentation, which has a strong impact on the predicted local temperatures and hence may improve simulation guided hyperthermia.« less

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028

Intra-individual diagnostic image quality and organ-specific-radiation dose comparison between spiral cCT with iterative image reconstruction and z-axis automated tube current modulation and sequential cCT.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Gawlitza, Joshua; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Groden, Christoph; Henzler, Thomas

2016-01-01

To prospectively evaluate image quality and organ-specific-radiation dose of spiral cranial CT (cCT) combined with automated tube current modulation (ATCM) and iterative image reconstruction (IR) in comparison to sequential tilted cCT reconstructed with filtered back projection (FBP) without ATCM. 31 patients with a previous performed tilted non-contrast enhanced sequential cCT aquisition on a 4-slice CT system with only FBP reconstruction and no ATCM were prospectively enrolled in this study for a clinical indicated cCT scan. All spiral cCT examinations were performed on a 3rd generation dual-source CT system using ATCM in z-axis direction. Images were reconstructed using both, FBP and IR (level 1-5). A Monte-Carlo-simulation-based analysis was used to compare organ-specific-radiation dose. Subjective image quality for various anatomic structures was evaluated using a 4-point Likert-scale and objective image quality was evaluated by comparing signal-to-noise ratios (SNR). Spiral cCT led to a significantly lower (p < 0.05) organ-specific-radiation dose in all targets including eye lense. Subjective image quality of spiral cCT datasets with an IR reconstruction level 5 was rated significantly higher compared to the sequential cCT acquisitions (p < 0.0001). Consecutive mean SNR was significantly higher in all spiral datasets (FBP, IR 1-5) when compared to sequential cCT with a mean SNR improvement of 44.77% (p < 0.0001). Spiral cCT combined with ATCM and IR allows for significant-radiation dose reduction including a reduce eye lens organ-dose when compared to a tilted sequential cCT while improving subjective and objective image quality.

Accuracy of CT-based attenuation correction in PET/CT bone imaging

NASA Astrophysics Data System (ADS)

Abella, Monica; Alessio, Adam M.; Mankoff, David A.; MacDonald, Lawrence R.; Vaquero, Juan Jose; Desco, Manuel; Kinahan, Paul E.

2012-05-01

We evaluate the accuracy of scaling CT images for attenuation correction of PET data measured for bone. While the standard tri-linear approach has been well tested for soft tissues, the impact of CT-based attenuation correction on the accuracy of tracer uptake in bone has not been reported in detail. We measured the accuracy of attenuation coefficients of bovine femur segments and patient data using a tri-linear method applied to CT images obtained at different kVp settings. Attenuation values at 511 keV obtained with a 68Ga/68Ge transmission scan were used as a reference standard. The impact of inaccurate attenuation images on PET standardized uptake values (SUVs) was then evaluated using simulated emission images and emission images from five patients with elevated levels of FDG uptake in bone at disease sites. The CT-based linear attenuation images of the bovine femur segments underestimated the true values by 2.9 ± 0.3% for cancellous bone regardless of kVp. For compact bone the underestimation ranged from 1.3% at 140 kVp to 14.1% at 80 kVp. In the patient scans at 140 kVp the underestimation was approximately 2% averaged over all bony regions. The sensitivity analysis indicated that errors in PET SUVs in bone are approximately proportional to errors in the estimated attenuation coefficients for the same regions. The variability in SUV bias also increased approximately linearly with the error in linear attenuation coefficients. These results suggest that bias in bone uptake SUVs of PET tracers ranges from 2.4% to 5.9% when using CT scans at 140 and 120 kVp for attenuation correction. Lower kVp scans have the potential for considerably more error in dense bone. This bias is present in any PET tracer with bone uptake but may be clinically insignificant for many imaging tasks. However, errors from CT-based attenuation correction methods should be carefully evaluated if quantitation of tracer uptake in bone is important.

Nano-Computed Tomography: Technique and Applications.

PubMed

Kampschulte, M; Langheinirch, A C; Sender, J; Litzlbauer, H D; Althöhn, U; Schwab, J D; Alejandre-Lafont, E; Martels, G; Krombach, G A

2016-02-01

Nano-computed tomography (nano-CT) is an emerging, high-resolution cross-sectional imaging technique and represents a technical advancement of the established micro-CT technology. Based on the application of a transmission target X-ray tube, the focal spot size can be decreased down to diameters less than 400 nanometers (nm). Together with specific detectors and examination protocols, a superior spatial resolution up to 400 nm (10 % MTF) can be achieved, thereby exceeding the resolution capacity of typical micro-CT systems. The technical concept of nano-CT imaging as well as the basics of specimen preparation are demonstrated exemplarily. Characteristics of atherosclerotic plaques (intraplaque hemorrhage and calcifications) in a murine model of atherosclerosis (ApoE (-/-)/LDLR(-/-) double knockout mouse) are demonstrated in the context of superior spatial resolution in comparison to micro-CT. Furthermore, this article presents the application of nano-CT for imaging cerebral microcirculation (murine), lung structures (porcine), and trabecular microstructure (ovine) in contrast to micro-CT imaging. This review shows the potential of nano-CT as a radiological method in biomedical basic research and discusses the application of experimental, high resolution CT techniques in consideration of other high resolution cross-sectional imaging techniques. Nano-computed tomography is a high resolution CT-technology for 3D imaging at sub-micrometer resolution. The technical concept bases on a further development of the established ex-vivo-micro-CT technology. By improvement of the spatial resolution, structures at a cellular level become visible (e.g. osteocyte lacunae). © Georg Thieme Verlag KG Stuttgart · New York.

Diagnostic Value of Software-Based Image Fusion of Computed Tomography and F18-FDG PET Scans in Patients with Malignant Lymphoma

PubMed Central

Henninger, B.; Putzer, D.; Kendler, D.; Uprimny, C.; Virgolini, I.; Gunsilius, E.; Bale, R.

2012-01-01

Aim. The purpose of this study was to evaluate the accuracy of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (FDG) positron emission tomography (PET), computed tomography (CT), and software-based image fusion of both modalities in the imaging of non-Hodgkin's lymphoma (NHL) and Hodgkin's disease (HD). Methods. 77 patients with NHL (n = 58) or HD (n = 19) underwent a FDG PET scan, a contrast-enhanced CT, and a subsequent digital image fusion during initial staging or followup. 109 examinations of each modality were evaluated and compared to each other. Conventional staging procedures, other imaging techniques, laboratory screening, and follow-up data constituted the reference standard for comparison with image fusion. Sensitivity and specificity were calculated for CT and PET separately. Results. Sensitivity and specificity for detecting malignant lymphoma were 90% and 76% for CT and 94% and 91% for PET, respectively. A lymph node region-based analysis (comprising 14 defined anatomical regions) revealed a sensitivity of 81% and a specificity of 97% for CT and 96% and 99% for FDG PET, respectively. Only three of 109 image fusion findings needed further evaluation (false positive). Conclusion. Digital fusion of PET and CT improves the accuracy of staging, restaging, and therapy monitoring in patients with malignant lymphoma and may reduce the need for invasive diagnostic procedures. PMID:22654631

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

PubMed Central

Lee, Ki Baek

2018-01-01

Objective To describe the quantitative image quality and histogram-based evaluation of an iterative reconstruction (IR) algorithm in chest computed tomography (CT) scans at low-to-ultralow CT radiation dose levels. Materials and Methods In an adult anthropomorphic phantom, chest CT scans were performed with 128-section dual-source CT at 70, 80, 100, 120, and 140 kVp, and the reference (3.4 mGy in volume CT Dose Index [CTDIvol]), 30%-, 60%-, and 90%-reduced radiation dose levels (2.4, 1.4, and 0.3 mGy). The CT images were reconstructed by using filtered back projection (FBP) algorithms and IR algorithm with strengths 1, 3, and 5. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were statistically compared between different dose levels, tube voltages, and reconstruction algorithms. Moreover, histograms of subtraction images before and after standardization in x- and y-axes were visually compared. Results Compared with FBP images, IR images with strengths 1, 3, and 5 demonstrated image noise reduction up to 49.1%, SNR increase up to 100.7%, and CNR increase up to 67.3%. Noteworthy image quality degradations on IR images including a 184.9% increase in image noise, 63.0% decrease in SNR, and 51.3% decrease in CNR, and were shown between 60% and 90% reduced levels of radiation dose (p < 0.0001). Subtraction histograms between FBP and IR images showed progressively increased dispersion with increased IR strength and increased dose reduction. After standardization, the histograms appeared deviated and ragged between FBP images and IR images with strength 3 or 5, but almost normally-distributed between FBP images and IR images with strength 1. Conclusion The IR algorithm may be used to save radiation doses without substantial image quality degradation in chest CT scanning of the adult anthropomorphic phantom, down to approximately 1.4 mGy in CTDIvol (60% reduced dose). PMID:29354008

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fogg, P; Aland, T; West, M

Purpose: To investigate the effects of external surrogate and tumour motion by observing the reconstructed phases and AveCT in an Amplitude and Time based 4DCT. Methods: Based on patient motion studies, Cos6 and sinusoidal motions were simulated as external surrogate and tumour motions in a motion phantom. The diaphragm and tumour motions may or may not display the same waveform therefore the same and different waveforms were programmed into the phantom, scanned and reconstructed based on Amplitude and Time. The AveCT and phases were investigated with these different scenarios. The AveCT phantom images were also compared with CBCT phantom imagesmore » programmed with the same motions. Results: For the same surrogate and tumour sin motions, the phases (Amplitude and Time) and AveCT indicated similar motions based on the position of the BB at the slice and displayed contrast values respectively. For cos6 motions, due to the varied time the tumour spends at each position, the Amplitude and Time based phases differed. The AveCT images represented the actual tumour motions and the Time and Amplitude based phases were represented by the surrogate with varied times. Conclusion: Different external surrogate and tumour motions may result in different displayed image motions when observing the AveCT and reconstructed phases. During the 4DCT, the surrogate motion is readily available for observation of the amplitude and time of the diaphragm position. Following image reconstruction, the user may need to observe the AveCT in addition to the reconstructed phases to comprehend the time weightings of the tumour motion during the scan. This may also apply to 3D CBCT images where the displayed tumour position in the images is influenced by the long duration of the CBCT. Knowledge of the tumour motion represented by the greyscale of the AveCT may also assist in CBCT treatment beam verification matching.« less

Parameter-based estimation of CT dose index and image quality using an in-house android™-based software

NASA Astrophysics Data System (ADS)

Mubarok, S.; Lubis, L. E.; Pawiro, S. A.

2016-03-01

Compromise between radiation dose and image quality is essential in the use of CT imaging. CT dose index (CTDI) is currently the primary dosimetric formalisms in CT scan, while the low and high contrast resolutions are aspects indicating the image quality. This study was aimed to estimate CTDIvol and image quality measures through a range of exposure parameters variation. CTDI measurements were performed using PMMA (polymethyl methacrylate) phantom of 16 cm diameter, while the image quality test was conducted by using catphan ® 600. CTDI measurements were carried out according to IAEA TRS 457 protocol using axial scan mode, under varied parameters of tube voltage, collimation or slice thickness, and tube current. Image quality test was conducted accordingly under the same exposure parameters with CTDI measurements. An Android™ based software was also result of this study. The software was designed to estimate the value of CTDIvol with maximum difference compared to actual CTDIvol measurement of 8.97%. Image quality can also be estimated through CNR parameter with maximum difference to actual CNR measurement of 21.65%.

WE-AB-207A-07: A Planning CT-Guided Scatter Artifact Correction Method for CBCT Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, X; Liu, T; Dong, X

Purpose: Cone beam computed tomography (CBCT) imaging is on increasing demand for high-performance image-guided radiotherapy such as online tumor delineation and dose calculation. However, the current CBCT imaging has severe scatter artifacts and its current clinical application is therefore limited to patient setup based mainly on the bony structures. This study’s purpose is to develop a CBCT artifact correction method. Methods: The proposed scatter correction method utilizes the planning CT to improve CBCT image quality. First, an image registration is used to match the planning CT with the CBCT to reduce the geometry difference between the two images. Then, themore » planning CT-based prior information is entered into the Bayesian deconvolution framework to iteratively perform a scatter artifact correction for the CBCT mages. This technique was evaluated using Catphan phantoms with multiple inserts. Contrast-to-noise ratios (CNR) and signal-to-noise ratios (SNR), and the image spatial nonuniformity (ISN) in selected volume of interests (VOIs) were calculated to assess the proposed correction method. Results: Post scatter correction, the CNR increased by a factor of 1.96, 3.22, 3.20, 3.46, 3.44, 1.97 and 1.65, and the SNR increased by a factor 1.05, 2.09, 1.71, 3.95, 2.52, 1.54 and 1.84 for the Air, PMP, LDPE, Polystryrene, Acrylic, Delrin and Teflon inserts, respectively. The ISN decreased from 21.1% to 4.7% in the corrected images. All values of CNR, SNR and ISN in the corrected CBCT image were much closer to those in the planning CT images. The results demonstrated that the proposed method reduces the relevant artifacts and recovers CT numbers. Conclusion: We have developed a novel CBCT artifact correction method based on CT image, and demonstrated that the proposed CT-guided correction method could significantly reduce scatter artifacts and improve the image quality. This method has great potential to correct CBCT images allowing its use in adaptive radiotherapy.« less

Substitute CT generation from a single ultra short time echo MRI sequence: preliminary study

NASA Astrophysics Data System (ADS)

Ghose, Soumya; Dowling, Jason A.; Rai, Robba; Liney, Gary P.

2017-04-01

In MR guided radiation therapy planning both MR and CT images for a patient are acquired and co-registered to obtain a tissue specific HU map. Generation of the HU map directly from the MRI would eliminate the CT acquisition and may improve radiation therapy planning. In this preliminary study of substitute CT (sCT) generation, two porcine leg phantoms were scanned using a 3D ultrashort echo time (PETRA) sequence and co-registered to corresponding CT images to build tissue specific regression models. The model was created from one co-registered CT-PETRA pair to generate the sCT for the other PETRA image. An expectation maximization based clustering was performed on the co-registered PETRA image to identify the soft tissues, dense bone and air class membership probabilities. A tissue specific non linear regression model was built from one registered CT-PETRA pair dataset to predict the sCT of the second PETRA image in a two-fold cross validation schema. A complete substitute CT is generated in 3 min. The mean absolute HU error for air was 0.3 HU, bone was 95 HU, fat was 30 HU and for muscle it was 10 HU. The mean surface reconstruction error for the bone was 1.3 mm. The PETRA sequence enabled a low mean absolute surface distance for the bone and a low HU error for other classes. The sCT generated from a single PETRA sequence shows promise for the generation of fast sCT for MRI based radiation therapy planning.

Comparison of conventional and synchrotron-radiation-based microtomography of bone around dental implants

NASA Astrophysics Data System (ADS)

Cattaneo, Paolo M.; Dalstra, Michel; Beckmann, Felix; Donath, Tilman; Melsen, Birte

2004-10-01

This study explores the application of conventional micro tomography (μCT) and synchrotron radiation (SR) based μCT to evaluate the bone around titanium dental implants. The SR experiment was performed at beamline W2 of HASYLAB at DESY using a monochromatic X-ray beam of 50 keV. The testing material consisted of undecalcified bone segments harvested from the upper jaw of a macaca fascicularis monkey each containing a titanium dental implant. The results from the two different techniques were qualitatively compared with conventional histological sections examined under light microscopy. The SR-based μCT produced images that, especially at the bone-implant interface, are less noisy and sharper than the ones obtained with conventional μCT. For the proper evaluation of the implant-bone interface, only the SR-based μCT technique is able to display the areas of bony contact and visualize the true 3D structure of bone around dental implants correctly. This investigation shows that both conventional and SR-based μCT scanning techniques are non-destructive methods, which provide detailed images of bone. However with SR-based μCT it is possible to obtain an improved image quality of the bone surrounding dental implants, which display a level of detail comparable to histological sections. Therefore, SR-based μCT scanning could represent a valid, unbiased three-dimensional alternative to evaluate osseointegration of dental implants

Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model.

PubMed

Hertanto, Agung; Zhang, Qinghui; Hu, Yu-Chi; Dzyubak, Oleksandr; Rimner, Andreas; Mageras, Gig S

2012-06-01

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data. © 2012 American Association of Physicists in Medicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kohli, K; Liu, F; Krishnan, K

Purpose: Multi-frequency EIT has been reported to be a potential tool in distinguishing a tissue anomaly from background. In this study, we investigate the feasibility of acquiring functional information by comparing multi-frequency EIT images in reference to the structural information from the CT image through fusion. Methods: EIT data was acquired from a slice of winter melon using sixteen electrodes around the phantom, injecting a current of 0.4mA at 100, 66, 24.8 and 9.9 kHz. Differential EIT images were generated by considering different combinations of pair frequencies, one serving as reference data and the other as test data. The experimentmore » was repeated after creating an anomaly in the form of an off-centered cavity of diameter 4.5 cm inside the melon. All EIT images were reconstructed using Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS) package in 2-D differential imaging mode using one-step Gaussian Newton minimization solver. CT image of the melon was obtained using a Phillips CT Scanner. A segmented binary mask image was generated based on the reference electrode position and the CT image to define the regions of interest. The region selected by the user was fused with the CT image through logical indexing. Results: Differential images based on the reference and test signal frequencies were reconstructed from EIT data. Result illustrated distinct structural inhomogeneity in seeded region compared to fruit flesh. The seeded region was seen as a higherimpedance region if the test frequency was lower than the base frequency in the differential EIT reconstruction. When the test frequency was higher than the base frequency, the signal experienced less electrical impedance in the seeded region during the EIT data acquisition. Conclusion: Frequency-based differential EIT imaging can be explored to provide additional functional information along with structural information from CT for identifying different tissues.« less

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

PubMed

Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

2017-10-18

In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.

Development of Prior Image-based, High-Quality, Low-Dose Kilovoltage Cone Beam CT for Use in Adaptive Radiotherapy of Prostate Cancer

DTIC Science & Technology

2012-05-01

employs kilovoltage (KV) cone- beam CT (CBCT) for guiding treatment. High quality CBCT images are important in achieving improved treatment effect...necessary for achieving successful adaptive RT. Kilovoltage cone-beam CT (CBCT) has shown its capability of yielding such images to guide the prostate cancer...study of low-dose intra-operative cone-beam CT for image- guided surgery,” Proc. SPIE, 7961, 79615P, 2011 10. X. Han, E. Pearson, J. Bian, S. Cho, E. Y

High-resolution breast tomography at high energy: a feasibility study of phase contrast imaging on a whole breast

NASA Astrophysics Data System (ADS)

Sztrókay, A.; Diemoz, P. C.; Schlossbauer, T.; Brun, E.; Bamberg, F.; Mayr, D.; Reiser, M. F.; Bravin, A.; Coan, P.

2012-05-01

Previous studies on phase contrast imaging (PCI) mammography have demonstrated an enhancement of breast morphology and cancerous tissue visualization compared to conventional imaging. We show here the first results of the PCI analyser-based imaging (ABI) in computed tomography (CT) mode on whole and large (>12 cm) tumour-bearing breast tissues. We demonstrate in this work the capability of the technique of working at high x-ray energies and producing high-contrast images of large and complex specimens. One entire breast of an 80-year-old woman with invasive ductal cancer was imaged using ABI-CT with monochromatic 70 keV x-rays and an area detector of 92×92 µm2 pixel size. Sagittal slices were reconstructed from the acquired data, and compared to corresponding histological sections. Comparison with conventional absorption-based CT was also performed. Five blinded radiologists quantitatively evaluated the visual aspects of the ABI-CT images with respect to sharpness, soft tissue contrast, tissue boundaries and the discrimination of different structures/tissues. ABI-CT excellently depicted the entire 3D architecture of the breast volume by providing high-resolution and high-contrast images of the normal and cancerous breast tissues. These results are an important step in the evolution of PCI-CT towards its clinical implementation.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Mascolo-Fortin, Julia, E-mail: julia.mascolo-fortin.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca

Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numericalmore » simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.« less

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

PubMed

Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

2015-11-01

The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.

Staging of neuroendocrine tumours: comparison of [68Ga]DOTATOC multiphase PET/CT and whole-body MRI

PubMed Central

Schwenzer, N. F.; Sperling, O.; Aschoff, P.; Lichy, M. P.; Müller, M.; Brendle, C.; Werner, M. K.; Claussen, C. D.; Pfannenberg, C.

2013-01-01

Abstract Purpose: In patients with a neuroendocrine tumour (NET), the extent of disease strongly influences the outcome and multidisciplinary therapeutic management. Thus, systematic analysis of the diagnostic performance of the existing staging modalities is necessary. The aim of this study was to compare the diagnostic performance of 2 whole-body imaging modalities, [68Ga]DOTATOC positron emission tomography (PET)/computed tomography (CT) and magnetic resonance imaging (MRI) in patients with NET with regard to possible impact on treatment decisions. Materials and methods: [68Ga]DOTATOC-PET/CT and whole-body magnetic resonance imaging (wbMRI) were performed on 51 patients (25 females, 26 males, mean age 57 years) with histologically proven NET and suspicion of metastatic spread within a mean interval of 2.4 days (range 0–28 days). PET/CT was performed after intravenous administration of 150 MBq [68Ga]DOTATOC. The CT protocol comprised multiphase contrast-enhanced imaging. The MRI protocol consisted of standard sequences before and after intravenous contrast administration at 1.5 T. Each modality (PET, CT, PET/CT, wbMRI) was evaluated independently by 2 experienced readers. Consensus decision based on correlation of all imaging data, histologic and surgical findings and clinical follow-up was established as the standard of reference. Lesion-based and patient-based analysis was performed. Detection rates and accuracy were compared using the McNemar test. P values <0.05 were considered significant. The impact of whole-body imaging on the treatment decision was evaluated by the interdisciplinary tumour board of our institution. Results: 593 metastatic lesions were detected in 41 of 51 (80%) patients with NET (lung 54, liver 266, bone 131, lymph node 99, other 43). One hundred and twenty PET-negative lesions were detected by CT or MRI. Of all 593 lesions detected, PET identified 381 (64%) true-positive lesions, CT 482 (81%), PET/CT 545 (92%) and wbMRI 540 (91%). Comparison of lesion-based detection rates between PET/CT and wbMRI revealed significantly higher sensitivity of PET/CT for metastatic lymph nodes (100% vs 73%; P < 0.0001) and pulmonary lesions (100% vs 87%; P = 0.0233), whereas wbMRI had significantly higher detection rates for liver (99% vs 92%; P < 0.0001) and bone lesions (96% vs 82%; P < 0.0001). Of all 593 lesions, 22 were found only in PET, 11 only in CT and 47 only in wbMRI. The patient-based overall assessment of the metastatic status of the patient showed comparable sensitivity of PET/CT and MRI with slightly higher accuracy of PET/CT. Patient-based analysis of metastatic organ involvement revealed significantly higher accuracy of PET/CT for bone and lymph node metastases (100% vs 88%; P = 0.0412 and 98% vs 78%; P = 0.0044) and for the overall comparison (99% vs 89%; P < 0.0001). The imaging results influenced the treatment decision in 30 patients (59%) with comparable information from PET/CT and wbMRI in 30 patients, additional relevant information from PET/CT in 16 patients and from wbMRI in 7 patients. Conclusion: PET/CT and wbMRI showed comparable overall lesion-based detection rates for metastatic involvement in NET but significantly differed in organ-based detection rates with superiority of PET/CT for lymph node and pulmonary lesions and of wbMRI for liver and bone metastases. Patient-based analysis revealed superiority of PET/CT for NET staging. Individual treatment strategies benefit from complementary information from PET/CT and MRI. PMID:23466785

DOE Office of Scientific and Technical Information (OSTI.GOV)

Korhonen, Juha, E-mail: juha.p.korhonen@hus.fi; Kapanen, Mika; Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS

Purpose: The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents. Methods: T{sub 1}/T{sub 2}*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRImore » intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm. Results: The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from −2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images. Conclusions: This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.« less

Improving the imaging of calcifications in CT by histogram-based selective deblurring

NASA Astrophysics Data System (ADS)

Rollano-Hijarrubia, Empar; van der Meer, Frits; van der Lugt, Add; Weinans, Harrie; Vrooman, Henry; Vossepoel, Albert; Stokking, Rik

2005-04-01

Imaging of small high-density structures, such as calcifications, with computed tomography (CT) is limited by the spatial resolution of the system. Blur causes small calcifications to be imaged with lower contrast and overestimated volume, thereby hampering the analysis of vessels. The aim of this work is to reduce the blur of calcifications by applying three-dimensional (3D) deconvolution. Unfortunately, the high-frequency amplification of the deconvolution produces edge-related ring artifacts and enhances noise and original artifacts, which degrades the imaging of low-density structures. A method, referred to as Histogram-based Selective Deblurring (HiSD), was implemented to avoid these negative effects. HiSD uses the histogram information to generate a restored image in which the low-intensity voxel information of the observed image is combined with the high-intensity voxel information of the deconvolved image. To evaluate HiSD we scanned four in-vitro atherosclerotic plaques of carotid arteries with a multislice spiral CT and with a microfocus CT (μCT), used as reference. Restored images were generated from the observed images, and qualitatively and quantitatively compared with their corresponding μCT images. Transverse views and maximum-intensity projections of restored images show the decrease of blur of the calcifications in 3D. Measurements of the areas of 27 calcifications and total volumes of calcification of 4 plaques show that the overestimation of calcification was smaller for restored images (mean-error: 90% for area; 92% for volume) than for observed images (143%; 213%, respectively). The qualitative and quantitative analyses show that the imaging of calcifications in CT can be improved considerably by applying HiSD.

Improving the Diagnostic Specificity of CT for Early Detection of Lung Cancer: 4D CT-Based Pulmonary Nodule Elastometry

DTIC Science & Technology

2015-10-01

malignant PNs treated with stereotactic ablative radiotherapy ( SABR ) with those of the lung. Methods: We analyzed breath-hold images of 30...patients with malignant PNs who underwent SABR in our department. A parametric nonrigid transformation model based on multi-level B-spline guided by Sum of...and 50 of 4D CT and deep inhale and natural exhale of breath-hold CT images of 30 MPN treated with stereotactic ablative radiotherapy ( SABR ). The

Feasibility assessment of yttrium-90 liver radioembolization imaging using amplitude-based gated PET/CT

PubMed Central

Acuff, Shelley N.; Neveu, Melissa L.; Syed, Mumtaz; Kaman, Austin D.; Fu, Yitong

2018-01-01

Purpose The usage of PET/computed tomography (CT) to monitor hepatocellular carcinoma patients following yttrium-90 (90Y) radioembolization has increased. Respiratory motion causes liver movement, which can be corrected using gating techniques at the expense of added noise. This work examines the use of amplitude-based gating on 90Y-PET/CT and its potential impact on diagnostic integrity. Patients and methods Patients were imaged using PET/CT following 90Y radioembolization. A respiratory band was used to collect respiratory cycle data. Patient data were processed as both standard and motion-corrected images. Regions of interest were drawn and compared using three methods. Activity concentrations were calculated and converted into dose estimates using previously determined and published scaling factors. Diagnostic assessments were performed using a binary scale created from published 90Y-PET/CT image interpretation guidelines. Results Estimates of radiation dose were increased (P<0.05) when using amplitude-gating methods with 90Y PET/CT imaging. Motion-corrected images show increased noise, but the diagnostic determination of success, using the Kao criteria, did not change between static and motion-corrected data. Conclusion Amplitude-gated PET/CT following 90Y radioembolization is feasible and may improve 90Y dose estimates while maintaining diagnostic assessment integrity. PMID:29351124

Whole-body MRI including diffusion-weighted MRI compared with 5-HTP PET/CT in the detection of neuroendocrine tumors

PubMed Central

Carlbom, Lina; Caballero-Corbalán, José; Granberg, Dan; Sörensen, Jens; Eriksson, Barbro; Ahlström, Håkan

2017-01-01

Aim We wanted to explore if whole-body magnetic resonance imaging (MRI) including diffusion-weighted (DW) and liver-specific contrast agent-enhanced imaging could be valuable in lesion detection of neuroendocrine tumors (NET). [11C]-5-Hydroxytryptophan positron emission tomography/computed tomography (5-HTP PET/CT) was used for comparison. Materials and methods Twenty-one patients with NET were investigated with whole-body MRI, including DW imaging (DWI) and contrast-enhanced imaging of the liver, and whole-body 5-HTP PET/CT. Seven additional patients underwent upper abdomen MRI including DWI, liver-specific contrast agent-enhanced imaging, and 5-HTP PET/CT. Results There was a patient-based concordance of 61% and a lesion-based concordance of 53% between the modalities. MRI showed good concordance with PET in detecting bone metastases but was less sensitive in detecting metastases in mediastinal lymph nodes. MRI detected more liver metastases than 5-HTP PET/CT. Conclusion Whole-body MRI with DWI did not detect all NET lesions found with whole-body 5-HTP PET/CT. Our findings indicate that MRI of the liver including liver-specific contrast agent-enhanced imaging and DWI could be a useful complement to whole-body 5-HTP PET/CT. PMID:27894208

MR to CT registration of brains using image synthesis

NASA Astrophysics Data System (ADS)

Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

2014-03-01

Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

Evaluation of the ablation margin of hepatocellular carcinoma using CEUS-CT/MR image fusion in a phantom model and in patients.

PubMed

Li, Kai; Su, Zhongzhen; Xu, Erjiao; Huang, Qiannan; Zeng, Qingjing; Zheng, Rongqin

2017-01-19

To assess the accuracy of contrast-enhanced ultrasound (CEUS)-CT/MR image fusion in evaluating the radiofrequency ablative margin (AM) of hepatocellular carcinoma (HCC) based on a custom-made phantom model and in HCC patients. Twenty-four phantoms were randomly divided into a complete ablation group (n = 6) and an incomplete ablation group (n = 18). After radiofrequency ablation (RFA), the AM was evaluated using ultrasound (US)-CT image fusion, and the results were compared with the AM results that were directly measured in a gross specimen. CEUS-CT/MR image fusion and CT-CT / MR-MR image fusion were used to evaluate the AM in 37 tumors from 33 HCC patients who underwent RFA. The sensitivity, specificity, and accuracy of US-CT image fusion for evaluating AM in the phantom model were 93.8, 85.7 and 91.3%, respectively. The maximal thicknesses of the residual AM were 3.5 ± 2.0 mm and 3.2 ± 2.0 mm in the US-CT image fusion and gross specimen, respectively. No significant difference was observed between the US-CT image fusion and direct measurements of the AM of HCC. In the clinical study, the success rate of the AM evaluation was 100% for both CEUS-CT/MR and CT-CT/MR-MR, and the duration was 8.5 ± 2.8 min (range: 4-12 min) and 13.5 ± 4.5 min (range: 8-16 min) for CEUS-CT/MR and CT-CT/MR-MR, respectively. The sensitivity, specificity, and accuracy of CEUS-CT/MR imaging for evaluating the AM were 100.0, 80.0, and 90.0%, respectively. A phantom model composed of carrageenan gel and additives was suitable for the evaluation of HCC AM. CEUS-CT/MR image fusion can be used to evaluate HCC AM with high accuracy.

MR-based synthetic CT generation using a deep convolutional neural network method.

PubMed

Han, Xiao

2017-04-01

Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images. The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion. The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN method also provided significantly better accuracy when being evaluated using two other metrics: the mean squared error (188.6 ± 33.7 versus 198.3 ± 33.0) and the Pearson correlation coefficient(0.906 ± 0.03 versus 0.896 ± 0.03). Although training a DCNN model can be slow, training only need be done once. Applying a trained model to generate a complete sCT volume for each new patient MR image only took 9 s, which was much faster than the atlas-based approach. A DCNN model method was developed, and shown to be able to produce highly accurate sCT estimations from conventional, single-sequence MR images in near real time. Quantitative results also showed that the proposed method competed favorably with an atlas-based method, in terms of both accuracy and computation speed at test time. Further validation on dose computation accuracy and on a larger patient cohort is warranted. Extensions of the method are also possible to further improve accuracy or to handle multi-sequence MR images. © 2017 American Association of Physicists in Medicine.

Medipix-based Spectral Micro-CT.

PubMed

Yu, Hengyong; Xu, Qiong; He, Peng; Bennett, James; Amir, Raja; Dobbs, Bruce; Mou, Xuanqin; Wei, Biao; Butler, Anthony; Butler, Phillip; Wang, Ge

2012-12-01

Since Hounsfield's Nobel Prize winning breakthrough decades ago, X-ray CT has been widely applied in the clinical and preclinical applications - producing a huge number of tomographic gray-scale images. However, these images are often insufficient to distinguish crucial differences needed for diagnosis. They have poor soft tissue contrast due to inherent photon-count issues, involving high radiation dose. By physics, the X-ray spectrum is polychromatic, and it is now feasible to obtain multi-energy, spectral, or true-color, CT images. Such spectral images promise powerful new diagnostic information. The emerging Medipix technology promises energy-sensitive, high-resolution, accurate and rapid X-ray detection. In this paper, we will review the recent progress of Medipix-based spectral micro-CT with the emphasis on the results obtained by our team. It includes the state- of-the-art Medipix detector, the system and method of a commercial MARS (Medipix All Resolution System) spectral micro-CT, and the design and color diffusion of a hybrid spectral micro-CT.

Limited diagnostic value of Dual-Time-Point (18)F-FDG PET/CT imaging for classifying solitary pulmonary nodules in granuloma-endemic regions both at visual and quantitative analyses.

PubMed

Chen, Song; Li, Xuena; Chen, Meijie; Yin, Yafu; Li, Na; Li, Yaming

2016-10-01

This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions. SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores. One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation. In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Zero TE-based pseudo-CT image conversion in the head and its application in PET/MR attenuation correction and MR-guided radiation therapy planning.

PubMed

Wiesinger, Florian; Bylund, Mikael; Yang, Jaewon; Kaushik, Sandeep; Shanbhag, Dattesh; Ahn, Sangtae; Jonsson, Joakim H; Lundman, Josef A; Hope, Thomas; Nyholm, Tufve; Larson, Peder; Cozzini, Cristina

2018-02-18

To describe a method for converting Zero TE (ZTE) MR images into X-ray attenuation information in the form of pseudo-CT images and demonstrate its performance for (1) attenuation correction (AC) in PET/MR and (2) dose planning in MR-guided radiation therapy planning (RTP). Proton density-weighted ZTE images were acquired as input for MR-based pseudo-CT conversion, providing (1) efficient capture of short-lived bone signals, (2) flat soft-tissue contrast, and (3) fast and robust 3D MR imaging. After bias correction and normalization, the images were segmented into bone, soft-tissue, and air by means of thresholding and morphological refinements. Fixed Hounsfield replacement values were assigned for air (-1000 HU) and soft-tissue (+42 HU), whereas continuous linear mapping was used for bone. The obtained ZTE-derived pseudo-CT images accurately resembled the true CT images (i.e., Dice coefficient for bone overlap of 0.73 ± 0.08 and mean absolute error of 123 ± 25 HU evaluated over the whole head, including errors from residual registration mismatches in the neck and mouth regions). The linear bone mapping accounted for bone density variations. Averaged across five patients, ZTE-based AC demonstrated a PET error of -0.04 ± 1.68% relative to CT-based AC. Similarly, for RTP assessed in eight patients, the absolute dose difference over the target volume was found to be 0.23 ± 0.42%. The described method enables MR to pseudo-CT image conversion for the head in an accurate, robust, and fast manner without relying on anatomical prior knowledge. Potential applications include PET/MR-AC, and MR-guided RTP. © 2018 International Society for Magnetic Resonance in Medicine.

Fully automatic segmentation of the femur from 3D-CT images using primitive shape recognition and statistical shape models.

PubMed

Ben Younes, Lassad; Nakajima, Yoshikazu; Saito, Toki

2014-03-01

Femur segmentation is well established and widely used in computer-assisted orthopedic surgery. However, most of the robust segmentation methods such as statistical shape models (SSM) require human intervention to provide an initial position for the SSM. In this paper, we propose to overcome this problem and provide a fully automatic femur segmentation method for CT images based on primitive shape recognition and SSM. Femur segmentation in CT scans was performed using primitive shape recognition based on a robust algorithm such as the Hough transform and RANdom SAmple Consensus. The proposed method is divided into 3 steps: (1) detection of the femoral head as sphere and the femoral shaft as cylinder in the SSM and the CT images, (2) rigid registration between primitives of SSM and CT image to initialize the SSM into the CT image, and (3) fitting of the SSM to the CT image edge using an affine transformation followed by a nonlinear fitting. The automated method provided good results even with a high number of outliers. The difference of segmentation error between the proposed automatic initialization method and a manual initialization method is less than 1 mm. The proposed method detects primitive shape position to initialize the SSM into the target image. Based on primitive shapes, this method overcomes the problem of inter-patient variability. Moreover, the results demonstrate that our method of primitive shape recognition can be used for 3D SSM initialization to achieve fully automatic segmentation of the femur.

Feature-based US to CT registration of the aortic root

NASA Astrophysics Data System (ADS)

Lang, Pencilla; Chen, Elvis C. S.; Guiraudon, Gerard M.; Jones, Doug L.; Bainbridge, Daniel; Chu, Michael W.; Drangova, Maria; Hata, Noby; Jain, Ameet; Peters, Terry M.

2011-03-01

A feature-based registration was developed to align biplane and tracked ultrasound images of the aortic root with a preoperative CT volume. In transcatheter aortic valve replacement, a prosthetic valve is inserted into the aortic annulus via a catheter. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to significant morbidity and mortality. Registration of pre-operative CT to transesophageal ultrasound and fluoroscopy images is a major step towards providing augmented image guidance for this procedure. The proposed registration approach uses an iterative closest point algorithm to register a surface mesh generated from CT to 3D US points reconstructed from a single biplane US acquisition, or multiple tracked US images. The use of a single simultaneous acquisition biplane image eliminates reconstruction error introduced by cardiac gating and TEE probe tracking, creating potential for real-time intra-operative registration. A simple initialization procedure is used to minimize changes to operating room workflow. The algorithm is tested on images acquired from excised porcine hearts. Results demonstrate a clinically acceptable accuracy of 2.6mm and 5mm for tracked US to CT and biplane US to CT registration respectively.

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y. X.; Van Reeth, E.; Poh, C. L., E-mail: clpoh@ntu.edu.sg

2015-08-15

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite elementmore » method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.« less

Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2007-03-01

Multislice CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multislice CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. Moreover, we have provided diagnostic assistance methods to medical screening specialists by using a lung cancer screening algorithm built into mobile helical CT scanner for the lung cancer mass screening done in the region without the hospital. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system.

Patient-specific lean body mass can be estimated from limited-coverage computed tomography images.

PubMed

Devriese, Joke; Beels, Laurence; Maes, Alex; van de Wiele, Christophe; Pottel, Hans

2018-06-01

In PET/CT, quantitative evaluation of tumour metabolic activity is possible through standardized uptake values, usually normalized for body weight (BW) or lean body mass (LBM). Patient-specific LBM can be estimated from whole-body (WB) CT images. As most clinical indications only warrant PET/CT examinations covering head to midthigh, the aim of this study was to develop a simple and reliable method to estimate LBM from limited-coverage (LC) CT images and test its validity. Head-to-toe PET/CT examinations were retrospectively retrieved and semiautomatically segmented into tissue types based on thresholding of CT Hounsfield units. LC was obtained by omitting image slices. Image segmentation was validated on the WB CT examinations by comparing CT-estimated BW with actual BW, and LBM estimated from LC images were compared with LBM estimated from WB images. A direct method and an indirect method were developed and validated on an independent data set. Comparing LBM estimated from LC examinations with estimates from WB examinations (LBMWB) showed a significant but limited bias of 1.2 kg (direct method) and nonsignificant bias of 0.05 kg (indirect method). This study demonstrates that LBM can be estimated from LC CT images with no significant difference from LBMWB.

CT-based attenuation and scatter correction compared with uniform attenuation correction in brain perfusion SPECT imaging for dementia

NASA Astrophysics Data System (ADS)

Gillen, Rebecca; Firbank, Michael J.; Lloyd, Jim; O'Brien, John T.

2015-09-01

This study investigated if the appearance and diagnostic accuracy of HMPAO brain perfusion SPECT images could be improved by using CT-based attenuation and scatter correction compared with the uniform attenuation correction method. A cohort of subjects who were clinically categorized as Alzheimer’s Disease (n=38 ), Dementia with Lewy Bodies (n=29 ) or healthy normal controls (n=30 ), underwent SPECT imaging with Tc-99m HMPAO and a separate CT scan. The SPECT images were processed using: (a) correction map derived from the subject’s CT scan or (b) the Chang uniform approximation for correction or (c) no attenuation correction. Images were visually inspected. The ratios between key regions of interest known to be affected or spared in each condition were calculated for each correction method, and the differences between these ratios were evaluated. The images produced using the different corrections were noted to be visually different. However, ROI analysis found similar statistically significant differences between control and dementia groups and between AD and DLB groups regardless of the correction map used. We did not identify an improvement in diagnostic accuracy in images which were corrected using CT-based attenuation and scatter correction, compared with those corrected using a uniform correction map.

Novel Cs-Based Upconversion Nanoparticles as Dual-Modal CT and UCL Imaging Agents for Chemo-Photothermal Synergistic Therapy.

PubMed

Liu, Yuxin; Li, Luoyuan; Guo, Quanwei; Wang, Lu; Liu, Dongdong; Wei, Ziwei; Zhou, Jing

2016-01-01

Lanthanide-based contrast agents have attracted increasing attention for their unique properties and potential applications in cancer theranostics. To date, many of these agents have been studied extensively in cells and small animal models. However, performance of these theranostic nanoparticles requires further improvement. In this study, a novel CsLu2F7:Yb,Er,Tm-based visual therapeutic platform was developed for imaging-guided synergistic cancer therapy. Due to the presence of the heavy alkali metal Cesium (Cs) in host lattice, the nanoplatform can provide a higher resolution X-ray CT imaging than many other reported lanthanide-based CT contrast agents. Furthermore, by using the targeted RGD motif, chemotherapy drug alpha-tocopheryl succinate (α-TOS), and photothermal coupling agent ICG, this nanoplatform simultaneously provides multifunctional imaging and targeted synergistic therapy. To demonstrate the theranostic performance of this novel nanoplatform in vivo, visual diagnosis in the small animal model was realized by UCL/CT imaging which was further integrated with targeted chemo-photothermal synergistic therapy. These results provided evidence for the successful construction of a novel lanthanide-based nanoplatform coupled with multimodal imaging diagnosis and potential application in synergistic cancer theranostics.

Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI.

PubMed

Leynes, Andrew P; Yang, Jaewon; Wiesinger, Florian; Kaushik, Sandeep S; Shanbhag, Dattesh D; Seo, Youngho; Hope, Thomas A; Larson, Peder E Z

2018-05-01

Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone is neglected. Ultrashort-echo-time or zero-echo-time (ZTE) pulse sequences can capture bone information. We propose the use of patient-specific multiparametric MRI consisting of Dixon MRI and proton-density-weighted ZTE MRI to directly synthesize pseudo-CT images with a deep learning model: we call this method ZTE and Dixon deep pseudo-CT (ZeDD CT). Methods: Twenty-six patients were scanned using an integrated 3-T time-of-flight PET/MRI system. Helical CT images of the patients were acquired separately. A deep convolutional neural network was trained to transform ZTE and Dixon MR images into pseudo-CT images. Ten patients were used for model training, and 16 patients were used for evaluation. Bone and soft-tissue lesions were identified, and the SUV max was measured. The root-mean-squared error (RMSE) was used to compare the MR-based attenuation correction with the ground-truth CT attenuation correction. Results: In total, 30 bone lesions and 60 soft-tissue lesions were evaluated. The RMSE in PET quantification was reduced by a factor of 4 for bone lesions (10.24% for Dixon PET and 2.68% for ZeDD PET) and by a factor of 1.5 for soft-tissue lesions (6.24% for Dixon PET and 4.07% for ZeDD PET). Conclusion: ZeDD CT produces natural-looking and quantitatively accurate pseudo-CT images and reduces error in pelvic PET/MRI attenuation correction compared with standard methods. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.

PubMed

Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua

2018-02-01

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Intensity-based dual model method for generation of synthetic CT images from standard T2-weighted MR images - Generalized technique for four different MR scanners.

PubMed

Koivula, Lauri; Kapanen, Mika; Seppälä, Tiina; Collan, Juhani; Dowling, Jason A; Greer, Peter B; Gustafsson, Christian; Gunnlaugsson, Adalsteinn; Olsson, Lars E; Wee, Leonard; Korhonen, Juha

2017-12-01

Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2 w ) MR images of the pelvis. This study developed a generalized dual model HU conversion method to convert standard T2 w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors. For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 ± 6 HUs (34 HUs) and -46 ± 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 ± 0.4% (-1.3%). The study provides a generalized method for sCT creation from standard T2 w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samei, Ehsan, E-mail: samei@duke.edu; Richard, Samuel

2015-01-15

Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD,more » Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.« less

Hybrid SPECT-CT and PET-CT imaging of differentiated thyroid carcinoma.

PubMed

Wong, K K; Zarzhevsky, N; Cahill, J M; Frey, K A; Avram, A M

2009-10-01

Hybrid imaging modalities such as radioiodine single photon emission CT with integrated CT ((131)I SPECT-CT) and 2-(fluorine-18)-fluoro-2-deoxy-D-glucose positron emission tomography with integrated CT (FDG PET-CT) allow the rapid and efficient fusion of functional and anatomic images, and provide diagnostic information that may influence management decisions in patients with differentiated thyroid carcinoma (DTC). Diagnostic localisation and therapy of these tumours are dependent upon their capacity to concentrate radioiodine ((131)I) via uptake through the sodium-iodide symporter and retention within the tumour. The prognosis for most patients with DTC is favourable, although controversy exists regarding the role of post-operative (131)I therapy in patients at low-risk for disease. Accurate identification of functional thyroid tissue (benign or malignant) using diagnostic (131)I planar scintigraphy complemented by SPECT-CT imaging enables the completion of post-operative staging and patient risk stratification prior to (131)I therapy administration. In patients with non-iodine-avid tumours (negative (131)I scan but elevated thyroglobulin indicative of persistent or recurrent disease), FDG PET-CT is used to identify tumours with enhanced glucose metabolism and to localise the source of thyroglobulin production. The CT component of this hybrid technology provides anatomic localisation of activity and allows CT-based attenuation correction of PET images. Images from 15 patients illustrate the applications of (131)I SPECT-CT and FDG PET-CT.

Correction of oral contrast artifacts in CT-based attenuation correction of PET images using an automated segmentation algorithm.

PubMed

Ahmadian, Alireza; Ay, Mohammad R; Bidgoli, Javad H; Sarkar, Saeed; Zaidi, Habib

2008-10-01

Oral contrast is usually administered in most X-ray computed tomography (CT) examinations of the abdomen and the pelvis as it allows more accurate identification of the bowel and facilitates the interpretation of abdominal and pelvic CT studies. However, the misclassification of contrast medium with high-density bone in CT-based attenuation correction (CTAC) is known to generate artifacts in the attenuation map (mumap), thus resulting in overcorrection for attenuation of positron emission tomography (PET) images. In this study, we developed an automated algorithm for segmentation and classification of regions containing oral contrast medium to correct for artifacts in CT-attenuation-corrected PET images using the segmented contrast correction (SCC) algorithm. The proposed algorithm consists of two steps: first, high CT number object segmentation using combined region- and boundary-based segmentation and second, object classification to bone and contrast agent using a knowledge-based nonlinear fuzzy classifier. Thereafter, the CT numbers of pixels belonging to the region classified as contrast medium are substituted with their equivalent effective bone CT numbers using the SCC algorithm. The generated CT images are then down-sampled followed by Gaussian smoothing to match the resolution of PET images. A piecewise calibration curve was then used to convert CT pixel values to linear attenuation coefficients at 511 keV. The visual assessment of segmented regions performed by an experienced radiologist confirmed the accuracy of the segmentation and classification algorithms for delineation of contrast-enhanced regions in clinical CT images. The quantitative analysis of generated mumaps of 21 clinical CT colonoscopy datasets showed an overestimation ranging between 24.4% and 37.3% in the 3D-classified regions depending on their volume and the concentration of contrast medium. Two PET/CT studies known to be problematic demonstrated the applicability of the technique in clinical setting. More importantly, correction of oral contrast artifacts improved the readability and interpretation of the PET scan and showed substantial decrease of the SUV (104.3%) after correction. An automated segmentation algorithm for classification of irregular shapes of regions containing contrast medium was developed for wider applicability of the SCC algorithm for correction of oral contrast artifacts during the CTAC procedure. The algorithm is being refined and further validated in clinical setting.

Automated segmentation of middle hepatic vein in non-contrast x-ray CT images based on an atlas-driven approach

NASA Astrophysics Data System (ADS)

Kitagawa, Teruhiko; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki

2008-03-01

In order to support the diagnosis of hepatic diseases, understanding the anatomical structures of hepatic lobes and hepatic vessels is necessary. Although viewing and understanding the hepatic vessels in contrast media-enhanced CT images is easy, the observation of the hepatic vessels in non-contrast X-ray CT images that are widely used for the screening purpose is difficult. We are developing a computer-aided diagnosis (CAD) system to support the liver diagnosis based on non-contrast X-ray CT images. This paper proposes a new approach to segment the middle hepatic vein (MHV), a key structure (landmark) for separating the liver region into left and right lobes. Extraction and classification of hepatic vessels are difficult in non-contrast X-ray CT images because the contrast between hepatic vessels and other liver tissues is low. Our approach uses an atlas-driven method by the following three stages. (1) Construction of liver atlases of left and right hepatic lobes using a learning datasets. (2) Fully-automated enhancement and extraction of hepatic vessels in liver regions. (3) Extraction of MHV based on the results of (1) and (2). The proposed approach was applied to 22 normal liver cases of non-contrast X-ray CT images. The preliminary results show that the proposed approach achieves the success in 14 cases for MHV extraction.

Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

2006-03-01

Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

Preliminary evaluation of the dosimetric accuracy of cone-beam computed tomography for cases with respiratory motion

NASA Astrophysics Data System (ADS)

Kim, Dong Wook; Bae, Sunhyun; Chung, Weon Kuu; Lee, Yoonhee

2014-04-01

Cone-beam computed tomography (CBCT) images are currently used for patient positioning and adaptive dose calculation; however, the degree of CBCT uncertainty in cases of respiratory motion remains an interesting issue. This study evaluated the uncertainty of CBCT-based dose calculations for a moving target. Using a phantom, we estimated differences in the geometries and the Hounsfield units (HU) between CT and CBCT. The calculated dose distributions based on CT and CBCT images were also compared using a radiation treatment planning system, and the comparison included cases with respiratory motion. The geometrical uncertainties of the CT and the CBCT images were less than 0.15 cm. The HU differences between CT and CBCT images for standard-dose-head, high-quality-head, normal-pelvis, and low-dose-thorax modes were 31, 36, 23, and 33 HU, respectively. The gamma (3%, 0.3 cm)-dose distribution between CT and CBCT was greater than 1 in 99% of the area. The gamma-dose distribution between CT and CBCT during respiratory motion was also greater than 1 in 99% of the area. The uncertainty of the CBCT-based dose calculation was evaluated for cases with respiratory motion. In conclusion, image distortion due to motion did not significantly influence dosimetric parameters.

SU-F-J-186: Enabling Adaptive IMPT with CBCT-Based Dose Recalculation for H&N and Prostate Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurz, C; LMU Munich, Munich; Park, Y

2016-06-15

Purpose: To enable adaptive intensity modulated proton therapy for sites sensitive to inter-fractional changes on the basis of accurate CBCT-based proton dose calculations. To this aim two CBCT intensity correction methods are considered: planning CT (pCT) to CBCT DIR and projection correction based on pCT DIR prior. Methods: 3 H&N and 3 prostate cancer patients with CBCT images and corresponding projections were used in this study, in addition to pCT and re-planning CT (rpCT) images (H&N only). A virtual CT (vCT) was generated by pCT to CBCT DIR. In a second approach, the vCT was used as prior for scattermore » correction of the CBCT projections to yield a CBCTcor image. BEV 2D range maps of SFUD IMPT plans were compared. For the prostate cases, the geometric accuracy of the vCT was also evaluated by contour comparison to physician delineation of the CBCTcor and original CBCT. Results: SFUD dose calculations on vCT and CBCTcor were found to be within 3mm for 97% to 99% of 2D range maps. Median range differences compared to rpCT were below 0.5mm. Analysis showed that the DIR-based vCT approach exhibits inaccuracies in the pelvic region due to the very low soft-tissue contrast in the CBCT. The CBCTcor approach yielded results closer to the original CBCT in terms of DICE coefficients than the vCT (median 0.91 vs 0.81) for targets and OARs. In general, the CBCTcor approach was less affected by inaccuracies of the DIR used during the generation of the vCT prior. Conclusion: Both techniques yield 3D CBCT images with intensities equivalent to diagnostic CT and appear suitable for IMPT dose calculation for most sites. For H&N cases, no considerable differences between the two techniques were found, while improved results of the CBCTcor were observed for pelvic cases due to the reduced sensitivity to registration inaccuracies. Deutsche Forschungsgemeinschaft (MAP); Bundesministerium fur Bildung und Forschung (01IB13001)« less

Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

PubMed

Wu, Junfeng; Dai, Fang; Hu, Gang; Mou, Xuanqin

2018-04-18

Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has been developed to reconstruct CT images from the low dose and few-view dataset in order to reduce radiation dose. Nonetheless, the sparse regularization term adopted in this approach is l0-norm, which cannot guarantee the global convergence of the proposed algorithm. To address this problem, in this study we introduced the l1-norm dictionary learning penalty into SIR framework for low dose CT image reconstruction, and developed an alternating minimization algorithm to minimize the associated objective function, which transforms CT image reconstruction problem into a sparse coding subproblem and an image updating subproblem. During the image updating process, an efficient model function approach based on balancing principle is applied to choose the regularization parameters. The proposed alternating minimization algorithm was evaluated first using real projection data of a sheep lung CT perfusion and then using numerical simulation based on sheep lung CT image and chest image. Both visual assessment and quantitative comparison using terms of root mean square error (RMSE) and structural similarity (SSIM) index demonstrated that the new image reconstruction algorithm yielded similar performance with l0-norm dictionary learning penalty and outperformed the conventional filtered backprojection (FBP) and total variation (TV) minimization algorithms.

Registration of 2D to 3D joint images using phase-based mutual information

NASA Astrophysics Data System (ADS)

Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul

2007-03-01

Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.

Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation.

PubMed

Hatt, Mathieu; Cheze-le Rest, Catherine; van Baardwijk, Angela; Lambin, Philippe; Pradier, Olivier; Visvikis, Dimitris

2011-11-01

The objectives of this study were to investigate the relationship between CT- and (18)F-FDG PET-based tumor volumes in non-small cell lung cancer (NSCLC) and the impact of tumor size and uptake heterogeneity on various approaches to delineating uptake on PET images. Twenty-five NSCLC cancer patients with (18)F-FDG PET/CT were considered. Seventeen underwent surgical resection of their tumor, and the maximum diameter was measured. Two observers manually delineated the tumors on the CT images and the tumor uptake on the corresponding PET images, using a fixed threshold at 50% of the maximum (T(50)), an adaptive threshold methodology, and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Maximum diameters of the delineated volumes were compared with the histopathology reference when available. The volumes of the tumors were compared, and correlations between the anatomic volume and PET uptake heterogeneity and the differences between delineations were investigated. All maximum diameters measured on PET and CT images significantly correlated with the histopathology reference (r > 0.89, P < 0.0001). Significant differences were observed among the approaches: CT delineation resulted in large overestimation (+32% ± 37%), whereas all delineations on PET images resulted in underestimation (from -15% ± 17% for T(50) to -4% ± 8% for FLAB) except manual delineation (+8% ± 17%). Overall, CT volumes were significantly larger than PET volumes (55 ± 74 cm(3) for CT vs. from 18 ± 25 to 47 ± 76 cm(3) for PET). A significant correlation was found between anatomic tumor size and heterogeneity (larger lesions were more heterogeneous). Finally, the more heterogeneous the tumor uptake, the larger was the underestimation of PET volumes by threshold-based techniques. Volumes based on CT images were larger than those based on PET images. Tumor size and tracer uptake heterogeneity have an impact on threshold-based methods, which should not be used for the delineation of cases of large heterogeneous NSCLC, as these methods tend to largely underestimate the spatial extent of the functional tumor in such cases. For an accurate delineation of PET volumes in NSCLC, advanced image segmentation algorithms able to deal with tracer uptake heterogeneity should be preferred.

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

PubMed Central

Grosser, Oliver S.; Kupitz, Dennis; Ruf, Juri; Czuczwara, Damian; Steffen, Ingo G.; Furth, Christian; Thormann, Markus; Loewenthal, David; Ricke, Jens; Amthauer, Holger

2015-01-01

Background Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images. Methodology/Principal Findings Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001). Conclusion/Significance In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality. PMID:26390216

Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

PubMed

Tanabe, Yuki; Kido, Teruhito; Kurata, Akira; Fukuyama, Naoki; Yokoi, Takahiro; Kido, Tomoyuki; Uetani, Teruyoshi; Vembar, Mani; Dhanantwari, Amar; Tokuyasu, Shinichi; Yamashita, Natsumi; Mochizuki, Teruhito

2017-10-01

We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The study investigated 35 patients who underwent a comprehensive cardiac CT protocol and LGE-MRI for the assessment of coronary artery disease. The CT protocol consisted of stress dynamic myocardial CT perfusion, coronary CT angiography (CTA) and LIE-CT using 256-slice CT. LIE-CT scans were acquired 5 min after CTA without additional contrast medium and reconstructed with filtered back projection (FBP), a hybrid iterative reconstruction (HIR), and IMR. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed. Sensitivity and specificity of LIE-CT for detecting MI were assessed according to the 16-segment model. Image quality scores, and diagnostic performance were compared among LIE-CT with FBP, HIR and IMR. Among the 35 patients, 139 of 560 segments showed MI in LGE-MRI. On LIE-CT with FBP, HIR, and IMR, the median SNRs were 2.1, 2.9, and 6.1; and the median CNRs were 1.7, 2.2, and 4.7, respectively. Sensitivity and specificity were 56 and 93% for FBP, 62 and 91% for HIR, and 80 and 91% for IMR. LIE-CT with IMR showed the highest image quality and sensitivity (p < 0.05). The use of IMR enables significant improvement of image quality and diagnostic performance of LIE-CT for detecting MI in comparison with FBP and HIR.

Potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Satake, M.; Kusumoto, M.; Tsuchida, T.; Aokage, K.; Eguchi, K.; Kaneko, M.; Moriyama, N.

2014-03-01

In this work, we investigate a potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection. The elucidation of the subcategorization of a pulmonary nodule type in CT images is an important preliminary step towards developing the nodule managements that are specific to each patient. We categorize lung cancers by analyzing volumetric distributions of CT values within lung cancers via a topic model such as latent Dirichlet allocation. Through applying our scheme to 3D CT images of nonsmall- cell lung cancer (maximum lesion size of 3 cm) , we demonstrate the potential usefulness of the topic model-based categorization of lung cancers as quantitative CT biomarkers.

Accurate registration of temporal CT images for pulmonary nodules detection

NASA Astrophysics Data System (ADS)

Yan, Jichao; Jiang, Luan; Li, Qiang

2017-02-01

Interpretation of temporal CT images could help the radiologists to detect some subtle interval changes in the sequential examinations. The purpose of this study was to develop a fully automated scheme for accurate registration of temporal CT images for pulmonary nodule detection. Our method consisted of three major registration steps. Firstly, affine transformation was applied in the segmented lung region to obtain global coarse registration images. Secondly, B-splines based free-form deformation (FFD) was used to refine the coarse registration images. Thirdly, Demons algorithm was performed to align the feature points extracted from the registered images in the second step and the reference images. Our database consisted of 91 temporal CT cases obtained from Beijing 301 Hospital and Shanghai Changzheng Hospital. The preliminary results showed that approximately 96.7% cases could obtain accurate registration based on subjective observation. The subtraction images of the reference images and the rigid and non-rigid registered images could effectively remove the normal structures (i.e. blood vessels) and retain the abnormalities (i.e. pulmonary nodules). This would be useful for the screening of lung cancer in our future study.

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Angelis, L; Landry, G; Dedes, G

Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBsmore » was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)« less

SU-F-J-156: The Feasibility of MR-Only IMRT Planning for Prostate Anatomy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vaitheeswaran, R; Sivaramakrishnan, KR; Kumar, Prashant

Purpose: For prostate anatomy, previous investigations have shown that simulated CT (sCT) generated from MR images can be used for accurate dose computation. In this study, we demonstrate the feasibility of MR-only IMRT planning for prostate case. Methods: Regular CT (rCT) and MR images of the same patient were acquired for prostate anatomy. Regions-of-interest (ROIs) i.e. target and risk structures are delineated on the rCT. A simulated CT (sCT) is generated from the MR image using the method described by Schadewaldt N et al. Their work establishes the clinical acceptability of dose calculation results on the sCT when compared tomore » rCT. rCT and sCT are rigidly registered to ensure proper alignment between the two images. rCT and sCT are overlaid on each other and slice-wise visual inspection confirms excellent agreement between the two images. ROIs on the rCT are copied over to sCT. Philips AutoPlanning solution is used for generating treatment plans. The same treatment technique protocol (plan parameters and clinical goals) is used to generate AutoPlan-rCT and AutoPlan-sCT respectively for rCT and and sCT. DVH comparison on ROIs and slice-wise evaluation of dose is performed between AutoPlan-rCT and AutoPlan-sCT. Delivery parameters i.e. beam and corresponding segments from the AutoPlan-sCT are copied over to rCT and dose is computed to get AutoPlan-sCT-on-rCT. Results: Plan evaluation is done based on Dose Volume Histogram (DVH) of ROIs and manual slice-wise inspection of dose distribution. Both AutoPlan-rCT and AutoPlan-sCT provide a clinically acceptable plan. Also, AutoPlan-sCT-on-rCT shows excellent agreement with AutoPlan-sCT. Conclusion: The study demonstrates that it is feasible to do IMRT planning on the simulated CT image obtained from MR image for prostate anatomy. The research is supported by Philips India Ltd.« less

Registration of parametric dynamic F-18-FDG PET/CT breast images with parametric dynamic Gd-DTPA breast images

NASA Astrophysics Data System (ADS)

Magri, Alphonso; Krol, Andrzej; Lipson, Edward; Mandel, James; McGraw, Wendy; Lee, Wei; Tillapaugh-Fay, Gwen; Feiglin, David

2009-02-01

This study was undertaken to register 3D parametric breast images derived from Gd-DTPA MR and F-18-FDG PET/CT dynamic image series. Nonlinear curve fitting (Levenburg-Marquardt algorithm) based on realistic two-compartment models was performed voxel-by-voxel separately for MR (Brix) and PET (Patlak). PET dynamic series consists of 50 frames of 1-minute duration. Each consecutive PET image was nonrigidly registered to the first frame using a finite element method and fiducial skin markers. The 12 post-contrast MR images were nonrigidly registered to the precontrast frame using a free-form deformation (FFD) method. Parametric MR images were registered to parametric PET images via CT using FFD because the first PET time frame was acquired immediately after the CT image on a PET/CT scanner and is considered registered to the CT image. We conclude that nonrigid registration of PET and MR parametric images using CT data acquired during PET/CT scan and the FFD method resulted in their improved spatial coregistration. The success of this procedure was limited due to relatively large target registration error, TRE = 15.1+/-7.7 mm, as compared to spatial resolution of PET (6-7 mm), and swirling image artifacts created in MR parametric images by the FFD. Further refinement of nonrigid registration of PET and MR parametric images is necessary to enhance visualization and integration of complex diagnostic information provided by both modalities that will lead to improved diagnostic performance.

Quantitative myocardial blood flow imaging with integrated time-of-flight PET-MR.

PubMed

Kero, Tanja; Nordström, Jonny; Harms, Hendrik J; Sörensen, Jens; Ahlström, Håkan; Lubberink, Mark

2017-12-01

The use of integrated PET-MR offers new opportunities for comprehensive assessment of cardiac morphology and function. However, little is known on the quantitative accuracy of cardiac PET imaging with integrated time-of-flight PET-MR. The aim of the present work was to validate the GE Signa PET-MR scanner for quantitative cardiac PET perfusion imaging. Eleven patients (nine male; mean age 59 years; range 46-74 years) with known or suspected coronary artery disease underwent 15 O-water PET scans at rest and during adenosine-induced hyperaemia on a GE Discovery ST PET-CT and a GE Signa PET-MR scanner. PET-MR images were reconstructed using settings recommended by the manufacturer, including time-of-flight (TOF). Data were analysed semi-automatically using Cardiac VUer software, resulting in both parametric myocardial blood flow (MBF) images and segment-based MBF values. Correlation and agreement between PET-CT-based and PET-MR-based MBF values for all three coronary artery territories were assessed using regression analysis and intra-class correlation coefficients (ICC). In addition to the cardiac PET-MR reconstruction protocol as recommended by the manufacturer, comparisons were made using a PET-CT resolution-matched reconstruction protocol both without and with TOF to assess the effect of time-of-flight and reconstruction parameters on quantitative MBF values. Stress MBF data from one patient was excluded due to movement during the PET-CT scanning. Mean MBF values at rest and stress were (0.92 ± 0.12) and (2.74 ± 1.37) mL/g/min for PET-CT and (0.90 ± 0.23) and (2.65 ± 1.15) mL/g/min for PET-MR (p = 0.33 and p = 0.74). ICC between PET-CT-based and PET-MR-based regional MBF was 0.98. Image quality was improved with PET-MR as compared to PET-CT. ICC between PET-MR-based regional MBF with and without TOF and using different filter and reconstruction settings was 1.00. PET-MR-based MBF values correlated well with PET-CT-based MBF values and the parametric PET-MR images were excellent. TOF and reconstruction settings had little impact on MBF values.

2D-3D registration using gradient-based MI for image guided surgery systems

NASA Astrophysics Data System (ADS)

Yim, Yeny; Chen, Xuanyi; Wakid, Mike; Bielamowicz, Steve; Hahn, James

2011-03-01

Registration of preoperative CT data to intra-operative video images is necessary not only to compare the outcome of the vocal fold after surgery with the preplanned shape but also to provide the image guidance for fusion of all imaging modalities. We propose a 2D-3D registration method using gradient-based mutual information. The 3D CT scan is aligned to 2D endoscopic images by finding the corresponding viewpoint between the real camera for endoscopic images and the virtual camera for CT scans. Even though mutual information has been successfully used to register different imaging modalities, it is difficult to robustly register the CT rendered image to the endoscopic image due to varying light patterns and shape of the vocal fold. The proposed method calculates the mutual information in the gradient images as well as original images, assigning more weight to the high gradient regions. The proposed method can emphasize the effect of vocal fold and allow a robust matching regardless of the surface illumination. To find the viewpoint with maximum mutual information, a downhill simplex method is applied in a conditional multi-resolution scheme which leads to a less-sensitive result to local maxima. To validate the registration accuracy, we evaluated the sensitivity to initial viewpoint of preoperative CT. Experimental results showed that gradient-based mutual information provided robust matching not only for two identical images with different viewpoints but also for different images acquired before and after surgery. The results also showed that conditional multi-resolution scheme led to a more accurate registration than single-resolution.

Comparison of 3 different postimplant dosimetry methods following permanent {sup 125}I prostate seed brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marcu, Loredana G., E-mail: loredana@marcunet.com; Faculty of Science, University of Oradea; School of Chemistry and Physics, University of Adelaide, South Australia

2013-10-01

Postimplant dosimetry (PID) after Iodine-125 ({sup 125}I) implant of the prostate should offer a reliable qualitative assessment. So far, there is no consensus regarding the optimum PID method, though the latest literature is in favor of magnetic resonance imaging (MRI). This study aims to simultaneously compare 3 PID techniques: (1) MRI-computed tomography (CT) fusion; (2) ultrasound (US)-CT fusion; and (3) manual target delineation on CT. The study comprised 10 patients with prostate cancer. CT/MR scans with urinary catheters in place for PID were done either on day 0 or day 1 postimplantation. The main parameter evaluated and compared among methodsmore » was target D90. The results show that CT-based D90s are lower than US-CT D90s (median difference,−6.85%), whereas MR-CT PID gives higher D90 than US-CT PID (median difference, 4.25%). Manual contouring on CT images tends to overestimate the prostate volume compared with transrectal ultrasound (TRUS) (median difference, 23.33%), whereas on US images the target is overestimated compared with MR-based contouring (median difference, 13.25%). Although there are certain differences among the results given by various PID techniques, the differences are statistically insignificant for this small group of patients. Any dosimetric comparison between 2 PID techniques should also account for the limitations of each technique, to allow for an accurate quantification of data. Given that PID after permanent radioactive seed implant is mandatory for quality assurance, any imaging method–based PID (MR-CT, US-CT, and CT) available in a radiotherapy department can be indicative of the quality of the procedure.« less

Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumarasiri, Akila, E-mail: akumara1@hfhs.org; Siddiqui, Farzan; Liu, Chang

2014-12-15

Purpose: To evaluate the clinical potential of deformable image registration (DIR)-based automatic propagation of physician-drawn contours from a planning CT to midtreatment CT images for head and neck (H and N) adaptive radiotherapy. Methods: Ten H and N patients, each with a planning CT (CT1) and a subsequent CT (CT2) taken approximately 3–4 week into treatment, were considered retrospectively. Clinically relevant organs and targets were manually delineated by a radiation oncologist on both sets of images. Four commercial DIR algorithms, two B-spline-based and two Demons-based, were used to deform CT1 and the relevant contour sets onto corresponding CT2 images. Agreementmore » of the propagated contours with manually drawn contours on CT2 was visually rated by four radiation oncologists in a scale from 1 to 5, the volume overlap was quantified using Dice coefficients, and a distance analysis was done using center of mass (CoM) displacements and Hausdorff distances (HDs). Performance of these four commercial algorithms was validated using a parameter-optimized Elastix DIR algorithm. Results: All algorithms attained Dice coefficients of >0.85 for organs with clear boundaries and those with volumes >9 cm{sup 3}. Organs with volumes <3 cm{sup 3} and/or those with poorly defined boundaries showed Dice coefficients of ∼0.5–0.6. For the propagation of small organs (<3 cm{sup 3}), the B-spline-based algorithms showed higher mean Dice values (Dice = 0.60) than the Demons-based algorithms (Dice = 0.54). For the gross and planning target volumes, the respective mean Dice coefficients were 0.8 and 0.9. There was no statistically significant difference in the Dice coefficients, CoM, or HD among investigated DIR algorithms. The mean radiation oncologist visual scores of the four algorithms ranged from 3.2 to 3.8, which indicated that the quality of transferred contours was “clinically acceptable with minor modification or major modification in a small number of contours.” Conclusions: Use of DIR-based contour propagation in the routine clinical setting is expected to increase the efficiency of H and N replanning, reducing the amount of time needed for manual target and organ delineations.« less

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

PubMed

Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz

2014-05-01

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.

SU-E-J-97: Evaluation of Multi-Modality (CT/MR/PET) Image Registration Accuracy in Radiotherapy Planning.

PubMed

Sethi, A; Rusu, I; Surucu, M; Halama, J

2012-06-01

Evaluate accuracy of multi-modality image registration in radiotherapy planning process. A water-filled anthropomorphic head phantom containing eight 'donut-shaped' fiducial markers (3 internal + 5 external) was selected for this study. Seven image sets (3CTs, 3MRs and PET) of phantom were acquired and fused in a commercial treatment planning system. First, a narrow slice (0.75mm) baseline CT scan was acquired (CT1). Subsequently, the phantom was re-scanned with a coarse slice width = 1.5mm (CT2) and after subjecting phantom to rotation/displacement (CT3). Next, the phantom was scanned in a 1.5 Tesla MR scanner and three MR image sets (axial T1, axial T2, coronal T1) were acquired at 2mm slice width. Finally, the phantom and center of fiducials were doped with 18F and a PET scan was performed with 2mm cubic voxels. All image scans (CT/MR/PET) were fused to the baseline (CT1) data using automated mutual-information based fusion algorithm. Difference between centroids of fiducial markers in various image modalities was used to assess image registration accuracy. CT/CT image registration was superior to CT/MR and CT/PET: average CT/CT fusion error was found to be 0.64 ± 0.14 mm. Corresponding values for CT/MR and CT/PET fusion were 1.33 ± 0.71mm and 1.11 ± 0.37mm. Internal markers near the center of phantom fused better than external markers placed on the phantom surface. This was particularly true for the CT/MR and CT/PET. The inferior quality of external marker fusion indicates possible distortion effects toward the edges of MR image. Peripheral targets in the PET scan may be subject to parallax error caused by depth of interaction of photons in detectors. Current widespread use of multimodality imaging in radiotherapy planning calls for periodic quality assurance of image registration process. Such studies may help improve safety and accuracy in treatment planning. © 2012 American Association of Physicists in Medicine.

How many CT detector rows are necessary to perform adequate three dimensional visualization?

PubMed

Fischer, Lars; Tetzlaff, Ralf; Schöbinger, Max; Radeleff, Boris; Bruckner, Thomas; Meinzer, H P; Büchler, M W; Schemmer, Peter

2010-06-01

The technical development of computer tomography (CT) imaging has experienced great progress. As consequence, CT data to be used for 3D visualization is not only based on 4 row CTs and 16 row CTs but also on 64 row CTs, respectively. The main goal of this study was to examine whether the increased amount of CT detector rows is correlated with improved quality of the 3D images. All CTs were acquired during routinely performed preoperative evaluation. Overall, there were 12 data sets based on 4 detector row CT, 12 data sets based on 16 detector row CT, and 10 data sets based on 64 detector row CT. Imaging data sets were transferred to the DKFZ Heidelberg using the CHILI teleradiology system. For the analysis all CT scans were examined in a blinded fashion, i.e. both the name of the patient as well as the name of the CT brand were erased. For analysis, the time for segmentation of liver, both portal and hepatic veins as well as the branching depth of portal veins and hepatic veins was recorded automatically. In addition, all results were validated in a blinded fashion based on given quality index. Segmentation of the liver was performed in significantly shorter time (p<0.01, Kruskal-Wallis test) in the 16 row CT (median 479 s) compared to 4 row CT (median 611 s), and 64 row CT (median 670 s), respectively. The branching depth of the portal vein did not differ significantly among the 3 different data sets (p=0.37, Kruskal-Wallis test). However, the branching depth of the hepatic veins was significantly better (p=0.028, Kruskal-Wallis test) in the 4 row CT and 16 row CT compared to 64 row CT. The grading of the quality index was not statistically different for portal veins and hepatic veins (p=0.80, Kruskal-Wallis test). Even though the total quality index was better for the vessel tree based on 64 row CT data sets (mean scale 2.6) compared to 4 CT row data (mean scale 3.25) and 16 row CT data (mean scale 3.0), these differences did not reach statistical difference (p=0.53, Kruskal-Wallis test). Even though 3D visualization is useful in operation planning, the quality of the 3D images appears to be not dependent of the number of CT detector rows. Copyright (c) 2009. Published by Elsevier Ireland Ltd.

Test of 3D CT reconstructions by EM + TV algorithm from undersampled data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da

2013-05-06

Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry withmore » alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.« less

Technical Note: Deep learning based MRAC using rapid ultra-short echo time imaging.

PubMed

Jang, Hyungseok; Liu, Fang; Zhao, Gengyan; Bradshaw, Tyler; McMillan, Alan B

2018-05-15

In this study, we explore the feasibility of a novel framework for MR-based attenuation correction for PET/MR imaging based on deep learning via convolutional neural networks, which enables fully automated and robust estimation of a pseudo CT image based on ultrashort echo time (UTE), fat, and water images obtained by a rapid MR acquisition. MR images for MRAC are acquired using dual echo ramped hybrid encoding (dRHE), where both UTE and out-of-phase echo images are obtained within a short single acquisition (35 sec). Tissue labeling of air, soft tissue, and bone in the UTE image is accomplished via a deep learning network that was pre-trained with T1-weighted MR images. UTE images are used as input to the network, which was trained using labels derived from co-registered CT images. The tissue labels estimated by deep learning are refined by a conditional random field based correction. The soft tissue labels are further separated into fat and water components using the two-point Dixon method. The estimated bone, air, fat, and water images are then assigned appropriate Hounsfield units, resulting in a pseudo CT image for PET attenuation correction. To evaluate the proposed MRAC method, PET/MR imaging of the head was performed on 8 human subjects, where Dice similarity coefficients of the estimated tissue labels and relative PET errors were evaluated through comparison to a registered CT image. Dice coefficients for air (within the head), soft tissue, and bone labels were 0.76±0.03, 0.96±0.006, and 0.88±0.01. In PET quantification, the proposed MRAC method produced relative PET errors less than 1% within most brain regions. The proposed MRAC method utilizing deep learning with transfer learning and an efficient dRHE acquisition enables reliable PET quantification with accurate and rapid pseudo CT generation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Comparison of hand and semiautomatic tracing methods for creating maxillofacial artificial organs using sequences of computed tomography (CT) and cone beam computed tomography (CBCT) images.

PubMed

Szabo, Bence T; Aksoy, Seçil; Repassy, Gabor; Csomo, Krisztian; Dobo-Nagy, Csaba; Orhan, Kaan

2017-06-09

The aim of this study was to compare the paranasal sinus volumes obtained by manual and semiautomatic imaging software programs using both CT and CBCT imaging. 121 computed tomography (CT) and 119 cone beam computed tomography (CBCT) examinations were selected from the databases of the authors' institutes. The Digital Imaging and Communications in Medicine (DICOM) images were imported into 3-dimensonal imaging software, in which hand mode and semiautomatic tracing methods were used to measure the volumes of both maxillary sinuses and the sphenoid sinus. The determined volumetric means were compared to previously published averages. Isometric CBCT-based volume determination results were closer to the real volume conditions, whereas the non-isometric CT-based volume measurements defined coherently lower volumes. By comparing the 2 volume measurement modes, the values gained from hand mode were closer to the literature data. Furthermore, CBCT-based image measurement results corresponded to the known averages. Our results suggest that CBCT images provide reliable volumetric information that can be depended on for artificial organ construction, and which may aid the guidance of the operator prior to or during the intervention.

Tensor-based Dictionary Learning for Spectral CT Reconstruction

PubMed Central

Zhang, Yanbo; Wang, Ge

2016-01-01

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

Optimization of dose and image quality in adult and pediatric computed tomography scans

NASA Astrophysics Data System (ADS)

Chang, Kwo-Ping; Hsu, Tzu-Kun; Lin, Wei-Ting; Hsu, Wen-Lin

2017-11-01

Exploration to maximize CT image and reduce radiation dose was conducted while controlling for multiple factors. The kVp, mAs, and iteration reconstruction (IR), affect the CT image quality and radiation dose absorbed. The optimal protocols (kVp, mAs, IR) are derived by figure of merit (FOM) based on CT image quality (CNR) and CT dose index (CTDIvol). CT image quality metrics such as CT number accuracy, SNR, low contrast materials' CNR and line pair resolution were also analyzed as auxiliary assessments. CT protocols were carried out with an ACR accreditation phantom and a five-year-old pediatric head phantom. The threshold values of the adult CT scan parameters, 100 kVp and 150 mAs, were determined from the CT number test and line pairs in ACR phantom module 1and module 4 respectively. The findings of this study suggest that the optimal scanning parameters for adults be set at 100 kVp and 150-250 mAs. However, for improved low- contrast resolution, 120 kVp and 150-250 mAs are optimal. Optimal settings for pediatric head CT scan were 80 kVp/50 mAs, for maxillary sinus and brain stem, while 80 kVp /300 mAs for temporal bone. SNR is not reliable as the independent image parameter nor the metric for determining optimal CT scan parameters. The iteration reconstruction (IR) approach is strongly recommended for both adult and pediatric CT scanning as it markedly improves image quality without affecting radiation dose.

Comparison of CT-derived Ventilation Maps with Deposition Patterns of Inhaled Microspheres in Rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacob, Rick E.; Lamm, W. J.; Einstein, Daniel R.

2015-04-01

Purpose: Computer models for inhalation toxicology and drug-aerosol delivery studies rely on ventilation pattern inputs for predictions of particle deposition and vapor uptake. However, changes in lung mechanics due to disease can impact airflow dynamics and model results. It has been demonstrated that non-invasive, in vivo, 4DCT imaging (3D imaging at multiple time points in the breathing cycle) can be used to map heterogeneities in ventilation patterns under healthy and disease conditions. The purpose of this study was to validate ventilation patterns measured from CT imaging by exposing the same rats to an aerosol of fluorescent microspheres (FMS) and examiningmore » particle deposition patterns using cryomicrotome imaging. Materials and Methods: Six male Sprague-Dawley rats were intratracheally instilled with elastase to a single lobe to induce a heterogeneous disease. After four weeks, rats were imaged over the breathing cycle by CT then immediately exposed to an aerosol of ~1µm FMS for ~5 minutes. After the exposure, the lungs were excised and prepared for cryomicrotome imaging, where a 3D image of FMS deposition was acquired using serial sectioning. Cryomicrotome images were spatially registered to match the live CT images to facilitate direct quantitative comparisons of FMS signal intensity with the CT-based ventilation maps. Results: Comparisons of fractional ventilation in contiguous, non-overlapping, 3D regions between CT-based ventilation maps and FMS images showed strong correlations in fractional ventilation (r=0.888, p<0.0001). Conclusion: We conclude that ventilation maps derived from CT imaging are predictive of the 1µm aerosol deposition used in ventilation-perfusion heterogeneity inhalation studies.« less

MR and CT data with multiobserver delineations of organs in the pelvic area-Part of the Gold Atlas project.

PubMed

Nyholm, Tufve; Svensson, Stina; Andersson, Sebastian; Jonsson, Joakim; Sohlin, Maja; Gustafsson, Christian; Kjellén, Elisabeth; Söderström, Karin; Albertsson, Per; Blomqvist, Lennart; Zackrisson, Björn; Olsson, Lars E; Gunnlaugsson, Adalsteinn

2018-03-01

We describe a public dataset with MR and CT images of patients performed in the same position with both multiobserver and expert consensus delineations of relevant organs in the male pelvic region. The purpose was to provide means for training and validation of segmentation algorithms and methods to convert MR to CT like data, i.e., so called synthetic CT (sCT). T1- and T2-weighted MR images as well as CT data were collected for 19 patients at three different departments. Five experts delineated nine organs for each patient based on the T2-weighted MR images. An automatic method was used to fuse the delineations. Starting from each fused delineation, a consensus delineation was agreed upon by the five experts for each organ and patient. Segmentation overlap between user delineations with respect to the consensus delineations was measured to describe the spread of the collected data. Finally, an open-source software was used to create deformation vector fields describing the relation between MR and CT images to further increase the usability of the dataset. The dataset has been made publically available to be used for academic purposes, and can be accessed from https://zenodo.org/record/583096. The dataset provides a useful source for training and validation of segmentation algorithms as well as methods to convert MR to CT-like data (sCT). To give some examples: The T2-weighted MR images with their consensus delineations can directly be used as a template in an existing atlas-based segmentation engine; the expert delineations are useful to validate the performance of a segmentation algorithm as they provide a way to measure variability among users which can be compared with the result of an automatic segmentation; and the pairwise deformably registered MR and CT images can be a source for an atlas-based sCT algorithm or for validation of sCT algorithm. © 2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Improving ultrasound quality to reduce computed tomography use in pediatric appendicitis: the Safe and Sound campaign.

PubMed

Kotagal, Meera; Richards, Morgan K; Chapman, Teresa; Finch, Lisa; McCann, Bessie; Ormazabal, Amaya; Rush, Robert J; Goldin, Adam B

2015-05-01

Safety concerns about the use of radiation-based imaging such as computed tomography (CT) in children have resulted in national recommendations to use ultrasound (US) for the diagnosis of appendicitis when possible. We evaluated the trends in CT and US use in a statewide sample and the accuracy of these modalities. Patients less than or equal to 18 years undergoing appendectomy in Washington State from 2008 to 2013 were evaluated for preoperative US/CT use, as well as imaging/pathology concordance using data from the Surgical Care and Outcomes Assessment Program. Among 3,353 children, 98.3% underwent preoperative imaging. There was a significant increase in the use of US first over the study period (P < .001). The use of CT at any time during the evaluation decreased. Despite this, in 2013, over 40% of the children still underwent CT imaging. Concordance between US imaging and pathology varied between 40% and 75% at hospitals performing greater than or equal to 10 appendectomies in 2013. Over one third (34.9%) of CT scans performed in the evaluation of children with appendicitis were performed after an indeterminate US. Although the use of US as the first imaging modality to diagnose pediatric appendicitis has increased over the past 5 years, over 40% of children still undergo a CT scan during their preoperative evaluation. Causality for this persistence of CT use is unclear, but could include variability in US accuracy, lack of training, and lack of awareness of the risks of radiation-based imaging. Developing a campaign to focus on continued reduction in CT and increased use of high-quality US should be pursued. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessment of phase based dose modulation for improved dose efficiency in cardiac CT on an anthropomorphic motion phantom

NASA Astrophysics Data System (ADS)

Budde, Adam; Nilsen, Roy; Nett, Brian

2014-03-01

State of the art automatic exposure control modulates the tube current across view angle and Z based on patient anatomy for use in axial full scan reconstructions. Cardiac CT, however, uses a fundamentally different image reconstruction that applies a temporal weighting to reduce motion artifacts. This paper describes a phase based mA modulation that goes beyond axial and ECG modulation; it uses knowledge of the temporal view weighting applied within the reconstruction algorithm to improve dose efficiency in cardiac CT scanning. Using physical phantoms and synthetic noise emulation, we measure how knowledge of sinogram temporal weighting and the prescribed cardiac phase can be used to improve dose efficiency. First, we validated that a synthetic CT noise emulation method produced realistic image noise. Next, we used the CT noise emulation method to simulate mA modulation on scans of a physical anthropomorphic phantom where a motion profile corresponding to a heart rate of 60 beats per minute was used. The CT noise emulation method matched noise to lower dose scans across the image within 1.5% relative error. Using this noise emulation method to simulate modulating the mA while keeping the total dose constant, the image variance was reduced by an average of 11.9% on a scan with 50 msec padding, demonstrating improved dose efficiency. Radiation dose reduction in cardiac CT can be achieved while maintaining the same level of image noise through phase based dose modulation that incorporates knowledge of the cardiac reconstruction algorithm.

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

PubMed Central

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael; Niu, Tianye; Zhu, Lei

2016-01-01

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan©600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan©600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution. PMID:27147376

Advanced imaging technologies for mapping cadaveric lymphatic anatomy: magnetic resonance and computed tomography lymphangiography.

PubMed

Pan, W R; Rozen, W M; Stretch, J; Thierry, B; Ashton, M W; Corlett, R J

2008-09-01

Lymphatic anatomy has become increasingly clinically important as surgical techniques evolve for investigating and treating cancer metastases. However, due to limited anatomical techniques available, research in this field has been insufficient. The techniques of computed tomography (CT) and magnetic resonance (MR) lymphangiography have not been described previously in the imaging of cadaveric lymphatic anatomy. This preliminary work describes the feasibility of these advanced imaging technologies for imaging lymphatic anatomy. A single, fresh cadaveric lower limb underwent lymphatic dissection and cannulation utilizing microsurgical techniques. Contrast materials for both CT and MR studies were chosen based on their suitability for subsequent clinical use, and imaging was undertaken with a view to mapping lymphatic anatomy. Microdissection studies were compared with imaging findings in each case. Both MR-based and CT-based contrast media in current clinical use were found to be suitable for demonstrating cadaveric lymphatic anatomy upon direct intralymphatic injection. MR lymphangiography and CT lymphangiography are feasible modalities for cadaveric anatomical research for lymphatic anatomy. Future studies including refinements in scanning techniques may offer these technologies to the clinical setting.

Image Fusion of CT and MR with Sparse Representation in NSST Domain

PubMed Central

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. PMID:29250134

Image Fusion of CT and MR with Sparse Representation in NSST Domain.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan; Xia, Shunren

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

Development of a Carbon Nanotube-Based Micro-CT and its Applications in Preclinical Research

NASA Astrophysics Data System (ADS)

Burk, Laurel May

Due to the dependence of researchers on mouse models for the study of human disease, diagnostic tools available in the clinic must be modified for use on these much smaller subjects. In addition to high spatial resolution, cardiac and lung imaging of mice presents extreme temporal challenges, and physiological gating methods must be developed in order to image these organs without motion blur. Commercially available micro-CT imaging devices are equipped with conventional thermionic x-ray sources and have a limited temporal response and are not ideal for in vivo small animal studies. Recent development of a field-emission x-ray source with carbon nanotube (CNT) cathode in our lab presented the opportunity to create a micro-CT device well-suited for in vivo lung and cardiac imaging of murine models for human disease. The goal of this thesis work was to present such a device, to develop and refine protocols which allow high resolution in vivo imaging of free-breathing mice, and to demonstrate the use of this new imaging tool for the study many different disease models. In Chapter 1, I provide background information about x-rays, CT imaging, and small animal micro-CT. In Chapter 2, CNT-based x-ray sources are explained, and details of a micro-focus x-ray tube specialized for micro-CT imaging are presented. In Chapter 3, the first and second generation CNT micro-CT devices are characterized, and successful respiratory- and cardiac-gated live animal imaging on normal, wild-type mice is achieved. In Chapter 4, respiratory-gated imaging of mouse disease models is demonstrated, limitations to the method are discussed, and a new contactless respiration sensor is presented which addresses many of these limitations. In Chapter 5, cardiac-gated imaging of disease models is demonstrated, including studies of aortic calcification, left ventricular hypertrophy, and myocardial infarction. In Chapter 6, several methods for image and system improvement are explored, and radiation therapy-related micro-CT imaging is present. Finally, in Chapter 7 I discuss future directions for this research and for the CNT micro-CT.

Interactive CT-Video Registration for the Continuous Guidance of Bronchoscopy

PubMed Central

Merritt, Scott A.; Khare, Rahul; Bascom, Rebecca

2014-01-01

Bronchoscopy is a major step in lung cancer staging. To perform bronchoscopy, the physician uses a procedure plan, derived from a patient’s 3D computed-tomography (CT) chest scan, to navigate the bronchoscope through the lung airways. Unfortunately, physicians vary greatly in their ability to perform bronchoscopy. As a result, image-guided bronchoscopy systems, drawing upon the concept of CT-based virtual bronchoscopy (VB), have been proposed. These systems attempt to register the bronchoscope’s live position within the chest to a CT-based virtual chest space. Recent methods, which register the bronchoscopic video to CT-based endoluminal airway renderings, show promise but do not enable continuous real-time guidance. We present a CT-video registration method inspired by computer-vision innovations in the fields of image alignment and image-based rendering. In particular, motivated by the Lucas–Kanade algorithm, we propose an inverse-compositional framework built around a gradient-based optimization procedure. We next propose an implementation of the framework suitable for image-guided bronchoscopy. Laboratory tests, involving both single frames and continuous video sequences, demonstrate the robustness and accuracy of the method. Benchmark timing tests indicate that the method can run continuously at 300 frames/s, well beyond the real-time bronchoscopic video rate of 30 frames/s. This compares extremely favorably to the ≥1 s/frame speeds of other methods and indicates the method’s potential for real-time continuous registration. A human phantom study confirms the method’s efficacy for real-time guidance in a controlled setting, and, hence, points the way toward the first interactive CT-video registration approach for image-guided bronchoscopy. Along this line, we demonstrate the method’s efficacy in a complete guidance system by presenting a clinical study involving lung cancer patients. PMID:23508260

An evaluation on CT image acquisition method for medical VR applications

NASA Astrophysics Data System (ADS)

Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang

2017-02-01

Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gong, G; Liu, C; Liu, C

Purpose: To analyze the error in contouring the brainstem for patients with head and neck cancer who underwent radiotherapy based on computed tomography (CT) and magnetic resonance (MR) images. Methods: 20 brain tumor and 17 nasopharyngeal cancer patients were randomly selected. Each patient underwent MR and CT scanning. For each patient, one observer contoured the brainstem on CT and MR images for 10 times, and 10 observers from five centers delineated the brainstem on CT and MR images only one time. The inter- and intra-observers volume and outline variations were compared. Results: The volumes of brainstem contoured by inter- andmore » intra-observers on CT and MR images were similar (p>0.05). The reproducibility of contouring brainstem on MR images was better than that on CT images (p<0.05) for both inter- and intra-observer variability. The inter- and intra-observer for contouring on CT images reached mean values of 0.81±0.05 (p>0.05) and of 0.85±0.05 (p>0.05), respectively, while on MR images these respective values were 0.90±0.05 (p>0.05) and 0.92±0.04 (p>0.05). Conclusion: Contouring the brainstem on MR images was more accurate and reproducible than that on CT images. Precise information might be more helpful for protecting the brainstem radiation injury the patients whose lesion were closed to brainstem.« less

Imaging of skull base lesions.

PubMed

Kelly, Hillary R; Curtin, Hugh D

2016-01-01

Skull base imaging requires a thorough knowledge of the complex anatomy of this region, including the numerous fissures and foramina and the major neurovascular structures that traverse them. Computed tomography (CT) and magnetic resonance imaging (MRI) play complementary roles in imaging of the skull base. MR is the preferred modality for evaluation of the soft tissues, the cranial nerves, and the medullary spaces of bone, while CT is preferred for demonstrating thin cortical bone structure. The anatomic location and origin of a lesion as well as the specific CT and MR findings can often narrow the differential diagnosis to a short list of possibilities. However, the primary role of the imaging specialist in evaluating the skull base is usually to define the extent of the lesion and determine its relationship to vital neurovascular structures. Technologic advances in imaging and radiation therapy, as well as surgical technique, have allowed for more aggressive approaches and improved outcomes, further emphasizing the importance of precise preoperative mapping of skull base lesions via imaging. Tumors arising from and affecting the cranial nerves at the skull base are considered here. © 2016 Elsevier B.V. All rights reserved.

WE-EF-207-09: Single-Scan Dual-Energy CT Using Primary Modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrongolo, M; Zhu, L

Purpose: Compared with conventional CT, dual energy CT (DECT) provides better material differentiation but requires projection data with two different effective x-ray spectra. Current DECT scanners use either a two-scan setting or costly imaging components, which are not feasible or available on open-gantry cone-beam CT systems. We propose a hardware-based method which utilizes primary modulation to enable single-scan DECT on a conventional CT scanner. The CT imaging geometry of primary modulation is identical to that used in our previous method for scatter removal, making it possible for future combination with effective scatter correction on the same CT scanner. Methods: Wemore » insert an attenuation sheet with a spatially-varying pattern - primary modulator-between the x-ray source and the imaged object. During the CT scan, the modulator selectively hardens the x-ray beam at specific detector locations. Thus, the proposed method simultaneously acquires high and low energy data. High and low energy CT images are then reconstructed from projections with missing data via an iterative CT reconstruction algorithm with gradient weighting. Proof-of-concept studies are performed using a copper modulator on a cone-beam CT system. Results: Our preliminary results on the Catphan(c) 600 phantom indicate that the proposed method for single-scan DECT is able to successfully generate high-quality high and low energy CT images and distinguish different materials through basis material decomposition. By applying correction algorithms and using all of the acquired projection data, we can reconstruct a single CT image of comparable image quality to conventional CT images, i.e., without primary modulation. Conclusion: This work shows great promise in using a primary modulator to perform high-quality single-scan DECT imaging. Future studies will test method performance on anthropomorphic phantoms and perform quantitative analyses on image qualities and DECT decomposition accuracy. We will use simulations to optimize the modulator material and geometry parameters.« less

Submillisievert Radiation Dose Coronary CT Angiography: Clinical Impact of the Knowledge-Based Iterative Model Reconstruction.

PubMed

Iyama, Yuji; Nakaura, Takeshi; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Sakaino, Naritsugu; Tokuyasu, Shinichi; Osakabe, Hirokazu; Harada, Kazunori; Yamashita, Yasuyuki

2016-11-01

The purpose of this study was to evaluate the noise and image quality of images reconstructed with a knowledge-based iterative model reconstruction (knowledge-based IMR) in ultra-low dose cardiac computed tomography (CT). We performed submillisievert radiation dose coronary CT angiography on 43 patients. We also performed a phantom study to evaluate the influence of object size with the automatic exposure control phantom. We reconstructed clinical and phantom studies with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and knowledge-based IMR. We measured effective dose of patients and compared CT number, image noise, and contrast noise ratio in ascending aorta of each reconstruction technique. We compared the relationship between image noise and body mass index for the clinical study, and object size for phantom study. The mean effective dose was 0.98 ± 0.25 mSv. The image noise of knowledge-based IMR images was significantly lower than those of FBP and hybrid IR images (knowledge-based IMR: 19.4 ± 2.8; FBP: 126.7 ± 35.0; hybrid IR: 48.8 ± 12.8, respectively) (P < .01). The contrast noise ratio of knowledge-based IMR images was significantly higher than those of FBP and hybrid IR images (knowledge-based IMR: 29.1 ± 5.4; FBP: 4.6 ± 1.3; hybrid IR: 13.1 ± 3.5, respectively) (P < .01). There were moderate correlations between image noise and body mass index in FBP (r = 0.57, P < .01) and hybrid IR techniques (r = 0.42, P < .01); however, these correlations were weak in knowledge-based IMR (r = 0.27, P < .01). Compared to FBP and hybrid IR, the knowledge-based IMR offers significant noise reduction and improvement in image quality in submillisievert radiation dose cardiac CT. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Automatic lumbar spine measurement in CT images

NASA Astrophysics Data System (ADS)

Mao, Yunxiang; Zheng, Dong; Liao, Shu; Peng, Zhigang; Yan, Ruyi; Liu, Junhua; Dong, Zhongxing; Gong, Liyan; Zhou, Xiang Sean; Zhan, Yiqiang; Fei, Jun

2017-03-01

Accurate lumbar spine measurement in CT images provides an essential way for quantitative spinal diseases analysis such as spondylolisthesis and scoliosis. In today's clinical workflow, the measurements are manually performed by radiologists and surgeons, which is time consuming and irreproducible. Therefore, automatic and accurate lumbar spine measurement algorithm becomes highly desirable. In this study, we propose a method to automatically calculate five different lumbar spine measurements in CT images. There are three main stages of the proposed method: First, a learning based spine labeling method, which integrates both the image appearance and spine geometry information, is used to detect lumbar and sacrum vertebrae in CT images. Then, a multiatlases based image segmentation method is used to segment each lumbar vertebra and the sacrum based on the detection result. Finally, measurements are derived from the segmentation result of each vertebra. Our method has been evaluated on 138 spinal CT scans to automatically calculate five widely used clinical spine measurements. Experimental results show that our method can achieve more than 90% success rates across all the measurements. Our method also significantly improves the measurement efficiency compared to manual measurements. Besides benefiting the routine clinical diagnosis of spinal diseases, our method also enables the large scale data analytics for scientific and clinical researches.

Design of CT reconstruction kernel specifically for clinical lung imaging

NASA Astrophysics Data System (ADS)

Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

2005-04-01

In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

Skull base, orbits, temporal bone, and cranial nerves: anatomy on MR imaging.

PubMed

Morani, Ajaykumar C; Ramani, Nisha S; Wesolowski, Jeffrey R

2011-08-01

Accurate delineation, diagnosis, and treatment planning of skull base lesions require knowledge of the complex anatomy of the skull base. Because the skull base cannot be directly evaluated, imaging is critical for the diagnosis and management of skull base diseases. Although computed tomography (CT) is excellent for outlining the bony detail, magnetic resonance (MR) imaging provides better soft tissue detail and is helpful for evaluating the adjacent meninges, brain parenchyma, and bone marrow of the skull base. Thus, CT and MR imaging are often used together for evaluating skull base lesions. This article focuses on the radiologic anatomy of the skull base pertinent to MR imaging evaluation. Copyright © 2011 Elsevier Inc. All rights reserved.

Accuracy and feasibility of three different methods for software-based image fusion in whole-body PET and CT.

PubMed

Putzer, Daniel; Henninger, Benjamin; Kovacs, Peter; Uprimny, Christian; Kendler, Dorota; Jaschke, Werner; Bale, Reto J

2016-06-01

Even as PET/CT provides valuable diagnostic information in a great number of clinical indications, availability of hybrid PET/CT scanners is mainly limited to clinical centers. A software-based image fusion would facilitate combined image reading of CT and PET data sets if hardware image fusion is not available. To analyze the relevance of retrospective image fusion of separately acquired PET and CT data sets, we studied the accuracy, practicability and reproducibility of three different image registration techniques. We evaluated whole-body 18F-FDG-PET and CT data sets of 71 oncologic patients. Images were fused retrospectively using Stealth Station System, Treon (Medtronic Inc., Louisville, CO, USA) equipped with Cranial4 Software. External markers fixed to a vacuum mattress were used as reference for exact repositioning. Registration was repeated using internal anatomic landmarks and Automerge software, assessing accuracy for all three methods, measuring distances of liver representation in CT and PET with reference to a common coordinate system. On first measurement of image fusions with external markers, 53 were successful, 16 feasible and 2 not successful. Using anatomic landmarks, 42 were successful, 26 feasible and 3 not successful. Using Automerge Software only 13 were successful. The mean distance between center points in PET and CT was 7.69±4.96 mm on first, and 7.65±4.2 mm on second measurement. Results with external markers correlate very well and inaccuracies are significantly lower (P<0.001) than results using anatomical landmarks (10.38±6.13 mm and 10.83±6.23 mm). Analysis revealed a significantly faster alignment using external markers (P<0.001). External fiducials in combination with immobilization devices and breathing protocols allow for highly accurate image fusion cost-effectively and significantly less time, posing an attractive alternative for PET/CT interpretation when a hybrid scanner is not available.

The role of FDG PET/CT in patients with locoregional breast cancer recurrence: a comparison to conventional imaging techniques.

PubMed

Aukema, T S; Rutgers, E J Th; Vogel, W V; Teertstra, H J; Oldenburg, H S; Vrancken Peeters, M T F D; Wesseling, J; Russell, N S; Valdés Olmos, R A

2010-04-01

The aim of this study was to evaluate the impact of (18)F-fluorodeoxyglucose positron-emission tomography/computed tomography (FDG PET/CT) on clinical management in patients with locoregional breast cancer recurrence amenable for locoregional treatment and to compare the PET/CT results with the conventional imaging data. From January 2006 to August 2008, all patients with locoregional breast cancer recurrence underwent whole-body PET/CT. PET/CT findings were compared with results of the conventional imaging techniques and final pathology. The impact of PET/CT results on clinical management was evaluated based on clinical decisions obtained from patient files. 56 patients were included. In 32 patients (57%) PET/CT revealed additional tumour localisations. Distant metastases were detected in 11 patients on conventional imaging and in 23 patients on PET/CT images (p < 0.01). In 25 patients (45%), PET/CT detected additional lesions not visible on conventional imaging. PET/CT had an impact on clinical management in 27 patients (48%) by detecting more extensive locoregional disease or distant metastases. In 20 patients (36%) extensive surgery was prevented and treatment was changed to palliative treatment. The sensitivity, specificity, accuracy, positive and negative predictive values of FDG PET/CT were respectively 97%, 92%, 95%, 94% and 96%. PET/CT, in addition to conventional imaging techniques, plays an important role in staging patients with locoregional breast cancer recurrence since its result changed the clinical management in almost half of the patients. PET/CT could potentially replace conventional staging imaging in patients with a locoregional breast cancer recurrence. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Zero-Extra-Dose PET Delayed Imaging with Data-Driven Attenuation Correction Estimation.

PubMed

Pang, Lifang; Zhu, Wentao; Dong, Yun; Lv, Yang; Shi, Hongcheng

2018-05-08

Delayed positron emission tomography (PET) imaging may improve sensitivity and specificity in lesion detection. We proposed a PET data-driven method to estimate the attenuation map (AM) for the delayed scan without an additional x-ray computed tomography (CT). An emission-attenuation-scatter joint estimation framework was developed. Several practical issues for clinical datasets were addressed. Particularly, the unknown scatter correction was incorporated in the joint estimation algorithm. The scaling problem was solved using prior information from the early CT scan. Fourteen patient datasets were added to evaluate the method. These patients went through two separate PET/CT scans. The delayed CT-based AM served as ground truth for the delayed scan. Standard uptake values (SUVmean and SUVmax) of lesion and normal tissue regions of interests (ROIs) in the early and delayed phase and the respective %DSUV (percentage change of SUVmean at two different time points) were analyzed, all with estimated and the true AM. Three radiologists participated in lesion detection tasks with images reconstructed with both AMs and rated scores for detectability. The mean relative difference of SUVmean in lesion and normal liver tissue were 3.30 and 6.69 %. The average lesion-to-background contrast (detectability) with delayed PET images using CT AM was 60 % higher than that of the earlier PET image, and was 64 % higher when using the data-based AM. %DSUV for lesions and liver backgrounds with CT-based AM were - 0.058 ± 0.25 and - 0.33 ± 0.08 while with data-based AM were - 0.00 ± 0.26 and - 0.28 ± 0.08. Only slight significance difference was found between using CT-based AM and using the data-based AM reconstruction delay phase on %DSUV of lesion. The scores associated with the two AMs matched well consistently. Our method may be used in delayed PET imaging, which allows no secondary CT radiation in delayed phase. The quantitative analysis for lesion detection purpose could be ensured.

WE-FG-207B-04: Noise Suppression for Energy-Resolved CT Via Variance Weighted Non-Local Filtration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harms, J; Zhu, L

Purpose: The photon starvation problem is exacerbated in energy-resolved CT, since the detected photons are shared by multiple energy channels. Using pixel similarity-based non-local filtration, we aim to produce accurate and high-resolution energy-resolved CT images with significantly reduced noise. Methods: Averaging CT images reconstructed from different energy channels reduces noise at the price of losing spectral information, while conventional denoising techniques inevitably degrade image resolution. Inspired by the fact that CT images of the same object at different energies share the same structures, we aim to reduce noise of energy-resolved CT by averaging only pixels of similar materials - amore » non-local filtration technique. For each CT image, an empirical exponential model is used to calculate the material similarity between two pixels based on their CT values and the similarity values are organized in a matrix form. A final similarity matrix is generated by averaging these similarity matrices, with weights inversely proportional to the estimated total noise variance in the sinogram of different energy channels. Noise suppression is achieved for each energy channel via multiplying the image vector by the similarity matrix. Results: Multiple scans on a tabletop CT system are used to simulate 6-channel energy-resolved CT, with energies ranging from 75 to 125 kVp. On a low-dose acquisition at 15 mA of the Catphan©600 phantom, our method achieves the same image spatial resolution as a high-dose scan at 80 mA with a noise standard deviation (STD) lower by a factor of >2. Compared with another non-local noise suppression algorithm (ndiNLM), the proposed algorithms obtains images with substantially improved resolution at the same level of noise reduction. Conclusion: We propose a noise-suppression method for energy-resolved CT. Our method takes full advantage of the additional structural information provided by energy-resolved CT and preserves image values at each energy level. Research reported in this publication was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB019597. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers.

PubMed

Bellesi, Luca; Wyttenbach, Rolf; Gaudino, Diego; Colleoni, Paolo; Pupillo, Francesco; Carrara, Mauro; Braghetti, Antonio; Puligheddu, Carla; Presilla, Stefano

2017-01-01

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images. Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

A PET/CT-Based Strategy Is a Stronger Predictor of Survival Than a Standard Imaging Strategy in Patients with Head and Neck Squamous Cell Carcinoma.

PubMed

Rohde, Max; Nielsen, Anne L; Pareek, Manan; Johansen, Jørgen; Sørensen, Jens A; Diaz, Anabel; Nielsen, Mie K; Christiansen, Janus M; Asmussen, Jon T; Nguyen, Nina; Gerke, Oke; Thomassen, Anders; Alavi, Abass; Høilund-Carlsen, Poul Flemming; Godballe, Christian

2018-04-01

Our purpose was to examine whether staging of head and neck squamous cell carcinoma (HNSCC) by upfront 18 F-FDG PET/CT (i.e., on the day of biopsy and before the biopsy) discriminates survival better than the traditional imaging strategies based on chest x-ray plus head and neck MRI (CXR/MRI) or chest CT plus head and neck MRI (CCT/MRI). Methods: We performed a masked prospective cohort study based on paired data. Consecutive patients with histologically verified primary HNSCC were recruited from Odense University Hospital from September 2013 to March 2016. All patients underwent CXR/MRI, CCT/MRI, and PET/CT on the same day. Tumors were categorized as localized (stages I and II), locally advanced (stages III and IVB), or metastatic (stage IVC). Discriminative ability for each imaging modality with respect to HNSCC staging were compared using Kaplan-Meier analysis, Cox proportional hazards regression with the Harrell C-index, and net reclassification improvement. Results: In total, 307 patients with histologically verified HNSCC were included. Use of PET/CT significantly altered the stratification of tumor stage when compared with either CXR/MRI or CCT/MRI (χ 2 , P < 0.001 for both). Cancer stages based on PET/CT, but not CXR/MRI or CCT/MRI, were associated with significant differences in mortality risk on Kaplan-Meier analyses ( P ≤ 0.002 for all PET/CT-based comparisons). Furthermore, overall discriminative ability was significantly greater for PET/CT (C-index, 0.712) than for CXR/MRI (C-index, 0.675; P = 0.04) or CCT/MRI (C-index, 0.657; P = 0.02). Finally, PET/CT was significantly associated with a positive net reclassification improvement when compared with CXR/MRI (0.184, P = 0.03) but not CCT/MRI (0.094%, P = 0.31). Conclusion: Tumor stages determined by PET/CT were associated with more distinct prognostic properties in terms of survival than those determined by standard imaging strategies. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Comparative diagnostic value of 18F-fluoride PET-CT versus MRI for skull-base bone invasion in nasopharyngeal carcinoma.

PubMed

Le, Yali; Chen, Yu; Zhou, Fan; Liu, Guangfu; Huang, Zhanwen; Chen, Yue

2016-10-01

This study compared the diagnostic value of F-fluoride PET-computed tomography (PET-CT) and MRI in skull-base bone erosion in nasopharyngeal carcinoma (NPC) patients. A total of 93 patients with biopsy-confirmed NPC were enrolled, including 68 men and 25 women between 23 and 74 years of age. All patients were evaluated by both F-fluoride PET-CT and MRI, and the interval between the two imaging examinations was less than 20 days. The patients received no treatment either before or between scans. The studies were interpreted by two nuclear medicine physicians or two radiologists with more than 10 years of professional experience who were blinded to both the diagnosis and the results of the other imaging studies. The reference standard was skull-base bone erosion at a 20-week follow-up imaging study. On the basis of the results of the follow-up imaging studies, 52 patients showed skull-base bone erosion. The numbers of true positives, false positives, true negatives, and false negatives with F-fluoride PET-CT were 49, 4, 37, and 3, respectively. The numbers of true positives, false positives, true negatives, and false negatives with MRI were 46, 5, 36, and 6, respectively. The sensitivity, specificity, and crude accuracy of F-fluoride PET-CT were 94.23, 90.24, and 92.47%, respectively; for MRI, these values were 88.46, 87.80, and 88.17%. Of the 52 patients, 43 showed positive findings both on F-fluoride PET-CT and on MRI. Within the patient cohort, F-fluoride PET-CT and MRI detected 178 and 135 bone lesions, respectively. Both F-fluoride PET-CT and MRI have high sensitivity, specificity, and crude accuracy for detecting skull-base bone invasion in patients with NPC. F-fluoride PET-CT detected more lesions than did MRI in the skull-base bone. This suggests that F-fluoride PET-CT has a certain advantage in evaluating the skull-base bone of NPC patients. Combining the two methods could improve the diagnostic accuracy of skull-base bone invasion for NPC.

Low-dose dynamic myocardial perfusion CT image reconstruction using pre-contrast normal-dose CT scan induced structure tensor total variation regularization

NASA Astrophysics Data System (ADS)

Gong, Changfei; Han, Ce; Gan, Guanghui; Deng, Zhenxiang; Zhou, Yongqiang; Yi, Jinling; Zheng, Xiaomin; Xie, Congying; Jin, Xiance

2017-04-01

Dynamic myocardial perfusion CT (DMP-CT) imaging provides quantitative functional information for diagnosis and risk stratification of coronary artery disease by calculating myocardial perfusion hemodynamic parameter (MPHP) maps. However, the level of radiation delivered by dynamic sequential scan protocol can be potentially high. The purpose of this work is to develop a pre-contrast normal-dose scan induced structure tensor total variation regularization based on the penalized weighted least-squares (PWLS) criteria to improve the image quality of DMP-CT with a low-mAs CT acquisition. For simplicity, the present approach was termed as ‘PWLS-ndiSTV’. Specifically, the ndiSTV regularization takes into account the spatial-temporal structure information of DMP-CT data and further exploits the higher order derivatives of the objective images to enhance denoising performance. Subsequently, an effective optimization algorithm based on the split-Bregman approach was adopted to minimize the associative objective function. Evaluations with modified dynamic XCAT phantom and preclinical porcine datasets have demonstrated that the proposed PWLS-ndiSTV approach can achieve promising gains over other existing approaches in terms of noise-induced artifacts mitigation, edge details preservation, and accurate MPHP maps calculation.

A feasibility study of X-ray phase-contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron.

PubMed

Nesterets, Yakov I; Gureyev, Timur E; Mayo, Sheridan C; Stevenson, Andrew W; Thompson, Darren; Brown, Jeremy M C; Kitchen, Marcus J; Pavlov, Konstantin M; Lockie, Darren; Brun, Francesco; Tromba, Giuliana

2015-11-01

Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.

Phantom-less bone mineral density (BMD) measurement using dual energy computed tomography-based 3-material decomposition

NASA Astrophysics Data System (ADS)

Hofmann, Philipp; Sedlmair, Martin; Krauss, Bernhard; Wichmann, Julian L.; Bauer, Ralf W.; Flohr, Thomas G.; Mahnken, Andreas H.

2016-03-01

Osteoporosis is a degenerative bone disease usually diagnosed at the manifestation of fragility fractures, which severely endanger the health of especially the elderly. To ensure timely therapeutic countermeasures, noninvasive and widely applicable diagnostic methods are required. Currently the primary quantifiable indicator for bone stability, bone mineral density (BMD), is obtained either by DEXA (Dual-energy X-ray absorptiometry) or qCT (quantitative CT). Both have respective advantages and disadvantages, with DEXA being considered as gold standard. For timely diagnosis of osteoporosis, another CT-based method is presented. A Dual Energy CT reconstruction workflow is being developed to evaluate BMD by evaluating lumbar spine (L1-L4) DE-CT images. The workflow is ROI-based and automated for practical use. A dual energy 3-material decomposition algorithm is used to differentiate bone from soft tissue and fat attenuation. The algorithm uses material attenuation coefficients on different beam energy levels. The bone fraction of the three different tissues is used to calculate the amount of hydroxylapatite in the trabecular bone of the corpus vertebrae inside a predefined ROI. Calibrations have been performed to obtain volumetric bone mineral density (vBMD) without having to add a calibration phantom or to use special scan protocols or hardware. Accuracy and precision are dependent on image noise and comparable to qCT images. Clinical indications are in accordance with the DEXA gold standard. The decomposition-based workflow shows bone degradation effects normally not visible on standard CT images which would induce errors in normal qCT results.

SU-F-303-12: Implementation of MR-Only Simulation for Brain Cancer: A Virtual Clinical Trial

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glide-Hurst, C; Zheng, W; Kim, J

2015-06-15

Purpose: To perform a retrospective virtual clinical trial using an MR-only workflow for a variety of brain cancer cases by incorporating novel imaging sequences, tissue segmentation using phase images, and an innovative synthetic CT (synCT) solution. Methods: Ten patients (16 lesions) were evaluated using a 1.0T MR-SIM including UTE-DIXON imaging (TE = 0.144/3.4/6.9ms). Bone-enhanced images were generated from DIXON-water/fat and inverted UTE. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating intersection and Dice similarity coefficients (DSC) using CT-SIM as ground truth. SynCTs were generated using voxel-based weighted summation incorporating T2, FLAIR, UTE1,more » and bone-enhanced images. Mean absolute error (MAE) characterized HU differences between synCT and CT-SIM. Dose was recalculated on synCTs; differences were quantified using planar gamma analysis (2%/2 mm dose difference/distance to agreement) at isocenter. Digitally reconstructed radiographs (DRRs) were compared. Results: On average, air maps intersected 80.8 ±5.5% (range: 71.8–88.8%) between MR-SIM and CT-SIM yielding DSCs of 0.78 ± 0.04 (range: 0.70–0.83). Whole-brain MAE between synCT and CT-SIM was 160.7±8.8 HU, with the largest uncertainty arising from bone (MAE = 423.3±33.2 HU). Gamma analysis revealed pass rates of 99.4 ± 0.04% between synCT and CT-SIM for the cohort. Dose volume histogram analysis revealed that synCT tended to yield slightly higher doses. Organs at risk such as the chiasm and optic nerves were most sensitive due to their proximities to air/bone interfaces. DRRs generated via synCT and CT-SIM were within clinical tolerances. Conclusion: Our approach for MR-only simulation for brain cancer treatment planning yielded clinically acceptable results relative to the CT-based benchmark. While slight dose differences were observed, reoptimization of treatment plans and improved image registration can address this limitation. Future work will incorporate automated registration between setup images (cone-beam CT and kilovoltage images) for synCT and CT-SIM. Submitting institution holds research agreements with Philips HealthCare, Best, Netherlands and Varian Medical Systems, Palo Alto, CA. Research partially sponsored via an Internal Mentored Research Grant.« less

SU-E-E-16: The Application of Texture Analysis for Differentiation of Central Cancer From Atelectasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, M; Fan, T; Duan, J

2015-06-15

Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET-CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET-CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co-occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05).more » Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.« less

Advances in cardiac CT contrast injection and acquisition protocols.

PubMed

Scholtz, Jan-Erik; Ghoshhajra, Brian

2017-10-01

Cardiac computed tomography (CT) imaging has become an important part of modern cardiovascular care. Coronary CT angiography (CTA) is the first choice imaging modality for non-invasive visualization of coronary artery stenosis. In addition, cardiac CT does not only provide anatomical evaluation, but also functional and valvular assessment, and myocardial perfusion evaluation. In this article we outline the factors which influence contrast enhancement, give an overview of current contrast injection and acquisition protocols, with focus on current emerging topics such as pre-transcatheter aortic valve replacement (TAVR) planning, cardiac CT for congenital heart disease (CHD) patients, and myocardial CT perfusion (CTP). Further, we point out areas where we see potential for future improvements in cardiac CT imaging based on a closer interaction between CT scanner settings and contrast injection protocols to tailor injections to patient- and exam-specific factors.

Advances in cardiac CT contrast injection and acquisition protocols

PubMed Central

Scholtz, Jan-Erik

2017-01-01

Cardiac computed tomography (CT) imaging has become an important part of modern cardiovascular care. Coronary CT angiography (CTA) is the first choice imaging modality for non-invasive visualization of coronary artery stenosis. In addition, cardiac CT does not only provide anatomical evaluation, but also functional and valvular assessment, and myocardial perfusion evaluation. In this article we outline the factors which influence contrast enhancement, give an overview of current contrast injection and acquisition protocols, with focus on current emerging topics such as pre-transcatheter aortic valve replacement (TAVR) planning, cardiac CT for congenital heart disease (CHD) patients, and myocardial CT perfusion (CTP). Further, we point out areas where we see potential for future improvements in cardiac CT imaging based on a closer interaction between CT scanner settings and contrast injection protocols to tailor injections to patient- and exam-specific factors. PMID:29255688

A proposal for a CT driven classification of left colon acute diverticulitis.

PubMed

Sartelli, Massimo; Moore, Frederick A; Ansaloni, Luca; Di Saverio, Salomone; Coccolini, Federico; Griffiths, Ewen A; Coimbra, Raul; Agresta, Ferdinando; Sakakushev, Boris; Ordoñez, Carlos A; Abu-Zidan, Fikri M; Karamarkovic, Aleksandar; Augustin, Goran; Costa Navarro, David; Ulrych, Jan; Demetrashvili, Zaza; Melo, Renato B; Marwah, Sanjay; Zachariah, Sanoop K; Wani, Imtiaz; Shelat, Vishal G; Kim, Jae Il; McFarlane, Michael; Pintar, Tadaja; Rems, Miran; Bala, Miklosh; Ben-Ishay, Offir; Gomes, Carlos Augusto; Faro, Mario Paulo; Pereira, Gerson Alves; Catani, Marco; Baiocchi, Gianluca; Bini, Roberto; Anania, Gabriele; Negoi, Ionut; Kecbaja, Zurabs; Omari, Abdelkarim H; Cui, Yunfeng; Kenig, Jakub; Sato, Norio; Vereczkei, Andras; Skrovina, Matej; Das, Koray; Bellanova, Giovanni; Di Carlo, Isidoro; Segovia Lohse, Helmut A; Kong, Victor; Kok, Kenneth Y; Massalou, Damien; Smirnov, Dmitry; Gachabayov, Mahir; Gkiokas, Georgios; Marinis, Athanasios; Spyropoulos, Charalampos; Nikolopoulos, Ioannis; Bouliaris, Konstantinos; Tepp, Jaan; Lohsiriwat, Varut; Çolak, Elif; Isik, Arda; Rios-Cruz, Daniel; Soto, Rodolfo; Abbas, Ashraf; Tranà, Cristian; Caproli, Emanuele; Soldatenkova, Darija; Corcione, Francesco; Piazza, Diego; Catena, Fausto

2015-01-01

Computed tomography (CT) imaging is the most appropriate diagnostic tool to confirm suspected left colonic diverticulitis. However, the utility of CT imaging goes beyond accurate diagnosis of diverticulitis; the grade of severity on CT imaging may drive treatment planning of patients presenting with acute diverticulitis. The appropriate management of left colon acute diverticulitis remains still debated because of the vast spectrum of clinical presentations and different approaches to treatment proposed. The authors present a new simple classification system based on both CT scan results driving decisions making management of acute diverticulitis that may be universally accepted for day to day practice.

Low-dose CT reconstruction with patch based sparsity and similarity constraints

NASA Astrophysics Data System (ADS)

Xu, Qiong; Mou, Xuanqin

2014-03-01

As the rapid growth of CT based medical application, low-dose CT reconstruction becomes more and more important to human health. Compared with other methods, statistical iterative reconstruction (SIR) usually performs better in lowdose case. However, the reconstructed image quality of SIR highly depends on the prior based regularization due to the insufficient of low-dose data. The frequently-used regularization is developed from pixel based prior, such as the smoothness between adjacent pixels. This kind of pixel based constraint cannot distinguish noise and structures effectively. Recently, patch based methods, such as dictionary learning and non-local means filtering, have outperformed the conventional pixel based methods. Patch is a small area of image, which expresses structural information of image. In this paper, we propose to use patch based constraint to improve the image quality of low-dose CT reconstruction. In the SIR framework, both patch based sparsity and similarity are considered in the regularization term. On one hand, patch based sparsity is addressed by sparse representation and dictionary learning methods, on the other hand, patch based similarity is addressed by non-local means filtering method. We conducted a real data experiment to evaluate the proposed method. The experimental results validate this method can lead to better image with less noise and more detail than other methods in low-count and few-views cases.

Hounsfield unit recovery in clinical cone beam CT images of the thorax acquired for image guided radiation therapy

NASA Astrophysics Data System (ADS)

Slot Thing, Rune; Bernchou, Uffe; Mainegra-Hing, Ernesto; Hansen, Olfred; Brink, Carsten

2016-08-01

A comprehensive artefact correction method for clinical cone beam CT (CBCT) images acquired for image guided radiation therapy (IGRT) on a commercial system is presented. The method is demonstrated to reduce artefacts and recover CT-like Hounsfield units (HU) in reconstructed CBCT images of five lung cancer patients. Projection image based artefact corrections of image lag, detector scatter, body scatter and beam hardening are described and applied to CBCT images of five lung cancer patients. Image quality is evaluated through visual appearance of the reconstructed images, HU-correspondence with the planning CT images, and total volume HU error. Artefacts are reduced and CT-like HUs are recovered in the artefact corrected CBCT images. Visual inspection confirms that artefacts are indeed suppressed by the proposed method, and the HU root mean square difference between reconstructed CBCTs and the reference CT images are reduced by 31% when using the artefact corrections compared to the standard clinical CBCT reconstruction. A versatile artefact correction method for clinical CBCT images acquired for IGRT has been developed. HU values are recovered in the corrected CBCT images. The proposed method relies on post processing of clinical projection images, and does not require patient specific optimisation. It is thus a powerful tool for image quality improvement of large numbers of CBCT images.

Limiting CT radiation dose in children with craniosynostosis: phantom study using model-based iterative reconstruction.

PubMed

Kaasalainen, Touko; Palmu, Kirsi; Lampinen, Anniina; Reijonen, Vappu; Leikola, Junnu; Kivisaari, Riku; Kortesniemi, Mika

2015-09-01

Medical professionals need to exercise particular caution when developing CT scanning protocols for children who require multiple CT studies, such as those with craniosynostosis. To evaluate the utility of ultra-low-dose CT protocols with model-based iterative reconstruction techniques for craniosynostosis imaging. We scanned two pediatric anthropomorphic phantoms with a 64-slice CT scanner using different low-dose protocols for craniosynostosis. We measured organ doses in the head region with metal-oxide-semiconductor field-effect transistor (MOSFET) dosimeters. Numerical simulations served to estimate organ and effective doses. We objectively and subjectively evaluated the quality of images produced by adaptive statistical iterative reconstruction (ASiR) 30%, ASiR 50% and Veo (all by GE Healthcare, Waukesha, WI). Image noise and contrast were determined for different tissues. Mean organ dose with the newborn phantom was decreased up to 83% compared to the routine protocol when using ultra-low-dose scanning settings. Similarly, for the 5-year phantom the greatest radiation dose reduction was 88%. The numerical simulations supported the findings with MOSFET measurements. The image quality remained adequate with Veo reconstruction, even at the lowest dose level. Craniosynostosis CT with model-based iterative reconstruction could be performed with a 20-μSv effective dose, corresponding to the radiation exposure of plain skull radiography, without compromising required image quality.

Fully Convolutional Architecture for Low-Dose CT Image Noise Reduction

NASA Astrophysics Data System (ADS)

Badretale, S.; Shaker, F.; Babyn, P.; Alirezaie, J.

2017-10-01

One of the critical topics in medical low-dose Computed Tomography (CT) imaging is how best to maintain image quality. As the quality of images decreases with lowering the X-ray radiation dose, improving image quality is extremely important and challenging. We have proposed a novel approach to denoise low-dose CT images. Our algorithm learns directly from an end-to-end mapping from the low-dose Computed Tomography images for denoising the normal-dose CT images. Our method is based on a deep convolutional neural network with rectified linear units. By learning various low-level to high-level features from a low-dose image the proposed algorithm is capable of creating a high-quality denoised image. We demonstrate the superiority of our technique by comparing the results with two other state-of-the-art methods in terms of the peak signal to noise ratio, root mean square error, and a structural similarity index.

Effect of slice thickness on image noise and diagnostic content of single-source-dual energy computed tomography

NASA Astrophysics Data System (ADS)

Alshipli, Marwan; Kabir, Norlaili A.

2017-05-01

Computed tomography (CT) employs X-ray radiation to create cross-sectional images. Dual-energy CT acquisition includes the images acquired from an alternating voltage of X-ray tube: a low- and a high-peak kilovoltage. The main objective of this study is to determine the best slice thickness that reduces image noise with adequate diagnostic information using dual energy CT head protocol. The study used the ImageJ software and statistical analyses to aid the medical image analysis of dual-energy CT. In this study, ImageJ software and F-test were utilised as the combination methods to analyse DICOM CT images. They were used to investigate the effect of slice thickness on noise and visibility in dual-energy CT head protocol images. Catphan-600 phantom was scanned at different slice thickness values;.6, 1, 2, 3, 4, 5 and 6 mm, then quantitative analyses were carried out. The DECT operated in helical mode with another fixed scan parameter values. Based on F-test statistical analyses, image noise at 0.6, 1, and 2 mm were significantly different compared to the other images acquired at slice thickness of 3, 4, 5, and 6 mm. However, no significant differences of image noise were observed at 3, 4, 5, and 6 mm. As a result, better diagnostic image value, image visibility, and lower image noise in dual-energy CT head protocol was observed at a slice thickness of 3 mm.

SU-G-IeP4-11: Monitoring Tumor Growth in Subcutaneous Murine Tumor Model in Vivo: A Comparison Between MRI and Small Animal CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, B; He, W; Cvetkovic, D

Purpose: The purpose of the study is to compare the volume measurement of subcutaneous tumors in mice with different imaging platforms, namely a GE MRI and a Sofie-Biosciences small animal CT scanner. Methods: A549 human lung carcinoma cells and FaDu human head and neck squamous cell carcinoma cells were implanted subcutaneously into flanks of nude mice. Three FaDu tumors and three A549 tumors were included in this study. The MRI scans were done with a GE Signa 1.5 Tesla MR scanner using a fast T2-weighted sequence (70mm FOV and 1.2mm slice thickness), while the CT scans were done with themore » CT scanner on a Sofie-Biosciences G8 PET/CT platform dedicated for small animal studies (48mm FOV and 0.2mm slice thickness). Imaging contrast agent was not used in this study. Based on the DICOM images from MRI and CT scans, the tumors were contoured with Philips DICOM Viewer and the tumor volumes were obtained by summing up the contoured area and multiplied by the slice thickness. Results: The volume measurements based on the CT scans agree reasonably with that obtained with MR images for the subcutaneous tumors. The mean difference in the absolute tumor volumes between MRI- and CT-based measurements was found to be −6.2% ± 1.0%, with the difference defined as (VMR – VCT)*100%/VMR. Furthermore, we evaluated the normalized tumor volumes, which were defined for each tumor as V/V{sub 0} where V{sub 0} stands for the volume from the first MR or CT scan. The mean difference in the normalized tumor volumes was found to be 0.10% ± 0.96%. Conclusion: Despite the fact that the difference between normal and abnormal tissues is often less clear on small animal CT images than on MR images, one can still obtain reasonable tumor volume information with the small animal CT scans for subcutaneous murine xenograft models.« less

SU-E-T-428: Feasibility Study of 4D Image Reconstruction by Organ Motion Vector Extension Based On Portal Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, J; Jung, J; Yeo, I

2015-06-15

Purpose: To develop and to test a method to generate a new 4D CT images of the treatment day from the old 4D CT and the portal images of the day when the motion extent exceeded from that represented by plan CTs. Methods: A motion vector of a moving tumor in a patient may be extended to reconstruct the tumor position when the motion extent exceeded from that represented by plan CTs. To test this, 1. a phantom that consists of a polystyrene cylinder (tumor) embedded in cork (lung) was placed on a moving platform with 4 sec/cycle and amplitudesmore » of 1 cm and 2 cm, and was 4D-scanned. 2. A 6MV photon beam was irradiated on the moving phantoms and cineEPID images were obtained. 3. A motion vector of the tumor was acquired from 4D CT images of the phantom with 1 cm amplitude. 4. From cine EPID images of the phantom with the 2 cm amplitude, various motion extents (0.3 cm, 0.5 cm, etc) were acquired and programmed into the motion vector, producing CT images at each position. 5. The reconstructed CT images were then compared with pre-acquired “reference” 4D CT images at each position (i.e. phase). Results: The CT image was reconstructed and compared with the reference image, showing a slight mismatch in the transition direction limited by voxel size (slice thickness) in CT image. Due to the rigid nature of the phantom studied, the modeling the displacement of the center of object was sufficient. When deformable tumors are to be modeled, more complex scheme is necessary, which utilize cine EPID and 4D CT images. Conclusion: The new idea of CT image reconstruction was demonstrated. Deformable tumor movements need to be considered in the future.« less

SU-E-J-141: Comparison of Dose Calculation On Automatically Generated MRBased ED Maps and Corresponding Patient CT for Clinical Prostate EBRT Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schadewaldt, N; Schulz, H; Helle, M

2014-06-01

Purpose: To analyze the effect of computing radiation dose on automatically generated MR-based simulated CT images compared to true patient CTs. Methods: Six prostate cancer patients received a regular planning CT for RT planning as well as a conventional 3D fast-field dual-echo scan on a Philips 3.0T Achieva, adding approximately 2 min of scan time to the clinical protocol. Simulated CTs (simCT) where synthesized by assigning known average CT values to the tissue classes air, water, fat, cortical and cancellous bone. For this, Dixon reconstruction of the nearly out-of-phase (echo 1) and in-phase images (echo 2) allowed for water andmore » fat classification. Model based bone segmentation was performed on a combination of the DIXON images. A subsequent automatic threshold divides into cortical and cancellous bone. For validation, the simCT was registered to the true CT and clinical treatment plans were re-computed on the simCT in pinnacle{sup 3}. To differentiate effects related to the 5 tissue classes and changes in the patient anatomy not compensated by rigid registration, we also calculate the dose on a stratified CT, where HU values are sorted in to the same 5 tissue classes as the simCT. Results: Dose and volume parameters on PTV and risk organs as used for the clinical approval were compared. All deviations are below 1.1%, except the anal sphincter mean dose, which is at most 2.2%, but well below clinical acceptance threshold. Average deviations are below 0.4% for PTV and risk organs and 1.3% for the anal sphincter. The deviations of the stratifiedCT are in the same range as for the simCT. All plans would have passed clinical acceptance thresholds on the simulated CT images. Conclusion: This study demonstrated the clinical usability of MR based dose calculation with the presented Dixon acquisition and subsequent fully automatic image processing. N. Schadewaldt, H. Schulz, M. Helle and S. Renisch are employed by Phlips Technologie Innovative Techonologies, a subsidiary of Royal Philips NV.« less

TH-C-18A-06: Combined CT Image Quality and Radiation Dose Monitoring Program Based On Patient Data to Assess Consistency of Clinical Imaging Across Scanner Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christianson, O; Winslow, J; Samei, E

2014-06-15

Purpose: One of the principal challenges of clinical imaging is to achieve an ideal balance between image quality and radiation dose across multiple CT models. The number of scanners and protocols at large medical centers necessitates an automated quality assurance program to facilitate this objective. Therefore, the goal of this work was to implement an automated CT image quality and radiation dose monitoring program based on actual patient data and to use this program to assess consistency of protocols across CT scanner models. Methods: Patient CT scans are routed to a HIPPA compliant quality assurance server. CTDI, extracted using opticalmore » character recognition, and patient size, measured from the localizers, are used to calculate SSDE. A previously validated noise measurement algorithm determines the noise in uniform areas of the image across the scanned anatomy to generate a global noise level (GNL). Using this program, 2358 abdominopelvic scans acquired on three commercial CT scanners were analyzed. Median SSDE and GNL were compared across scanner models and trends in SSDE and GNL with patient size were used to determine the impact of differing automatic exposure control (AEC) algorithms. Results: There was a significant difference in both SSDE and GNL across scanner models (9–33% and 15–35% for SSDE and GNL, respectively). Adjusting all protocols to achieve the same image noise would reduce patient dose by 27–45% depending on scanner model. Additionally, differences in AEC methodologies across vendors resulted in disparate relationships of SSDE and GNL with patient size. Conclusion: The difference in noise across scanner models indicates that protocols are not optimally matched to achieve consistent image quality. Our results indicated substantial possibility for dose reduction while achieving more consistent image appearance. Finally, the difference in AEC methodologies suggests the need for size-specific CT protocols to minimize variability in image quality across CT vendors.« less

A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

PubMed

Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

2014-06-21

As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

Image quality improvement in cone-beam CT using the super-resolution technique.

PubMed

Oyama, Asuka; Kumagai, Shinobu; Arai, Norikazu; Takata, Takeshi; Saikawa, Yusuke; Shiraishi, Kenshiro; Kobayashi, Takenori; Kotoku, Jun'ichi

2018-04-05

This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.

(⁹⁹m)Tc-MAA overestimates the absorbed dose to the lungs in radioembolization: a quantitative evaluation in patients treated with ¹⁶⁶Ho-microspheres.

PubMed

Elschot, Mattijs; Nijsen, Johannes F W; Lam, Marnix G E H; Smits, Maarten L J; Prince, Jip F; Viergever, Max A; van den Bosch, Maurice A A J; Zonnenberg, Bernard A; de Jong, Hugo W A M

2014-10-01

Radiation pneumonitis is a rare but serious complication of radioembolic therapy of liver tumours. Estimation of the mean absorbed dose to the lungs based on pretreatment diagnostic (99m)Tc-macroaggregated albumin ((99m)Tc-MAA) imaging should prevent this, with administered activities adjusted accordingly. The accuracy of (99m)Tc-MAA-based lung absorbed dose estimates was evaluated and compared to absorbed dose estimates based on pretreatment diagnostic (166)Ho-microsphere imaging and to the actual lung absorbed doses after (166)Ho radioembolization. This prospective clinical study included 14 patients with chemorefractory, unresectable liver metastases treated with (166)Ho radioembolization. (99m)Tc-MAA-based and (166)Ho-microsphere-based estimation of lung absorbed doses was performed on pretreatment diagnostic planar scintigraphic and SPECT/CT images. The clinical analysis was preceded by an anthropomorphic torso phantom study with simulated lung shunt fractions of 0 to 30 % to determine the accuracy of the image-based lung absorbed dose estimates after (166)Ho radioembolization. In the phantom study, (166)Ho SPECT/CT-based lung absorbed dose estimates were more accurate (absolute error range 0.1 to -4.4 Gy) than (166)Ho planar scintigraphy-based lung absorbed dose estimates (absolute error range 9.5 to 12.1 Gy). Clinically, the actual median lung absorbed dose was 0.02 Gy (range 0.0 to 0.7 Gy) based on posttreatment (166)Ho-microsphere SPECT/CT imaging. Lung absorbed doses estimated on the basis of pretreatment diagnostic (166)Ho-microsphere SPECT/CT imaging (median 0.02 Gy, range 0.0 to 0.4 Gy) were significantly better predictors of the actual lung absorbed doses than doses estimated on the basis of (166)Ho-microsphere planar scintigraphy (median 10.4 Gy, range 4.0 to 17.3 Gy; p < 0.001), (99m)Tc-MAA SPECT/CT imaging (median 2.5 Gy, range 1.2 to 12.3 Gy; p < 0.001), and (99m)Tc-MAA planar scintigraphy (median 5.5 Gy, range 2.3 to 18.2 Gy; p < 0.001). In clinical practice, lung absorbed doses are significantly overestimated by pretreatment diagnostic (99m)Tc-MAA imaging. Pretreatment diagnostic (166)Ho-microsphere SPECT/CT imaging accurately predicts lung absorbed doses after (166)Ho radioembolization.

Inter-slice bidirectional registration-based segmentation of the prostate gland in MR and CT image sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khalvati, Farzad, E-mail: farzad.khalvati@uwaterloo.ca; Tizhoosh, Hamid R.; Salmanpour, Aryan

Purpose: Accurate segmentation and volume estimation of the prostate gland in magnetic resonance (MR) and computed tomography (CT) images are necessary steps in diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semiautomated segmentation of individual slices in T2-weighted MR and CT image sequences. Methods: The proposedInter-Slice Bidirectional Registration-based Segmentation (iBRS) algorithm relies on interslice image registration of volume data to segment the prostate gland without the use of an anatomical atlas. It requires the user to mark only three slices in a given volume dataset, i.e., themore » first, middle, and last slices. Next, the proposed algorithm uses a registration algorithm to autosegment the remaining slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid techniques). Results: The results with the proposed technique were compared with manual marking using prostate MR and CT images from 117 patients. Manual marking was performed by an expert user for all 117 patients. The median accuracies for individual slices measured using the Dice similarity coefficient (DSC) were 92% and 91% for MR and CT images, respectively. The iBRS algorithm was also evaluated regarding user variability, which confirmed that the algorithm was robust to interuser variability when marking the prostate gland. Conclusions: The proposed algorithm exploits the interslice data redundancy of the images in a volume dataset of MR and CT images and eliminates the need for an atlas, minimizing the computational cost while producing highly accurate results which are robust to interuser variability.« less

Inter-slice bidirectional registration-based segmentation of the prostate gland in MR and CT image sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khalvati, Farzad, E-mail: farzad.khalvati@uwaterloo.ca; Tizhoosh, Hamid R.; Salmanpour, Aryan

2013-12-15

Purpose: Accurate segmentation and volume estimation of the prostate gland in magnetic resonance (MR) and computed tomography (CT) images are necessary steps in diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semiautomated segmentation of individual slices in T2-weighted MR and CT image sequences. Methods: The proposedInter-Slice Bidirectional Registration-based Segmentation (iBRS) algorithm relies on interslice image registration of volume data to segment the prostate gland without the use of an anatomical atlas. It requires the user to mark only three slices in a given volume dataset, i.e., themore » first, middle, and last slices. Next, the proposed algorithm uses a registration algorithm to autosegment the remaining slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid techniques). Results: The results with the proposed technique were compared with manual marking using prostate MR and CT images from 117 patients. Manual marking was performed by an expert user for all 117 patients. The median accuracies for individual slices measured using the Dice similarity coefficient (DSC) were 92% and 91% for MR and CT images, respectively. The iBRS algorithm was also evaluated regarding user variability, which confirmed that the algorithm was robust to interuser variability when marking the prostate gland. Conclusions: The proposed algorithm exploits the interslice data redundancy of the images in a volume dataset of MR and CT images and eliminates the need for an atlas, minimizing the computational cost while producing highly accurate results which are robust to interuser variability.« less

Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

PubMed

Li, Liang; Wang, Bigong; Wang, Ge

2016-01-01

In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.

Towards quantitative PET/MRI: a review of MR-based attenuation correction techniques.

PubMed

Hofmann, Matthias; Pichler, Bernd; Schölkopf, Bernhard; Beyer, Thomas

2009-03-01

Positron emission tomography (PET) is a fully quantitative technology for imaging metabolic pathways and dynamic processes in vivo. Attenuation correction of raw PET data is a prerequisite for quantification and is typically based on separate transmission measurements. In PET/CT attenuation correction, however, is performed routinely based on the available CT transmission data. Recently, combined PET/magnetic resonance (MR) has been proposed as a viable alternative to PET/CT. Current concepts of PET/MRI do not include CT-like transmission sources and, therefore, alternative methods of PET attenuation correction must be found. This article reviews existing approaches to MR-based attenuation correction (MR-AC). Most groups have proposed MR-AC algorithms for brain PET studies and more recently also for torso PET/MR imaging. Most MR-AC strategies require the use of complementary MR and transmission images, or morphology templates generated from transmission images. We review and discuss these algorithms and point out challenges for using MR-AC in clinical routine. MR-AC is work-in-progress with potentially promising results from a template-based approach applicable to both brain and torso imaging. While efforts are ongoing in making clinically viable MR-AC fully automatic, further studies are required to realize the potential benefits of MR-based motion compensation and partial volume correction of the PET data.

Accounting for patient size in the optimization of dose and image quality of pelvis cone beam CT protocols on the Varian OBI system.

PubMed

Wood, Tim J; Moore, Craig S; Horsfield, Carl J; Saunderson, John R; Beavis, Andrew W

2015-01-01

The purpose of this study was to develop size-based radiotherapy kilovoltage cone beam CT (CBCT) protocols for the pelvis. Image noise was measured in an elliptical phantom of varying size for a range of exposure factors. Based on a previously defined "small pelvis" reference patient and CBCT protocol, appropriate exposure factors for small, medium, large and extra-large patients were derived which approximate the image noise behaviour observed on a Philips CT scanner (Philips Medical Systems, Best, Netherlands) with automatic exposure control (AEC). Selection criteria, based on maximum tube current-time product per rotation selected during the radiotherapy treatment planning scan, were derived based on an audit of patient size. It has been demonstrated that 110 kVp yields acceptable image noise for reduced patient dose in pelvic CBCT scans of small, medium and large patients, when compared with manufacturer's default settings (125 kVp). Conversely, extra-large patients require increased exposure factors to give acceptable images. 57% of patients in the local population now receive much lower radiation doses, whereas 13% require higher doses (but now yield acceptable images). The implementation of size-based exposure protocols has significantly reduced radiation dose to the majority of patients with no negative impact on image quality. Increased doses are required on the largest patients to give adequate image quality. The development of size-based CBCT protocols that use the planning CT scan (with AEC) to determine which protocol is appropriate ensures adequate image quality whilst minimizing patient radiation dose.

Local reconstruction in computed tomography of diffraction enhanced imaging

NASA Astrophysics Data System (ADS)

Huang, Zhi-Feng; Zhang, Li; Kang, Ke-Jun; Chen, Zhi-Qiang; Zhu, Pei-Ping; Yuan, Qing-Xi; Huang, Wan-Xia

2007-07-01

Computed tomography of diffraction enhanced imaging (DEI-CT) based on synchrotron radiation source has extremely high sensitivity of weakly absorbing low-Z samples in medical and biological fields. The authors propose a modified backprojection filtration(BPF)-type algorithm based on PI-line segments to reconstruct region of interest from truncated refraction-angle projection data in DEI-CT. The distribution of refractive index decrement in the sample can be directly estimated from its reconstruction images, which has been proved by experiments at the Beijing Synchrotron Radiation Facility. The algorithm paves the way for local reconstruction of large-size samples by the use of DEI-CT with small field of view based on synchrotron radiation source.

A sparsity-based iterative algorithm for reconstruction of micro-CT images from highly undersampled projection datasets obtained with a synchrotron X-ray source

NASA Astrophysics Data System (ADS)

Melli, S. Ali; Wahid, Khan A.; Babyn, Paul; Cooper, David M. L.; Gopi, Varun P.

2016-12-01

Synchrotron X-ray Micro Computed Tomography (Micro-CT) is an imaging technique which is increasingly used for non-invasive in vivo preclinical imaging. However, it often requires a large number of projections from many different angles to reconstruct high-quality images leading to significantly high radiation doses and long scan times. To utilize this imaging technique further for in vivo imaging, we need to design reconstruction algorithms that reduce the radiation dose and scan time without reduction of reconstructed image quality. This research is focused on using a combination of gradient-based Douglas-Rachford splitting and discrete wavelet packet shrinkage image denoising methods to design an algorithm for reconstruction of large-scale reduced-view synchrotron Micro-CT images with acceptable quality metrics. These quality metrics are computed by comparing the reconstructed images with a high-dose reference image reconstructed from 1800 equally spaced projections spanning 180°. Visual and quantitative-based performance assessment of a synthetic head phantom and a femoral cortical bone sample imaged in the biomedical imaging and therapy bending magnet beamline at the Canadian Light Source demonstrates that the proposed algorithm is superior to the existing reconstruction algorithms. Using the proposed reconstruction algorithm to reduce the number of projections in synchrotron Micro-CT is an effective way to reduce the overall radiation dose and scan time which improves in vivo imaging protocols.

Adaptive iterative dose reduction (AIDR) 3D in low dose CT abdomen-pelvis: Effects on image quality and radiation exposure

NASA Astrophysics Data System (ADS)

Ang, W. C.; Hashim, S.; Karim, M. K. A.; Bahruddin, N. A.; Salehhon, N.; Musa, Y.

2017-05-01

The widespread use of computed tomography (CT) has increased the medical radiation exposure and cancer risk. We aimed to evaluate the impact of AIDR 3D in CT abdomen-pelvic examinations based on image quality and radiation dose in low dose (LD) setting compared to standard dose (STD) with filtered back projection (FBP) reconstruction. We retrospectively reviewed the images of 40 patients who underwent CT abdomen-pelvic using a 80 slice CT scanner. Group 1 patients (n=20, mean age 41 ± 17 years) were performed at LD with AIDR 3D reconstruction and Group 2 patients (n=20, mean age 52 ± 21 years) were scanned with STD using FBP reconstruction. Objective image noise was assessed by region of interest (ROI) measurements in the liver and aorta as standard deviation (SD) of the attenuation value (Hounsfield Unit, HU) while subjective image quality was evaluated by two radiologists. Statistical analysis was used to compare the scan length, CT dose index volume (CTDIvol) and image quality of both patient groups. Although both groups have similar mean scan length, the CTDIvol significantly decreased by 38% in LD CT compared to STD CT (p<0.05). Objective and subjective image quality were statistically improved with AIDR 3D (p<0.05). In conclusion, AIDR 3D enables significant dose reduction of 38% with superior image quality in LD CT abdomen-pelvis.

Use and accuracy of diagnostic imaging in the evaluation of pediatric appendicitis.

PubMed

Kotagal, Meera; Richards, Morgan K; Flum, David R; Acierno, Stephanie P; Weinsheimer, Robert L; Goldin, Adam B

2015-04-01

There are safety concerns about the use of radiation-based imaging (computed tomography [CT]) to diagnose appendicitis in children. Factors associated with CT use remain to be determined. For patients ≤18 years old undergoing appendectomy, we evaluated diagnostic imaging performed, patient characteristics, hospital type, and imaging/pathology concordance (2008-2012) using data from Washington State's Surgical Care and Outcomes Assessment Program. Among 2538 children, 99.7% underwent pre-operative imaging. 52.7% had a CT scan as their first study. After adjustment, age >10 years (OR 2.9 (95% CI 2.2-4.0), Hispanic ethnicity (OR 1.7, 95% CI 1.5-1.9), and being obese (OR 1.7, 95% CI 1.4-2.1) were associated with CT use first. Evaluation at a non-children's hospital was associated with higher odds of CT use (OR 7.9, 95% CI 7.5-8.4). Ultrasound concordance with pathology was higher for males (72.3 vs. 66.4%, p=.03), in perforated appendicitis (75.9 vs. 67.5%, p=.009), and at children's hospitals compared to general adult hospitals (77.3 vs. 62.2%, p<.001). CT use has decreased yearly statewide. Over 50% of children with appendicitis had radiation-based imaging. Understanding factors associated with CT use should allow for more specific QI interventions to reduce radiation exposure. Site of care remains a significant factor in radiation exposure for children. Copyright © 2015 Elsevier Inc. All rights reserved.

Group-wise feature-based registration of CT and ultrasound images of spine

NASA Astrophysics Data System (ADS)

Rasoulian, Abtin; Mousavi, Parvin; Hedjazi Moghari, Mehdi; Foroughi, Pezhman; Abolmaesumi, Purang

2010-02-01

Registration of pre-operative CT and freehand intra-operative ultrasound of lumbar spine could aid surgeons in the spinal needle injection which is a common procedure for pain management. Patients are always in a supine position during the CT scan, and in the prone or sitting position during the intervention. This leads to a difference in the spinal curvature between the two imaging modalities, which means a single rigid registration cannot be used for all of the lumbar vertebrae. In this work, a method for group-wise registration of pre-operative CT and intra-operative freehand 2-D ultrasound images of the lumbar spine is presented. The approach utilizes a pointbased registration technique based on the unscented Kalman filter, taking as input segmented vertebrae surfaces in both CT and ultrasound data. Ultrasound images are automatically segmented using a dynamic programming approach, while the CT images are semi-automatically segmented using thresholding. Since the curvature of the spine is different between the pre-operative and the intra-operative data, the registration approach is designed to simultaneously align individual groups of points segmented from each vertebra in the two imaging modalities. A biomechanical model is used to constrain the vertebrae transformation parameters during the registration and to ensure convergence. The mean target registration error achieved for individual vertebrae on five spine phantoms generated from CT data of patients, is 2.47 mm with standard deviation of 1.14 mm.

A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT

NASA Astrophysics Data System (ADS)

Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo

2016-11-01

Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.

Tight-frame based iterative image reconstruction for spectral breast CT

PubMed Central

Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

2013-01-01

Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

Image quality assessment for CT used on small animals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cisneros, Isabela Paredes, E-mail: iparedesc@unal.edu.co; Agulles-Pedrós, Luis, E-mail: lagullesp@unal.edu.co

Image acquisition on a CT scanner is nowadays necessary in almost any kind of medical study. Its purpose, to produce anatomical images with the best achievable quality, implies the highest diagnostic radiation exposure to patients. Image quality can be measured quantitatively based on parameters such as noise, uniformity and resolution. This measure allows the determination of optimal parameters of operation for the scanner in order to get the best diagnostic image. A human Phillips CT scanner is the first one minded for veterinary-use exclusively in Colombia. The aim of this study was to measure the CT image quality parameters usingmore » an acrylic phantom and then, using the computational tool MATLAB, determine these parameters as a function of current value and window of visualization, in order to reduce dose delivery by keeping the appropriate image quality.« less

Image quality assessment for CT used on small animals

NASA Astrophysics Data System (ADS)

Cisneros, Isabela Paredes; Agulles-Pedrós, Luis

2016-07-01

Image acquisition on a CT scanner is nowadays necessary in almost any kind of medical study. Its purpose, to produce anatomical images with the best achievable quality, implies the highest diagnostic radiation exposure to patients. Image quality can be measured quantitatively based on parameters such as noise, uniformity and resolution. This measure allows the determination of optimal parameters of operation for the scanner in order to get the best diagnostic image. A human Phillips CT scanner is the first one minded for veterinary-use exclusively in Colombia. The aim of this study was to measure the CT image quality parameters using an acrylic phantom and then, using the computational tool MatLab, determine these parameters as a function of current value and window of visualization, in order to reduce dose delivery by keeping the appropriate image quality.

Single-energy pediatric chest computed tomography with spectral filtration at 100 kVp: effects on radiation parameters and image quality.

PubMed

Bodelle, Boris; Fischbach, Constanze; Booz, Christian; Yel, Ibrahim; Frellesen, Claudia; Kaup, Moritz; Beeres, Martin; Vogl, Thomas J; Scholtz, Jan-Erik

2017-06-01

Most of the applied radiation dose at CT is in the lower photon energy range, which is of limited diagnostic importance. To investigate image quality and effects on radiation parameters of 100-kVp spectral filtration single-energy chest CT using a tin-filter at third-generation dual-source CT in comparison to standard 100-kVp chest CT. Thirty-three children referred for a non-contrast chest CT performed on a third-generation dual-source CT scanner were examined at 100 kVp with a dedicated tin filter with a tube current-time product resulting in standard protocol dose. We compared resulting images with images from children examined using standard single-source chest CT at 100 kVp. We assessed objective and subjective image quality and compared radiation dose parameters. Radiation dose was comparable for children 5 years old and younger, and it was moderately decreased for older children when using spectral filtration (P=0.006). Effective tube current increased significantly (P=0.0001) with spectral filtration, up to a factor of 10. Signal-to-noise ratio and image noise were similar for both examination techniques (P≥0.06). Subjective image quality showed no significant differences (P≥0.2). Using 100-kVp spectral filtration chest CT in children by means of a tube-based tin-filter on a third-generation dual-source CT scanner increases effective tube current up to a factor of 10 to provide similar image quality at equivalent dose compared to standard single-source CT without spectral filtration.

Feasibility of a low-dose orbital CT protocol with a knowledge-based iterative model reconstruction algorithm for evaluating Graves' orbitopathy.

PubMed

Lee, Ho-Joon; Kim, Jinna; Kim, Ki Wook; Lee, Seung-Koo; Yoon, Jin Sook

2018-06-23

To evaluate the clinical feasibility of low-dose orbital CT with a knowledge-based iterative model reconstruction (IMR) algorithm for evaluating Graves' orbitopathy. Low-dose orbital CT was performed with a CTDI vol of 4.4 mGy. In 12 patients for whom prior or subsequent non-low-dose orbital CT data obtained within 12 months were available, background noise, SNR, and CNR were compared for images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose 4 ), and IMR and non-low-dose CT images. Comparison of clinically relevant measurements for Graves' orbitopathy, such as rectus muscle thickness and retrobulbar fat area, was performed in a subset of 6 patients who underwent CT for causes other than Graves' orbitopathy, by using the Wilcoxon signed-rank test. The lens dose estimated from skin dosimetry on a phantom was 4.13 mGy, which was on average 59.34% lower than that of the non-low-dose protocols. Image quality in terms of background noise, SNR, and CNR was the best for IMR, followed by non-low-dose CT, iDose 4 , and FBP, in descending order. A comparison of clinically relevant measurements revealed no significant difference in the retrobulbar fat area and the inferior and medial rectus muscle thicknesses between the low-dose and non-low-dose CT images. Low-dose CT with IMR may be performed without significantly affecting the measurement of prognostic parameters for Graves' orbitopathy while lowering the lens dose and image noise. Copyright © 2018 Elsevier Inc. All rights reserved.

Model-based Iterative Reconstruction: Effect on Patient Radiation Dose and Image Quality in Pediatric Body CT

PubMed Central

Dillman, Jonathan R.; Goodsitt, Mitchell M.; Christodoulou, Emmanuel G.; Keshavarzi, Nahid; Strouse, Peter J.

2014-01-01

Purpose To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection. Materials and Methods Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDIvol) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis. Results In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDIvol was 46% (range, 19%–65%) and mean decrease in SSDE was 44% (range, 19%–64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% ASIR. Conclusion CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality. © RSNA, 2013 Online supplemental material is available for this article. PMID:24091359

Nanoparticle Contrast Agents for Computed Tomography: A Focus on Micelles

PubMed Central

Cormode, David P.; Naha, Pratap C.; Fayad, Zahi A.

2014-01-01

Computed tomography (CT) is an X-ray based whole body imaging technique that is widely used in medicine. Clinically approved contrast agents for CT are iodinated small molecules or barium suspensions. Over the past seven years there has been a great increase in the development of nanoparticles as CT contrast agents. Nanoparticles have several advantages over small molecule CT contrast agents, such as long blood-pool residence times, and the potential for cell tracking and targeted imaging applications. Furthermore, there is a need for novel CT contrast agents, due to the growing population of renally impaired patients and patients hypersensitive to iodinated contrast. Micelles and lipoproteins, a micelle-related class of nanoparticle, have notably been adapted as CT contrast agents. In this review we discuss the principles of CT image formation and the generation of CT contrast. We discuss the progress in developing non-targeted, targeted and cell tracking nanoparticle CT contrast agents. We feature agents based on micelles and used in conjunction with spectral CT. The large contrast agent doses needed will necessitate careful toxicology studies prior to clinical translation. However, the field has seen tremendous advances in the past decade and we expect many more advances to come in the next decade. PMID:24470293

Improved patient size estimates for accurate dose calculations in abdomen computed tomography

NASA Astrophysics Data System (ADS)

Lee, Chang-Lae

2017-07-01

The radiation dose of CT (computed tomography) is generally represented by the CTDI (CT dose index). CTDI, however, does not accurately predict the actual patient doses for different human body sizes because it relies on a cylinder-shaped head (diameter : 16 cm) and body (diameter : 32 cm) phantom. The purpose of this study was to eliminate the drawbacks of the conventional CTDI and to provide more accurate radiation dose information. Projection radiographs were obtained from water cylinder phantoms of various sizes, and the sizes of the water cylinder phantoms were calculated and verified using attenuation profiles. The effective diameter was also calculated using the attenuation of the abdominal projection radiographs of 10 patients. When the results of the attenuation-based method and the geometry-based method shown were compared with the results of the reconstructed-axial-CT-image-based method, the effective diameter of the attenuation-based method was found to be similar to the effective diameter of the reconstructed-axial-CT-image-based method, with a difference of less than 3.8%, but the geometry-based method showed a difference of less than 11.4%. This paper proposes a new method of accurately computing the radiation dose of CT based on the patient sizes. This method computes and provides the exact patient dose before the CT scan, and can therefore be effectively used for imaging and dose control.

State of the art: dual-energy CT of the abdomen.

PubMed

Marin, Daniele; Boll, Daniel T; Mileto, Achille; Nelson, Rendon C

2014-05-01

Recent technologic advances in computed tomography (CT)--enabling the nearly simultaneous acquisition of clinical images using two different x-ray energy spectra--have sparked renewed interest in dual-energy CT. By interrogating the unique characteristics of different materials at different x-ray energies, dual-energy CT can be used to provide quantitative information about tissue composition, overcoming the limitations of attenuation-based conventional single-energy CT imaging. In the past few years, intensive research efforts have been devoted to exploiting the unique and powerful opportunities of dual-energy CT for a variety of clinical applications. This has led to CT protocol modifications for radiation dose reduction, improved diagnostic performance for detection and characterization of diseases, as well as image quality optimization. In this review, the authors discuss the basic principles, instrumentation and design, examples of current clinical applications in the abdomen and pelvis, and future opportunities of dual-energy CT.

TU-AB-202-07: A Novel Method for Registration of Mid-Treatment PET/CT Images Under Conditions of Tumor Regression for Patients with Locally Advanced Lung Cancers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharifi, Hoda; Department of Physics, Oakland University, Rochester, MI; Zhang, Hong

Purpose: In PET-guided adaptive radiotherapy (RT), changes in the metabolic activity at individual voxels cannot be derived until the duringtreatment CT images are appropriately registered to pre-treatment CT images. However, deformable image registration (DIR) usually does not preserve tumor volume. This may induce errors when comparing to the target. The aim of this study was to develop a DIR-integrated mechanical modeling technique to track radiation-induced metabolic changes on PET images. Methods: Three patients with non-small cell lung cancer (NSCLC) were treated with adaptive radiotherapy under RTOG 1106. Two PET/CT image sets were acquired 2 weeks before RT and 18 fractionsmore » after the start of treatment. DIR was performed to register the during-RT CT to the pre-RT CT using a B-spline algorithm and the resultant displacements in the region of tumor were remodeled using a hybrid finite element method (FEM). Gross tumor volume (GTV) was delineated on the during-RT PET/CT image sets and deformed using the 3D deformation vector fields generated by the CT-based registrations. Metabolic tumor volume (MTV) was calculated using the pre- and during–RT image set. The quality of the PET mapping was evaluated based on the constancy of the mapped MTV and landmark comparison. Results: The B-spline-based registrations changed MTVs by 7.3%, 4.6% and −5.9% for the 3 patients and the correspondent changes for the hybrid FEM method −2.9%, 1% and 6.3%, respectively. Landmark comparisons were used to evaluate the Rigid, B-Spline, and hybrid FEM registrations with the mean errors of 10.1 ± 1.6 mm, 4.4 ± 0.4 mm, and 3.6 ± 0.4 mm for three patients. The hybrid FEM method outperforms the B-Spline-only registration for patients with tumor regression Conclusion: The hybrid FEM modeling technique improves the B-Spline registrations in tumor regions. This technique may help compare metabolic activities between two PET/CT images with regressing tumors. The author gratefully acknowledges the financial support from the National Institutes of Health Grant.« less

TU-AB-202-05: GPU-Based 4D Deformable Image Registration Using Adaptive Tetrahedral Mesh Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, Z; Zhuang, L; Gu, X

Purpose: Deformable image registration (DIR) has been employed today as an automated and effective segmentation method to transfer tumor or organ contours from the planning image to daily images, instead of manual segmentation. However, the computational time and accuracy of current DIR approaches are still insufficient for online adaptive radiation therapy (ART), which requires real-time and high-quality image segmentation, especially in a large datasets of 4D-CT images. The objective of this work is to propose a new DIR algorithm, with fast computational speed and high accuracy, by using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step ismore » to generate the adaptive tetrahedral mesh based on the image features of a reference phase of 4D-CT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. Subsequently, the deformation vector fields (DVF) and other phases of 4D-CT can be obtained by matching each phase of the target 4D-CT images with the corresponding deformed reference phase. The proposed 4D DIR method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its parallel computing ability. Results: A 4D NCAT digital phantom was used to test the efficiency and accuracy of our method. Both the image and DVF results show that the fine structures and shapes of lung are well preserved, and the tumor position is well captured, i.e., 3D distance error is 1.14 mm. Compared to the previous voxel-based CPU implementation of DIR, such as demons, the proposed method is about 160x faster for registering a 10-phase 4D-CT with a phase dimension of 256×256×150. Conclusion: The proposed 4D DIR method uses feature-based mesh and GPU-based parallelism, which demonstrates the capability to compute both high-quality image and motion results, with significant improvement on the computational speed.« less

Antibiofouling polymer-coated gold nanoparticles as a contrast agent for in vivo X-ray computed tomography imaging.

PubMed

Kim, Dongkyu; Park, Sangjin; Lee, Jae Hyuk; Jeong, Yong Yeon; Jon, Sangyong

2007-06-20

Current computed tomography (CT) contrast agents such as iodine-based compounds have several limitations, including short imaging times due to rapid renal clearance, renal toxicity, and vascular permeation. Here, we describe a new CT contrast agent based on gold nanoparticles (GNPs) that overcomes these limitations. Because gold has a higher atomic number and X-ray absorption coefficient than iodine, we expected that GNPs can be used as CT contrast agents. We prepared uniform GNPs ( approximately 30 nm in diameter) by general reduction of HAuCl4 by boiling with sodium citrate. The resulting GNPs were coated with polyethylene glycol (PEG) to impart antibiofouling properties, which extends their lifetime in the bloodstream. Measurement of the X-ray absorption coefficient in vitro revealed that the attenuation of PEG-coated GNPs is 5.7 times higher than that of the current iodine-based CT contrast agent, Ultravist. Furthermore, when injected intravenously into rats, the PEG-coated GNPs had a much longer blood circulation time (>4 h) than Ultravist (<10 min). Consequently, CT images of rats using PEG-coated GNPs showed a clear delineation of cardiac ventricles and great vessels. On the other hand, relatively high levels of GNPs accumulated in the spleen and liver, which contain phagocytic cells. Intravenous injection of PEG-coated GNPs into hepatoma-bearing rats resulted in a high contrast ( approximately 2-fold) between hepatoma and normal liver tissue on CT images. These results suggest that PEG-coated GNPs can be useful as a CT contrast agent for a blood pool and hepatoma imaging.

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less

The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT image acquisition conditions

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Wahi-Anwar, Muhammad; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael

2018-02-01

Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as 1)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.

Convolutional auto-encoder for image denoising of ultra-low-dose CT.

PubMed

Nishio, Mizuho; Nagashima, Chihiro; Hirabayashi, Saori; Ohnishi, Akinori; Sasaki, Kaori; Sagawa, Tomoyuki; Hamada, Masayuki; Yamashita, Tatsuo

2017-08-01

The purpose of this study was to validate a patch-based image denoising method for ultra-low-dose CT images. Neural network with convolutional auto-encoder and pairs of standard-dose CT and ultra-low-dose CT image patches were used for image denoising. The performance of the proposed method was measured by using a chest phantom. Standard-dose and ultra-low-dose CT images of the chest phantom were acquired. The tube currents for standard-dose and ultra-low-dose CT were 300 and 10 mA, respectively. Ultra-low-dose CT images were denoised with our proposed method using neural network, large-scale nonlocal mean, and block-matching and 3D filtering. Five radiologists and three technologists assessed the denoised ultra-low-dose CT images visually and recorded their subjective impressions of streak artifacts, noise other than streak artifacts, visualization of pulmonary vessels, and overall image quality. For the streak artifacts, noise other than streak artifacts, and visualization of pulmonary vessels, the results of our proposed method were statistically better than those of block-matching and 3D filtering (p-values < 0.05). On the other hand, the difference in the overall image quality between our proposed method and block-matching and 3D filtering was not statistically significant (p-value = 0.07272). The p-values obtained between our proposed method and large-scale nonlocal mean were all less than 0.05. Neural network with convolutional auto-encoder could be trained using pairs of standard-dose and ultra-low-dose CT image patches. According to the visual assessment by radiologists and technologists, the performance of our proposed method was superior to that of large-scale nonlocal mean and block-matching and 3D filtering.

SU-C-206-03: Metal Artifact Reduction in X-Ray Computed Tomography Based On Local Anatomical Similarity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, X; Yang, X; Rosenfield, J

Purpose: Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set-up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices. Methods: Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact-free slices. A gamma map,more » which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact-corrupted CT image. The minimum value in each pixel’s gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact-corrupted pixel. This replacement only occurs if the minimum value in a particular pixel’s gamma map is larger than a threshold. The proposed method was evaluated with clinical images. Results: Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non-uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively. Conclusions: The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.« less

Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose.

PubMed

Aurumskjöld, Marie-Louise; Söderberg, Marcus; Stålhammar, Fredrik; von Steyern, Kristina Vult; Tingberg, Anders; Ydström, Kristina

2018-06-01

Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose 4 ), and images from the low-dose examinations were reconstructed with both iDose 4 and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose 4 and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose 4 images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60-0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose 4 method for evaluating pediatric abdominal CT, even with a 32% dose reduction.

Multienergy CT acquisition and reconstruction with a stepped tube potential scan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Le; Xing, Yuxiang, E-mail: xingyx@mail.tsinghua.edu.cn

Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT canmore » be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed SegMECT can provide both attenuation images and material decomposition images of reasonable image quality. Compared to existing methods, the new system configuration demonstrates advantages in simplicity of implementation, system cost, and dose control. Conclusions: This proposed SegMECT imaging approach has great potential for practical applications. It can be readily realized on a conventional CT system.« less

Rendering-based video-CT registration with physical constraints for image-guided endoscopic sinus surgery

NASA Astrophysics Data System (ADS)

Otake, Y.; Leonard, S.; Reiter, A.; Rajan, P.; Siewerdsen, J. H.; Ishii, M.; Taylor, R. H.; Hager, G. D.

2015-03-01

We present a system for registering the coordinate frame of an endoscope to pre- or intra- operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours

NASA Astrophysics Data System (ADS)

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-01

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.

PubMed

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-07

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET

NASA Astrophysics Data System (ADS)

Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan

2016-02-01

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

Additional value of hybrid SPECT/CT systems in neuroendocrine tumors, adrenal tumors, pheochromocytomas and paragangliomas.

PubMed

Wong, K K; Chondrogiannis, S; Fuster, D; Ruiz, C; Marzola, M C; Giammarile, F; Colletti, P M; Rubello, D

The aim of this review was to evaluate the potential advantages of SPECT/CT hybrid imaging in the management of neuroendocrine tumors, adrenal tumors, pheochromocytomas and paragangliomas. From the collected data, the superiority of fused images was observed as providing both functional/molecular and morphological imaging compared to planar imaging. This provided an improvement in diagnostic imaging, with significant advantages as regards: (1) precise locating of the lesions; (2) an improvement in characterization of the findings, resulting higher specificity, improved sensitivity, and overall greater accuracy, (3) additional anatomical information derived from the CT component; (4) CT-based attenuation correction and potential for volumetric dosimetry calculations, and (5) improvement on the impact on patient management (e.g. in better defining treatment plans, in shortening surgical operating times). It can be concluded that SPECT/CT hybrid imaging provides the nuclear medicine physician with a powerful imaging modality in comparison to planar imaging, providing essential information about the location of lesions, and high quality homogeneous images. Copyright © 2016 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Technical Note: FreeCT_ICD: An Open Source Implementation of a Model-Based Iterative Reconstruction Method using Coordinate Descent Optimization for CT Imaging Investigations.

PubMed

Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael

2018-06-01

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Extracting alveolar structure of human lung tissue specimens based on surface skeleton representation from 3D micro-CT images

NASA Astrophysics Data System (ADS)

Ishimori, Hiroyuki; Kawata, Yoshiki; Niki, Noboru; Nakaya, Yoshihiro; Ohmatsu, Hironobu; Matsui, Eisuke; Fujii, Masashi; Moriyama, Noriyuki

2007-03-01

We have developed a Micro CT system for understanding lung function at a high resolution of the micrometer order (up to 5µm in spatial resolution). Micro CT system enables the removal specimen of lungs to be observed at micro level, has expected a big contribution for micro internal organs morphology and the image diagnosis study. In this research, we develop system to visualize lung microstructures in three dimensions from micro CT images and analyze them. They characterize in that high CT value of the noise area is, and the difficulty of only using threshold processing to extract the alveolar wall of micro CT images. Thus, we are developing a method of extracting the alveolar wall with surface thinning algorithm. In this report, we propose the method which reduces the excessive degeneracy of figure which caused by surface thinning process. And, we apply this algorithm to the micro CT image of the actual pulmonary specimen. It is shown that the extraction of the alveolus wall becomes possible in the high precision.

4D-Listmode-PET-CT and 4D-CT for optimizing PTV margins in gastric lymphoma : Determination of intra- and interfractional gastric motion.

PubMed

Reinartz, Gabriele; Haverkamp, Uwe; Wullenkord, Ramona; Lehrich, Philipp; Kriz, Jan; Büther, Florian; Schäfers, Klaus; Schäfers, Michael; Eich, Hans Theodor

2016-05-01

New imaging protocols for radiotherapy in localized gastric lymphoma were evaluated to optimize planning target volume (PTV) margin and determine intra-/interfractional variation of the stomach. Imaging of 6 patients was explored prospectively. Intensity-modulated radiotherapy (IMRT) planning was based on 4D/3D imaging of computed tomography (CT) and positron-emission tomography (PET)-CT. Static and motion gross tumor volume (sGTV and mGTV, respectively) were distinguished by defining GTV (empty stomach), clinical target volume (CTV = GTV + 5 mm margin), PTV (GTV + 10/15/20/25 mm margins)  plus paraaortic lymph nodes and proximal duodenum. Overlap of 4D-Listmode-PET-based mCTV with 3D-CT-based PTV (increasing margins) and V95/D95 of mCTV were evaluated. Gastric shifts were determined using online cone-beam CT. Dose contribution to organs at risk was assessed. The 4D data demonstrate considerable intra-/interfractional variation of the stomach, especially along the vertical axis. Conventional 3D-CT planning utilizing advancing PTV margins of 10/15/20/25 mm resulted in rising dose coverage of mCTV (4D-Listmode-PET-Summation-CT) and rising D95 and V95 of mCTV. A PTV margin of 15 mm was adequate in 3 of 6 patients, a PTV margin of 20 mm was adequate in 4 of 6 patients, and a PTV margin of 25 mm was adequate in 5 of 6 patients. IMRT planning based on 4D-PET-CT/4D-CT together with online cone-beam CT is advisable to individualize the PTV margin and optimize target coverage in gastric lymphoma.

MR Image Based Approach for Metal Artifact Reduction in X-Ray CT

PubMed Central

2013-01-01

For decades, computed tomography (CT) images have been widely used to discover valuable anatomical information. Metallic implants such as dental fillings cause severe streaking artifacts which significantly degrade the quality of CT images. In this paper, we propose a new method for metal-artifact reduction using complementary magnetic resonance (MR) images. The method exploits the possibilities which arise from the use of emergent trimodality systems. The proposed algorithm corrects reconstructed CT images. The projected data which is affected by dental fillings is detected and the missing projections are replaced with data obtained from a corresponding MR image. A simulation study was conducted in order to compare the reconstructed images with images reconstructed through linear interpolation, which is a common metal-artifact reduction technique. The results show that the proposed method is successful in reducing severe metal artifacts without introducing significant amount of secondary artifacts. PMID:24302860

SU-E-J-44: Design a Platform and Phantom Model for Photoacoustic Imaging in Combination with CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sick, J; Alsanea, F; Rancilio, N

2014-06-01

Purpose: Our (long-term) objective is to develop a US manipulator that will provide in situ radiation response and image-guided therapy for bladder cancer based on photoacoustic molecular imaging. Methods: A platform was devised to provide a reproducible positional frame of reference for targeting anatomic structure between MDCT and US scans, in lieu of CBCT, and to fuse photoacoustic molecular imaging. US and photoacoustic scans are taken of a patient while in the CT scanner and IRMT. Through co-registration, based on anatomical positions, we identified a common coordinate system to be used in Eclipse. A bladder phantom was constructed to validatemore » anatomical tracking via US and photoacoustic imaging. We tested the platform using phantom model to demonstrate validity once moved from the CT couch to the linear accelerator couch. Results: This platform interlocks with Varian exact couch index points for reproducibility of positioning. Construction from low Z material and sized appropriately to fit in CT/IMRT gantry. Error in conversion from cylindrical coordinates of the manipulator to X, Y, Z coordinates of the treatment couch was less than 1mm. We measured the bladder size in 3 different directions in both Eclipse from the CT and Acuson from US. The error was less than 2mm in all directions. CT and US images were co-registered in MATLAB. Co-registration of photoacoustic images is still being developed. Conclusion: For Linear Accelerators without on board imaging, MV portal images are not a viable option for the localization of soft tissue anatomy. We believe our manipulator provides an alternative using US imaging, which will be examined in an upcoming clinical trial. We plan to examine the value of hypoxia guided treatment through photoacoustic imaging during this trial.« less

Comparison of volumetric breast density estimations from mammography and thorax CT

NASA Astrophysics Data System (ADS)

Geeraert, N.; Klausz, R.; Cockmartin, L.; Muller, S.; Bosmans, H.; Bloch, I.

2014-08-01

Breast density has become an important issue in current breast cancer screening, both as a recognized risk factor for breast cancer and by decreasing screening efficiency by the masking effect. Different qualitative and quantitative methods have been proposed to evaluate area-based breast density and volumetric breast density (VBD). We propose a validation method comparing the computation of VBD obtained from digital mammographic images (VBDMX) with the computation of VBD from thorax CT images (VBDCT). We computed VBDMX by applying a conversion function to the pixel values in the mammographic images, based on models determined from images of breast equivalent material. VBDCT is computed from the average Hounsfield Unit (HU) over the manually delineated breast volume in the CT images. This average HU is then compared to the HU of adipose and fibroglandular tissues from patient images. The VBDMX method was applied to 663 mammographic patient images taken on two Siemens Inspiration (hospL) and one GE Senographe Essential (hospJ). For the comparison study, we collected images from patients who had a thorax CT and a mammography screening exam within the same year. In total, thorax CT images corresponding to 40 breasts (hospL) and 47 breasts (hospJ) were retrieved. Averaged over the 663 mammographic images the median VBDMX was 14.7% . The density distribution and the inverse correlation between VBDMX and breast thickness were found as expected. The average difference between VBDMX and VBDCT is smaller for hospJ (4%) than for hospL (10%). This study shows the possibility to compare VBDMX with the VBD from thorax CT exams, without additional examinations. In spite of the limitations caused by poorly defined breast limits, the calibration of mammographic images to local VBD provides opportunities for further quantitative evaluations.

Automated tru-cut imaging-guided core needle biopsy of canine orbital neoplasia. A prospective feasibility study

PubMed Central

Cirla, A.; Rondena, M.; Bertolini, G.

2016-01-01

The purpose of this study was to evaluate the diagnostic value of imaging-guided core needle biopsy for canine orbital mass diagnosis. A second excisional biopsy obtained during surgery or necropsy was used as the reference standard. A prospective feasibility study was conducted in 23 canine orbital masses at a single centre. A complete ophthalmic examination was always followed by orbital ultrasound and computed tomography (CT) examination of the head. All masses were sampled with the patient still on the CT table using ultrasound (US) guided automatic tru-cut device. The most suitable sampling approach to the orbit was chosen each time based on the CT image analysis. One of the following different approaches was used: trans-orbital, trans-conjunctival or trans-masseteric. In all cases, the imaging-guided biopsy provided a sufficient amount of tissue for the histopathological diagnosis, which concurred with the biopsies obtained using the excisional technique. CT examination was essential for morphological diagnosis and provided detailed topographic information that allowed us to choose the safest orbital approach for the biopsy. US guided automatic tru-cut biopsy based on CT images, performed with patient still on the CT table, resulted in a minimally invasive, relatively easy, and accurate diagnostic procedure in dogs with orbital masses. PMID:27540512

CT/FMT dual-model imaging of breast cancer based on peptide-lipid nanoparticles

NASA Astrophysics Data System (ADS)

Xu, Guoqiang; Lin, Qiaoya; Lian, Lichao; Qian, Yuan; Lu, Lisen; Zhang, Zhihong

2016-03-01

Breast cancer is one of the most harmful cancers in human. Its early diagnosis is expected to improve the patients' survival rate. X-ray computed tomography (CT) has been widely used in tumor detection for obtaining three-dimentional information. Fluorescence Molecular Tomography (FMT) imaging combined with near-infrared fluorescent dyes provides a powerful tool for the acquisition of molecular biodistribution information in deep tissues. Thus, the combination of CT and FMT imaging modalities allows us to better differentiate diseased tissues from normal tissues. Here we developed a tumor-targeting nanoparticle for dual-modality imaging based on a biocompatible HDL-mimicking peptide-phospholipid scaffold (HPPS) nanocarrier. By incorporation of CT contrast agents (iodinated oil) and far-infrared fluorescent dyes (DiR-BOA) into the hydrophobic core of HPPS, we obtained the FMT and CT signals simultaneously. Increased accumulation of the nanoparticles in the tumor lesions was achieved through the effect of the tumor-targeting peptide on the surface of nanoparticle. It resulted in excellent contrast between lesions and normal tissues. Together, the abilities to sensitively separate the lesions from adjacent normal tissues with the aid of a FMT/CT dual-model imaging approach make the targeting nanoparticles a useful tool for the diagnostics of breast cancer.

Automated tru-cut imaging-guided core needle biopsy of canine orbital neoplasia. A prospective feasibility study.

PubMed

Cirla, A; Rondena, M; Bertolini, G

2016-01-01

The purpose of this study was to evaluate the diagnostic value of imaging-guided core needle biopsy for canine orbital mass diagnosis. A second excisional biopsy obtained during surgery or necropsy was used as the reference standard. A prospective feasibility study was conducted in 23 canine orbital masses at a single centre. A complete ophthalmic examination was always followed by orbital ultrasound and computed tomography (CT) examination of the head. All masses were sampled with the patient still on the CT table using ultrasound (US) guided automatic tru-cut device. The most suitable sampling approach to the orbit was chosen each time based on the CT image analysis. One of the following different approaches was used: trans-orbital, trans-conjunctival or trans-masseteric. In all cases, the imaging-guided biopsy provided a sufficient amount of tissue for the histopathological diagnosis, which concurred with the biopsies obtained using the excisional technique. CT examination was essential for morphological diagnosis and provided detailed topographic information that allowed us to choose the safest orbital approach for the biopsy. US guided automatic tru-cut biopsy based on CT images, performed with patient still on the CT table, resulted in a minimally invasive, relatively easy, and accurate diagnostic procedure in dogs with orbital masses.

RADIANCE: An automated, enterprise-wide solution for archiving and reporting CT radiation dose estimates.

PubMed

Cook, Tessa S; Zimmerman, Stefan L; Steingall, Scott R; Maidment, Andrew D A; Kim, Woojin; Boonn, William W

2011-01-01

There is growing interest in the ability to monitor, track, and report exposure to radiation from medical imaging. Historically, however, dose information has been stored on an image-based dose sheet, an arrangement that precludes widespread indexing. Although scanner manufacturers are beginning to include dose-related parameters in the Digital Imaging and Communications in Medicine (DICOM) headers of imaging studies, there remains a vast repository of retrospective computed tomographic (CT) data with image-based dose sheets. Consequently, it is difficult for imaging centers to monitor their dose estimates or participate in the American College of Radiology (ACR) Dose Index Registry. An automated extraction software pipeline known as Radiation Dose Intelligent Analytics for CT Examinations (RADIANCE) has been designed that quickly and accurately parses CT dose sheets to extract and archive dose-related parameters. Optical character recognition of information in the dose sheet leads to creation of a text file, which along with the DICOM study header is parsed to extract dose-related data. The data are then stored in a relational database that can be queried for dose monitoring and report creation. RADIANCE allows efficient dose analysis of CT examinations and more effective education of technologists, radiologists, and referring physicians regarding patient exposure to radiation at CT. RADIANCE also allows compliance with the ACR's dose reporting guidelines and greater awareness of patient radiation dose, ultimately resulting in improved patient care and treatment.

SU-C-17A-01: MRI-Based Radiotherapy Treatment Planning In Pelvis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hsu, S; Cao, Y; Jolly, S

2014-06-15

Purpose: To support radiotherapy dose calculation, synthetic CT (MRCT) image volumes need to represent the electron density of tissues with sufficient accuracy. This study compares CT and MRCT for pelvic radiotherapy. Methods: CT and multi-contrast MRI acquired using T1- based Dixon, T2 TSE, and PETRA sequences were acquired on an IRBapproved protocol patient. A previously published method was used to create a MRCT image volume by applying fuzzy classification on T1- weighted and calculated water image volumes (air and fluid voxels were excluded using thresholds applied to PETRA and T2-weighted images). The correlation of pelvic bone intensity between CT andmore » MRCT was investigated. Two treatment plans, based on CT and MRCT, were performed to mimic treatment for: (a) pelvic bone metastasis with a 16MV parallel beam arrangement, and (b) gynecological cancer with 6MV volumetric modulated arc therapy (VMAT) using two full arcs. The CT-calculated fluence maps were used to recalculate doses using the MRCT-derived density grid. The dose-volume histograms and dose distributions were compared. Results: Bone intensities in the MRCT volume correlated linearly with CT intensities up to 800 HU (containing 96% of the bone volume), and then decreased with CT intensity increase (4% volume). There was no significant difference in dose distributions between CT- and MRCTbased plans, except for the rectum and bladder, for which the V45 differed by 15% and 9%, respectively. These differences may be attributed to normal and visualized organ movement and volume variations between CT and MR scans. Conclusion: While MRCT had lower bone intensity in highly-dense bone, this did not cause significant dose deviations from CT due to its small percentage of volume. These results indicate that treatment planning using MRCT could generate comparable dose distributions to that using CT, and further demonstrate the feasibility of using MRI-alone to support Radiation Oncology workflow. NIH R01EB016079.« less

Computer-based quantitative computed tomography image analysis in idiopathic pulmonary fibrosis: A mini review.

PubMed

Ohkubo, Hirotsugu; Nakagawa, Hiroaki; Niimi, Akio

2018-01-01

Idiopathic pulmonary fibrosis (IPF) is the most common type of progressive idiopathic interstitial pneumonia in adults. Many computer-based image analysis methods of chest computed tomography (CT) used in patients with IPF include the mean CT value of the whole lungs, density histogram analysis, density mask technique, and texture classification methods. Most of these methods offer good assessment of pulmonary functions, disease progression, and mortality. Each method has merits that can be used in clinical practice. One of the texture classification methods is reported to be superior to visual CT scoring by radiologist for correlation with pulmonary function and prediction of mortality. In this mini review, we summarize the current literature on computer-based CT image analysis of IPF and discuss its limitations and several future directions. Copyright © 2017 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

A quantitative comparison of noise reduction across five commercial (hybrid and model-based) iterative reconstruction techniques: an anthropomorphic phantom study.

PubMed

Patino, Manuel; Fuentes, Jorge M; Hayano, Koichi; Kambadakone, Avinash R; Uyeda, Jennifer W; Sahani, Dushyant V

2015-02-01

OBJECTIVE. The objective of our study was to compare the performance of three hybrid iterative reconstruction techniques (IRTs) (ASiR, iDose4, SAFIRE) and their respective strengths for image noise reduction on low-dose CT examinations using filtered back projection (FBP) as the standard reference. Also, we compared the performance of these three hybrid IRTs with two model-based IRTs (Veo and IMR) for image noise reduction on low-dose examinations. MATERIALS AND METHODS. An anthropomorphic abdomen phantom was scanned at 100 and 120 kVp and different tube current-exposure time products (25-100 mAs) on three CT systems (for ASiR and Veo, Discovery CT750 HD; for iDose4 and IMR, Brilliance iCT; and for SAFIRE, Somatom Definition Flash). Images were reconstructed using FBP and using IRTs at various strengths. Nine noise measurements (mean ROI size, 423 mm(2)) on extracolonic fat for the different strengths of IRTs were recorded and compared with FBP using ANOVA. Radiation dose, which was measured as the volume CT dose index and dose-length product, was also compared. RESULTS. There were no significant differences in radiation dose and image noise among the scanners when FBP was used (p > 0.05). Gradual image noise reduction was observed with each increasing increment of hybrid IRT strength, with a maximum noise suppression of approximately 50% (48.2-53.9%). Similar noise reduction was achieved on the scanners by applying specific hybrid IRT strengths. Maximum noise reduction was higher on model-based IRTs (68.3-81.1%) than hybrid IRTs (48.2-53.9%) (p < 0.05). CONCLUSION. When constant scanning parameters are used, radiation dose and image noise on FBP are similar for CT scanners made by different manufacturers. Significant image noise reduction is achieved on low-dose CT examinations rendered with IRTs. The image noise on various scanners can be matched by applying specific hybrid IRT strengths. Model-based IRTs attain substantially higher noise reduction than hybrid IRTs irrespective of the radiation dose.

Effect of film-based versus filmless operation on the productivity of CT technologists.

PubMed

Reiner, B I; Siegel, E L; Hooper, F J; Glasser, D

1998-05-01

To determine the relative time required for a technologist to perform a computed tomographic (CT) examination in a "filmless" versus a film-based environment. Time-motion studies were performed in 204 consecutive CT examinations. Images from 96 examinations were electronically transferred to a picture archiving and communication system (PACS) without being printed to film, and 108 were printed to film. The time required to obtain and electronically transfer the images or print the images to film and make the current and previous studies available to the radiologists for interpretation was recorded. The time required for a technologist to complete a CT examination was reduced by 45% with direct image transfer to the PACS compared with the time required in the film-based mode. This reduction was due to the elimination of a number of steps in the filming process, such as the printing at multiple window or level settings. The use of a PACS can result in the elimination of multiple time-intensive tasks for the CT technologist, resulting in a marked reduction in examination time. This reduction can result in increased productivity, and, hence greater cost-effectiveness with filmless operation.

Equally sloped tomography based X-ray full-field nano-CT at Shanghai Synchrotron Radiation Facility

NASA Astrophysics Data System (ADS)

Wang, Yudan; Ren, Yuqi; Zhou, Guangzhao; Du, Guohao; Xie, Honglan; Deng, Biao; Xiao, Tiqiao

2018-07-01

X-ray full-field nano-computed tomography (nano-CT) has non-destructive three-dimensional imaging capabilities with high spatial resolution, and has been widely applied to investigate morphology and structures in various areas. Conventional tomography reconstructs a 3D object from a large number of equal-angle projections. For nano-CT, it takes long collecting time due to the large projection numbers and long exposure time. Here, equally-sloped tomography (EST) based nano-CT was implemented and constructed on X-ray imaging beamline at the Shanghai Synchrotron Radiation Facility (SSRF) to overcome or alleviate these difficulties. Preliminary results show that hard TXM with the spatial resolution of 100 nm and the EST-based nano-CT with the ability of 3D nano non-destructive characterization have been realized. This technique promotes hard X-ray imaging capability to nano scales at SSRF and could have applications in many fields including nanomaterials, new energy and life sciences. The study will be helpful for the construction of the new full field X-ray nano-imaging beamline with the spatial resolution of 20 nm at SSRF phase II project.

Design and development of C-arm based cone-beam CT for image-guided interventions: initial results

NASA Astrophysics Data System (ADS)

Chen, Guang-Hong; Zambelli, Joseph; Nett, Brian E.; Supanich, Mark; Riddell, Cyril; Belanger, Barry; Mistretta, Charles A.

2006-03-01

X-ray cone-beam computed tomography (CBCT) is of importance in image-guided intervention (IGI) and image-guided radiation therapy (IGRT). In this paper, we present a cone-beam CT data acquisition system using a GE INNOVA 4100 (GE Healthcare Technologies, Waukesha, Wisconsin) clinical system. This new cone-beam data acquisition mode was developed for research purposes without interfering with any clinical function of the system. It provides us a basic imaging pipeline for more advanced cone-beam data acquisition methods. It also provides us a platform to study and overcome the limiting factors such as cone-beam artifacts and limiting low contrast resolution in current C-arm based cone-beam CT systems. A geometrical calibration method was developed to experimentally determine parameters of the scanning geometry to correct the image reconstruction for geometric non-idealities. Extensive phantom studies and some small animal studies have been conducted to evaluate the performance of our cone-beam CT data acquisition system.

Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT.

PubMed

Ferrario, Damien; Grychtol, Bartłomiej; Adler, Andy; Solà, Josep; Böhm, Stephan H; Bodenstein, Marc

2012-11-01

Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the ability of EIT technology to reconstruct relevant impedance changes at their anatomical locations, provided that information about the thoracic boundary shape (and electrode positions) are used for reconstruction.

Automatic extraction of via in the CT image of PCB

NASA Astrophysics Data System (ADS)

Liu, Xifeng; Hu, Yuwei

2018-04-01

In modern industry, the nondestructive testing of printed circuit board (PCB) can prevent effectively the system failure and is becoming more and more important. In order to detect the via in the PCB base on the CT image automatically accurately and reliably, a novel algorithm for via extraction based on weighting stack combining the morphologic character of via is designed. Every slice data in the vertical direction of the PCB is superimposed to enhanced vias target. The OTSU algorithm is used to segment the slice image. OTSU algorithm of thresholding gray level images is efficient for separating an image into two classes where two types of fairly distinct classes exist in the image. Randomized Hough Transform was used to locate the region of via in the segmented binary image. Then the 3D reconstruction of via based on sequence slice images was done by volume rendering. The accuracy of via positioning and detecting from a CT images of PCB was demonstrated by proposed algorithm. It was found that the method is good in veracity and stability for detecting of via in three dimensional.

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is basedmore » on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan{sup ©}600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan{sup ©}600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution.« less

Diagnosis demystified: CT as diagnostic tool in endodontics

PubMed Central

Shruthi, Nagaraja; Sreenivasa Murthy, B V; Sundaresh, K J; Mallikarjuna, Rachappa

2013-01-01

Diagnosis in endodontics is usually based on clinical and radiographical presentations, which are only empirical methods. The role of healing profession is to apply knowledge and skills towards maintaining and restoring the patient's health. Recent advances in imaging technologies have added to correct interpretation and diagnosis. CT is proving to be an effective tool in solving endodontic mysteries through its three-dimensional visualisation. CT imaging offers many diagnostic advantages to produce reconstructed images in selected projection and low-contrast resolution far superior to that of all other X-ray imaging modalities. This case report is an endeavour towards effective treatment planning of cases with root fracture, root resorption using spiral CT as an adjuvant diagnostic tool. PMID:23814212

Cardiac CT for myocardial ischaemia detection and characterization--comparative analysis.

PubMed

Bucher, A M; De Cecco, C N; Schoepf, U J; Wang, R; Meinel, F G; Binukrishnan, S R; Spearman, J V; Vogl, T J; Ruzsics, B

2014-11-01

The assessment of patients presenting with symptoms of myocardial ischaemia remains one of the most common and challenging clinical scenarios faced by physicians. Current imaging modalities are capable of three-dimensional, functional and anatomical views of the heart and as such offer a unique contribution to understanding and managing the pathology involved. Evidence has accumulated that visual anatomical coronary evaluation does not adequately predict haemodynamic relevance and should be complemented by physiological evaluation, highlighting the importance of functional assessment. Technical advances in CT technology over the past decade have progressively moved cardiac CT imaging into the clinical workflow. In addition to anatomical evaluation, cardiac CT is capable of providing myocardial perfusion parameters. A variety of CT techniques can be used to assess the myocardial perfusion. The single energy first-pass CT and dual energy first-pass CT allow static assessment of myocardial blood pool. Dynamic cardiac CT imaging allows quantification of myocardial perfusion through time-resolved attenuation data. CT-based myocardial perfusion imaging (MPI) is showing promising diagnostic accuracy compared with the current reference modalities. The aim of this review is to present currently available myocardial perfusion techniques with a focus on CT imaging in light of recent clinical investigations. This article provides a comprehensive overview of currently available CT approaches of static and dynamic MPI and presents the results of corresponding clinical trials.

SU-F-T-427: Utilization and Evaluation of Diagnostic CT Imaging with MAR Technique for Radiation Therapy Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, M; Foster, R; Parks, H

Purpose: The objective was to utilize and evaluate diagnostic CT-MAR technique for radiation therapy treatment planning. Methods: A Toshiba-diagnostic-CT acquisition with SEMAR(Single-energy-MAR)-algorism was performed to make the metal-artifact-reduction (MAR) for patient treatment planning. CT-imaging datasets with and without SEMAR were taken on a Catphan-phantom. Two sets of CT-numbers were calibrated with the relative electron densities (RED). A tissue characterization phantom with Gammex various simulating material rods was used to establish the relationship between known REDs and corresponding CT-numbers. A GE-CT-sim acquisition was taken on the Catphan for comparison. A patient with bilateral hip arthroplasty was scanned in the radiotherapy CT-simmore » and the diagnostic SEMAR-CT on a flat panel. The derived SEMAR images were used as a primary CT dataset to create contours for the target, critical-structures, and for planning. A deformable registration was performed with VelocityAI to track voxel changes between SEMAR and CT-sim images. The SEMAR-CT images with minimal artifacts and high quality of geometrical and spatial integrity were employed for a treatment plan. Treatment-plans were evaluated based on deformable registration of SEMAR-CT and CT-sim dataset with assigned CT-numbers in the metal artifact regions in Eclipse v11 TPS. Results: The RED and CT-number relationships were consistent for the datasets in CT-sim and CT’s with and without SEMAR. SEMAR datasets with high image quality were used for PTV and organ delineation in the treatment planning process. For dose distribution to the PTV through the DVH analysis, the plan using CT-sim with the assigned CT-number showed a good agreement to those on deformable CT-SEMAR. Conclusion: A diagnostic-CT with MAR-algorithm can be utilized for radiotherapy treatment planning with CT-number calibrated to the RED. Treatment planning comparison and DVH shows a good agreement in the PTV and critical organs between the plans on CT-sim with assigned CT-number and the deformable SEMAR CT datasets.« less

Comparison Study of Regularizations in Spectral Computed Tomography Reconstruction

NASA Astrophysics Data System (ADS)

Salehjahromi, Morteza; Zhang, Yanbo; Yu, Hengyong

2018-12-01

The energy-resolving photon-counting detectors in spectral computed tomography (CT) can acquire projections of an object in different energy channels. In other words, they are able to reliably distinguish the received photon energies. These detectors lead to the emerging spectral CT, which is also called multi-energy CT, energy-selective CT, color CT, etc. Spectral CT can provide additional information in comparison with the conventional CT in which energy integrating detectors are used to acquire polychromatic projections of an object being investigated. The measurements obtained by X-ray CT detectors are noisy in reality, especially in spectral CT where the photon number is low in each energy channel. Therefore, some regularization should be applied to obtain a better image quality for this ill-posed problem in spectral CT image reconstruction. Quadratic-based regularizations are not often satisfactory as they blur the edges in the reconstructed images. As a result, different edge-preserving regularization methods have been adopted for reconstructing high quality images in the last decade. In this work, we numerically evaluate the performance of different regularizers in spectral CT, including total variation, non-local means and anisotropic diffusion. The goal is to provide some practical guidance to accurately reconstruct the attenuation distribution in each energy channel of the spectral CT data.

[Anatomy of the skull base and the cranial nerves in slice imaging].

PubMed

Bink, A; Berkefeld, J; Zanella, F

2009-07-01

Computed tomography (CT) and magnetic resonance imaging (MRI) are suitable methods for examination of the skull base. Whereas CT is used to evaluate mainly bone destruction e.g. for planning surgical therapy, MRI is used to show pathologies in the soft tissue and bone invasion. High resolution and thin slice thickness are indispensible for both modalities of skull base imaging. Detailed anatomical knowledge is necessary even for correct planning of the examination procedures. This knowledge is a requirement to be able to recognize and interpret pathologies. MRI is the method of choice for examining the cranial nerves. The total path of a cranial nerve can be visualized by choosing different sequences taking into account the tissue surrounding this cranial nerve. This article summarizes examination methods of the skull base in CT and MRI, gives a detailed description of the anatomy and illustrates it with image examples.

Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification

PubMed Central

Chen, Xiang; Gilkeson, Robert; Fei, Baowei

2013-01-01

We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the “gold standard” to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 ± 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 ± 0.03 to 0.25 ± 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification. PMID:24386527

Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification.

PubMed

Chen, Xiang; Gilkeson, Robert; Fei, Baowei

2007-03-03

We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 ± 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 ± 0.03 to 0.25 ± 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification.

Automatic intensity-based 3D-to-2D registration of CT volume and dual-energy digital radiography for the detection of cardiac calcification

NASA Astrophysics Data System (ADS)

Chen, Xiang; Gilkeson, Robert; Fei, Baowei

2007-03-01

We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 +/- 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 +/- 0.03 to 0.25 +/- 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Lesion detection performance: comparative analysis of low-dose CT data of the chest on two hybrid imaging systems.

PubMed

Jessop, Maryam; Thompson, John D; Coward, Joanne; Sanderud, Audun; Jorge, José; de Groot, Martijn; Lança, Luís; Hogg, Peter

2015-03-01

Incidental findings on low-dose CT images obtained during hybrid imaging are an increasing phenomenon as CT technology advances. Understanding the diagnostic value of incidental findings along with the technical limitations is important when reporting image results and recommending follow-up, which may result in an additional radiation dose from further diagnostic imaging and an increase in patient anxiety. This study assessed lesions incidentally detected on CT images acquired for attenuation correction on two SPECT/CT systems. An anthropomorphic chest phantom containing simulated lesions of varying size and density was imaged on an Infinia Hawkeye 4 and a Symbia T6 using the low-dose CT settings applied for attenuation correction acquisitions in myocardial perfusion imaging. Twenty-two interpreters assessed 46 images from each SPECT/CT system (15 normal images and 31 abnormal images; 41 lesions). Data were evaluated using a jackknife alternative free-response receiver-operating-characteristic analysis (JAFROC). JAFROC analysis showed a significant difference (P < 0.0001) in lesion detection, with the figures of merit being 0.599 (95% confidence interval, 0.568, 0.631) and 0.810 (95% confidence interval, 0.781, 0.839) for the Infinia Hawkeye 4 and Symbia T6, respectively. Lesion detection on the Infinia Hawkeye 4 was generally limited to larger, higher-density lesions. The Symbia T6 allowed improved detection rates for midsized lesions and some lower-density lesions. However, interpreters struggled to detect small (5 mm) lesions on both image sets, irrespective of density. Lesion detection is more reliable on low-dose CT images from the Symbia T6 than from the Infinia Hawkeye 4. This phantom-based study gives an indication of potential lesion detection in the clinical context as shown by two commonly used SPECT/CT systems, which may assist the clinician in determining whether further diagnostic imaging is justified. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

SU-E-I-09: The Impact of X-Ray Scattering On Image Noise for Dedicated Breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, K; Gazi, P; Boone, J

2015-06-15

Purpose: To quantify the impact of detected x-ray scatter on image noise in flat panel based dedicated breast CT systems and to determine the optimal scanning geometry given practical trade-offs between radiation dose and scatter reduction. Methods: Four different uniform polyethylene cylinders (104, 131, 156, and 184 mm in diameter) were scanned as the phantoms on a dedicated breast CT scanner developed in our laboratory. Both stationary projection imaging and rotational cone-beam CT imaging was performed. For each acquisition type, three different x-ray beam collimations were used (12, 24, and 109 mm measured at isocenter). The aim was to quantifymore » image noise properties (pixel variance, SNR, and image NPS) under different levels of x-ray scatter, in order to optimize the scanning geometry. For both projection images and reconstructed CT images, individual pixel variance and NPS were determined and compared. Noise measurement from the CT images were also performed with different detector binning modes and reconstruction matrix sizes. Noise propagation was also tracked throughout the intermediate steps of cone-beam CT reconstruction, including the inverse-logarithmic process, Fourier-filtering before backprojection. Results: Image noise was lower in the presence of higher scatter levels. For the 184 mm polyethylene phantom, the image noise (measured in pixel variance) was ∼30% lower with full cone-beam acquisition compared to a narrow (12 mm) fan-beam acquisition. This trend is consistent across all phantom sizes and throughout all steps of CT image reconstruction. Conclusion: From purely a noise perspective, the cone-beam geometry (i.e. the full cone-angle acquisition) produces lower image noise compared to the lower-scatter fan-beam acquisition for breast CT. While these results are relevant in homogeneous phantoms, the full impact of scatter on noise in bCT should involve contrast-to-noise-ratio measurements in heterogeneous phantoms if the goal is to optimize the scanning geometry for dedicated breast CT. This work was supported by a grant from the National Institute for Biomedical Imaging and Bioengineering (R01 EB002138)« less

Estimating Glenoid Width for Instability-Related Bone Loss: A CT Evaluation of an MRI Formula.

PubMed

Giles, Joshua W; Owens, Brett D; Athwal, George S

2015-07-01

Determining the magnitude of glenoid bone loss in cases of shoulder instability is an important step in selecting the optimal reconstructive procedure. Recently, a formula has been proposed that estimates native glenoid width based on magnetic resonance imaging (MRI) measurements of height (1/3 × glenoid height + 15 mm). This technique, however, has not been validated for use with computed tomography (CT), which is often the preferred imaging modality to assess bone deficiencies. The purpose of this project was 2-fold: (1) to determine if the MRI-based formula that predicts glenoid width from height is valid with CT and (2) to determine if a more accurate regression can be resolved for use specifically with CT data. Descriptive laboratory study. Ninety normal shoulder CT scans with preserved osseous anatomy were drawn from an existing database and analyzed. Measurements of glenoid height and width were performed by 2 observers on reconstructed 3-dimensional models. After assessment of reliability, the data were correlated, and regression models were created for male and female shoulders. The accuracy of the MRI-based model's predictions was then compared with that of the CT-based models. Intra- and interrater reliabilities were good to excellent for height and width, with intraclass correlation coefficients of 0.765 to 0.992. The height and width values had a strong correlation of 0.900 (P < .001). Regression analyses for male and female shoulders produced CT-specific formulas: for men, glenoid width = 2/3 × glenoid height + 5 mm; for women, glenoid width = 2/3 × glenoid height + 3 mm. Comparison of predictions from the MRI- and CT-specific formulas demonstrated good agreement (intraclass correlation coefficient = 0.818). The CT-specific formulas produced a root mean squared error of 1.2 mm, whereas application of the MRI-specific formula to CT images resulted in a root mean squared error of 1.5 mm. Use of the MRI-based formula on CT scans to predict glenoid width produced estimates that were nearly as accurate as the CT-specific formulas. The CT-specific formulas, however, are more accurate at predicting native glenoid width when applied to CT data. Imaging-specific (CT and MRI) formulas have been developed to estimate glenoid bone loss in patients with instability. The CT-specific formula can accurately predict native glenoid width, having an error of only 2.2% of average glenoid width. © 2015 The Author(s).

A New Approach to Automated Labeling of Internal Features of Hardwood Logs Using CT Images

Treesearch

Daniel L. Schmoldt; Pei Li; A. Lynn Abbott

1996-01-01

The feasibility of automatically identifying internal features of hardwood logs using CT imagery has been established previously. Features of primary interest are bark, knots, voids, decay, and clear wood. Our previous approach: filtered original CT images, applied histogram segmentation, grew volumes to extract 3-d regions, and applied a rule base, with Dempster-...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ching-Ching, E-mail: cyang@tccn.edu.tw; Liu, Shu-Hsin; Mok, Greta S. P.

Purpose: This study aimed to tailor the CT imaging protocols for pediatric patients undergoing whole-body PET/CT examinations with appropriate attention to radiation exposure while maintaining adequate image quality for anatomic delineation of PET findings and attenuation correction of PET emission data. Methods: The measurements were made by using three anthropomorphic phantoms representative of 1-, 5-, and 10-year-old children with tube voltages of 80, 100, and 120 kVp, tube currents of 10, 40, 80, and 120 mA, and exposure time of 0.5 s at 1.75:1 pitch. Radiation dose estimates were derived from the dose-length product and were used to calculate riskmore » estimates for radiation-induced cancer. The influence of image noise on image contrast and attenuation map for CT scans were evaluated based on Pearson's correlation coefficient and covariance, respectively. Multiple linear regression methods were used to investigate the effects of patient age, tube voltage, and tube current on radiation-induced cancer risk and image noise for CT scans. Results: The effective dose obtained using three anthropomorphic phantoms and 12 combinations of kVp and mA ranged from 0.09 to 4.08 mSv. Based on our results, CT scans acquired with 80 kVp/60 mA, 80 kVp/80 mA, and 100 kVp/60 mA could be performed on 1-, 5-, and 10-year-old children, respectively, to minimize cancer risk due to CT scans while maintaining the accuracy of attenuation map and CT image contrast. The effective doses of the proposed protocols for 1-, 5- and 10-year-old children were 0.65, 0.86, and 1.065 mSv, respectively. Conclusions: Low-dose pediatric CT protocols were proposed to balance the tradeoff between radiation-induced cancer risk and image quality for patients ranging in age from 1 to 10 years old undergoing whole-body PET/CT examinations.« less

Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approach

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2017-02-01

We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using "convolution" and "deconvolution" networks to achieve the conventional "coarse recognition" and "fine extraction" functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.

SU-E-P-41: Imaging Coordination of Cone Beam CT, On-Board Image Conjunction with Optical Image Guidance for SBRT Treatment with Respiratory Motion Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Campbell, J

2015-06-15

Purpose: To spare normal tissue for SBRT lung/liver patients, especially for patients with significant tumor motion, image guided respiratory motion management has been widely implemented in clinical practice. The purpose of this study was to evaluate imaging coordination of cone beam CT, on-board X-ray image conjunction with optical image guidance for SBRT treatment with motion management. Methods: Currently in our clinic a Varian Novlis Tx was utilized for treating SBRT patients implementing CBCT. A BrainLAB X-ray ExacTrac imaging system in conjunction with optical guidance was primarily used for SRS patients. CBCT and X-ray imaging system were independently calibrated with 1.0more » mm tolerance. For SBRT lung/liver patients, the magnitude of tumor motion was measured based-on 4DCT and the measurement was analyzed to determine if patients would be beneficial with respiratory motion management. For patients eligible for motion management, an additional CT with breath holding would be scanned and used as primary planning CT and as reference images for Cone beam CT. During the SBRT treatment, a CBCT with pause and continuing technology would be performed with patients holding breath, which may require 3–4 partially scanned CBCT to combine as a whole CBCT depending on how long patients capable of holding breath. After patients being setup by CBCT images, the ExactTrac X-ray imaging system was implemented with patients’ on-board X-ray images compared to breath holding CT-based DRR. Results: For breath holding patients SBRT treatment, after initially localizing patients with CBCT, we then position patients with ExacTrac X-ray and optical imaging system. The observed deviations of real-time optical guided position average at 3.0, 2.5 and 1.5 mm in longitudinal, vertical and lateral respectively based on 35 treatments. Conclusion: The respiratory motion management clinical practice improved our physician confidence level to give tighter tumor margin for sparing normal tissue for SBRT lung/liver patients.« less

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy.

PubMed

Yoo, Boyeol; Son, Kihong; Pua, Rizza; Kim, Jinsung; Solodov, Alexander; Cho, Seungryong

2016-10-01

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT. An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment. The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan. The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

Image Reconstruction for Hybrid True-Color Micro-CT

PubMed Central

Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge

2013-01-01

X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid “true-color” micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a “color diffusion” phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose. PMID:22481806

Relationship between solitary pulmonary nodule lung cancer and CT image features based on gradual clustering

NASA Astrophysics Data System (ADS)

Zhang, Weipeng

2017-06-01

The relationship between the medical characteristics of lung cancers and computer tomography (CT) images are explored so as to improve the early diagnosis rate of lung cancers. This research collected CT images of patients with solitary pulmonary nodule lung cancer, and used gradual clustering methodology to classify them. Preliminary classifications were made, followed by continuous modification and iteration to determine the optimal condensation point, until iteration stability was achieved. Reasonable classification results were obtained. the clustering results fell into 3 categories. The first type of patients was mostly female, with ages between 50 and 65 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, with pleural indentation; The second type of patients was mostly male with ages between 50 and 80 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, but with no pleural indentation; The third type of patients was also mostly male with ages between 50 and 80 years. CT images for this group showed no abnormalities. the application of gradual clustering methodology can scientifically classify CT image features of patients with lung cancer in the initial lesion stage. These findings provide the basis for early detection and treatment of malignant lesions in patients with lung cancer.

MRI vs. CT for orthodontic applications: comparison of two MRI protocols and three CT (multislice, cone-beam, industrial) technologies.

PubMed

Detterbeck, Andreas; Hofmeister, Michael; Hofmann, Elisabeth; Haddad, Daniel; Weber, Daniel; Hölzing, Astrid; Zabler, Simon; Schmid, Matthias; Hiller, Karl-Heinz; Jakob, Peter; Engel, Jens; Hiller, Jochen; Hirschfelder, Ursula

2016-07-01

To examine the relative usefulness and suitability of magnetic resonance imaging (MRI) in daily clinical practice as compared to various technologies of computed tomography (CT) in addressing questions of orthodontic interest. Three blinded raters evaluated 2D slices and 3D reconstructions created from scans of two pig heads. Five imaging modalities were used, including three CT technologies-multislice (MSCT), cone-beam CT (CBCT), and industrial (µCT)-and two MRI protocols with different scan durations. Defined orthodontic parameters were rated one by one on the 2D slices and the 3D reconstructions, followed by final overall ratings for each modality. A mixed linear model was used for statistical analysis. Based on the 2D slices, the parameter of visualizing tooth-germ topography did not yield any significantly different ratings for MRI versus any of the CT scans. While some ratings for the other parameters did involve significant differences, how these should be interpreted depends greatly on the relevance of each parameter. Based on the 3D reconstructions, the only significant difference between technologies was noted for the parameter of visualizing root-surface morphology. Based on the final overall ratings, the imaging performance of the standard MRI protocol was noninferior to the performance of the three CT technologies. On comparing the imaging performance of MRI and CT scans, it becomes clear that MRI has a huge potential for applications in daily clinical practice. Given its additional benefits of a good contrast ratio and complete absence of ionizing radiation, further studies are needed to explore this clinical potential in greater detail.

Real-time fusion of endoscopic views with dynamic 3-D cardiac images: a phantom study.

PubMed

Szpala, Stanislaw; Wierzbicki, Marcin; Guiraudon, Gerard; Peters, Terry M

2005-09-01

Minimally invasive robotically assisted cardiac surgical systems currently do not routinely employ 3-D image guidance. However, preoperative magnetic resonance and computed tomography (CT) images have the potential to be used in this role, if appropriately registered with the patient anatomy and animated synchronously with the motion of the actual heart. This paper discusses the fusion of optical images of a beating heart phantom obtained from an optically tracked endoscope, with volumetric images of the phantom created from a dynamic CT dataset. High quality preoperative dynamic CT images are created by first extracting the motion parameters of the heart from the series of temporal frames, and then applying this information to animate a high-quality heart image acquired at end systole. Temporal synchronization of the endoscopic and CT model is achieved by selecting the appropriate CT image from the dynamic set, based on an electrocardiographic trigger signal. The spatial error between the optical and virtual images is 1.4 +/- 1.1 mm, while the time discrepancy is typically 50-100 ms. Index Terms-Image guidance, image warping, minimally invasive cardiac surgery, virtual endoscopy, virtual reality.

Investigating the generalisation of an atlas-based synthetic-CT algorithm to another centre and MR scanner for prostate MR-only radiotherapy

NASA Astrophysics Data System (ADS)

Wyatt, Jonathan J.; Dowling, Jason A.; Kelly, Charles G.; McKenna, Jill; Johnstone, Emily; Speight, Richard; Henry, Ann; Greer, Peter B.; McCallum, Hazel M.

2017-12-01

There is increasing interest in MR-only radiotherapy planning since it provides superb soft-tissue contrast without the registration uncertainties inherent in a CT-MR registration. However, MR images cannot readily provide the electron density information necessary for radiotherapy dose calculation. An algorithm which generates synthetic CTs for dose calculations from MR images of the prostate using an atlas of 3 T MR images has been previously reported by two of the authors. This paper aimed to evaluate this algorithm using MR data acquired at a different field strength and a different centre to the algorithm atlas. Twenty-one prostate patients received planning 1.5 T MR and CT scans with routine immobilisation devices on a flat-top couch set-up using external lasers. The MR receive coils were supported by a coil bridge. Synthetic CTs were generated from the planning MR images with (sCT1V ) and without (sCT) a one voxel body contour expansion included in the algorithm. This was to test whether this expansion was required for 1.5 T images. Both synthetic CTs were rigidly registered to the planning CT (pCT). A 6 MV volumetric modulated arc therapy plan was created on the pCT and recalculated on the sCT and sCT1V . The synthetic CTs’ dose distributions were compared to the dose distribution calculated on the pCT. The percentage dose difference at isocentre without the body contour expansion (sCT-pCT) was Δ D_sCT=(0.9 +/- 0.8) % and with (sCT1V -pCT) was Δ D_sCT1V=(-0.7 +/- 0.7) % (mean  ±  one standard deviation). The sCT1V result was within one standard deviation of zero and agreed with the result reported previously using 3 T MR data. The sCT dose difference only agreed within two standard deviations. The mean  ±  one standard deviation gamma pass rate was Γ_sCT = 96.1 +/- 2.9 % for the sCT and Γ_sCT1V = 98.8 +/- 0.5 % for the sCT1V (with 2% global dose difference and 2~mm distance to agreement gamma criteria). The one voxel body contour expansion improves the synthetic CT accuracy for MR images acquired at 1.5 T but requires the MR voxel size to be similar to the atlas MR voxel size. This study suggests that the atlas-based algorithm can be generalised to MR data acquired using a different field strength at a different centre.

Variance analysis of x-ray CT sinograms in the presence of electronic noise background.

PubMed

Ma, Jianhua; Liang, Zhengrong; Fan, Yi; Liu, Yan; Huang, Jing; Chen, Wufan; Lu, Hongbing

2012-07-01

Low-dose x-ray computed tomography (CT) is clinically desired. Accurate noise modeling is a fundamental issue for low-dose CT image reconstruction via statistics-based sinogram restoration or statistical iterative image reconstruction. In this paper, the authors analyzed the statistical moments of low-dose CT data in the presence of electronic noise background. The authors first studied the statistical moment properties of detected signals in CT transmission domain, where the noise of detected signals is considered as quanta fluctuation upon electronic noise background. Then the authors derived, via the Taylor expansion, a new formula for the mean-variance relationship of the detected signals in CT sinogram domain, wherein the image formation becomes a linear operation between the sinogram data and the unknown image, rather than a nonlinear operation in the CT transmission domain. To get insight into the derived new formula by experiments, an anthropomorphic torso phantom was scanned repeatedly by a commercial CT scanner at five different mAs levels from 100 down to 17. The results demonstrated that the electronic noise background is significant when low-mAs (or low-dose) scan is performed. The influence of the electronic noise background should be considered in low-dose CT imaging.

Variance analysis of x-ray CT sinograms in the presence of electronic noise background

PubMed Central

Ma, Jianhua; Liang, Zhengrong; Fan, Yi; Liu, Yan; Huang, Jing; Chen, Wufan; Lu, Hongbing

2012-01-01

Purpose: Low-dose x-ray computed tomography (CT) is clinically desired. Accurate noise modeling is a fundamental issue for low-dose CT image reconstruction via statistics-based sinogram restoration or statistical iterative image reconstruction. In this paper, the authors analyzed the statistical moments of low-dose CT data in the presence of electronic noise background. Methods: The authors first studied the statistical moment properties of detected signals in CT transmission domain, where the noise of detected signals is considered as quanta fluctuation upon electronic noise background. Then the authors derived, via the Taylor expansion, a new formula for the mean–variance relationship of the detected signals in CT sinogram domain, wherein the image formation becomes a linear operation between the sinogram data and the unknown image, rather than a nonlinear operation in the CT transmission domain. To get insight into the derived new formula by experiments, an anthropomorphic torso phantom was scanned repeatedly by a commercial CT scanner at five different mAs levels from 100 down to 17. Results: The results demonstrated that the electronic noise background is significant when low-mAs (or low-dose) scan is performed. Conclusions: The influence of the electronic noise background should be considered in low-dose CT imaging. PMID:22830738

Vision 20/20: Simultaneous CT-MRI — Next chapter of multimodality imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Ge, E-mail: wangg6@rpi.edu; Xi, Yan; Gjesteby, Lars

Multimodality imaging systems such as positron emission tomography-computed tomography (PET-CT) and MRI-PET are widely available, but a simultaneous CT-MRI instrument has not been developed. Synergies between independent modalities, e.g., CT, MRI, and PET/SPECT can be realized with image registration, but such postprocessing suffers from registration errors that can be avoided with synchronized data acquisition. The clinical potential of simultaneous CT-MRI is significant, especially in cardiovascular and oncologic applications where studies of the vulnerable plaque, response to cancer therapy, and kinetic and dynamic mechanisms of targeted agents are limited by current imaging technologies. The rationale, feasibility, and realization of simultaneous CT-MRImore » are described in this perspective paper. The enabling technologies include interior tomography, unique gantry designs, open magnet and RF sequences, and source and detector adaptation. Based on the experience with PET-CT, PET-MRI, and MRI-LINAC instrumentation where hardware innovation and performance optimization were instrumental to construct commercial systems, the authors provide top-level concepts for simultaneous CT-MRI to meet clinical requirements and new challenges. Simultaneous CT-MRI fills a major gap of modality coupling and represents a key step toward the so-called “omnitomography” defined as the integration of all relevant imaging modalities for systems biology and precision medicine.« less

Recommendations of the Spanish Societies of Radiation Oncology (SEOR), Nuclear Medicine & Molecular Imaging (SEMNiM), and Medical Physics (SEFM) on (18)F-FDG PET-CT for radiotherapy treatment planning.

PubMed

Caballero Perea, Begoña; Villegas, Antonio Cabrera; Rodríguez, José Miguel Delgado; Velloso, María José García; Vicente, Ana María García; Cabrerizo, Carlos Huerga; López, Rosa Morera; Romasanta, Luis Alberto Pérez; Beltrán, Moisés Sáez

2012-01-01

Positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process.

Recommendations of the Spanish Societies of Radiation Oncology (SEOR), Nuclear Medicine & Molecular Imaging (SEMNiM), and Medical Physics (SEFM) on 18F-FDG PET-CT for radiotherapy treatment planning

PubMed Central

Caballero Perea, Begoña; Villegas, Antonio Cabrera; Rodríguez, José Miguel Delgado; Velloso, María José García; Vicente, Ana María García; Cabrerizo, Carlos Huerga; López, Rosa Morera; Romasanta, Luis Alberto Pérez; Beltrán, Moisés Sáez

2012-01-01

Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process. PMID:24377032

Ventricular Geometry From Non-contrast Non-ECG-gated CT Scans: An Imaging Marker of Cardiopulmonary Disease in Smokers.

PubMed

Rahaghi, Farbod N; Vegas-Sanchez-Ferrero, Gonzalo; Minhas, Jasleen K; Come, Carolyn E; De La Bruere, Isaac; Wells, James M; González, Germán; Bhatt, Surya P; Fenster, Brett E; Diaz, Alejandro A; Kohli, Puja; Ross, James C; Lynch, David A; Dransfield, Mark T; Bowler, Russel P; Ledesma-Carbayo, Maria J; San José Estépar, Raúl; Washko, George R

2017-05-01

Imaging-based assessment of cardiovascular structure and function provides clinically relevant information in smokers. Non-cardiac-gated thoracic computed tomographic (CT) scanning is increasingly leveraged for clinical care and lung cancer screening. We sought to determine if more comprehensive measures of ventricular geometry could be obtained from CT using an atlas-based surface model of the heart. Subcohorts of 24 subjects with cardiac magnetic resonance imaging (MRI) and 262 subjects with echocardiography were identified from COPDGene, a longitudinal observational study of smokers. A surface model of the heart was manually initialized, and then automatically optimized to fit the epicardium for each CT. Estimates of right and left ventricular (RV and LV) volume and free-wall curvature were then calculated and compared to structural and functional metrics obtained from MRI and echocardiograms. CT measures of RV dimension and curvature correlated with similar measures obtained using MRI. RV and LV volume obtained from CT inversely correlated with echocardiogram-based estimates of RV systolic pressure using tricuspid regurgitation jet velocity and LV ejection fraction respectively. Patients with evidence of RV or LV dysfunction on echocardiogram had larger RV and LV dimensions on CT. Logistic regression models based on demographics and ventricular measures from CT had an area under the curve of >0.7 for the prediction of elevated right ventricular systolic pressure and ventricular failure. These data suggest that non-cardiac-gated, non-contrast-enhanced thoracic CT scanning may provide insight into cardiac structure and function in smokers. Copyright © 2017. Published by Elsevier Inc.

Kidney segmentation in CT sequences using graph cuts based active contours model and contextual continuity.

PubMed

Zhang, Pin; Liang, Yanmei; Chang, Shengjiang; Fan, Hailun

2013-08-01

Accurate segmentation of renal tissues in abdominal computed tomography (CT) image sequences is an indispensable step for computer-aided diagnosis and pathology detection in clinical applications. In this study, the goal is to develop a radiology tool to extract renal tissues in CT sequences for the management of renal diagnosis and treatments. In this paper, the authors propose a new graph-cuts-based active contours model with an adaptive width of narrow band for kidney extraction in CT image sequences. Based on graph cuts and contextual continuity, the segmentation is carried out slice-by-slice. In the first stage, the middle two adjacent slices in a CT sequence are segmented interactively based on the graph cuts approach. Subsequently, the deformable contour evolves toward the renal boundaries by the proposed model for the kidney extraction of the remaining slices. In this model, the energy function combining boundary with regional information is optimized in the constructed graph and the adaptive search range is determined by contextual continuity and the object size. In addition, in order to reduce the complexity of the min-cut computation, the nodes in the graph only have n-links for fewer edges. The total 30 CT images sequences with normal and pathological renal tissues are used to evaluate the accuracy and effectiveness of our method. The experimental results reveal that the average dice similarity coefficient of these image sequences is from 92.37% to 95.71% and the corresponding standard deviation for each dataset is from 2.18% to 3.87%. In addition, the average automatic segmentation time for one kidney in each slice is about 0.36 s. Integrating the graph-cuts-based active contours model with contextual continuity, the algorithm takes advantages of energy minimization and the characteristics of image sequences. The proposed method achieves effective results for kidney segmentation in CT sequences.

Reducing 4D CT artifacts using optimized sorting based on anatomic similarity.

PubMed

Johnston, Eric; Diehn, Maximilian; Murphy, James D; Loo, Billy W; Maxim, Peter G

2011-05-01

Four-dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4D CT algorithms sort images by the associated respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4D CT by incorporating anatomic similarity into phase or displacement based sorting protocols. Ten patient datasets were retrospectively sorted using both the displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest-neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using the Dijkstra's shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the resorted 4D datasets pairwise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Anatomically based image selection resulted in 4D CT datasets with significantly reduced motion artifacts with both displacement (P = 0.0063) and phase sorting (P = 0.00022). There was good agreement between the two reviewers, with complete agreement 34 times and complete disagreement 6 times. Optimized sorting using anatomic similarity significantly reduces 4D CT motion artifacts compared to conventional phase or displacement based sorting. This improved sorting algorithm is a straightforward extension of the two most common 4D CT sorting algorithms.

Quantitative micro-CT based coronary artery profiling using interactive local thresholding and cylindrical coordinates.

PubMed

Panetta, Daniele; Pelosi, Gualtiero; Viglione, Federica; Kusmic, Claudia; Terreni, Marianna; Belcari, Nicola; Guerra, Alberto Del; Athanasiou, Lambros; Exarchos, Themistoklis; Fotiadis, Dimitrios I; Filipovic, Nenad; Trivella, Maria Giovanna; Salvadori, Piero A; Parodi, Oberdan

2015-01-01

Micro-CT is an established imaging technique for high-resolution non-destructive assessment of vascular samples, which is gaining growing interest for investigations of atherosclerotic arteries both in humans and in animal models. However, there is still a lack in the definition of micro-CT image metrics suitable for comprehensive evaluation and quantification of features of interest in the field of experimental atherosclerosis (ATS). A novel approach to micro-CT image processing for profiling of coronary ATS is described, providing comprehensive visualization and quantification of contrast agent-free 3D high-resolution reconstruction of full-length artery walls. Accelerated coronary ATS has been induced by high fat cholesterol-enriched diet in swine and left coronary artery (LCA) harvested en bloc for micro-CT scanning and histologic processing. A cylindrical coordinate system has been defined on the image space after curved multiplanar reformation of the coronary vessel for the comprehensive visualization of the main vessel features such as wall thickening and calcium content. A novel semi-automatic segmentation procedure based on 2D histograms has been implemented and the quantitative results validated by histology. The potentiality of attenuation-based micro-CT at low kV to reliably separate arterial wall layers from adjacent tissue as well as identify wall and plaque contours and major tissue components has been validated by histology. Morphometric indexes from histological data corresponding to several micro-CT slices have been derived (double observer evaluation at different coronary ATS stages) and highly significant correlations (R2 > 0.90) evidenced. Semi-automatic morphometry has been validated by double observer manual morphometry of micro-CT slices and highly significant correlations were found (R2 > 0.92). The micro-CT methodology described represents a handy and reliable tool for quantitative high resolution and contrast agent free full length coronary wall profiling, able to assist atherosclerotic vessels morphometry in a preclinical experimental model of coronary ATS and providing a link between in vivo imaging and histology.

Evaluation of aortic contractility based on analysis of CT images of the heart

NASA Astrophysics Data System (ADS)

DzierŻak, RóŻa; Maciejewski, Ryszard; Uhlig, Sebastian

2017-08-01

The paper presents a method to assess the aortic contractility based on the analysis of CT images of the heart. This is an alternative method that can be used for patients who cannot be examined by using echocardiography. Usage of medical imaging application for DICOM file processing allows to evaluate the aortic cross section during systole and diastole. It makes possible to assess the level of aortic contractility.

PSMA-Targeted Nano-Conjugates as Dual-Modality (MRI/PET) Imaging Probes for the Non-Invasive Detection of Prostate Cancer

DTIC Science & Technology

2009-10-01

be made. Currently, iodine based compounds are used to enhance contrast of CT which have the limitations of short imaging window due to rapid...number compared to conventionally used iodine compounds . Nanoparticle based CT contrast agents have been demonstrated for vascular imaging, which...constructs with gamma or positron emitting isotopes through a covalent attachment of a bifunctional chelator to the nanoparticles surface. However, in

Assessment of the effects of CT dose in averaged x-ray CT images of a dose-sensitive polymer gel

NASA Astrophysics Data System (ADS)

Kairn, T.; Kakakhel, M. B.; Johnston, H.; Jirasek, A.; Trapp, J. V.

2015-01-01

The signal-to-noise ratio achievable in x-ray computed tomography (CT) images of polymer gels can be increased by averaging over multiple scans of each sample. However, repeated scanning delivers a small additional dose to the gel which may compromise the accuracy of the dose measurement. In this study, a NIPAM-based polymer gel was irradiated and then CT scanned 25 times, with the resulting data used to derive an averaged image and a "zero-scan" image of the gel. Comparison between these two results and the first scan of the gel showed that the averaged and zero-scan images provided better contrast, higher contrast-to- noise and higher signal-to-noise than the initial scan. The pixel values (Hounsfield units, HU) in the averaged image were not noticeably elevated, compared to the zero-scan result and the gradients used in the linear extrapolation of the zero-scan images were small and symmetrically distributed around zero. These results indicate that the averaged image was not artificially lightened by the small, additional dose delivered during CT scanning. This work demonstrates the broader usefulness of the zero-scan method as a means to verify the dosimetric accuracy of gel images derived from averaged x-ray CT data.

Emerging Techniques for Dose Optimization in Abdominal CT

PubMed Central

Platt, Joel F.; Goodsitt, Mitchell M.; Al-Hawary, Mahmoud M.; Maturen, Katherine E.; Wasnik, Ashish P.; Pandya, Amit

2014-01-01

Recent advances in computed tomographic (CT) scanning technique such as automated tube current modulation (ATCM), optimized x-ray tube voltage, and better use of iterative image reconstruction have allowed maintenance of good CT image quality with reduced radiation dose. ATCM varies the tube current during scanning to account for differences in patient attenuation, ensuring a more homogeneous image quality, although selection of the appropriate image quality parameter is essential for achieving optimal dose reduction. Reducing the x-ray tube voltage is best suited for evaluating iodinated structures, since the effective energy of the x-ray beam will be closer to the k-edge of iodine, resulting in a higher attenuation for the iodine. The optimal kilovoltage for a CT study should be chosen on the basis of imaging task and patient habitus. The aim of iterative image reconstruction is to identify factors that contribute to noise on CT images with use of statistical models of noise (statistical iterative reconstruction) and selective removal of noise to improve image quality. The degree of noise suppression achieved with statistical iterative reconstruction can be customized to minimize the effect of altered image quality on CT images. Unlike with statistical iterative reconstruction, model-based iterative reconstruction algorithms model both the statistical noise and the physical acquisition process, allowing CT to be performed with further reduction in radiation dose without an increase in image noise or loss of spatial resolution. Understanding these recently developed scanning techniques is essential for optimization of imaging protocols designed to achieve the desired image quality with a reduced dose. © RSNA, 2014 PMID:24428277

Improved proton CT imaging using a bismuth germanium oxide scintillator.

PubMed

Tanaka, Sodai; Nishio, Teiji; Tsuneda, Masato; Matsushita, Keiichiro; Kabuki, Shigeto; Uesaka, Mitsuru

2018-02-02

Range uncertainty is among the most formidable challenges associated with the treatment planning of proton therapy. Proton imaging, which includes proton radiography and proton computed tomography (pCT), is a useful verification tool. We have developed a pCT detection system that uses a thick bismuth germanium oxide (BGO) scintillator and a CCD camera. The current method is based on a previous detection system that used a plastic scintillator, and implements improved image processing techniques. In the new system, the scintillation light intensity is integrated along the proton beam path by the BGO scintillator, and acquired as a two-dimensional distribution with the CCD camera. The range of a penetrating proton is derived from the integrated light intensity using a light-to-range conversion table, and a pCT image can be reconstructed. The proton range in the BGO scintillator is shorter than in the plastic scintillator, so errors due to extended proton ranges can be reduced. To demonstrate the feasibility of the pCT system, an experiment was performed using a 70 MeV proton beam created by the AVF930 cyclotron at the National Institute of Radiological Sciences. The accuracy of the light-to-range conversion table, which is susceptible to errors due to its spatial dependence, was investigated, and the errors in the acquired pixel values were less than 0.5 mm. Images of various materials were acquired, and the pixel-value errors were within 3.1%, which represents an improvement over previous results. We also obtained a pCT image of an edible chicken piece, the first of its kind for a biological material, and internal structures approximately one millimeter in size were clearly observed. This pCT imaging system is fast and simple, and based on these findings, we anticipate that we can acquire 200 MeV pCT images using the BGO scintillator system.

Parametric boundary reconstruction algorithm for industrial CT metrology application.

PubMed

Yin, Zhye; Khare, Kedar; De Man, Bruno

2009-01-01

High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.

Improved proton CT imaging using a bismuth germanium oxide scintillator

NASA Astrophysics Data System (ADS)

Tanaka, Sodai; Nishio, Teiji; Tsuneda, Masato; Matsushita, Keiichiro; Kabuki, Shigeto; Uesaka, Mitsuru

2018-02-01

Range uncertainty is among the most formidable challenges associated with the treatment planning of proton therapy. Proton imaging, which includes proton radiography and proton computed tomography (pCT), is a useful verification tool. We have developed a pCT detection system that uses a thick bismuth germanium oxide (BGO) scintillator and a CCD camera. The current method is based on a previous detection system that used a plastic scintillator, and implements improved image processing techniques. In the new system, the scintillation light intensity is integrated along the proton beam path by the BGO scintillator, and acquired as a two-dimensional distribution with the CCD camera. The range of a penetrating proton is derived from the integrated light intensity using a light-to-range conversion table, and a pCT image can be reconstructed. The proton range in the BGO scintillator is shorter than in the plastic scintillator, so errors due to extended proton ranges can be reduced. To demonstrate the feasibility of the pCT system, an experiment was performed using a 70 MeV proton beam created by the AVF930 cyclotron at the National Institute of Radiological Sciences. The accuracy of the light-to-range conversion table, which is susceptible to errors due to its spatial dependence, was investigated, and the errors in the acquired pixel values were less than 0.5 mm. Images of various materials were acquired, and the pixel-value errors were within 3.1%, which represents an improvement over previous results. We also obtained a pCT image of an edible chicken piece, the first of its kind for a biological material, and internal structures approximately one millimeter in size were clearly observed. This pCT imaging system is fast and simple, and based on these findings, we anticipate that we can acquire 200 MeV pCT images using the BGO scintillator system.

Chest CT in children: anesthesia and atelectasis.

PubMed

Newman, Beverley; Krane, Elliot J; Gawande, Rakhee; Holmes, Tyson H; Robinson, Terry E

2014-02-01

There has been an increasing tendency for anesthesiologists to be responsible for providing sedation or anesthesia during chest CT imaging in young children. Anesthesia-related atelectasis noted on chest CT imaging has proven to be a common and troublesome problem, affecting image quality and diagnostic sensitivity. To evaluate the safety and effectiveness of a standardized anesthesia, lung recruitment, controlled-ventilation technique developed at our institution to prevent atelectasis for chest CT imaging in young children. Fifty-six chest CT scans were obtained in 42 children using a research-based intubation, lung recruitment and controlled-ventilation CT scanning protocol. These studies were compared with 70 non-protocolized chest CT scans under anesthesia taken from 18 of the same children, who were tested at different times, without the specific lung recruitment and controlled-ventilation technique. Two radiology readers scored all inspiratory chest CT scans for overall CT quality and atelectasis. Detailed cardiorespiratory parameters were evaluated at baseline, and during recruitment and inspiratory imaging on 21 controlled-ventilation cases and 8 control cases. Significant differences were noted between groups for both quality and atelectasis scores with optimal scoring demonstrated in the controlled-ventilation cases where 70% were rated very good to excellent quality scans compared with only 24% of non-protocol cases. There was no or minimal atelectasis in 48% of the controlled ventilation cases compared to 51% of non-protocol cases with segmental, multisegmental or lobar atelectasis present. No significant difference in cardiorespiratory parameters was found between controlled ventilation and other chest CT cases and no procedure-related adverse events occurred. Controlled-ventilation infant CT scanning under general anesthesia, utilizing intubation and recruitment maneuvers followed by chest CT scans, appears to be a safe and effective method to obtain reliable and reproducible high-quality, motion-free chest CT images in children.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

Accounting for patient size in the optimization of dose and image quality of pelvis cone beam CT protocols on the Varian OBI system

PubMed Central

Moore, Craig S; Horsfield, Carl J; Saunderson, John R; Beavis, Andrew W

2015-01-01

Objective: The purpose of this study was to develop size-based radiotherapy kilovoltage cone beam CT (CBCT) protocols for the pelvis. Methods: Image noise was measured in an elliptical phantom of varying size for a range of exposure factors. Based on a previously defined “small pelvis” reference patient and CBCT protocol, appropriate exposure factors for small, medium, large and extra-large patients were derived which approximate the image noise behaviour observed on a Philips CT scanner (Philips Medical Systems, Best, Netherlands) with automatic exposure control (AEC). Selection criteria, based on maximum tube current–time product per rotation selected during the radiotherapy treatment planning scan, were derived based on an audit of patient size. Results: It has been demonstrated that 110 kVp yields acceptable image noise for reduced patient dose in pelvic CBCT scans of small, medium and large patients, when compared with manufacturer's default settings (125 kVp). Conversely, extra-large patients require increased exposure factors to give acceptable images. 57% of patients in the local population now receive much lower radiation doses, whereas 13% require higher doses (but now yield acceptable images). Conclusion: The implementation of size-based exposure protocols has significantly reduced radiation dose to the majority of patients with no negative impact on image quality. Increased doses are required on the largest patients to give adequate image quality. Advances in knowledge: The development of size-based CBCT protocols that use the planning CT scan (with AEC) to determine which protocol is appropriate ensures adequate image quality whilst minimizing patient radiation dose. PMID:26419892

SU-E-T-416: VMAT Dose Calculations Using Cone Beam CT Images: A Preliminary Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, S; Sehgal, V; Kuo, J

Purpose: Cone beam CT (CBCT) images have been used routinely for patient positioning throughout the treatment course. However, use of CBCT for dose calculation is still investigational. The purpose of this study is to assess the utility of CBCT images for Volumetric Modulated Arc Therapy (VMAT) plan dose calculation. Methods: A CATPHAN 504 phantom (The Phantom Laboratory, Salem, NY) was used to compare the dosimetric and geometric accuracy between conventional CT and CBCT (in both full and half fan modes). Hounsfield units (HU) profiles at different density areas were evaluated. A C shape target that surrounds a central avoidance structuremore » was created and a VMAT plan was generated on the CT images and copied to the CBCT phantom images. Patient studies included three brain patients, and one head and neck (H'N) patient. VMAT plans generated on the patients treatment planning CT was applied to CBCT images obtained during the first treatment. Isodose distributions and dosevolume- histograms (DVHs) were compared. Results: For the phantom study, the HU difference between CT and CBCT is within 100 (maximum 96 HU for Teflon CBCT images in full fan mode). The impact of these differences on the calculated dose distributions was clinically insignificant. In both phantom and patient studies, target DVHs based on CBCT images were in excellent agreement with those based on planning CT images. Mean, Median, near minimum (D98%), and near maximum (D2%) doses agreed within 0-2.5%. A slightly larger discrepancy is observed in the patient studies compared to that seen in the phantom study, (0-1% vs. 0 - 2.5%). Conclusion: CBCT images can be used to accurately predict dosimetric results, without any HU correction. It is feasible to use CBCT to evaluate the actual dose delivered at each fraction. The dosimetric consequences resulting from tumor response and patient geometry changes could be monitored.« less

Ultra-low-dose lung screening CT with model-based iterative reconstruction: an assessment of image quality and lesion conspicuity.

PubMed

Ju, Yun Hye; Lee, Geewon; Lee, Ji Won; Hong, Seung Baek; Suh, Young Ju; Jeong, Yeon Joo

2018-05-01

Background Reducing radiation dose inevitably increases image noise, and thus, it is important in low-dose computed tomography (CT) to maintain image quality and lesion detection performance. Purpose To assess image quality and lesion conspicuity of ultra-low-dose CT with model-based iterative reconstruction (MBIR) and to determine a suitable protocol for lung screening CT. Material and Methods A total of 120 heavy smokers underwent lung screening CT and were randomly and equally assigned to one of five groups: group 1 = 120 kVp, 25 mAs, with FBP reconstruction; group 2 = 120 kVp, 10 mAs, with MBIR; group 3 = 100 kVp, 15 mAs, with MBIR; group 4 = 100 kVp, 10 mAs, with MBIR; and group 5 = 100 kVp, 5 mAs, with MBIR. Two radiologists evaluated intergroup differences with respect to radiation dose, image noise, image quality, and lesion conspicuity using the Kruskal-Wallis test and the Chi-square test. Results Effective doses were 61-87% lower in groups 2-5 than in group 1. Image noises in groups 1 and 5 were significantly higher than in the other groups ( P < 0.001). Overall image quality was best in group 1, but diagnostic acceptability of overall image qualities in groups 1-3 was not significantly different (all P values > 0.05). Lesion conspicuities were similar in groups 1-4, but were significantly poorer in group 5. Conclusion Lung screening CT with MBIR obtained at 100 kVp and 15 mAs enables a ∼60% reduction in radiation dose versus low-dose CT, while maintaining image quality and lesion conspicuity.

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences.

PubMed

Ghose, Soumya; Greer, Peter B; Sun, Jidi; Pichler, Peter; Rivest-Henault, David; Mitra, Jhimli; Richardson, Haylea; Wratten, Chris; Martin, Jarad; Arm, Jameen; Best, Leah; Dowling, Jason A

2017-10-27

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most 'similar' to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be [Formula: see text] (mean  ±  standard deviation) for 39 patients. The 3D Gamma pass rate was [Formula: see text] (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences

NASA Astrophysics Data System (ADS)

Ghose, Soumya; Greer, Peter B.; Sun, Jidi; Pichler, Peter; Rivest-Henault, David; Mitra, Jhimli; Richardson, Haylea; Wratten, Chris; Martin, Jarad; Arm, Jameen; Best, Leah; Dowling, Jason A.

2017-11-01

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most ‘similar’ to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be 0.3%+/-0.9% (mean  ±  standard deviation) for 39 patients. The 3D Gamma pass rate was 99.8+/-0.00 (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

Use of PET and Other Functional Imaging to Guide Target Delineation in Radiation Oncology.

PubMed

Verma, Vivek; Choi, J Isabelle; Sawant, Amit; Gullapalli, Rao P; Chen, Wengen; Alavi, Abass; Simone, Charles B

2018-06-01

Molecular and functional imaging is increasingly being used to guide radiotherapy (RT) management and target delineation. This review summarizes existing data in several disease sites of various functional imaging modalities, chiefly positron emission tomography/computed tomography (PET/CT), with respect to RT target definition and management. For gliomas, differentiation between postoperative changes and viable tumor is discussed, as well as focal dose escalation and reirradiation. Head and neck neoplasms may also benefit from precise PET/CT-based target delineation, especially for cancers of unknown primary; focal dose escalation is also described. In lung cancer, PET/CT can influence coverage of tumor volumes, dose escalation, and adaptive management. For cervical cancer, PET/CT as an adjunct to magnetic resonance imaging planning is discussed, as are dose escalation and delineation of avoidance targets such as the bone marrow. The emerging role of choline-based PET for prostate cancer and its impact on dose escalation is also described. Lastly, given the essential role of PET/CT for target definition in lymphoma, phase III trials of PET-directed management are reviewed, along with novel imaging modalities. Taken together, molecular and functional imaging approaches offer a major step to individualize radiotherapeutic care going forward. Copyright © 2018 Elsevier Inc. All rights reserved.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: experimental assessment of noise performance.

PubMed

Li, Ke; Tang, Jie; Chen, Guang-Hong

2014-04-01

To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo(®), GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a "redder" NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose)(-β) with the component β ≈ 0.25, which violated the classical σ ∝ (dose)(-0.5) power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement. © 2014 American Association of Physicists in Medicine.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ke; Tang, Jie; Chen, Guang-Hong, E-mail: gchen7@wisc.edu

Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD,more » GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. Conclusions: The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement.« less

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images.

PubMed

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-10-01

To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% ± 2.0%. A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images

PubMed Central

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-01-01

Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors’ classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors’ automatic classification and manual segmentation were 91.6% ± 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. PMID:23039675

A practical material decomposition method for x-ray dual spectral computed tomography.

PubMed

Hu, Jingjing; Zhao, Xing

2016-03-17

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

Congenital bronchopulmonary malformation: CT histopathological correlation.

PubMed

Kyncl, Martin; Koci, Martin; Ptackova, Lea; Hornofova, Ludmila; Ondrej, Fabian; Snajdauf, Jiri; Pychova, Marcela

2016-12-01

This study evaluated the accuracy of postnatal computed tomography (CT) imaging in the identification of congenital bronchopulmonary malformation (BPM) in comparison with histopathological analysis. CT scans of prenatally diagnosed BPMs from 24 patients with available histology were analysed retrospectively. The CT images were reviewed blinded to histological findings by two radiologists. Specific diagnosis was assigned based on predetermined criteria. The accuracy of CT was evaluated. The agreement rate in CT diagnosis between two radiologists was 100%. In 75% the lesions were located in the lower lobes. An overlap of 71% in CT and histopathological diagnoses was reached. The least matching diagnosis was type 2 CPAM. Contrast enhanced chest CT is very accurate in characterizing the BPM spectrum and provides important information on lesion type and structure.

2D to 3D fusion of echocardiography and cardiac CT for TAVR and TAVI image guidance.

PubMed

Khalil, Azira; Faisal, Amir; Lai, Khin Wee; Ng, Siew Cheok; Liew, Yih Miin

2017-08-01

This study proposed a registration framework to fuse 2D echocardiography images of the aortic valve with preoperative cardiac CT volume. The registration facilitates the fusion of CT and echocardiography to aid the diagnosis of aortic valve diseases and provide surgical guidance during transcatheter aortic valve replacement and implantation. The image registration framework consists of two major steps: temporal synchronization and spatial registration. Temporal synchronization allows time stamping of echocardiography time series data to identify frames that are at similar cardiac phase as the CT volume. Spatial registration is an intensity-based normalized mutual information method applied with pattern search optimization algorithm to produce an interpolated cardiac CT image that matches the echocardiography image. Our proposed registration method has been applied on the short-axis "Mercedes Benz" sign view of the aortic valve and long-axis parasternal view of echocardiography images from ten patients. The accuracy of our fully automated registration method was 0.81 ± 0.08 and 1.30 ± 0.13 mm in terms of Dice coefficient and Hausdorff distance for short-axis aortic valve view registration, whereas for long-axis parasternal view registration it was 0.79 ± 0.02 and 1.19 ± 0.11 mm, respectively. This accuracy is comparable to gold standard manual registration by expert. There was no significant difference in aortic annulus diameter measurement between the automatically and manually registered CT images. Without the use of optical tracking, we have shown the applicability of this technique for effective fusion of echocardiography with preoperative CT volume to potentially facilitate catheter-based surgery.

Is there a trend in CT scanning scaphoid nonunions for deformity assessment?-A systematic review.

PubMed

Ten Berg, Paul W L; de Roo, Marieke G A; Maas, Mario; Strackee, Simon D

2017-06-01

The effect of scaphoid nonunion deformity on wrist function is uncertain due to the lack of reliable imaging tools. Advanced three-dimensional (3-D) computed tomography (CT)-based imaging techniques may improve deformity assessment by using a mirrored image of the contralateral intact wrist as anatomic reference. The implementation of such techniques depends on the extent to which conventional CT is currently used in standard practice. The purpose of this systematic review of medical literature was to analyze the trend in CT scanning scaphoid nonunions, either unilaterally or bilaterally. Using Medline and Embase databases, two independent reviewers searched for original full-length clinical articles describing series with at least five patients focusing on reconstructive surgery of scaphoid nonunions with bone grafting and/or fixation, from the years 2000-2015. We excluded reports focusing on only nonunions suspected for avascular necrosis and/or treated with vascularized bone grafting, as their workup often includes magnetic resonance imaging. For data analysis, we evaluated the use of CT scans and distinguished between uni- and bilateral, and pre- and postoperative scans. Seventy-seven articles were included of which 16 were published between 2000 and 2005, 19 between 2006 and 2010, and 42 between 2011 and 2015. For these consecutive intervals, the rates of articles describing the use of pre- and postoperative CT scans increased from 13%, to 16%, to 31%, and from 25%, to 32%, to 52%, respectively. Hereof, only two (3%) articles described the use of bilateral CT scans. There is an evident trend in performing unilateral CT scans before and after reconstructive surgery of a scaphoid nonunion. To improve assessment of scaphoid nonunion deformity using 3-D CT-based imaging techniques, we recommend scanning the contralateral wrist as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Incremental value of 99mTc-HYNIC-TOC SPECT/CT over whole-body planar scintigraphy and SPECT in patients with neuroendocrine tumours.

PubMed

Trogrlic, Mate; Težak, Stanko

2017-06-12

The aim of this study was to evaluate the additional value of 99m Tc-HYNIC-TOC SPECT/CT over planar whole-body (WB) scintigraphy and SPECT alone in the detection and accurate localisation of neuroendocrine tumour (NET) lesions. This study included 65 patients with a definitive histological diagnosis of NET prior to scintigraphy. Planar WB scintigraphy, SPECT, and SPECT/CT images were acquired at 4 h post-administration of 670 MBq 99m Tc-HYNIC-TOC. Additional SPECT images at 10 min after tracer administration were also acquired. Clinical and imaging follow-up findings were considered as the reference standards (minimum follow-up period, 15 months). Patient and lesion-based analyses of the efficacies of the imaging modalities were performed. While 38 patients exhibited metastasis of NETs, 27 presented no evidence of metastasis. Upon patient-based analysis, the sensitivity and specificity of SPECT/CT were found to be 88.9 and 79.3 %, respectively. The diagnostic accuracies of WB scintigraphy, 4h-SPECT, and SPECT/CT were 72.3, 73.8, and 84.6 %, respectively. The area under curve (AUC) value for SPECT/CT (0.84) was the highest, followed by those for 4h-SPECT (0.75) and WB scintigraphy (0.74). The accuracy and AUC values of SPECT/CT were significantly better compared to those of WB scintigraphy (p < 0.001), 10 min-SPECT (p < 0.001), and 4 h-SPECT (p = 0.001). The findings of SPECT/CT led to the change in treatment plan of 11 patients (16.9 %). The sensitivity and diagnostic accuracy of SPECT/CT in the evaluation of NET lesions outperforms planar WB imaging or SPECT alone.

Feasibility of MRI-only treatment planning for proton therapy in brain and prostate cancers: Dose calculation accuracy in substitute CT images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koivula, Lauri

Purpose: Magnetic resonance imaging (MRI) is increasingly used for radiotherapy target delineation, image guidance, and treatment response monitoring. Recent studies have shown that an entire external x-ray radiotherapy treatment planning (RTP) workflow for brain tumor or prostate cancer patients based only on MRI reference images is feasible. This study aims to show that a MRI-only based RTP workflow is also feasible for proton beam therapy plans generated in MRI-based substitute computed tomography (sCT) images of the head and the pelvis. Methods: The sCTs were constructed for ten prostate cancer and ten brain tumor patients primarily by transforming the intensity valuesmore » of in-phase MR images to Hounsfield units (HUs) with a dual model HU conversion technique to enable heterogeneous tissue representation. HU conversion models for the pelvis were adopted from previous studies, further extended in this study also for head MRI by generating anatomical site-specific conversion models (a new training data set of ten other brain patients). This study also evaluated two other types of simplified sCT: dual bulk density (for bone and water) and homogeneous (water only). For every clinical case, intensity modulated proton therapy (IMPT) plans robustly optimized in standard planning CTs were calculated in sCT for evaluation, and vice versa. Overall dose agreement was evaluated using dose–volume histogram parameters and 3D gamma criteria. Results: In heterogeneous sCTs, the mean absolute errors in HUs were 34 (soft tissues: 13, bones: 92) and 42 (soft tissues: 9, bones: 97) in the head and in the pelvis, respectively. The maximum absolute dose differences relative to CT in the brain tumor clinical target volume (CTV) were 1.4% for heterogeneous sCT, 1.8% for dual bulk sCT, and 8.9% for homogenous sCT. The corresponding maximum differences in the prostate CTV were 0.6%, 1.2%, and 3.6%, respectively. The percentages of dose points in the head and pelvis passing 1% and 1 mm gamma index criteria were over 91%, 85%, and 38% with heterogeneous, dual bulk, and homogeneous sCTs, respectively. There were no significant changes to gamma index pass rates for IMPT plans first optimized in CT and then calculated in heterogeneous sCT versus IMPT plans first optimized in heterogeneous sCT and then calculated on standard CT. Conclusions: This study demonstrates that proton therapy dose calculations on heterogeneous sCTs are in good agreement with plans generated with standard planning CT. An MRI-only based RTP workflow is feasible in IMPT for brain tumors and prostate cancers.« less

Combined CT-based and image-free navigation systems in TKA reduces postoperative outliers of rotational alignment of the tibial component.

PubMed

Mitsuhashi, Shota; Akamatsu, Yasushi; Kobayashi, Hideo; Kusayama, Yoshihiro; Kumagai, Ken; Saito, Tomoyuki

2018-02-01

Rotational malpositioning of the tibial component can lead to poor functional outcome in TKA. Although various surgical techniques have been proposed, precise rotational placement of the tibial component was difficult to accomplish even with the use of a navigation system. The purpose of this study is to assess whether combined CT-based and image-free navigation systems replicate accurately the rotational alignment of tibial component that was preoperatively planned on CT, compared with the conventional method. We compared the number of outliers for rotational alignment of the tibial component using combined CT-based and image-free navigation systems (navigated group) with those of conventional method (conventional group). Seventy-two TKAs were performed between May 2012 and December 2014. In the navigated group, the anteroposterior axis was prepared using CT-based navigation system and the tibial component was positioned under control of the navigation. In the conventional group, the tibial component was placed with reference to the Akagi line that was determined visually. Fisher's exact probability test was performed to evaluate the results. There was a significant difference between the two groups with regard to the number of outliers: 3 outliers in the navigated group compared with 12 outliers in the conventional group (P < 0.01). We concluded that combined CT-based and image-free navigation systems decreased the number of rotational outliers of tibial component, and was helpful for the replication of the accurate rotational alignment of the tibial component that was preoperatively planned.

Automatic anatomy recognition in whole-body PET/CT images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Huiqian; Udupa, Jayaram K., E-mail: jay@mail.med.upenn.edu; Odhner, Dewey

Purpose: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therapeutic interventions. However, body-wide anatomy recognition in PET/CT is a critical first step for accurately and automatically quantifying disease body-wide, body-region-wise, and organwise. This latter process, however, has remained a challenge due to the lower quality of the anatomic information portrayed in the CT component of this imaging modality and the paucity ofmore » anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., “Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,” Med. Image Anal. 18, 752–771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. Methods: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the process, to bring performance to the level achieved on diagnostic CT and MR images in body-region-wise approaches. The intermodality approach fosters the use of already existing fuzzy models, previously created from diagnostic CT images, on PET/CT and other derived images, thus truly separating the modality-independent object assembly anatomy from modality-specific tissue property portrayal in the image. Results: Key ways of combining the above three basic ideas lead them to 15 different strategies for recognizing objects in PET/CT images. Utilizing 50 diagnostic CT image data sets from the thoracic and abdominal body regions and 16 whole-body PET/CT image data sets, the authors compare the recognition performance among these 15 strategies on 18 objects from the thorax, abdomen, and pelvis in object localization error and size estimation error. Particularly on texture membership images, object localization is within three voxels on whole-body low-dose CT images and 2 voxels on body-region-wise low-dose images of known true locations. Surprisingly, even on direct body-region-wise PET images, localization error within 3 voxels seems possible. Conclusions: The previous body-region-wise approach can be extended to whole-body torso with similar object localization performance. Combined use of image texture and intensity property yields the best object localization accuracy. In both body-region-wise and whole-body approaches, recognition performance on low-dose CT images reaches levels previously achieved on diagnostic CT images. The best object recognition strategy varies among objects; the proposed framework however allows employing a strategy that is optimal for each object.« less

Impact of intravenous contrast used in computed tomography on radiation dose to carotid arteries and thyroid in intensity-modulated radiation therapy planning for nasopharyngeal carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Victor Ho Fun, E-mail: vhflee@hku.hk; Ng, Sherry Chor Yi; Kwong, Dora Lai Wan

The aim of this study was to investigate if intravenous contrast injection affected the radiation doses to carotid arteries and thyroid during intensity-modulated radiation therapy (IMRT) planning for nasopharyngeal carcinoma (NPC). Thirty consecutive patients with NPC underwent plain computed tomography (CT) followed by repeated scanning after contrast injection. Carotid arteries (common, external, internal), thyroid, target volumes, and other organs-at-risk (OARs), as well as IMRT planning, were based on contrast-enhanced CT (CE-CT) images. All these structures and the IMRT plans were then copied and transferred to the non–contrast-enhanced CT (NCE-CT) images, and dose calculation without optimization was performed again. The radiationmore » doses to the carotid arteries and the thyroid based on CE-CT and NCE-CT were then compared. Based on CE-CT, no statistical differences, despite minute numeric decreases, were noted in all dosimetric parameters (minimum, maximum, mean, median, D05, and D01) of the target volumes, the OARs, the carotid arteries, and the thyroid compared with NCE-CT. Our results suggested that compared with NCE-CT planning, CE-CT scanning should be performed during IMRT for better target and OAR delineation, without discernible change in radiation doses.« less

Accuracy and precision of patient positioning for pelvic MR-only radiation therapy using digitally reconstructed radiographs

NASA Astrophysics Data System (ADS)

Kemppainen, R.; Vaara, T.; Joensuu, T.; Kiljunen, T.

2018-03-01

Background and Purpose. Magnetic resonance imaging (MRI) has in recent years emerged as an imaging modality to drive precise contouring of targets and organs at risk in external beam radiation therapy. Moreover, recent advances in MRI enable treatment of cancer without computed tomography (CT) simulation. A commercially available MR-only solution, MRCAT, offers a single-modality approach that provides density information for dose calculation and generation of positioning reference images. We evaluated the accuracy of patient positioning based on MRCAT digitally reconstructed radiographs (DRRs) by comparing to standard CT based workflow. Materials and Methods. Twenty consecutive prostate cancer patients being treated with external beam radiation therapy were included in the study. DRRs were generated for each patient based on the planning CT and MRCAT. The accuracy assessment was performed by manually registering the DRR images to planar kV setup images using bony landmarks. A Bayesian linear mixed effects model was used to separate systematic and random components (inter- and intra-observer variation) in the assessment. In addition, method agreement was assessed using a Bland-Altman analysis. Results. The systematic difference between MRCAT and CT based patient positioning, averaged over the study population, were found to be (mean [95% CI])  -0.49 [-0.85 to  -0.13] mm, 0.11 [-0.33 to  +0.57] mm and  -0.05 [-0.23 to  +0.36] mm in vertical, longitudinal and lateral directions, respectively. The increases in total random uncertainty were estimated to be below 0.5 mm for all directions, when using MR-only workflow instead of CT. Conclusions. The MRCAT pseudo-CT method provides clinically acceptable accuracy and precision for patient positioning for pelvic radiation therapy based on planar DRR images. Furthermore, due to the reduction of geometric uncertainty, compared to dual-modality workflow, the approach is likely to improve the total geometric accuracy of pelvic radiation therapy.

Evaluation of stability of stereotactic space defined by cone-beam CT for the Leksell Gamma Knife Icon.

PubMed

AlDahlawi, Ismail; Prasad, Dheerendra; Podgorsak, Matthew B

2017-05-01

The Gamma Knife Icon comes with an integrated cone-beam CT (CBCT) for image-guided stereotactic treatment deliveries. The CBCT can be used for defining the Leksell stereotactic space using imaging without the need for the traditional invasive frame system, and this allows also for frameless thermoplastic mask stereotactic treatments (single or fractionated) with the Gamma Knife unit. In this study, we used an in-house built marker tool to evaluate the stability of the CBCT-based stereotactic space and its agreement with the standard frame-based stereotactic space. We imaged the tool with a CT indicator box using our CT-simulator at the beginning, middle, and end of the study period (6 weeks) for determining the frame-based stereotactic space. The tool was also scanned with the Icon's CBCT on a daily basis throughout the study period, and the CBCT images were used for determining the CBCT-based stereotactic space. The coordinates of each marker were determined in each CT and CBCT scan using the Leksell GammaPlan treatment planning software. The magnitudes of vector difference between the means of each marker in frame-based and CBCT-based stereotactic space ranged from 0.21 to 0.33 mm, indicating good agreement of CBCT-based and frame-based stereotactic space definition. Scanning 4-month later showed good prolonged stability of the CBCT-based stereotactic space definition. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

The optimal imaging strategy for patients with stable chest pain: a cost-effectiveness analysis.

PubMed

Genders, Tessa S S; Petersen, Steffen E; Pugliese, Francesca; Dastidar, Amardeep G; Fleischmann, Kirsten E; Nieman, Koen; Hunink, M G Myriam

2015-04-07

The optimal imaging strategy for patients with stable chest pain is uncertain. To determine the cost-effectiveness of different imaging strategies for patients with stable chest pain. Microsimulation state-transition model. Published literature. 60-year-old patients with a low to intermediate probability of coronary artery disease (CAD). Lifetime. The United States, the United Kingdom, and the Netherlands. Coronary computed tomography (CT) angiography, cardiac stress magnetic resonance imaging, stress single-photon emission CT, and stress echocardiography. Lifetime costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. The strategy that maximized QALYs and was cost-effective in the United States and the Netherlands began with coronary CT angiography, continued with cardiac stress imaging if angiography found at least 50% stenosis in at least 1 coronary artery, and ended with catheter-based coronary angiography if stress imaging induced ischemia of any severity. For U.K. men, the preferred strategy was optimal medical therapy without catheter-based coronary angiography if coronary CT angiography found only moderate CAD or stress imaging induced only mild ischemia. In these strategies, stress echocardiography was consistently more effective and less expensive than other stress imaging tests. For U.K. women, the optimal strategy was stress echocardiography followed by catheter-based coronary angiography if echocardiography induced mild or moderate ischemia. Results were sensitive to changes in the probability of CAD and assumptions about false-positive results. All cardiac stress imaging tests were assumed to be available. Exercise electrocardiography was included only in a sensitivity analysis. Differences in QALYs among strategies were small. Coronary CT angiography is a cost-effective triage test for 60-year-old patients who have nonacute chest pain and a low to intermediate probability of CAD. Erasmus University Medical Center.

Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends

PubMed Central

Mansoor, Awais; Foster, Brent; Xu, Ziyue; Papadakis, Georgios Z.; Folio, Les R.; Udupa, Jayaram K.; Mollura, Daniel J.

2015-01-01

The computer-based process of identifying the boundaries of lung from surrounding thoracic tissue on computed tomographic (CT) images, which is called segmentation, is a vital first step in radiologic pulmonary image analysis. Many algorithms and software platforms provide image segmentation routines for quantification of lung abnormalities; however, nearly all of the current image segmentation approaches apply well only if the lungs exhibit minimal or no pathologic conditions. When moderate to high amounts of disease or abnormalities with a challenging shape or appearance exist in the lungs, computer-aided detection systems may be highly likely to fail to depict those abnormal regions because of inaccurate segmentation methods. In particular, abnormalities such as pleural effusions, consolidations, and masses often cause inaccurate lung segmentation, which greatly limits the use of image processing methods in clinical and research contexts. In this review, a critical summary of the current methods for lung segmentation on CT images is provided, with special emphasis on the accuracy and performance of the methods in cases with abnormalities and cases with exemplary pathologic findings. The currently available segmentation methods can be divided into five major classes: (a) thresholding-based, (b) region-based, (c) shape-based, (d) neighboring anatomy–guided, and (e) machine learning–based methods. The feasibility of each class and its shortcomings are explained and illustrated with the most common lung abnormalities observed on CT images. In an overview, practical applications and evolving technologies combining the presented approaches for the practicing radiologist are detailed. ©RSNA, 2015 PMID:26172351

Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

NASA Astrophysics Data System (ADS)

Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

Deep learning for staging liver fibrosis on CT: a pilot study.

PubMed

Yasaka, Koichiro; Akai, Hiroyuki; Kunimatsu, Akira; Abe, Osamu; Kiryu, Shigeru

2018-05-14

To investigate whether liver fibrosis can be staged by deep learning techniques based on CT images. This clinical retrospective study, approved by our institutional review board, included 496 CT examinations of 286 patients who underwent dynamic contrast-enhanced CT for evaluations of the liver and for whom histopathological information regarding liver fibrosis stage was available. The 396 portal phase images with age and sex data of patients (F0/F1/F2/F3/F4 = 113/36/56/66/125) were used for training a deep convolutional neural network (DCNN); the data for the other 100 (F0/F1/F2/F3/F4 = 29/9/14/16/32) were utilised for testing the trained network, with the histopathological fibrosis stage used as reference. To improve robustness, additional images for training data were generated by rotating or parallel shifting the images, or adding Gaussian noise. Supervised training was used to minimise the difference between the liver fibrosis stage and the fibrosis score obtained from deep learning based on CT images (F DLCT score) output by the model. Testing data were input into the trained DCNNs to evaluate their performance. The F DLCT scores showed a significant correlation with liver fibrosis stage (Spearman's correlation coefficient = 0.48, p < 0.001). The areas under the receiver operating characteristic curves (with 95% confidence intervals) for diagnosing significant fibrosis (≥ F2), advanced fibrosis (≥ F3) and cirrhosis (F4) by using F DLCT scores were 0.74 (0.64-0.85), 0.76 (0.66-0.85) and 0.73 (0.62-0.84), respectively. Liver fibrosis can be staged by using a deep learning model based on CT images, with moderate performance. • Liver fibrosis can be staged by a deep learning model based on magnified CT images including the liver surface, with moderate performance. • Scores from a trained deep learning model showed moderate correlation with histopathological liver fibrosis staging. • Further improvement are necessary before utilisation in clinical settings.

TH-E-BRF-04: Characterizing the Response of Texture-Based CT Image Features for Quantification of Radiation-Induced Normal Lung Damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krafft, S; Court, L; Briere, T

2014-06-15

Purpose: Radiation induced lung damage (RILD) is an important dose-limiting toxicity for patients treated with radiation therapy. Scoring systems for RILD are subjective and limit our ability to find robust predictors of toxicity. We investigate the dose and time-related response for texture-based lung CT image features that serve as potential quantitative measures of RILD. Methods: Pre- and post-RT diagnostic imaging studies were collected for retrospective analysis of 21 patients treated with photon or proton radiotherapy for NSCLC. Total lung and selected isodose contours (0–5, 5–15, 15–25Gy, etc.) were deformably registered from the treatment planning scan to the pre-RT and availablemore » follow-up CT studies for each patient. A CT image analysis framework was utilized to extract 3698 unique texture-based features (including co-occurrence and run length matrices) for each region of interest defined by the isodose contours and the total lung volume. Linear mixed models were fit to determine the relationship between feature change (relative to pre-RT), planned dose and time post-RT. Results: Seventy-three follow-up CT scans from 21 patients (median: 3 scans/patient) were analyzed to describe CT image feature change. At the p=0.05 level, dose affected feature change in 2706 (73.1%) of the available features. Similarly, time affected feature change in 408 (11.0%) of the available features. Both dose and time were significant predictors of feature change in a total of 231 (6.2%) of the extracted image features. Conclusion: Characterizing the dose and time-related response of a large number of texture-based CT image features is the first step toward identifying objective measures of lung toxicity necessary for assessment and prediction of RILD. There is evidence that numerous features are sensitive to both the radiation dose and time after RT. Beyond characterizing feature response, further investigation is warranted to determine the utility of these features as surrogates of clinically significant lung injury.« less

MO-FG-204-08: Optimization-Based Image Reconstruction From Unevenly Distributed Sparse Projection Views

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Huiqiao; Yang, Yi; Tang, Xiangyang

2015-06-15

Purpose: Optimization-based reconstruction has been proposed and investigated for reconstructing CT images from sparse views, as such the radiation dose can be substantially reduced while maintaining acceptable image quality. The investigation has so far focused on reconstruction from evenly distributed sparse views. Recognizing the clinical situations wherein only unevenly sparse views are available, e.g., image guided radiation therapy, CT perfusion and multi-cycle cardiovascular imaging, we investigate the performance of optimization-based image reconstruction from unevenly sparse projection views in this work. Methods: The investigation is carried out using the FORBILD and an anthropomorphic head phantoms. In the study, 82 views, whichmore » are evenly sorted out from a full (360°) axial CT scan consisting of 984 views, form sub-scan I. Another 82 views are sorted out in a similar manner to form sub-scan II. As such, a CT scan with sparse (164) views at 1:6 ratio are formed. By shifting the two sub-scans relatively in view angulation, a CT scan with unevenly distributed sparse (164) views at 1:6 ratio are formed. An optimization-based method is implemented to reconstruct images from the unevenly distributed views. By taking the FBP reconstruction from the full scan (984 views) as the reference, the root mean square (RMS) between the reference and the optimization-based reconstruction is used to evaluate the performance quantitatively. Results: In visual inspection, the optimization-based method outperforms the FBP substantially in the reconstruction from unevenly distributed, which are quantitatively verified by the RMS gauged globally and in ROIs in both the FORBILD and anthropomorphic head phantoms. The RMS increases with increasing severity in the uneven angular distribution, especially in the case of anthropomorphic head phantom. Conclusion: The optimization-based image reconstruction can save radiation dose up to 12-fold while providing acceptable image quality for advanced clinical applications wherein only unevenly distributed sparse views are available. Research Grants: W81XWH-12-1-0138 (DoD), Sinovision Technologies.« less

Probabilistic sparse matching for robust 3D/3D fusion in minimally invasive surgery.

PubMed

Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan

2015-01-01

Classical surgery is being overtaken by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm computed tomography (CT) and C-arm fluoroscopy are routinely used in clinical practice for intraoperative guidance. However, due to constraints regarding acquisition time and device configuration, intraoperative modalities have limited soft tissue image quality and reliable assessment of the cardiac anatomy typically requires contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a probabilistic sparse matching approach to fuse high-quality preoperative CT images and nongated, noncontrast intraoperative C-arm CT images by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the preoperative CT and mapped to the intraoperative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments on 95 clinical datasets demonstrate that our model-based fusion approach has an average execution time of 1.56 s, while the accuracy of 5.48 mm between the anchor anatomy in both images lies within expert user confidence intervals. In direct comparison with image-to-image registration based on an open-source state-of-the-art medical imaging library and a recently proposed quasi-global, knowledge-driven multi-modal fusion approach for thoracic-abdominal images, our model-based method exhibits superior performance in terms of registration accuracy and robustness with respect to both target anatomy and anchor anatomy alignment errors.

Value of PET/CT 3D visualization of head and neck squamous cell carcinoma extended to mandible.

PubMed

Lopez, R; Gantet, P; Julian, A; Hitzel, A; Herbault-Barres, B; Alshehri, S; Payoux, P

2018-05-01

To study an original 3D visualization of head and neck squamous cell carcinoma extending to the mandible by using [18F]-NaF PET/CT and [18F]-FDG PET/CT imaging along with a new innovative FDG and NaF image analysis using dedicated software. The main interest of the 3D evaluation is to have a better visualization of bone extension in such cancers and that could also avoid unsatisfying surgical treatment later on. A prospective study was carried out from November 2016 to September 2017. Twenty patients with head and neck squamous cell carcinoma extending to the mandible (stage 4 in the UICC classification) underwent [18F]-NaF and [18F]-FDG PET/CT. We compared the delineation of 3D quantification obtained with [18F]-NaF and [18F]-FDG PET/CT. In order to carry out this comparison, a method of visualisation and quantification of PET images was developed. This new approach was based on a process of quantification of radioactive activity within the mandibular bone that objectively defined the significant limits of this activity on PET images and on a 3D visualization. Furthermore, the spatial limits obtained by analysis of the PET/CT 3D images were compared to those obtained by histopathological examination of mandibular resection which confirmed intraosseous extension to the mandible. The [18F]-NaF PET/CT imaging confirmed the mandibular extension in 85% of cases and was not shown in [18F]-FDG PET/CT imaging. The [18F]-NaF PET/CT was significantly more accurate than [18F]-FDG PET/CT in 3D assessment of intraosseous extension of head and neck squamous cell carcinoma. This new 3D information shows the importance in the imaging approach of cancers. All cases of mandibular extension suspected on [18F]-NaF PET/CT imaging were confirmed based on histopathological results as a reference. The [18F]-NaF PET/CT 3D visualization should be included in the pre-treatment workups of head and neck cancers. With the use of a dedicated software which enables objective delineation of radioactive activity within the bone, it gives a very encouraging results. The [18F]-FDG PET/CT appears insufficient to confirm mandibular extension. This new 3D simulation management is expected to avoid under treatment of patients with intraosseous mandibular extension of head and neck cancers. However, there is also a need for a further study that will compare the interest of PET/CT and PET/MRI in this indication. Copyright © 2018 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Estimation of Error in Maximal Intensity Projection-Based Internal Target Volume of Lung Tumors: A Simulation and Comparison Study Using Dynamic Magnetic Resonance Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai Jing; Read, Paul W.; Baisden, Joseph M.

Purpose: To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Methods and Materials: Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA)more » from RedCAM ({epsilon}), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability ({nu}). Results: Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies ({epsilon} = -21.64% {+-} 8.23%) and lung tumor patient studies ({epsilon} = -20.31% {+-} 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly ({epsilon} = -5.13{nu} - 6.71, r{sup 2} = 0.76) with the subjects' respiratory variability. Conclusions: Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.« less

Estimation of error in maximal intensity projection-based internal target volume of lung tumors: a simulation and comparison study using dynamic magnetic resonance imaging.

PubMed

Cai, Jing; Read, Paul W; Baisden, Joseph M; Larner, James M; Benedict, Stanley H; Sheng, Ke

2007-11-01

To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA) from RedCAM (epsilon), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability (nu). Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies (epsilon = -21.64% +/- 8.23%) and lung tumor patient studies (epsilon = -20.31% +/- 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly (epsilon = -5.13nu - 6.71, r(2) = 0.76) with the subjects' respiratory variability. Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.

Prospective feasibility trial of radiotherapy target definition for head and neck cancer using 3-dimensional PET and CT imaging.

PubMed

Scarfone, Christopher; Lavely, William C; Cmelak, Anthony J; Delbeke, Dominique; Martin, William H; Billheimer, Dean; Hallahan, Dennis E

2004-04-01

The aim of this investigation was to evaluate the influence and accuracy of (18)F-FDG PET in target volume definition as a complementary modality to CT for patients with head and neck cancer (HNC) using dedicated PET and CT scanners. Six HNC patients were custom fitted with head and neck and upper body immobilization devices, and conventional radiotherapy CT simulation was performed together with (18)F-FDG PET imaging. Gross target volume (GTV) and pathologic nodal volumes were first defined in the conventional manner based on CT. A segmentation and surface-rendering registration technique was then used to coregister the (18)F-FDG PET and CT planning image datasets. (18)F-FDG PET GTVs were determined and displayed simultaneously with the CT contours. CT GTVs were then modified based on the PET data to form final PET/CT treatment volumes. Five-field intensity-modulated radiation therapy (IMRT) was then used to demonstrate dose targeting to the CT GTV or the PET/CT GTV. One patient was PET-negative after induction chemotherapy. The CT GTV was modified in all remaining patients based on (18)F-FDG PET data. The resulting PET/CT GTV was larger than the original CT volume by an average of 15%. In 5 cases, (18)F-FDG PET identified active lymph nodes that corresponded to lymph nodes contoured on CT. The pathologically enlarged CT lymph nodes were modified to create final lymph node volumes in 3 of 5 cases. In 1 of 6 patients, (18)F-FDG-avid lymph nodes were not identified as pathologic on CT. In 2 of 6 patients, registration of the independently acquired PET and CT data using segmentation and surface rendering resulted in a suboptimal alignment and, therefore, had to be repeated. Radiotherapy planning using IMRT demonstrated the capability of this technique to target anatomic or anatomic/physiologic target volumes. In this manner, metabolically active sites can be intensified to greater daily doses. Inclusion of (18)F-FDG PET data resulted in modified target volumes in radiotherapy planning for HNC. PET and CT data acquired on separate, dedicated scanners may be coregistered for therapy planning; however, dual-acquisition PET/CT systems may be considered to reduce the need for reregistrations. It is possible to use IMRT to target dose to metabolically active sites based on coregistered PET/CT data.

Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images*

PubMed Central

Botta, F; Mairani, A; Hobbs, R F; Vergara Gil, A; Pacilio, M; Parodi, K; Cremonesi, M; Coca Pérez, M A; Di Dia, A; Ferrari, M; Guerriero, F; Battistoni, G; Pedroli, G; Paganelli, G; Torres Aroche, L A; Sgouros, G

2014-01-01

Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 108 primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3–4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image-based dosimetry in nuclear medicine. PMID:24200697

MR-OPERA: A Multicenter/Multivendor Validation of Magnetic Resonance Imaging-Only Prostate Treatment Planning Using Synthetic Computed Tomography Images.

PubMed

Persson, Emilia; Gustafsson, Christian; Nordström, Fredrik; Sohlin, Maja; Gunnlaugsson, Adalsteinn; Petruson, Karin; Rintelä, Niina; Hed, Kristoffer; Blomqvist, Lennart; Zackrisson, Björn; Nyholm, Tufve; Olsson, Lars E; Siversson, Carl; Jonsson, Joakim

2017-11-01

To validate the dosimetric accuracy and clinical robustness of a commercially available software for magnetic resonance (MR) to synthetic computed tomography (sCT) conversion, in an MR imaging-only workflow for 170 prostate cancer patients. The 4 participating centers had MriPlanner (Spectronic Medical), an atlas-based sCT generation software, installed as a cloud-based service. A T2-weighted MR sequence, covering the body contour, was added to the clinical protocol. The MR images were sent from the MR scanner workstation to the MriPlanner platform. The sCT was automatically returned to the treatment planning system. Four MR scanners and 2 magnetic field strengths were included in the study. For each patient, a CT-treatment plan was created and approved according to clinical practice. The sCT was rigidly registered to the CT, and the clinical treatment plan was recalculated on the sCT. The dose distributions from the CT plan and the sCT plan were compared according to a set of dose-volume histogram parameters and gamma evaluation. Treatment techniques included volumetric modulated arc therapy, intensity modulated radiation therapy, and conventional treatment using 2 treatment planning systems and different dose calculation algorithms. The overall (multicenter/multivendor) mean dose differences between sCT and CT dose distributions were below 0.3% for all evaluated organs and targets. Gamma evaluation showed a mean pass rate of 99.12% (0.63%, 1 SD) in the complete body volume and 99.97% (0.13%, 1 SD) in the planning target volume using a 2%/2-mm global gamma criteria. Results of the study show that the sCT conversion method can be used clinically, with minimal differences between sCT and CT dose distributions for target and relevant organs at risk. The small differences seen are consistent between centers, indicating that an MR imaging-only workflow using MriPlanner is robust for a variety of field strengths, vendors, and treatment techniques. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2008-03-01

Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The function to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and Success in login" effective. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

Computer-aided diagnosis of splenic enlargement using wave pattern of spleen in abdominal CT images

NASA Astrophysics Data System (ADS)

Seong, Won; Cho, June-Sik; Noh, Seung-Moo; Park, Jong Won

2006-03-01

It is known that the spleen accompanied by liver cirrhosis is hypertrophied or enlarged. We have examined a wave pattern at the left boundary of spleen on the abdominal CT images having liver cirrhosis, and found that they are different from those on the images having a normal liver. It is noticed that the abdominal CT images of patient with liver cirrhosis shows strong bending in the wave pattern. In the case of normal liver, the images may also have a wave pattern, but its bends are not strong. Therefore, the total waving area of the spleen with liver cirrhosis is found to be greater than that of the spleen with a normal liver. Moreover, we found that the waves of the spleen from the image with liver cirrhosis have the higher degree of circularity compared to the normal liver case. Based on the two observations above, we propose an automatic method to diagnose splenic enlargement by using the wave pattern of the spleen in abdominal CT images. The proposed automatic method improves the diagnostic performance compared with the conventional process based on the size of spleen.

[Magnetic resonance imaging in facial injuries and digital fusion CT/MRI].

PubMed

Kozakiewicz, Marcin; Olszycki, Marek; Arkuszewski, Piotr; Stefańczyk, Ludomir

2006-01-01

Magnetic resonance images [MRI] and their digital fusion with computed tomography [CT] data, observed in patients affected with facial injuries, are presented in this study. The MR imaging of 12 posttraumatic patients was performed in the same plains as their previous CT scans. Evaluation focused on quality of the facial soft tissues depicting, which was unsatisfactory in CT. Using the own "Dental Studio" programme the digital fusion of the both modalities was performed. Pathologic dislocations and injures of facial soft tissues are visualized better in MRI than in CT examination. Especially MRI properly reveals disturbances in intraorbital soft structures. MRI-based assessment is valuable in patients affected with facial soft tissues injuries, especially in case of orbita/sinuses hernia. Fusion CT/MRI scans allows to evaluate simultaneously bone structure and soft tissues of the same region.

Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR)

NASA Astrophysics Data System (ADS)

Wang, Tonghe; Zhu, Lei

2016-09-01

Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an average error of less than 1%.

WHOLE BODY NONRIGID CT-PET REGISTRATION USING WEIGHTED DEMONS.

PubMed

Suh, J W; Kwon, Oh-K; Scheinost, D; Sinusas, A J; Cline, Gary W; Papademetris, X

2011-03-30

We present a new registration method for whole-body rat computed tomography (CT) image and positron emission tomography (PET) images using a weighted demons algorithm. The CT and PET images are acquired in separate scanners at different times and the inherent differences in the imaging protocols produced significant nonrigid changes between the two acquisitions in addition to heterogeneous image characteristics. In this situation, we utilized both the transmission-PET and the emission-PET images in the deformable registration process emphasizing particular regions of the moving transmission-PET image using the emission-PET image. We validated our results with nine rat image sets using M-Hausdorff distance similarity measure. We demonstrate improved performance compared to standard methods such as Demons and normalized mutual information-based non-rigid FFD registration.

Comparison of five segmentation tools for 18F-fluoro-deoxy-glucose-positron emission tomography-based target volume definition in head and neck cancer.

PubMed

Schinagl, Dominic A X; Vogel, Wouter V; Hoffmann, Aswin L; van Dalen, Jorn A; Oyen, Wim J; Kaanders, Johannes H A M

2007-11-15

Target-volume delineation for radiation treatment to the head and neck area traditionally is based on physical examination, computed tomography (CT), and magnetic resonance imaging. Additional molecular imaging with (18)F-fluoro-deoxy-glucose (FDG)-positron emission tomography (PET) may improve definition of the gross tumor volume (GTV). In this study, five methods for tumor delineation on FDG-PET are compared with CT-based delineation. Seventy-eight patients with Stages II-IV squamous cell carcinoma of the head and neck area underwent coregistered CT and FDG-PET. The primary tumor was delineated on CT, and five PET-based GTVs were obtained: visual interpretation, applying an isocontour of a standardized uptake value of 2.5, using a fixed threshold of 40% and 50% of the maximum signal intensity, and applying an adaptive threshold based on the signal-to-background ratio. Absolute GTV volumes were compared, and overlap analyses were performed. The GTV method of applying an isocontour of a standardized uptake value of 2.5 failed to provide successful delineation in 45% of cases. For the other PET delineation methods, volume and shape of the GTV were influenced heavily by the choice of segmentation tool. On average, all threshold-based PET-GTVs were smaller than on CT. Nevertheless, PET frequently detected significant tumor extension outside the GTV delineated on CT (15-34% of PET volume). The choice of segmentation tool for target-volume definition of head and neck cancer based on FDG-PET images is not trivial because it influences both volume and shape of the resulting GTV. With adequate delineation, PET may add significantly to CT- and physical examination-based GTV definition.

Delivery of Nanotethered Therapies to Brain Metastases of Primary Breast Cancer Using a Cellular Trojan Horse

DTIC Science & Technology

2016-12-01

medical images (CT). A critical advantage of a voxel-based code is not only to include tissue heterogeneities but to integrate medically acquired...transport in tissue based on the acquired medical images of an individual patient (CT and MRI) with sufficient accuracy and at accelerated rates for...Human Sciences (HHS) (2015). These latter awards provided Akshay the opportunity to present this research at the IEEE Medical Imaging (NSS/MIC 2014) and

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

NASA Astrophysics Data System (ADS)

Laguda, Edcer Jerecho

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient's medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method. Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated. Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated. Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Mutual-information-based registration for ultrasound and CT datasets

NASA Astrophysics Data System (ADS)

Firle, Evelyn A.; Wesarg, Stefan; Dold, Christian

2004-05-01

In many applications for minimal invasive surgery the acquisition of intra-operative medical images is helpful if not absolutely necessary. Especially for Brachytherapy imaging is critically important to the safe delivery of the therapy. Modern computed tomography (CT) and magnetic resonance (MR) scanners allow minimal invasive procedures to be performed under direct imaging guidance. However, conventional scanners do not have real-time imaging capability and are expensive technologies requiring a special facility. Ultrasound (U/S) is a much cheaper and one of the most flexible imaging modalities. It can be moved to the application room as required and the physician sees what is happening as it occurs. Nevertheless it may be easier to interpret these 3D intra-operative U/S images if they are used in combination with less noisier preoperative data such as CT. The purpose of our current investigation is to develop a registration tool for automatically combining pre-operative CT volumes with intra-operatively acquired 3D U/S datasets. The applied alignment procedure is based on the information theoretic approach of maximizing the mutual information of two arbitrary datasets from different modalities. Since the CT datasets include a much bigger field of view we introduced a bounding box to narrow down the region of interest within the CT dataset. We conducted a phantom experiment using a CIRS Model 53 U/S Prostate Training Phantom to evaluate the feasibility and accuracy of the proposed method.

Lung cancer mimicking lung abscess formation on CT images.

PubMed

Taira, Naohiro; Kawabata, Tsutomu; Gabe, Atsushi; Ichi, Takaharu; Kushi, Kazuaki; Yohena, Tomofumi; Kawasaki, Hidenori; Yamashiro, Toshimitsu; Ishikawa, Kiyoshi

2014-01-01

Male, 64 FINAL DIAGNOSIS: Lung pleomorphic carcinoma Symptoms: Cough • fever - Clinical Procedure: - Specialty: Oncology. Unusual clinical course. The diagnosis of lung cancer is often made based on computed tomography (CT) image findings if it cannot be confirmed on pathological examinations, such as bronchoscopy. However, the CT image findings of cancerous lesions are similar to those of abscesses.We herein report a case of lung cancer that resembled a lung abscess on CT. We herein describe the case of 64-year-old male who was diagnosed with lung cancer using surgery. In this case, it was quite difficult to distinguish between the lung cancer and a lung abscess on CT images, and a lung abscess was initially suspected due to symptoms, such as fever and coughing, contrast-enhanced CT image findings showing a ring-enhancing mass in the right upper lobe and the patient's laboratory test results. However, a pathological diagnosis of lung cancer was confirmed according to the results of a rapid frozen section biopsy of the lesion. This case suggests that physicians should not suspect both a lung abscesses and malignancy in cases involving masses presenting as ring-enhancing lesions on contrast-enhanced CT.

Registration-based assessment of regional lung function via volumetric CT images of normal subjects vs. severe asthmatics

PubMed Central

Choi, Sanghun; Hoffman, Eric A.; Wenzel, Sally E.; Tawhai, Merryn H.; Yin, Youbing; Castro, Mario

2013-01-01

The purpose of this work was to explore the use of image registration-derived variables associated with computed tomographic (CT) imaging of the lung acquired at multiple volumes. As an evaluation of the utility of such an imaging approach, we explored two groups at the extremes of population ranging from normal subjects to severe asthmatics. A mass-preserving image registration technique was employed to match CT images at total lung capacity (TLC) and functional residual capacity (FRC) for assessment of regional air volume change and lung deformation between the two states. Fourteen normal subjects and thirty severe asthmatics were analyzed via image registration-derived metrics together with their pulmonary function test (PFT) and CT-based air-trapping. Relative to the normal group, the severely asthmatic group demonstrated reduced air volume change (consistent with air trapping) and more isotropic deformation in the basal lung regions while demonstrating increased air volume change associated with increased anisotropic deformation in the apical lung regions. These differences were found despite the fact that both PFT-derived TLC and FRC in the two groups were nearly 100% of predicted values. Data suggest that reduced basal-lung air volume change in severe asthmatics was compensated by increased apical-lung air volume change and that relative increase in apical-lung air volume change in severe asthmatics was accompanied by enhanced anisotropic deformation. These data suggest that CT-based deformation, assessed via inspiration vs. expiration scans, provides a tool for distinguishing differences in lung mechanics when applied to the extreme ends of a population range. PMID:23743399

Inter- and intra-observer variability of radiography and computed tomography for evaluation of Zurich cementless acetabular cup placement ex vivo.

PubMed

Leasure, Jessica O; Peck, Jeffrey N; Villamil, Armando; Fiore, Kara L; Tano, Cheryl A

2016-11-23

To evaluate the inter- and intra-observer variability in measurement of the angle of lateral opening (ALO) and version angle measurement using digital radiography and computed tomography (CT). Each hemipelvis was implanted with a cementless acetabular cup. Ventrodorsal and mediolateral radiographs were made of each pelvis, followed by CT imaging. After removal of the first cup, the pelves were implanted with an acetabular cup in the contralateral acetabulum and imaging was repeated. Three surgeons measured the ALO and version angles three times for each cup from the mediolateral radiographic projection. The same measurements were made using three-dimensional multiplanar reconstructions from CT images. Two anatomical axes were used to measure pelvic inclination in the sagittal plane, resulting in six measurements per cup. Two-way repeated measures analysis of variance evaluated inter- and intra-observer repeatability for radiographic and CT-based measurements. Version angle based on radiographic measurement did not differ within surgeons (p = 0.433), but differed between surgeons (p <0.001). Radiographic measurement of ALO differed within surgeons (p = 0.006) but not between surgeons (p = 0.989). The ALO and version angle measured on CT images did not differ with or between surgeons. Assessment of inter- and intra-observer measurement of ALO and version angle was more reproducible using CT images than conventional mediolateral radiography for a Zurich cementless acetabular cup.

A generic framework to simulate realistic lung, liver and renal pathologies in CT imaging

NASA Astrophysics Data System (ADS)

Solomon, Justin; Samei, Ehsan

2014-11-01

Realistic three-dimensional (3D) mathematical models of subtle lesions are essential for many computed tomography (CT) studies focused on performance evaluation and optimization. In this paper, we develop a generic mathematical framework that describes the 3D size, shape, contrast, and contrast-profile characteristics of a lesion, as well as a method to create lesion models based on CT data of real lesions. Further, we implemented a technique to insert the lesion models into CT images in order to create hybrid CT datasets. This framework was used to create a library of realistic lesion models and corresponding hybrid CT images. The goodness of fit of the models was assessed using the coefficient of determination (R2) and the visual appearance of the hybrid images was assessed with an observer study using images of both real and simulated lesions and receiver operator characteristic (ROC) analysis. The average R2 of the lesion models was 0.80, implying that the models provide a good fit to real lesion data. The area under the ROC curve was 0.55, implying that the observers could not readily distinguish between real and simulated lesions. Therefore, we conclude that the lesion-modeling framework presented in this paper can be used to create realistic lesion models and hybrid CT images. These models could be instrumental in performance evaluation and optimization of novel CT systems.

In vivo tumor-targeted dual-modal fluorescence/CT imaging using a nanoprobe co-loaded with an aggregation-induced emission dye and gold nanoparticles.

PubMed

Zhang, Jimei; Li, Chan; Zhang, Xu; Huo, Shuaidong; Jin, Shubin; An, Fei-Fei; Wang, Xiaodan; Xue, Xiangdong; Okeke, C I; Duan, Guiyun; Guo, Fengguang; Zhang, Xiaohong; Hao, Jifu; Wang, Paul C; Zhang, Jinchao; Liang, Xing-Jie

2015-02-01

As an intensely studied computed tomography (CT) contrast agent, gold nanoparticle has been suggested to be combined with fluorescence imaging modality to offset the low sensitivity of CT. However, the strong quenching of gold nanoparticle on fluorescent dyes requires complicated design and shielding to overcome. Herein, we report a unique nanoprobe (M-NPAPF-Au) co-loading an aggregation-induced emission (AIE) red dye and gold nanoparticles into DSPE-PEG(2000) micelles for dual-modal fluorescence/CT imaging. The nanoprobe was prepared based on a facile method of "one-pot ultrasonic emulsification". Surprisingly, in the micelles system, fluorescence dye (NPAPF) efficiently overcame the strong fluorescence quenching of shielding-free gold nanoparticles and retained the crucial AIE feature. In vivo studies demonstrated the nanoprobe had superior tumor-targeting ability, excellent fluorescence and CT imaging effects. The totality of present studies clearly indicates the significant potential application of M-NPAPF-Au as a dual-modal non-invasive fluorescence/X-ray CT nanoprobe for in vivo tumor-targeted imaging and diagnosis. Copyright © 2014 Elsevier Ltd. All rights reserved.

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, S; Zhang, Y; Ma, J

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinctmore » from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.« less

Relationships between patient size, dose and image noise under automatic tube current modulation systems.

PubMed

Sookpeng, S; Martin, C J; Gentle, D J; Lopez-Gonzalez, M R

2014-03-01

Automatic tube current modulation (ATCM) systems are now used for the majority of CT scans. The principles of ATCM operation are different in CT scanners from different manufacturers. Toshiba and GE scanners base the current modulation on a target noise setting, while Philips and Siemens scanners use reference image and reference mAs concepts respectively. Knowledge of the relationships between patient size, dose and image noise are important for CT patient dose optimisation. In this study, the CT patient doses were surveyed for 14 CT scanners from four different CT scanner manufacturers. The patient cross sectional area, the tube current modulation and the image noise from the CT images were analysed using in-house software. The Toshiba and GE scanner results showed that noise levels are relatively constant but tube currents are dependent on patient size. As a result of this there is a wide range in tube current values across different patient sizes, and doses for large patients are significantly higher in these scanners. In contrast, in the Philips and Siemens scanners, tube currents are less dependent on patient size, the range in tube current is narrower, and the doses for larger patients are not as high. Image noise is more dependent on the patient size.

Dynamic CT myocardial perfusion imaging: performance of 3D semi-automated evaluation software.

PubMed

Ebersberger, Ullrich; Marcus, Roy P; Schoepf, U Joseph; Lo, Gladys G; Wang, Yining; Blanke, Philipp; Geyer, Lucas L; Gray, J Cranston; McQuiston, Andrew D; Cho, Young Jun; Scheuering, Michael; Canstein, Christian; Nikolaou, Konstantin; Hoffmann, Ellen; Bamberg, Fabian

2014-01-01

To evaluate the performance of three-dimensional semi-automated evaluation software for the assessment of myocardial blood flow (MBF) and blood volume (MBV) at dynamic myocardial perfusion computed tomography (CT). Volume-based software relying on marginal space learning and probabilistic boosting tree-based contour fitting was applied to CT myocardial perfusion imaging data of 37 subjects. In addition, all image data were analysed manually and both approaches were compared with SPECT findings. Study endpoints included time of analysis and conventional measures of diagnostic accuracy. Of 592 analysable segments, 42 showed perfusion defects on SPECT. Average analysis times for the manual and software-based approaches were 49.1 ± 11.2 and 16.5 ± 3.7 min respectively (P < 0.01). There was strong agreement between the two measures of interest (MBF, ICC = 0.91, and MBV, ICC = 0.88, both P < 0.01) and no significant difference in MBF/MBV with respect to diagnostic accuracy between the two approaches for both MBF and MBV for manual versus software-based approach; respectively; all comparisons P > 0.05. Three-dimensional semi-automated evaluation of dynamic myocardial perfusion CT data provides similar measures and diagnostic accuracy to manual evaluation, albeit with substantially reduced analysis times. This capability may aid the integration of this test into clinical workflows. • Myocardial perfusion CT is attractive for comprehensive coronary heart disease assessment. • Traditional image analysis methods are cumbersome and time-consuming. • Automated 3D perfusion software shortens analysis times. • Automated 3D perfusion software increases standardisation of myocardial perfusion CT. • Automated, standardised analysis fosters myocardial perfusion CT integration into clinical practice.

Deformable registration of x-ray to MRI for post-implant dosimetry in prostate brachytherapy

NASA Astrophysics Data System (ADS)

Park, Seyoun; Song, Danny Y.; Lee, Junghoon

2016-03-01

Post-implant dosimetric assessment in prostate brachytherapy is typically performed using CT as the standard imaging modality. However, poor soft tissue contrast in CT causes significant variability in target contouring, resulting in incorrect dose calculations for organs of interest. CT-MR fusion-based approach has been advocated taking advantage of the complementary capabilities of CT (seed identification) and MRI (soft tissue visibility), and has proved to provide more accurate dosimetry calculations. However, seed segmentation in CT requires manual review, and the accuracy is limited by the reconstructed voxel resolution. In addition, CT deposits considerable amount of radiation to the patient. In this paper, we propose an X-ray and MRI based post-implant dosimetry approach. Implanted seeds are localized using three X-ray images by solving a combinatorial optimization problem, and the identified seeds are registered to MR images by an intensity-based points-to-volume registration. We pre-process the MR images using geometric and Gaussian filtering. To accommodate potential soft tissue deformation, our registration is performed in two steps, an initial affine transformation and local deformable registration. An evolutionary optimizer in conjunction with a points-to-volume similarity metric is used for the affine registration. Local prostate deformation and seed migration are then adjusted by the deformable registration step with external and internal force constraints. We tested our algorithm on six patient data sets, achieving registration error of (1.2+/-0.8) mm in < 30 sec. Our proposed approach has the potential to be a fast and cost-effective solution for post-implant dosimetry with equivalent accuracy as the CT-MR fusion-based approach.

The Role of 18F-FDG PET/CT Integrated Imaging in Distinguishing Malignant from Benign Pleural Effusion.

PubMed

Sun, Yajuan; Yu, Hongjuan; Ma, Jingquan; Lu, Peiou

2016-01-01

The aim of our study was to evaluate the role of 18F-FDG PET/CT integrated imaging in differentiating malignant from benign pleural effusion. A total of 176 patients with pleural effusion who underwent 18F-FDG PET/CT examination to differentiate malignancy from benignancy were retrospectively researched. The images of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were visually analyzed. The suspected malignant effusion was characterized by the presence of nodular or irregular pleural thickening on CT imaging. Whereas on PET imaging, pleural 18F-FDG uptake higher than mediastinal activity was interpreted as malignant effusion. Images of 18F-FDG PET/CT integrated imaging were interpreted by combining the morphologic feature of pleura on CT imaging with the degree and form of pleural 18F-FDG uptake on PET imaging. One hundred and eight patients had malignant effusion, including 86 with pleural metastasis and 22 with pleural mesothelioma, whereas 68 patients had benign effusion. The sensitivities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging in detecting malignant effusion were 75.0%, 91.7% and 93.5%, respectively, which were 69.8%, 91.9% and 93.0% in distinguishing metastatic effusion. The sensitivity of 18F-FDG PET/CT integrated imaging in detecting malignant effusion was higher than that of CT imaging (p = 0.000). For metastatic effusion, 18F-FDG PET imaging had higher sensitivity (p = 0.000) and better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with CT imaging (Kappa = 0.917 and Kappa = 0.295, respectively). The specificities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were 94.1%, 63.2% and 92.6% in detecting benign effusion. The specificities of CT imaging and 18F-FDG PET/CT integrated imaging were higher than that of 18F-FDG PET imaging (p = 0.000 and p = 0.000, respectively), and CT imaging had better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with 18F-FDG PET imaging (Kappa = 0.881 and Kappa = 0.240, respectively). 18F-FDG PET/CT integrated imaging is a more reliable modality in distinguishing malignant from benign pleural effusion than 18F-FDG PET imaging and CT imaging alone. For image interpretation of 18F-FDG PET/CT integrated imaging, the PET and CT portions play a major diagnostic role in identifying metastatic effusion and benign effusion, respectively.

PET/CT alignment calibration with a non-radioactive phantom and the intrinsic 176Lu radiation of PET detector

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Ma, Tianyu; Wang, Shi; Liu, Yaqiang; Gu, Yu; Dai, Tiantian

2016-11-01

Positron emission tomography/computed tomography (PET/CT) is an important tool for clinical studies and pre-clinical researches which provides both functional and anatomical images. To achieve high quality co-registered PET/CT images, alignment calibration of PET and CT scanner is a critical procedure. The existing methods reported use positron source phantoms imaged both by PET and CT scanner and then derive the transformation matrix from the reconstructed images of the two modalities. In this paper, a novel PET/CT alignment calibration method with a non-radioactive phantom and the intrinsic 176Lu radiation of the PET detector was developed. Firstly, a multi-tungsten-alloy-sphere phantom without positron source was designed and imaged by CT and the PET scanner using intrinsic 176Lu radiation included in LYSO. Secondly, the centroids of the spheres were derived and matched by an automatic program. Lastly, the rotation matrix and the translation vector were calculated by least-square fitting of the centroid data. The proposed method was employed in an animal PET/CT system (InliView-3000) developed in our lab. Experimental results showed that the proposed method achieves high accuracy and is feasible to replace the conventional positron source based methods.

Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography.

PubMed

Müller, Mark; de Sena Oliveira, Ivo; Allner, Sebastian; Ferstl, Simone; Bidola, Pidassa; Mechlem, Korbinian; Fehringer, Andreas; Hehn, Lorenz; Dierolf, Martin; Achterhold, Klaus; Gleich, Bernhard; Hammel, Jörg U; Jahn, Henry; Mayer, Georg; Pfeiffer, Franz

2017-11-21

X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli , a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.

Usage of CT data in biomechanical research

NASA Astrophysics Data System (ADS)

Safonov, Roman A.; Golyadkina, Anastasiya A.; Kirillova, Irina V.; Kossovich, Leonid Y.

2017-02-01

Object of study: The investigation is focused on development of personalized medicine. The determination of mechanical properties of bone tissues based on in vivo data was considered. Methods: CT, MRI, natural experiments on versatile test machine Instron 5944, numerical experiments using Python programs. Results: The medical diagnostics methods, which allows determination of mechanical properties of bone tissues based on in vivo data. The series of experiments to define the values of mechanical parameters of bone tissues. For one and the same sample, computed tomography (CT), magnetic resonance imaging (MRI), ultrasonic investigations and mechanical experiments on single-column test machine Instron 5944 were carried out. The computer program for comparison of CT and MRI images was created. The grayscale values in the same points of the samples were determined on both CT and MRI images. The Haunsfield grayscale values were used to determine rigidity (Young module) and tensile strength of the samples. The obtained data was compared to natural experiments results for verification.

Evaluation of dosimetry and image of very low-dose computed tomography attenuation correction for pediatric positron emission tomography/computed tomography: phantom study

NASA Astrophysics Data System (ADS)

Bahn, Y. K.; Park, H. H.; Lee, C. H.; Kim, H. S.; Lyu, K. Y.; Dong, K. R.; Chung, W. K.; Cho, J. H.

2014-04-01

In this study, phantom was used to evaluate attenuation correction computed tomography (CT) dose and image in case of pediatric positron emission tomography (PET)/CT scan. Three PET/CT scanners were used along with acryl phantom in the size for infant and ion-chamber dosimeter. The CT image acquisition conditions were changed from 10 to 20, 40, 80, 100 and 160 mA and from 80 to 100, 120 and 140 kVp, which aimed at evaluating penetrate dose and computed tomography dose indexvolume (CTDIvol) value. And NEMA PET Phantom™ was used to obtain PET image under the same CT conditions in order to evaluate each attenuation-corrected PET image based on standard uptake value (SUV) value and signal-to-noise ratio (SNR). In general, the penetrate dose was reduced by around 92% under the minimum CT conditions (80 kVp and 10 mA) with the decrease in CTDIvol value by around 88%, compared with the pediatric abdomen CT conditions (100 kVp and 100 mA). The PET image with its attenuation corrected according to each CT condition showed no change in SUV value and no influence on the SNR. In conclusion, if the minimum dose CT that is properly applied to body of pediatric patient is corrected for attenuation to ensure that the effective dose is reduced by around 90% or more compared with that for adult patient, this will be useful to reduce radiation exposure level.

The application of positron emission tomography/computed tomography in radiation treatment planning: effect on gross target volume definition and treatment management.

PubMed

Iğdem, S; Alço, G; Ercan, T; Unalan, B; Kara, B; Geceer, G; Akman, C; Zengin, F O; Atilla, S; Okkan, S

2010-04-01

To analyse the effect of the use of molecular imaging on gross target volume (GTV) definition and treatment management. Fifty patients with various solid tumours who underwent positron emission tomography (PET)/computed tomography (CT) simulation for radiotherapy planning from 2006 to 2008 were enrolled in this study. First, F-18 fluorodeoxyglucose (FDG)-PET and CT scans of the treatment site in the treatment position and then a whole body scan were carried out with a dedicated PET/CT scanner and fused thereafter. FDG-avid primary tumour and lymph nodes were included into the GTV. A multidisciplinary team defined the target volume, and contouring was carried out by a radiation oncologist using visual methods. To compare the PET/CT-based volumes with CT-based volumes, contours were drawn on CT-only data with the help of site-specific radiologists who were blind to the PET/CT results after a median time of 7 months. In general, our PET/CT volumes were larger than our CT-based volumes. This difference was significant in patients with head and neck cancers. Major changes (> or =25%) in GTV delineation were observed in 44% of patients. In 16% of cases, PET/CT detected incidental second primaries and metastatic disease, changing the treatment strategy from curative to palliative. Integrating functional imaging with FDG-PET/CT into the radiotherapy planning process resulted in major changes in a significant proportion of our patients. An interdisciplinary approach between imaging and radiation oncology departments is essential in defining the target volumes. Copyright 2010 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Zero cylinder coordinate system approach to image reconstruction in fan beam ICT

NASA Astrophysics Data System (ADS)

Yan, Yan-Chun; Xian, Wu; Hall, Ernest L.

1992-11-01

The state-of-the-art of the transform algorithms has allowed the newest versions to produce excellent and efficient reconstructed images in most applications, especially in medical CT and industrial CT etc. Based on the Zero Cylinder Coordinate system (ZCC) presented in this paper, a new transform algorithm of image reconstruction in fan beam industrial CT is suggested. It greatly reduces the amount of computation of the backprojection, which requires only two INC instructions to calculate the weighted factor and the subcoordinate. A new backprojector is designed, which simplifies its assembly-line mechanism based on the ZCC method. Finally, a simulation results on microcomputer is given out, which proves this method is effective and practical.

Quantification of confounding factors in MRI-based dose calculations as applied to prostate IMRT

NASA Astrophysics Data System (ADS)

Maspero, Matteo; Seevinck, Peter R.; Schubert, Gerald; Hoesl, Michaela A. U.; van Asselen, Bram; Viergever, Max A.; Lagendijk, Jan J. W.; Meijer, Gert J.; van den Berg, Cornelis A. T.

2017-02-01

Magnetic resonance (MR)-only radiotherapy treatment planning requires pseudo-CT (pCT) images to enable MR-based dose calculations. To verify the accuracy of MR-based dose calculations, institutions interested in introducing MR-only planning will have to compare pCT-based and computer tomography (CT)-based dose calculations. However, interpreting such comparison studies may be challenging, since potential differences arise from a range of confounding factors which are not necessarily specific to MR-only planning. Therefore, the aim of this study is to identify and quantify the contribution of factors confounding dosimetric accuracy estimation in comparison studies between CT and pCT. The following factors were distinguished: set-up and positioning differences between imaging sessions, MR-related geometric inaccuracy, pCT generation, use of specific calibration curves to convert pCT into electron density information, and registration errors. The study comprised fourteen prostate cancer patients who underwent CT/MRI-based treatment planning. To enable pCT generation, a commercial solution (MRCAT, Philips Healthcare, Vantaa, Finland) was adopted. IMRT plans were calculated on CT (gold standard) and pCTs. Dose difference maps in a high dose region (CTV) and in the body volume were evaluated, and the contribution to dose errors of possible confounding factors was individually quantified. We found that the largest confounding factor leading to dose difference was the use of different calibration curves to convert pCT and CT into electron density (0.7%). The second largest factor was the pCT generation which resulted in pCT stratified into a fixed number of tissue classes (0.16%). Inter-scan differences due to patient repositioning, MR-related geometric inaccuracy, and registration errors did not significantly contribute to dose differences (0.01%). The proposed approach successfully identified and quantified the factors confounding accurate MRI-based dose calculation in the prostate. This study will be valuable for institutions interested in introducing MR-only dose planning in their clinical practice.

Plaque imaging with CT—a comprehensive review on coronary CT angiography based risk assessment

PubMed Central

Kolossváry, Márton; Szilveszter, Bálint; Merkely, Béla

2017-01-01

CT based technologies have evolved considerably in recent years. Coronary CT angiography (CTA) provides robust assessment of coronary artery disease (CAD). Early coronary CTA imaging—as a gate-keeper of invasive angiography—has focused on the presence of obstructive stenosis. Coronary CTA is currently the only non-invasive imaging modality for the evaluation of non-obstructive CAD, which has been shown to contribute to adverse cardiac events. Importantly, improved spatial resolution of CT scanners and novel image reconstruction algorithms enable the quantification and characterization of atherosclerotic plaques. State-of-the-art CT imaging can therefore reliably assess the extent of CAD and differentiate between various plaque features. Recent studies have demonstrated the incremental prognostic value of adverse plaque features over luminal stenosis. Comprehensive coronary plaque assessment holds potential to significantly improve individual risk assessment incorporating adverse plaque characteristics, the extent and severity of atherosclerotic plaque burden. As a result, several coronary CTA based composite risk scores have been proposed recently to determine patients at high risk for adverse events. Coronary CTA became a promising modality for the evaluation of functional significance of coronary lesions using CT derived fractional flow reserve (FFR-CT) and/or rest/dynamic myocardial CT perfusion. This could lead to substantial reduction in unnecessary invasive catheterization procedures and provide information on ischemic burden of CAD. Discordance between the degree of stenosis and ischemia has been recognized in clinical landmark trials using invasive FFR. Both lesion stenosis and composition are possibly related to myocardial ischemia. The evaluation of lesion-specific ischemia using combined functional and morphological plaque information could ultimately improve the diagnostic performance of CTA and thus patient care. In this review we aimed to summarize current evidence on comprehensive coronary artery plaque assessment using coronary CTA. PMID:29255692

Classification algorithm of lung lobe for lung disease cases based on multislice CT images

NASA Astrophysics Data System (ADS)

Matsuhiro, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Mishima, M.; Ohmatsu, H.; Tsuchida, T.; Eguchi, K.; Kaneko, M.; Moriyama, N.

2011-03-01

With the development of multi-slice CT technology, to obtain an accurate 3D image of lung field in a short time is possible. To support that, a lot of image processing methods need to be developed. In clinical setting for diagnosis of lung cancer, it is important to study and analyse lung structure. Therefore, classification of lung lobe provides useful information for lung cancer analysis. In this report, we describe algorithm which classify lungs into lung lobes for lung disease cases from multi-slice CT images. The classification algorithm of lung lobes is efficiently carried out using information of lung blood vessel, bronchus, and interlobar fissure. Applying the classification algorithms to multi-slice CT images of 20 normal cases and 5 lung disease cases, we demonstrate the usefulness of the proposed algorithms.

Feasibility of spectral CT imaging for the detection of liver lesions with gold-based contrast agents - A simulation study.

PubMed

Müllner, Marie; Schlattl, Helmut; Hoeschen, Christoph; Dietrich, Olaf

2015-12-01

To demonstrate the feasibility of gold-specific spectral CT imaging for the detection of liver lesions in humans at low concentrations of gold as targeted contrast agent. A Monte Carlo simulation study of spectral CT imaging with a photon-counting and energy-resolving detector (with 6 energy bins) was performed in a realistic phantom of the human abdomen. The detector energy thresholds were optimized for the detection of gold. The simulation results were reconstructed with the K-edge imaging algorithm; the reconstructed gold-specific images were filtered and evaluated with respect to signal-to-noise ratio and contrast-to-noise ratio (CNR). The simulations demonstrate the feasibility of spectral CT with CNRs of the specific gold signal between 2.7 and 4.8 after bilateral filtering. Using the optimized bin thresholds increases the CNRs of the lesions by up to 23% compared to bin thresholds described in former studies. Gold is a promising new CT contrast agent for spectral CT in humans; minimum tissue mass fractions of 0.2 wt% of gold are required for sufficient image contrast. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins

PubMed Central

Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

2013-01-01

Purpose To develop a robust tool for quantitative in situ pathology that allows visualization of heterogeneous tissue morphology and segmentation and quantification of image features. Materials and Methods Tissue excised from a genetically engineered mouse model of sarcoma was imaged using a subcellular resolution microendoscope after topical application of a fluorescent anatomical contrast agent: acriflavine. An algorithm based on sparse component analysis (SCA) and the circle transform (CT) was developed for image segmentation and quantification of distinct tissue types. The accuracy of our approach was quantified through simulations of tumor and muscle images. Specifically, tumor, muscle, and tumor+muscle tissue images were simulated because these tissue types were most commonly observed in sarcoma margins. Simulations were based on tissue characteristics observed in pathology slides. The potential clinical utility of our approach was evaluated by imaging excised margins and the tumor bed in a cohort of mice after surgical resection of sarcoma. Results Simulation experiments revealed that SCA+CT achieved the lowest errors for larger nuclear sizes and for higher contrast ratios (nuclei intensity/background intensity). For imaging of tumor margins, SCA+CT effectively isolated nuclei from tumor, muscle, adipose, and tumor+muscle tissue types. Differences in density were correctly identified with SCA+CT in a cohort of ex vivo and in vivo images, thus illustrating the diagnostic potential of our approach. Conclusion The combination of a subcellular-resolution microendoscope, acriflavine staining, and SCA+CT can be used to accurately isolate nuclei and quantify their density in anatomical images of heterogeneous tissue. PMID:23824589

Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins.

PubMed

Mueller, Jenna L; Harmany, Zachary T; Mito, Jeffrey K; Kennedy, Stephanie A; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G; Willett, Rebecca M; Brown, J Quincy; Ramanujam, Nimmi

2013-01-01

To develop a robust tool for quantitative in situ pathology that allows visualization of heterogeneous tissue morphology and segmentation and quantification of image features. TISSUE EXCISED FROM A GENETICALLY ENGINEERED MOUSE MODEL OF SARCOMA WAS IMAGED USING A SUBCELLULAR RESOLUTION MICROENDOSCOPE AFTER TOPICAL APPLICATION OF A FLUORESCENT ANATOMICAL CONTRAST AGENT: acriflavine. An algorithm based on sparse component analysis (SCA) and the circle transform (CT) was developed for image segmentation and quantification of distinct tissue types. The accuracy of our approach was quantified through simulations of tumor and muscle images. Specifically, tumor, muscle, and tumor+muscle tissue images were simulated because these tissue types were most commonly observed in sarcoma margins. Simulations were based on tissue characteristics observed in pathology slides. The potential clinical utility of our approach was evaluated by imaging excised margins and the tumor bed in a cohort of mice after surgical resection of sarcoma. Simulation experiments revealed that SCA+CT achieved the lowest errors for larger nuclear sizes and for higher contrast ratios (nuclei intensity/background intensity). For imaging of tumor margins, SCA+CT effectively isolated nuclei from tumor, muscle, adipose, and tumor+muscle tissue types. Differences in density were correctly identified with SCA+CT in a cohort of ex vivo and in vivo images, thus illustrating the diagnostic potential of our approach. The combination of a subcellular-resolution microendoscope, acriflavine staining, and SCA+CT can be used to accurately isolate nuclei and quantify their density in anatomical images of heterogeneous tissue.

Information granules in image histogram analysis.

PubMed

Wieclawek, Wojciech

2018-04-01

A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

Micro-CT of rodents: state-of-the-art and future perspectives

PubMed Central

Clark, D. P.; Badea, C. T.

2014-01-01

Micron-scale computed tomography (micro-CT) is an essential tool for phenotyping and for elucidating diseases and their therapies. This work is focused on preclinical micro-CT imaging, reviewing relevant principles, technologies, and applications. Commonly, micro-CT provides high-resolution anatomic information, either on its own or in conjunction with lower-resolution functional imaging modalities such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). More recently, however, advanced applications of micro-CT produce functional information by translating clinical applications to model systems (e.g. measuring cardiac functional metrics) and by pioneering new ones (e.g. measuring tumor vascular permeability with nanoparticle contrast agents). The primary limitations of micro-CT imaging are the associated radiation dose and relatively poor soft tissue contrast. We review several image reconstruction strategies based on iterative, statistical, and gradient sparsity regularization, demonstrating that high image quality is achievable with low radiation dose given ever more powerful computational resources. We also review two contrast mechanisms under intense development. The first is spectral contrast for quantitative material discrimination in combination with passive or actively targeted nanoparticle contrast agents. The second is phase contrast which measures refraction in biological tissues for improved contrast and potentially reduced radiation dose relative to standard absorption imaging. These technological advancements promise to develop micro-CT into a commonplace, functional and even molecular imaging modality. PMID:24974176

Dual-energy micro-CT imaging of pulmonary airway obstruction: correlation with micro-SPECT

NASA Astrophysics Data System (ADS)

Badea, C. T.; Befera, N.; Clark, D.; Qi, Y.; Johnson, G. A.

2014-03-01

To match recent clinical dual energy (DE) CT studies focusing on the lung, similar developments for DE micro-CT of the rodent lung are required. Our group has been actively engaged in designing pulmonary gating techniques for micro- CT, and has also introduced the first DE micro-CT imaging method of the rodent lung. The aim of this study was to assess the feasibility of DE micro-CT imaging for the evaluation of airway obstruction in mice, and to compare the method with micro single photon emission computed tomography (micro-SPECT) using technetium-99m labeled macroaggregated albumin (99mTc-MAA). The results suggest that the induced pulmonary airway obstruction causes either atelectasis, or air-trapping similar to asthma or chronic bronchitis. Atelectasis could only be detected at early time points in DE micro-CT images, and is associated with a large increase in blood fraction and decrease in air fraction. Air trapping had an opposite effect with larger air fraction and decreased blood fraction shown by DE micro-CT. The decrease in perfusion to the hypoventilated lung (hypoxic vasoconstriction) is also seen in micro-SPECT. The proposed DE micro-CT technique for imaging localized airway obstruction performed well in our evaluation, and provides a higher resolution compared to micro-SPECT. Both DE micro-CT and micro-SPECT provide critical, quantitative lung biomarkers for image-based anatomical and functional information in the small animal. The methods are readily linked to clinical methods allowing direct comparison of preclinical and clinical results.

Computer-aided diagnosis workstation and telemedicine network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kakinuma, Ryutaru; Moriyama, Noriyuki

2009-02-01

Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. Moreover, the doctor who diagnoses a medical image is insufficient in Japan. To overcome these problems, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The functions to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and "Success in login" effective. As a result, patients' private information is protected. We can share the screen of Web medical image conference system from two or more web conference terminals at the same time. An opinion can be exchanged mutually by using a camera and a microphone that are connected with workstation. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer.

PubMed

Wang, Hesheng; Chandarana, Hersh; Block, Kai Tobias; Vahle, Thomas; Fenchel, Matthias; Das, Indra J

2017-06-26

Interest in MR-only treatment planning for radiation therapy is growing rapidly with the emergence of integrated MRI/linear accelerator technology. The purpose of this study was to evaluate the feasibility of using synthetic CT images generated from conventional Dixon-based MRI scans for radiation treatment planning of lung cancer. Eleven patients who underwent whole-body PET/MR imaging following a PET/CT exam were randomly selected from an ongoing prospective IRB-approved study. Attenuation maps derived from the Dixon MR Images and atlas-based method was used to create CT data (synCT). Treatment planning for radiation treatment of lung cancer was optimized on the synCT and subsequently copied to the registered CT (planCT) for dose calculation. Planning target volumes (PTVs) with three sizes and four different locations in the lung were planned for irradiation. The dose-volume metrics comparison and 3D gamma analysis were performed to assess agreement between the synCT and CT calculated dose distributions. Mean differences between PTV doses on synCT and CT across all the plans were -0.1% ± 0.4%, 0.1% ± 0.5%, and 0.4% ± 0.5% for D95, D98 and D100, respectively. Difference in dose between the two datasets for organs at risk (OARs) had average differences of -0.14 ± 0.07 Gy, 0.0% ± 0.1%, and -0.1% ± 0.2% for maximum spinal cord, lung V20, and heart V40 respectively. In patient groups based on tumor size and location, no significant differences were observed in the PTV and OARs dose-volume metrics (p > 0.05), except for the maximum spinal-cord dose when the target volumes were located at the lung apex (p = 0.001). Gamma analysis revealed a pass rate of 99.3% ± 1.1% for 2%/2 mm (dose difference/distance to agreement) acceptance criteria in every plan. The synCT generated from Dixon-based MRI allows for dose calculation of comparable accuracy to the standard CT for lung cancer treatment planning. The dosimetric agreement between synCT and CT calculated doses warrants further development of a MR-only workflow for radiotherapy of lung cancer.

Female pelvic synthetic CT generation based on joint intensity and shape analysis

NASA Astrophysics Data System (ADS)

Liu, Lianli; Jolly, Shruti; Cao, Yue; Vineberg, Karen; Fessler, Jeffrey A.; Balter, James M.

2017-04-01

Using MRI for radiotherapy treatment planning and image guidance is appealing as it provides superior soft tissue information over CT scans and avoids possible systematic errors introduced by aligning MR to CT images. This study presents a method that generates Synthetic CT (MRCT) volumes by performing probabilistic tissue classification of voxels from MRI data using a single imaging sequence (T1 Dixon). The intensity overlap between different tissues on MR images, a major challenge for voxel-based MRCT generation methods, is addressed by adding bone shape information to an intensity-based classification scheme. A simple pelvic bone shape model, built from principal component analysis of pelvis shape from 30 CT image volumes, is fitted to the MR volumes. The shape model generates a rough bone mask that excludes air and covers bone along with some surrounding soft tissues. Air regions are identified and masked out from the tissue classification process by intensity thresholding outside the bone mask. A regularization term is added to the fuzzy c-means classification scheme that constrains voxels outside the bone mask from being assigned memberships in the bone class. MRCT image volumes are generated by multiplying the probability of each voxel being represented in each class with assigned attenuation values of the corresponding class and summing the result across all classes. The MRCT images presented intensity distributions similar to CT images with a mean absolute error of 13.7 HU for muscle, 15.9 HU for fat, 49.1 HU for intra-pelvic soft tissues, 129.1 HU for marrow and 274.4 HU for bony tissues across 9 patients. Volumetric modulated arc therapy (VMAT) plans were optimized using MRCT-derived electron densities, and doses were recalculated using corresponding CT-derived density grids. Dose differences to planning target volumes were small with mean/standard deviation of 0.21/0.42 Gy for D0.5cc and 0.29/0.33 Gy for D99%. The results demonstrate the accuracy of the method and its potential in supporting MRI only radiotherapy treatment planning.

Material decomposition images generated from spectral CT: detectability of urinary calculi and influencing factors.

PubMed

Lv, Peijie; Zhang, Yonggao; Liu, Jie; Ji, Lijuan; Chen, Yan; Gao, Jianbo

2014-01-01

To evaluate the detectability of urinary calculi on material decomposition (MD) images generated from spectral computed tomography (CT) and identify the influencing factors. Forty-six patients were examined with true nonenhanced (TNE) CT and spectral CT urography in the excretory phase. The contrast medium was removed from excretory phase images using water-based (WB) and calcium-based (CaB) MD analysis. The sensitivity for detection on WB and CaB images was evaluated using TNE results as the reference standard. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) on MD images were evaluated. Using logistic regression, the influences of image noise, attenuation, stone size, and patient's body mass index (BMI) were assessed. Threshold values with maximal sensitivity and specificity were calculated by means of receiver operating characteristic analyses. One hundred thirty-six calculi were detected on TNE images; 98 calculi were identified on WB images (sensitivity, 72.06%) and 101 calculi on CaB images (sensitivity, 74.26%). Sensitivities were 76.92% for the 3-5-mm stones and 84.51% for the 5-mm or larger stones on both WB and CaB images but reduced to 46.15% on WB images and 53.85% on CaB images for small calculi (<3 mm). Compared to WB images, CaB images showed lower image noise, higher SNR but similar CNR. Larger stone sizes (both >2.71 mm on WB and CaB) and greater CT attenuation (>280 Hounsfield units [HU] on WB, >215 HU on CaB) of the urinary stones were significantly associated with higher stone visibility rates on WB and CaB images (P ≤ .003). Image noise and BMI showed no impact on the stone detection. MD images generated from spectral CT showed good reliability for the detection of large (>2.71 mm) and hyperattenuating (>280 HU on WB, >215 HU on CaB) urinary calculi. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, L; Tan, S; Lu, W

Purpose: PET images are usually blurred due to the finite spatial resolution, while CT images suffer from low contrast. Segment a tumor from either a single PET or CT image is thus challenging. To make full use of the complementary information between PET and CT, we propose a novel variational method for simultaneous PET image restoration and PET/CT images co-segmentation. Methods: The proposed model was constructed based on the Γ-convergence approximation of Mumford-Shah (MS) segmentation model for PET/CT co-segmentation. Moreover, a PET de-blur process was integrated into the MS model to improve the segmentation accuracy. An interaction edge constraint termmore » over the two modalities were specially designed to share the complementary information. The energy functional was iteratively optimized using an alternate minimization (AM) algorithm. The performance of the proposed method was validated on ten lung cancer cases and five esophageal cancer cases. The ground truth were manually delineated by an experienced radiation oncologist using the complementary visual features of PET and CT. The segmentation accuracy was evaluated by Dice similarity index (DSI) and volume error (VE). Results: The proposed method achieved an expected restoration result for PET image and satisfactory segmentation results for both PET and CT images. For lung cancer dataset, the average DSI (0.72) increased by 0.17 and 0.40 than single PET and CT segmentation. For esophageal cancer dataset, the average DSI (0.85) increased by 0.07 and 0.43 than single PET and CT segmentation. Conclusion: The proposed method took full advantage of the complementary information from PET and CT images. This work was supported in part by the National Cancer Institute Grants R01CA172638. Shan Tan and Laquan Li were supported in part by the National Natural Science Foundation of China, under Grant Nos. 60971112 and 61375018.« less

Coregistered FDG PET/CT-based textural characterization of head and neck cancer for radiation treatment planning.

PubMed

Yu, Huan; Caldwell, Curtis; Mah, Katherine; Mozeg, Daniel

2009-03-01

Coregistered fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT) has shown potential to improve the accuracy of radiation targeting of head and neck cancer (HNC) when compared to the use of CT simulation alone. The objective of this study was to identify textural features useful in distinguishing tumor from normal tissue in head and neck via quantitative texture analysis of coregistered 18F-FDG PET and CT images. Abnormal and typical normal tissues were manually segmented from PET/CT images of 20 patients with HNC and 20 patients with lung cancer. Texture features including some derived from spatial grey-level dependence matrices (SGLDM) and neighborhood gray-tone-difference matrices (NGTDM) were selected for characterization of these segmented regions of interest (ROIs). Both K nearest neighbors (KNNs) and decision tree (DT)-based KNN classifiers were employed to discriminate images of abnormal and normal tissues. The area under the curve (AZ) of receiver operating characteristics (ROC) was used to evaluate the discrimination performance of features in comparison to an expert observer. The leave-one-out and bootstrap techniques were used to validate the results. The AZ of DT-based KNN classifier was 0.95. Sensitivity and specificity for normal and abnormal tissue classification were 89% and 99%, respectively. In summary, NGTDM features such as PET Coarseness, PET Contrast, and CT Coarseness extracted from FDG PET/CT images provided good discrimination performance. The clinical use of such features may lead to improvement in the accuracy of radiation targeting of HNC.

Improving the quality of reconstructed X-ray CT images of polymer gel dosimeters: zero-scan coupled with adaptive mean filtering.

PubMed

Kakakhel, M B; Jirasek, A; Johnston, H; Kairn, T; Trapp, J V

2017-03-01

This study evaluated the feasibility of combining the 'zero-scan' (ZS) X-ray computed tomography (CT) based polymer gel dosimeter (PGD) readout with adaptive mean (AM) filtering for improving the signal to noise ratio (SNR), and to compare these results with available average scan (AS) X-ray CT readout techniques. NIPAM PGD were manufactured, irradiated with 6 MV photons, CT imaged and processed in Matlab. AM filter for two iterations, with 3 × 3 and 5 × 5 pixels (kernel size), was used in two scenarios (a) the CT images were subjected to AM filtering (pre-processing) and these were further employed to generate AS and ZS gel images, and (b) the AS and ZS images were first reconstructed from the CT images and then AM filtering was carried out (post-processing). SNR was computed in an ROI of 30 × 30 for different pre and post processing cases. Results showed that the ZS technique combined with AM filtering resulted in improved SNR. Using the previously-recommended 25 images for reconstruction the ZS pre-processed protocol can give an increase of 44% and 80% in SNR for 3 × 3 and 5 × 5 kernel sizes respectively. However, post processing using both techniques and filter sizes introduced blur and a reduction in the spatial resolution. Based on this work, it is possible to recommend that the ZS method may be combined with pre-processed AM filtering using appropriate kernel size, to produce a large increase in the SNR of the reconstructed PGD images.

Ventilation/perfusion SPECT or SPECT/CT for lung function imaging in patients with pulmonary emphysema?

PubMed

Froeling, Vera; Heimann, Uwe; Huebner, Ralf-Harto; Kroencke, Thomas J; Maurer, Martin H; Doellinger, Felix; Geisel, Dominik; Hamm, Bernd; Brenner, Winfried; Schreiter, Nils F

2015-07-01

To evaluate the utility of attenuation correction (AC) of V/P SPECT images for patients with pulmonary emphysema. Twenty-one patients (mean age 67.6 years) with pulmonary emphysema who underwent V/P SPECT/CT were included. AC/non-AC V/P SPECT images were compared visually and semiquantitatively. Visual comparison of AC/non-AC images was based on a 5-point likert scale. Semiquantitative comparison assessed absolute counts per lung (aCpLu) and lung lobe (aCpLo) for AC/non-AC images using software-based analysis; percentage counts (PC = (aCpLo/aCpLu) × 100) were calculated. Correlation between AC/non-AC V/P SPECT images was analyzed using Spearman's rho correlation coefficient; differences were tested for significance with the Wilcoxon rank sum test. Visual analysis revealed high conformity for AC and non-AC V/P SPECT images. Semiquantitative analysis of PC in AC/non-AC images had an excellent correlation and showed no significant differences in perfusion (ρ = 0.986) or ventilation (ρ = 0.979, p = 0.809) SPECT/CT images. AC of V/P SPECT images for lung lobe-based function imaging in patients with pulmonary emphysema do not improve visual or semiquantitative image analysis.

Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach.

PubMed

Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J; Stayman, J Webster; Zbijewski, Wojciech; Brock, Kristy K; Daly, Michael J; Chan, Harley; Irish, Jonathan C; Siewerdsen, Jeffrey H

2011-04-01

A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values ("intensity"). A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5 +/- 2.8) mm compared to (3.5 +/- 3.0) mm with rigid registration. A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.

Enhanced CT images by the wavelet transform improving diagnostic accuracy of chest nodules.

PubMed

Guo, Xiuhua; Liu, Xiangye; Wang, Huan; Liang, Zhigang; Wu, Wei; He, Qian; Li, Kuncheng; Wang, Wei

2011-02-01

The objective of this study was to compare the diagnostic accuracy in the interpretation of chest nodules using original CT images versus enhanced CT images based on the wavelet transform. The CT images of 118 patients with cancers and 60 with benign nodules were used in this study. All images were enhanced through an algorithm based on the wavelet transform. Two experienced radiologists interpreted all the images in two reading sessions. The reading sessions were separated by a minimum of 1 month in order to minimize the effect of observer's recall. The Mann-Whitney U nonparametric test was used to analyze the interpretation results between original and enhanced images. The Kruskal-Wallis H nonparametric test of K independent samples was used to investigate the related factors which could affect the diagnostic accuracy of observers. The area under the ROC curves for the original and enhanced images was 0.681 and 0.736, respectively. There is significant difference in diagnosing the malignant nodules between the original and enhanced images (z = 7.122, P < 0.001), whereas there is no significant difference in diagnosing the benign nodules (z = 0.894, P = 0.371). The results showed that there is significant difference between original and enhancement images when the size of nodules was larger than 2 cm (Z = -2.509, P = 0.012, indicating the size of the nodules is a critical evaluating factor of the diagnostic accuracy of observers). This study indicated that the image enhancement based on wavelet transform could improve the diagnostic accuracy of radiologists for the malignant chest nodules.

SU-E-T-504: Usefulness of CT-MR Fusion in Radiotherapy Planning for Prostate Cancer Patient with Bilateral Hip Replacements

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, R.; Giri, Shankar; VA Medical Center at Jackson, Mississippi

2014-06-01

Purpose: Target localization of prostate for Intensity Modulated Radiation Therapy (IMRT) in patients with bilateral hip replacements is difficult due to artifacts in Computed Tomography (CT) images generated from the prostheses high Z materials. In this study, Magnetic Resonance (MR) images fused with CT images are tested as a solution. Methods: CT images of 2.5 mm slice thickness were acquired on a GE Lightspeed scanner with a flat-topped couch for a prostate cancer patient with bilateral hip replacements. T2 weighted images of 5 mm separation were acquired on a MR Scanner. After the MR-CT registration on a radiotherapy treatment planningmore » system (Eclipse, Varian), the target volumes were defined by the radiation oncologists on MR images and then transferred to CT images for planning and dose calculation. The CT Hounsfield Units (HU) was reassigned to zero (as water) for artifacts. The Varian flat panel treatment couch was modeled for dose calculation accuracy with heterogeneity correction. A Volume Matrix Arc Therapy (VMAT) and a seven-field IMRT plans were generated, each avoiding any beam transversing the prostheses; the two plans were compared. The superior VMAT plan was used for treating the patient. In-vivo dosimetry was performed using MOSFET (Best Canada) placed in a surgical tube inserted into the patient rectum during therapy. The measured dose was compared with planned dose for MOSFET location. Results: The registration of MR-CT images and the agreement of target volumes were confirmed by three physicians. VMAT plan was deemed superior to IMRT based on dose to critical nearby structures and overall conformality of target dosing. In-vivo measured dose compared with calculated dose was -4.5% which was likely due to attenuation of the surgical tube surrounding MOSFET. Conclusion: When artifacts are present on planning CT due to bilateral hip prostheses, MR-CT image fusion is a feasible solution for target delineation.« less

SU-E-J-224: Using UTE and T1 Weighted Spin Echo Pulse Sequences for MR-Only Treatment Planning; Phantom Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, H; Fatemi, A; Sahgal, A

Purpose: Investigating a new approach in MRI based treatment planning using the combination of (Ultrashort Echo Time) UTE and T1 weighted spin echo pulse sequences to delineate air, bone and water (soft tissues) in generating pseudo CT images comparable with CT. Methods: A gel phantom containing chicken bones, ping pang balls filled with distilled water and air bubbles, was made. It scanned with MRI using UTE and 2D T1W SE pulse sequences with (in plane resolution= 0.53mm, slice thickness= 2 mm) and CT with (in plane resolution= 0.5 mm and slice thickness= 0.75mm) as a ground truth for geometrical accuracy.more » The UTE and T1W SE images were registered with CT using mutual information registration algorithm provided by Philips Pinnacle treatment planning system. The phantom boundaries were detected using Canny edge detection algorithm for CT, and MR images. The bone, air bubbles and water in ping pong balls were segmented from CT images using threshold 300HU, - 950HU and 0HU, respectively. These tissue inserts were automatically segmented from combined UTE and T1W SE images using edge detection and relative intensity histograms of the phantom. The obtained segmentations of air, bone and water inserts were evaluated with those obtained from CT. Results: Bone and air can be clearly differentiated in UTE images comparable to CT. Combining UTE and T1W SE images successfully segmented the air, bone and water. The maximum segmentation differences from combine MRI images (UTE and T1W SE) and CT are within 1.3 mm, 1.1mm for bone, air, respectively. The geometric distortion of UTE sequence is small less than 1 pixel (0.53 mm) of MR image resolution. Conclusion: Our approach indicates that MRI can be used solely for treatment planning and its quality is comparable with CT.« less

Non-rigid CT/CBCT to CBCT registration for online external beam radiotherapy guidance

NASA Astrophysics Data System (ADS)

Zachiu, Cornel; de Senneville, Baudouin Denis; Tijssen, Rob H. N.; Kotte, Alexis N. T. J.; Houweling, Antonetta C.; Kerkmeijer, Linda G. W.; Lagendijk, Jan J. W.; Moonen, Chrit T. W.; Ries, Mario

2018-01-01

Image-guided external beam radiotherapy (EBRT) allows radiation dose deposition with a high degree of accuracy and precision. Guidance is usually achieved by estimating the displacements, via image registration, between cone beam computed tomography (CBCT) and computed tomography (CT) images acquired at different stages of the therapy. The resulting displacements are then used to reposition the patient such that the location of the tumor at the time of treatment matches its position during planning. Moreover, ongoing research aims to use CBCT-CT image registration for online plan adaptation. However, CBCT images are usually acquired using a small number of x-ray projections and/or low beam intensities. This often leads to the images being subject to low contrast, low signal-to-noise ratio and artifacts, which ends-up hampering the image registration process. Previous studies addressed this by integrating additional image processing steps into the registration procedure. However, these steps are usually designed for particular image acquisition schemes, therefore limiting their use on a case-by-case basis. In the current study we address CT to CBCT and CBCT to CBCT registration by the means of the recently proposed EVolution registration algorithm. Contrary to previous approaches, EVolution does not require the integration of additional image processing steps in the registration scheme. Moreover, the algorithm requires a low number of input parameters, is easily parallelizable and provides an elastic deformation on a point-by-point basis. Results have shown that relative to a pure CT-based registration, the intrinsic artifacts present in typical CBCT images only have a sub-millimeter impact on the accuracy and precision of the estimated deformation. In addition, the algorithm has low computational requirements, which are compatible with online image-based guidance of EBRT treatments.

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2017-03-01

Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.

Effect of image scaling and segmentation in digital rock characterisation

NASA Astrophysics Data System (ADS)

Jones, B. D.; Feng, Y. T.

2016-04-01

Digital material characterisation from microstructural geometry is an emerging field in computer simulation. For permeability characterisation, a variety of studies exist where the lattice Boltzmann method (LBM) has been used in conjunction with computed tomography (CT) imaging to simulate fluid flow through microscopic rock pores. While these previous works show that the technique is applicable, the use of binary image segmentation and the bounceback boundary condition results in a loss of grain surface definition when the modelled geometry is compared to the original CT image. We apply the immersed moving boundary (IMB) condition of Noble and Torczynski as a partial bounceback boundary condition which may be used to better represent the geometric definition provided by a CT image. The IMB condition is validated against published work on idealised porous geometries in both 2D and 3D. Following this, greyscale image segmentation is applied to a CT image of Diemelstadt sandstone. By varying the mapping of CT voxel densities to lattice sites, it is shown that binary image segmentation may underestimate the true permeability of the sample. A CUDA-C-based code, LBM-C, was developed specifically for this work and leverages GPU hardware in order to carry out computations.

Three-dimensional murine airway segmentation in micro-CT images

NASA Astrophysics Data System (ADS)

Shi, Lijun; Thiesse, Jacqueline; McLennan, Geoffrey; Hoffman, Eric A.; Reinhardt, Joseph M.

2007-03-01

Thoracic imaging for small animals has emerged as an important tool for monitoring pulmonary disease progression and therapy response in genetically engineered animals. Micro-CT is becoming the standard thoracic imaging modality in small animal imaging because it can produce high-resolution images of the lung parenchyma, vasculature, and airways. Segmentation, measurement, and visualization of the airway tree is an important step in pulmonary image analysis. However, manual analysis of the airway tree in micro-CT images can be extremely time-consuming since a typical dataset is usually on the order of several gigabytes in size. Automated and semi-automated tools for micro-CT airway analysis are desirable. In this paper, we propose an automatic airway segmentation method for in vivo micro-CT images of the murine lung and validate our method by comparing the automatic results to manual tracing. Our method is based primarily on grayscale morphology. The results show good visual matches between manually segmented and automatically segmented trees. The average true positive volume fraction compared to manual analysis is 91.61%. The overall runtime for the automatic method is on the order of 30 minutes per volume compared to several hours to a few days for manual analysis.

Model-based cartilage thickness measurement in the submillimeter range

DOE Office of Scientific and Technical Information (OSTI.GOV)

Streekstra, G. J.; Strackee, S. D.; Maas, M.

2007-09-15

Current methods of image-based thickness measurement in thin sheet structures utilize second derivative zero crossings to locate the layer boundaries. It is generally acknowledged that the nonzero width of the point spread function (PSF) limits the accuracy of this measurement procedure. We propose a model-based method that strongly reduces PSF-induced bias by incorporating the PSF into the thickness estimation method. We estimated the bias in thickness measurements in simulated thin sheet images as obtained from second derivative zero crossings. To gain insight into the range of sheet thickness where our method is expected to yield improved results, sheet thickness wasmore » varied between 0.15 and 1.2 mm with an assumed PSF as present in the high-resolution modes of current computed tomography (CT) scanners [full width at half maximum (FWHM) 0.5-0.8 mm]. Our model-based method was evaluated in practice by measuring layer thickness from CT images of a phantom mimicking two parallel cartilage layers in an arthrography procedure. CT arthrography images of cadaver wrists were also evaluated, and thickness estimates were compared to those obtained from high-resolution anatomical sections that served as a reference. The thickness estimates from the simulated images reveal that the method based on second derivative zero crossings shows considerable bias for layers in the submillimeter range. This bias is negligible for sheet thickness larger than 1 mm, where the size of the sheet is more than twice the FWHM of the PSF but can be as large as 0.2 mm for a 0.5 mm sheet. The results of the phantom experiments show that the bias is effectively reduced by our method. The deviations from the true thickness, due to random fluctuations induced by quantum noise in the CT images, are of the order of 3% for a standard wrist imaging protocol. In the wrist the submillimeter thickness estimates from the CT arthrography images correspond within 10% to those estimated from the anatomical sections. We present a method that yields virtually unbiased thickness estimates of cartilage layers in the submillimeter range. The good agreement of thickness estimates from CT images with estimates from anatomical sections is promising for clinical application of the method in cartilage integrity staging of the wrist and the ankle.« less

Impact of time-of-flight PET on quantification errors in MR imaging-based attenuation correction.

PubMed

Mehranian, Abolfazl; Zaidi, Habib

2015-04-01

Time-of-flight (TOF) PET/MR imaging is an emerging imaging technology with great capabilities offered by TOF to improve image quality and lesion detectability. We assessed, for the first time, the impact of TOF image reconstruction on PET quantification errors induced by MR imaging-based attenuation correction (MRAC) using simulation and clinical PET/CT studies. Standard 4-class attenuation maps were derived by segmentation of CT images of 27 patients undergoing PET/CT examinations into background air, lung, soft-tissue, and fat tissue classes, followed by the assignment of predefined attenuation coefficients to each class. For each patient, 4 PET images were reconstructed: non-TOF and TOF both corrected for attenuation using reference CT-based attenuation correction and the resulting 4-class MRAC maps. The relative errors between non-TOF and TOF MRAC reconstructions were compared with their reference CT-based attenuation correction reconstructions. The bias was locally and globally evaluated using volumes of interest (VOIs) defined on lesions and normal tissues and CT-derived tissue classes containing all voxels in a given tissue, respectively. The impact of TOF on reducing the errors induced by metal-susceptibility and respiratory-phase mismatch artifacts was also evaluated using clinical and simulation studies. Our results show that TOF PET can remarkably reduce attenuation correction artifacts and quantification errors in the lungs and bone tissues. Using classwise analysis, it was found that the non-TOF MRAC method results in an error of -3.4% ± 11.5% in the lungs and -21.8% ± 2.9% in bones, whereas its TOF counterpart reduced the errors to -2.9% ± 7.1% and -15.3% ± 2.3%, respectively. The VOI-based analysis revealed that the non-TOF and TOF methods resulted in an average overestimation of 7.5% and 3.9% in or near lung lesions (n = 23) and underestimation of less than 5% for soft tissue and in or near bone lesions (n = 91). Simulation results showed that as TOF resolution improves, artifacts and quantification errors are substantially reduced. TOF PET substantially reduces artifacts and improves significantly the quantitative accuracy of standard MRAC methods. Therefore, MRAC should be less of a concern on future TOF PET/MR scanners with improved timing resolution. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

PATIENT STUDY OF IN VIVO VERIFICATION OF BEAM DELIVERY AND RANGE, USING POSITRON EMISSION TOMOGRAPHY AND COMPUTED TOMOGRAPHY IMAGING AFTER PROTON THERAPY

PubMed Central

Parodi, Katia; Paganetti, Harald; Shih, Helen A.; Michaud, Susan; Loeffler, Jay S.; Delaney, Thomas F.; Liebsch, Norbert J.; Munzenrider, John E.; Fischman, Alan J.; Knopf, Antje; Bortfeld, Thomas

2007-01-01

Purpose To investigate the feasibility and value of positron emission tomography and computed tomography (PET/CT) for treatment verification after proton radiotherapy. Methods and Materials This study included 9 patients with tumors in the cranial base, spine, orbit, and eye. Total doses of 1.8–3 GyE and 10 GyE (for an ocular melanoma) per fraction were delivered in 1 or 2 fields. Imaging was performed with a commercial PET/CT scanner for 30 min, starting within 20 min after treatment. The same treatment immobilization device was used during imaging for all but 2 patients. Measured PET/CT images were coregistered to the planning CT and compared with the corresponding PET expectation, obtained from CT-based Monte Carlo calculations complemented by functional information. For the ocular case, treatment position was approximately replicated, and spatial correlation was deduced from reference clips visible in both the planning radiographs and imaging CT. Here, the expected PET image was obtained from an analytical model. Results Good spatial correlation and quantitative agreement within 30% were found between the measured and expected activity. For head-and-neck patients, the beam range could be verified with an accuracy of 1–2 mm in well-coregistered bony structures. Low spine and eye sites indicated the need for better fixation and coregistration methods. An analysis of activity decay revealed as tissue-effective half-lives of 800–1,150 s. Conclusions This study demonstrates the feasibility of postradiation PET/CT for in vivo treatment verification. It also indicates some technological and methodological improvements needed for optimal clinical application. PMID:17544003

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

PubMed

Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

2014-01-01

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

The Role of 18F-FDG PET/CT Integrated Imaging in Distinguishing Malignant from Benign Pleural Effusion

PubMed Central

Sun, Yajuan; Yu, Hongjuan; Ma, Jingquan

2016-01-01

Objective The aim of our study was to evaluate the role of 18F-FDG PET/CT integrated imaging in differentiating malignant from benign pleural effusion. Methods A total of 176 patients with pleural effusion who underwent 18F-FDG PET/CT examination to differentiate malignancy from benignancy were retrospectively researched. The images of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were visually analyzed. The suspected malignant effusion was characterized by the presence of nodular or irregular pleural thickening on CT imaging. Whereas on PET imaging, pleural 18F-FDG uptake higher than mediastinal activity was interpreted as malignant effusion. Images of 18F-FDG PET/CT integrated imaging were interpreted by combining the morphologic feature of pleura on CT imaging with the degree and form of pleural 18F-FDG uptake on PET imaging. Results One hundred and eight patients had malignant effusion, including 86 with pleural metastasis and 22 with pleural mesothelioma, whereas 68 patients had benign effusion. The sensitivities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging in detecting malignant effusion were 75.0%, 91.7% and 93.5%, respectively, which were 69.8%, 91.9% and 93.0% in distinguishing metastatic effusion. The sensitivity of 18F-FDG PET/CT integrated imaging in detecting malignant effusion was higher than that of CT imaging (p = 0.000). For metastatic effusion, 18F-FDG PET imaging had higher sensitivity (p = 0.000) and better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with CT imaging (Kappa = 0.917 and Kappa = 0.295, respectively). The specificities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were 94.1%, 63.2% and 92.6% in detecting benign effusion. The specificities of CT imaging and 18F-FDG PET/CT integrated imaging were higher than that of 18F-FDG PET imaging (p = 0.000 and p = 0.000, respectively), and CT imaging had better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with 18F-FDG PET imaging (Kappa = 0.881 and Kappa = 0.240, respectively). Conclusion 18F-FDG PET/CT integrated imaging is a more reliable modality in distinguishing malignant from benign pleural effusion than 18F-FDG PET imaging and CT imaging alone. For image interpretation of 18F-FDG PET/CT integrated imaging, the PET and CT portions play a major diagnostic role in identifying metastatic effusion and benign effusion, respectively. PMID:27560933

Dual-energy CT and ceramic or titanium prostheses material reduce CT artifacts and provide superior image quality of total knee arthroplasty.

PubMed

Kasparek, Maximilian F; Töpker, Michael; Lazar, Mathias; Weber, Michael; Kasparek, Michael; Mang, Thomas; Apfaltrer, Paul; Kubista, Bernd; Windhager, Reinhard; Ringl, Helmut

2018-06-07

To evaluate the influence of different scan parameters for single-energy CT and dual-energy CT, as well as the impact of different material used in a TKA prosthesis on image quality and the extent of metal artifacts. Eight pairs of TKA prostheses from different vendors were examined in a phantom set-up. Each pair consisted of a conventional CoCr prosthesis and the corresponding anti-allergic prosthesis (full titanium, ceramic, or ceramic-coated) from the same vendor. Nine different (seven dual-energy CT and two single-energy CT) scan protocols with different characteristics were used to determine the most suitable CT protocol for TKA imaging. Quantitative image analysis included assessment of blooming artifacts (metal implants appear thicker on CT than they are, given as virtual growth in mm in this paper) and streak artifacts (thick dark lines around metal). Qualitative image analysis was used to investigate the bone-prosthesis interface. The full titanium prosthesis and full ceramic knee showed significantly fewer blooming artifacts compared to the standard CoCr prosthesis (mean virtual growth 0.6-2.2 mm compared to 2.9-4.6 mm, p < 0.001). Dual-energy CT protocols showed less blooming (range 3.3-3.8 mm) compared to single-energy protocols (4.6-5.5 mm). The full titanium and full ceramic prostheses showed significantly fewer streak artifacts (mean standard deviation 77-86 Hounsfield unit (HU)) compared to the standard CoCr prosthesis (277-334 HU, p < 0.001). All dual-energy CT protocols had fewer metal streak artifacts (215-296 HU compared to single-energy CT protocols (392-497 HU)). Full titanium and ceramic prostheses were ranked superior with regard to the image quality at the bone/prosthesis interface compared to a standard CoCr prosthesis, and all dual-energy CT protocols were ranked better than single-energy protocols. Dual-energy CT and ceramic or titanium prostheses reduce CT artifacts and provide superior image quality of total knee arthroplasty at the bone/prosthesis interface. These findings support the use of dual-energy CT as a solid imaging base for clinical decision-making and the use of full-titanium or ceramic prostheses to allow for better CT visualization of the bone-prosthesis interface.

Magnetic Resonance–Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Weili; Kim, Joshua P.; Kadbi, Mo

2015-11-01

Purpose: To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Methods and Materials: Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessedmore » by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. Results: On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone–air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. Conclusions: A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical CTs, thereby supporting MR-only radiation therapy treatment planning in the brain.« less

Magnetic Resonance-Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region.

PubMed

Zheng, Weili; Kim, Joshua P; Kadbi, Mo; Movsas, Benjamin; Chetty, Indrin J; Glide-Hurst, Carri K

2015-11-01

To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone-air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical CTs, thereby supporting MR-only radiation therapy treatment planning in the brain. Copyright © 2015 Elsevier Inc. All rights reserved.

MRI-Only Based Radiotherapy Treatment Planning for the Rat Brain on a Small Animal Radiation Research Platform (SARRP).

PubMed

Gutierrez, Shandra; Descamps, Benedicte; Vanhove, Christian

2015-01-01

Computed tomography (CT) is the standard imaging modality in radiation therapy treatment planning (RTP). However, magnetic resonance (MR) imaging provides superior soft tissue contrast, increasing the precision of target volume selection. We present MR-only based RTP for a rat brain on a small animal radiation research platform (SARRP) using probabilistic voxel classification with multiple MR sequences. Six rat heads were imaged, each with one CT and five MR sequences. The MR sequences were: T1-weighted, T2-weighted, zero-echo time (ZTE), and two ultra-short echo time sequences with 20 μs (UTE1) and 2 ms (UTE2) echo times. CT data were manually segmented into air, soft tissue, and bone to obtain the RTP reference. Bias field corrected MR images were automatically segmented into the same tissue classes using a fuzzy c-means segmentation algorithm with multiple images as input. Similarities between segmented CT and automatic segmented MR (ASMR) images were evaluated using Dice coefficient. Three ASMR images with high similarity index were used for further RTP. Three beam arrangements were investigated. Dose distributions were compared by analysing dose volume histograms. The highest Dice coefficients were obtained for the ZTE-UTE2 combination and for the T1-UTE1-T2 combination when ZTE was unavailable. Both combinations, along with UTE1-UTE2, often used to generate ASMR images, were used for further RTP. Using 1 beam, MR based RTP underestimated the dose to be delivered to the target (range: 1.4%-7.6%). When more complex beam configurations were used, the calculated dose using the ZTE-UTE2 combination was the most accurate, with 0.7% deviation from CT, compared to 0.8% for T1-UTE1-T2 and 1.7% for UTE1-UTE2. The presented MR-only based workflow for RTP on a SARRP enables both accurate organ delineation and dose calculations using multiple MR sequences. This method can be useful in longitudinal studies where CT's cumulative radiation dose might contribute to the total dose.

CT cardiac imaging: evolution from 2D to 3D backprojection

NASA Astrophysics Data System (ADS)

Tang, Xiangyang; Pan, Tinsu; Sasaki, Kosuke

2004-04-01

The state-of-the-art multiple detector-row CT, which usually employs fan beam reconstruction algorithms by approximating a cone beam geometry into a fan beam geometry, has been well recognized as an important modality for cardiac imaging. At present, the multiple detector-row CT is evolving into volumetric CT, in which cone beam reconstruction algorithms are needed to combat cone beam artifacts caused by large cone angle. An ECG-gated cardiac cone beam reconstruction algorithm based upon the so-called semi-CB geometry is implemented in this study. To get the highest temporal resolution, only the projection data corresponding to 180° plus the cone angle are row-wise rebinned into the semi-CB geometry for three-dimensional reconstruction. Data extrapolation is utilized to extend the z-coverage of the ECG-gated cardiac cone beam reconstruction algorithm approaching the edge of a CT detector. A helical body phantom is used to evaluate the ECG-gated cone beam reconstruction algorithm"s z-coverage and capability of suppressing cone beam artifacts. Furthermore, two sets of cardiac data scanned by a multiple detector-row CT scanner at 16 x 1.25 (mm) and normalized pitch 0.275 and 0.3 respectively are used to evaluate the ECG-gated CB reconstruction algorithm"s imaging performance. As a reference, the images reconstructed by a fan beam reconstruction algorithm for multiple detector-row CT are also presented. The qualitative evaluation shows that, the ECG-gated cone beam reconstruction algorithm outperforms its fan beam counterpart from the perspective of cone beam artifact suppression and z-coverage while the temporal resolution is well maintained. Consequently, the scan speed can be increased to reduce the contrast agent amount and injection time, improve the patient comfort and x-ray dose efficiency. Based up on the comparison, it is believed that, with the transition of multiple detector-row CT into volumetric CT, ECG-gated cone beam reconstruction algorithms will provide better image quality for CT cardiac applications.

Positron emission tomography/computed tomography with 18F-fluorocholine improve tumor staging and treatment allocation in patients with hepatocellular carcinoma.

PubMed

Chalaye, Julia; Costentin, Charlotte E; Luciani, Alain; Amaddeo, Giuliana; Ganne-Carrié, Nathalie; Baranes, Laurence; Allaire, Manon; Calderaro, Julien; Azoulay, Daniel; Nahon, Pierre; Seror, Olivier; Mallat, Ariane; Soussan, Michael; Duvoux, Christophe; Itti, Emmanuel; Nault, Jean Charles

2018-03-06

Hepatocellular carcinoma (HCC) staging according to the Barcelona Clinical Liver Cancer (BCLC) classification is based on conventional imaging. The aim of our study was to assess the impact of dual-tracer 18F-fluorocholine and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) on tumor staging and treatment allocation. A total of 192 dual-tracer PET/CT scans (18F-fluorocholine and 18F-fluorodeoxyglucose PET/CT) were performed in 177 patients with HCC. BCLC staging and treatment proposal were retrospectively collected based on conventional imaging, along with any new lesions detected, and changes in BCLC classification or treatment allocation based on dual-tracer PET/CT. Patients were primarily men (87.5%) with cirrhosis (71%) due to alcohol ± non-alcoholic steatohepatitis (26%), viral infection (62%) or unknown causes (12%). Among 122 patients with PET/CT performed for staging, BCLC stage based on conventional imaging was 0/A in 61 patients (50%), B in 32 patients (26%) and C in 29 patients (24%). Dual-tracer PET/CT detected new lesions in 26 patients (21%), upgraded BCLC staging in 14 (11%) and modified treatment strategy in 17 (14%). In addition, dual-tracer PET/CT modified the final treatment in 4/9 (44%) patients with unexplained elevation of alpha-fetoprotein (AFP), 10/25 patients (40%) with doubtful lesions on conventional imaging and 3/36 patients (8%) waiting for liver transplantation without active HCC after tumor response following bridging therapy. When used for HCC staging, dual-tracer PET/CT enabled BCLC upgrading and treatment modification in 11% and 14% of patients, respectively. Dual-tracer PET/CT might also be useful in specific situations (an unexplained rise in AFP, doubtful lesions or pre-transplant evaluation of patients without active HCC). Using a combination of tracers 18F-fluorocholine and 18F-fluorodeoxyglucose when performing positron emission tomography/computed tomography (PET/CT), often called a PET scan, helps to identify new tumor lesions in patients with hepatocellular carcinoma. This technique enabled staging modification of patients' tumors and led to changes in treatment allocation in certain patients. Copyright © 2018. Published by Elsevier B.V.

Geometric validation of self-gating k-space-sorted 4D-MRI vs 4D-CT using a respiratory motion phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Yong, E-mail: yong.yue@cshs.org; Yang, Wensha; McKenzie, Elizabeth

Purpose: MRI is increasingly being used for radiotherapy planning, simulation, and in-treatment-room motion monitoring. To provide more detailed temporal and spatial MR data for these tasks, we have recently developed a novel self-gated (SG) MRI technique with advantage of k-space phase sorting, high isotropic spatial resolution, and high temporal resolution. The current work describes the validation of this 4D-MRI technique using a MRI- and CT-compatible respiratory motion phantom and comparison to 4D-CT. Methods: The 4D-MRI sequence is based on a spoiled gradient echo-based 3D projection reconstruction sequence with self-gating for 4D-MRI at 3 T. Respiratory phase is resolved by usingmore » SG k-space lines as the motion surrogate. 4D-MRI images are reconstructed into ten temporal bins with spatial resolution 1.56 × 1.56 × 1.56 mm{sup 3}. A MRI-CT compatible phantom was designed to validate the performance of the 4D-MRI sequence and 4D-CT imaging. A spherical target (diameter 23 mm, volume 6.37 ml) filled with high-concentration gadolinium (Gd) gel is embedded into a plastic box (35 × 40 × 63 mm{sup 3}) and stabilized with low-concentration Gd gel. The phantom, driven by an air pump, is able to produce human-type breathing patterns between 4 and 30 respiratory cycles/min. 4D-CT of the phantom has been acquired in cine mode, and reconstructed into ten phases with slice thickness 1.25 mm. The 4D images sets were imported into a treatment planning software for target contouring. The geometrical accuracy of the 4D MRI and CT images has been quantified using target volume, flattening, and eccentricity. The target motion was measured by tracking the centroids of the spheres in each individual phase. Motion ground-truth was obtained from input signals and real-time video recordings. Results: The dynamic phantom has been operated in four respiratory rate (RR) settings, 6, 10, 15, and 20/min, and was scanned with 4D-MRI and 4D-CT. 4D-CT images have target-stretching, partial-missing, and other motion artifacts in various phases, whereas the 4D-MRI images are visually free of those artifacts. Volume percentage difference for the 6.37 ml target ranged from 5.3% ± 4.3% to 10.3% ± 5.9% for 4D-CT, and 1.47 ± 0.52 to 2.12 ± 1.60 for 4D-MRI. With an increase of respiratory rate, the target volumetric and geometric deviations increase for 4D-CT images while remaining stable for the 4D-MRI images. Target motion amplitude errors at different RRs were measured with a range of 0.66–1.25 mm for 4D-CT and 0.2–0.42 mm for 4D-MRI. The results of Mann–Whitney tests indicated that 4D-MRI significantly outperforms 4D-CT in phase-based target volumetric (p = 0.027) and geometric (p < 0.001) measures. Both modalities achieve equivalent accuracy in measuring motion amplitude (p = 0.828). Conclusions: The k-space self-gated 4D-MRI technique provides a robust method for accurately imaging phase-based target motion and geometry. Compared to 4D-CT, the current 4D-MRI technique demonstrates superior spatiotemporal resolution, and robust resistance to motion artifacts caused by fast target motion and irregular breathing patterns. The technique can be used extensively in abdominal targeting, motion gating, and toward implementing MRI-based adaptive radiotherapy.« less

Diagnostic Imaging and workup of Malignant Pleural Mesothelioma.

PubMed

Cardinale, Luciano; Ardissone, Francesco; Gned, Dario; Sverzellati, Nicola; Piacibello, Edoardo; Veltri, Andrea

2017-08-23

Malignant pleural mesothelioma is the most frequent primary neoplasm of the pleura and its incidence is still increasing.This tumor has a strong association with exposure to occupational or environmental asbestos, often after a long latent period of 30-40 years.Plain chest radiography (CXR) is usually the first-line radiologic examination, but the radiographic findings are nonspecific due to its limited contrast resolution and they need to be complemented by other imaging modalities such as computed tomography (CT), magnetic resonance Imaging (MRI), Positron emission tomography-computed tomography (PET-CT) and ultrasound (US).The aim of this paper is to describe the imaging  features of this malignancy, underlining the peculiarity of CXR, CT, MRI, PET-CT and US and also focusing on diagnostic workup, based on the literature evidence and according to our experience.

Gadolinium-doped hollow CeO2-ZrO2 nanoplatform as multifunctional MRI/CT dual-modal imaging agent and drug delivery vehicle.

PubMed

Wei, Zuwu; Wu, Ming; Li, Zuanfang; Lin, Zhan; Zeng, Jinhua; Sun, Haiyan; Liu, Xiaolong; Liu, Jingfeng; Li, Buhong; Zeng, Yongyi

2018-11-01

Developing multifunctional nanoparticle-based theranostic platform for cancer diagnosis and treatment is highly desirable, however, most of the present theranostic platforms are fabricated via complicated structure/composition design and time-consuming synthesis procedures. Herein, the multifunctional Gd/CeO 2 -ZrO 2 /DOX-PEG nanoplatform with single nano-structure was fabricated through a facile route, which possessed MR/CT dual-model imaging and chemotherapy ability. The nanoplatform not only exhibited well-defined shapes, tunable compositions and narrow size distributions, but also presented a well anti-cancer effect and MR/CT imaging ability. Therefore, the Gd/CeO 2 -ZrO 2 /DOX-PEG nanoplatform could be applied for chemotherapy as well as dual-model MR/CT imaging.

Quantitative Assessment of Degenerative Cartilage and Subchondral Bony Lesions in a Preserved Cadaveric Knee: Propagation-Based Phase-Contrast CT Versus Conventional MRI and CT.

PubMed

Geith, Tobias; Brun, Emmanuel; Mittone, Alberto; Gasilov, Sergei; Weber, Loriane; Adam-Neumair, Silvia; Bravin, Alberto; Reiser, Maximilian; Coan, Paola; Horng, Annie

2018-06-01

The aim of this study was to quantitatively assess hyaline cartilage and subchondral bone conditions in a fully preserved cadaveric human knee joint using high-resolution x-ray propagation-based phase-contrast imaging (PBI) CT and to compare the performance of the new technique with conventional CT and MRI. A cadaveric human knee was examined using an x-ray beam of 60 keV, a detector with a 90-mm 2 FOV, and a pixel size of 46 × 46 μm 2 . PBI CT images were reconstructed with both the filtered back projection algorithm and the equally sloped tomography method. Conventional 3-T MRI and CT were also performed. Measurements of cartilage thickness, cartilage lesions, International Cartilage Repair Society scoring, and detection of subchondral bone changes were evaluated. Visual inspection of the specimen akin to arthroscopy was conducted and served as a standard of reference for lesion detection. Loss of cartilage height was visible on PBI CT and MRI. Quantification of cartilage thickness showed a strong correlation between the two modalities. Cartilage lesions appeared darker than the adjacent cartilage on PBI CT. PBI CT showed similar agreement to MRI for depicting cartilage substance defects or lesions compared with the visual inspection. The assessment of subchondral bone cysts showed moderate to strong agreement between PBI CT and CT. In contrast to the standard clinical methods of MRI and CT, PBI CT is able to simultaneously depict cartilage and bony changes at high resolution. Though still an experimental technique, PBI CT is a promising high-resolution imaging method to evaluate comprehensive changes of osteoarthritic disease in a clinical setting.

Implications of Artefacts Reduction in the Planning CT Originating from Implanted Fiducial Markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassim, Iskandar, E-mail: i.binkassim@erasmusmc.n; Joosten, Hans; Barnhoorn, Jaco C.

The efficacy of metal artefact reduction (MAR) software to suppress artefacts in reconstructed computed tomography (CT) images originating from small metal objects, like tumor markers and surgical clips, was evaluated. In addition, possible implications of using digital reconstructed radiographs (DRRs), based on the MAR CT images, for setup verification were analyzed. A phantom and 15 patients with different tumor sites and implanted markers were imaged with a multislice CT scanner. The raw image data was reconstructed both with the clinically used filtered-backprojection (FBP) and with the MAR software. Using the MAR software, improvements in image quality were often observed inmore » CT slices with markers or clips. Especially when several markers were located near to each other, fewer streak artefacts were observed than with the FBP algorithm. In addition, the shape and size of markers could be identified more accurately, reducing the contoured marker volumes by a factor of 2. For the phantom study, the CT numbers measured near to the markers corresponded more closely to the expected values. However, the MAR images were slightly more smoothed compared with the images reconstructed with FBP. For 8 prostate cancer patients in this study, the interobserver variation in 3D marker definition was similar (<0.4 mm) when using DRRs based on either FBP or MAR CT scans. Automatic marker matches also showed a similar success rate. However, differences in automatic match results up to 1 mm, caused by differences in the marker definition, were observed, which turned out to be (borderline) statistically significant (p = 0.06) for 2 patients. In conclusion, the MAR software might improve image quality by suppressing metal artefacts, probably allowing for a more reliable delineation of structures. When implanted markers or clips are used for setup verification, the accuracy may slightly be improved as well, which is relevant when using very tight clinical target volume (CTV) to planning target volume (PTV) margins for planning.« less

Development and application of pulmonary structure-function registration methods: towards pulmonary image-guidance tools for improved airway targeted therapies and outcomes

NASA Astrophysics Data System (ADS)

Guo, Fumin; Pike, Damien; Svenningsen, Sarah; Coxson, Harvey O.; Drozd, John J.; Yuan, Jing; Fenster, Aaron; Parraga, Grace

2014-03-01

Objectives: We aimed to develop a way to rapidly generate multi-modality (MRI-CT) pulmonary imaging structurefunction maps using novel non-rigid image registration methods. This objective is part of our overarching goal to provide an image processing pipeline to generate pulmonary structure-function maps and guide airway-targeted therapies. Methods: Anatomical 1H and functional 3He MRI were acquired in 5 healthy asymptomatic ex-smokers and 7 ex-smokers with chronic obstructive pulmonary disease (COPD) at inspiration breath-hold. Thoracic CT was performed within ten minutes of MRI using the same breath-hold volume. Landmark-based affine registration methods previously validated for imaging of COPD, was based on corresponding fiducial markers located in both CT and 1H MRI coronal slices and compared with shape-based CT-MRI non-rigid registration. Shape-based CT-MRI registration was developed by first identifying the shapes of the lung cavities manually, and then registering the two shapes using affine and thin-plate spline algorithms. We compared registration accuracy using the fiducial localization error (FLE) and target registration error (TRE). Results: For landmark-based registration, the TRE was 8.4±5.3 mm for whole lung and 7.8±4.6 mm for the R and L lungs registered independently (p=0.4). For shape-based registration, the TRE was 8.0±4.6 mm for whole lung as compared to 6.9±4.4 mm for the R and L lung registered independently and this difference was significant (p=0.01). The difference for shape-based (6.9±4.4 mm) and landmark-based R and L lung registration (7.8±4.6 mm) was also significant (p=.04) Conclusion: Shape-based registration TRE was significantly improved compared to landmark-based registration when considering L and R lungs independently.

Diffusible iodine-based contrast-enhanced computed tomography (diceCT): an emerging tool for rapid, high-resolution, 3-D imaging of metazoan soft tissues.

PubMed

Gignac, Paul M; Kley, Nathan J; Clarke, Julia A; Colbert, Matthew W; Morhardt, Ashley C; Cerio, Donald; Cost, Ian N; Cox, Philip G; Daza, Juan D; Early, Catherine M; Echols, M Scott; Henkelman, R Mark; Herdina, A Nele; Holliday, Casey M; Li, Zhiheng; Mahlow, Kristin; Merchant, Samer; Müller, Johannes; Orsbon, Courtney P; Paluh, Daniel J; Thies, Monte L; Tsai, Henry P; Witmer, Lawrence M

2016-06-01

Morphologists have historically had to rely on destructive procedures to visualize the three-dimensional (3-D) anatomy of animals. More recently, however, non-destructive techniques have come to the forefront. These include X-ray computed tomography (CT), which has been used most commonly to examine the mineralized, hard-tissue anatomy of living and fossil metazoans. One relatively new and potentially transformative aspect of current CT-based research is the use of chemical agents to render visible, and differentiate between, soft-tissue structures in X-ray images. Specifically, iodine has emerged as one of the most widely used of these contrast agents among animal morphologists due to its ease of handling, cost effectiveness, and differential affinities for major types of soft tissues. The rapid adoption of iodine-based contrast agents has resulted in a proliferation of distinct specimen preparations and scanning parameter choices, as well as an increasing variety of imaging hardware and software preferences. Here we provide a critical review of the recent contributions to iodine-based, contrast-enhanced CT research to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies. We provide a detailed summary of recent case studies, assess factors that govern success at each step of the specimen storage, preparation, and imaging processes, and make recommendations for standardizing both techniques and reporting practices. Finally, we discuss potential cutting-edge applications of diffusible iodine-based contrast-enhanced computed tomography (diceCT) and the issues that must still be overcome to facilitate the broader adoption of diceCT going forward. © 2016 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

SU-E-T-366: Clinical Implementation of MR-Guided Vaginal Cylinder Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owrangi, A; Jolly, S; Balter, J

2014-06-01

Purpose: To evaluate the accuracy of MR-based vaginal brachytherapy source localization using an in-house MR-visible marker versus the alignment of an applicator model to MR images. Methods: Three consecutive patients undergoing vaginal HDR brachytherapy with a plastic cylinder were scanned with both CT and MRI (including T1- and T2- weighted images). An MR-visible source localization marker, consisting of a sealed thin catheter filled with either water (for T2 contrast) or Gd-doped water (for T1 contrast), was assembled shortly before scanning. Clinically, the applicator channel was digitized on CT with an x-ray marker. To evaluate the efficacy of MR-based applicator reconstruction,more » each MR image volume was aligned locally to the CT images based on the region containing the cylinder. Applicator digitization was performed on the MR images using (1) the MR visible marker and (2) alignment of an applicator surface model from Varian's Brachytherapy Planning software to the MRI images. Resulting source positions were compared with the original CT digitization. Results: Although the source path was visualized by the MR marker, the applicator tip proved difficult to identify due to challenges in achieving a watertight seal. This resulted in observed displacements of the catheter tip, at times >1cm. Deviations between the central source positions identified via aligning the applicator surface model to MR and using the xray marker on CT ranged from 0.07 – 0.19 cm and 0.07 – 0.20 cm on T1- weighted and T2-weighted images, respectively. Conclusion: Based on the current study, aligning the applicator model to MRI provides a practical, current approach to perform MR-based brachytherapy planning. Further study is needed to produce catheters with reliably and reproducibly identifiable tips. Attempts are being made to improve catheter seals, as well as to increase the viscosity of the contrast material to decrease fluid mobility inside the catheter.« less

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning.

PubMed

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-07

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-01

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

MRI-based treatment planning with pseudo CT generated through atlas registration.

PubMed

Uh, Jinsoo; Merchant, Thomas E; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-05-01

To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787-0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%-98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs.

MRI-based treatment planning with pseudo CT generated through atlas registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uh, Jinsoo, E-mail: jinsoo.uh@stjude.org; Merchant, Thomas E.; Hua, Chiaho

2014-05-15

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration ofmore » conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. Conclusions: MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs.« less

MRI-based treatment planning with pseudo CT generated through atlas registration

PubMed Central

Uh, Jinsoo; Merchant, Thomas E.; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-01-01

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. Conclusions: MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs. PMID:24784377

DOE Office of Scientific and Technical Information (OSTI.GOV)

Negahdar, M; Loo, B; Maxim, P

Purpose: Elasticity may distinguish malignant from benign pulmonary nodules. To compare determining of malignant pulmonary nodule (MPN) elasticity from four dimensional computed tomography (4D CT) images versus inhale/exhale breath-hold CT images. Methods: We analyzed phase 00 and 50 of 4D CT and deep inhale and natural exhale of breath-hold CT images of 30 MPN treated with stereotactic ablative radiotherapy (SABR). The radius of the smallest MPN was 0.3 cm while the biggest one was 2.1 cm. An intensity based deformable image registration (DIR) workflow was applied to the 4D CT and breath-hold images to determine the volumes of the MPNsmore » and a 1 cm ring of surrounding lung tissue (ring) in each state. Next, an elasticity parameter was derived by calculating the ratio of the volume changes of MPN (exhale:inhale or phase50:phase00) to that of a 1 cm ring of lung tissue surrounding the MPN. The proposed formulation of elasticity enables us to compare volume changes of two different MPN in two different locations of lung. Results: The calculated volume ratio of MPNs from 4D CT (phase50:phase00) and breath-hold images (exhale:inhale) was 1.00±0.23 and 0.95±0.11, respectively. It shows the stiffness of MPN and comparably bigger volume changes of MPN in breath-hold images because of the deeper degree of inhalation. The calculated elasticity of MPNs from 4D CT and breath-hold images was 1.12±0.22 and 1.23±0.26, respectively. For five patients who have had two MPN in their lung, calculated elasticity of tumor A and tumor B follows same trend in both 4D CT and breath-hold images. Conclusion: We showed that 4D CT and breath-hold images are comparable in the ability to calculate the elasticity of MPN. This study has been supported by Department of Defense LCRP 2011 #W81XWH-12-1-0286.« less

TH-AB-BRA-04: Dosimetric Evaluation of MR-Guided HDR Brachytherapy Planning for Cervical Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamio, Y; Barkati, M; Beliveau-Nadeau, D

2016-06-15

Purpose: To perform a retrospective study on 16 patients that had both CT and T2-weighted MR scans done at first fraction using the Utrecht CT/MR applicator (Elekta Brachytherapy) in order to evaluate uncertainties associated with an MR-only planning workflow. Methods: MR-workflow uncertainties were classified in three categories: reconstruction, registration and contouring. A systematic comparison of the CT and MR contouring, manual reconstruction and optimization process was performed to evaluate the impact of these uncertainties on the recommended GEC ESTRO DVH parameters: D90% and V100% for HR-CTV as well as D2cc for bladder, rectum, sigmoid colon and small bowel. This comparisonmore » was done using the following four steps: 1. Catheter reconstruction done on MR images with original CT-plan contours and dwell times. 2. OAR contours adjusted on MR images with original CT-plan reconstruction and dwell times. 3. Both reconstruction and contours done on MR images with original CT-plan dwell times. 4. Entire MR-based workflow optimized dwell times reimported to the original CT-plan. Results: The MR-based reconstruction process showed average D2cc deviations of 4.5 ± 3.0%, 1.5 ± 2.0%, 2.5 ± 2.0% and 2.0 ± 1.0% for the bladder, rectum, sigmoid colon and small bowels respectively with a maximum of 10%, 6%, 6% and 4%. The HR-CTV’s D90% and V100% average deviations was found to be 4.0 ± 3.0%, and 2.0 ± 2.0% respectively with a maximum of 10% and 6%. Adjusting contours on MR-images was found to have a similar impact. Finally, the optimized MR-based workflow dwell times were found to still give acceptable plans when re-imported to the original CT-plan which validated the entire workflow. Conclusion: This work illustrates a systematic validation method for centers wanting to move towards an MR-only workflow. This work will be expanded to model based reconstruction, PD-weighted images and other types of applicators.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paliwal, B; Asprey, W; Yan, Y

Purpose: In order to take advantage of the high resolution soft tissue imaging available in MR images, we investigated 3D images obtained with the low field 0.35 T MR in ViewRay to serve as an alternative to CT scans for radiotherapy treatment planning. In these images, normal and target structure delineation can be visualized. Assessment is based upon comparison with the CT images and the ability to produce comparable contours. Methods: Routine radiation oncology CT scans were acquired on five patients. Contours of brain, brainstem, esophagus, heart, lungs, spinal cord, and the external body were drawn. The same five patientsmore » were then scanned on the ViewRay TrueFISP-based imaging pulse sequence. The same organs were selected on the MR images and compared to those from the CT scan. Physical volume and the Dice Similarity Coefficient (DSC) were used to assess the contours from the two systems. Image quality stability was quantitatively ensured throughout the study following the recommendations of the ACR MR accreditation procedure. Results: The highest DSC of 0.985, 0.863, and 0.843 were observed for brain, lungs, and heart respectively. On the other hand, the brainstem, spinal cord, and esophagus had the lowest DSC. Volume agreement was most satisfied for the heart (within 5%) and the brain (within 2%). Contour volume for the brainstem and lung (a widely dynamic organ) varied the most (27% and 19%). Conclusion: The DSC and volume measurements suggest that the results obtained from ViewRay images are quantitatively consistent and comparable to those obtained from CT scans for the brain, heart, and lungs. MR images from ViewRay are well-suited for treatment planning and for adaptive MRI-guided radiotherapy. The physical data from 0.35 T MR imaging is consistent with our geometrical understanding of normal structures.« less

Multimodal imaging of the human knee down to the cellular level

NASA Astrophysics Data System (ADS)

Schulz, G.; Götz, C.; Müller-Gerbl, M.; Zanette, I.; Zdora, M.-C.; Khimchenko, A.; Deyhle, H.; Thalmann, P.; Müller, B.

2017-06-01

Computed tomography reaches the best spatial resolution for the three-dimensional visualization of human tissues among the available nondestructive clinical imaging techniques. Nowadays, sub-millimeter voxel sizes are regularly obtained. Regarding investigations on true micrometer level, lab-based micro-CT (μCT) has become gold standard. The aim of the present study is firstly the hierarchical investigation of a human knee post mortem using hard X-ray μCT and secondly a multimodal imaging using absorption and phase contrast modes in order to investigate hard (bone) and soft (cartilage) tissues on the cellular level. After the visualization of the entire knee using a clinical CT, a hierarchical imaging study was performed using the lab-system nanotom® m. First, the entire knee was measured with a pixel length of 65 μm. The highest resolution with a pixel length of 3 μm could be achieved after extracting cylindrically shaped plugs from the femoral bones. For the visualization of the cartilage, grating-based phase contrast μCT (I13-2, Diamond Light Source) was performed. With an effective voxel size of 2.3 μm it was possible to visualize individual chondrocytes within the cartilage.

Positioning accuracy in a registration-free CT-based navigation system

NASA Astrophysics Data System (ADS)

Brandenberger, D.; Birkfellner, W.; Baumann, B.; Messmer, P.; Huegli, R. W.; Regazzoni, P.; Jacob, A. L.

2007-12-01

In order to maintain overall navigation accuracy established by a calibration procedure in our CT-based registration-free navigation system, the CT scanner has to repeatedly generate identical volume images of a target at the same coordinates. We tested the positioning accuracy of the prototype of an advanced workplace for image-guided surgery (AWIGS) which features an operating table capable of direct patient transfer into a CT scanner. Volume images (N = 154) of a specialized phantom were analysed for translational shifting after various table translations. Variables included added weight and phantom position on the table. The navigation system's calibration accuracy was determined (bias 2.1 mm, precision ± 0.7 mm, N = 12). In repeated use, a bias of 3.0 mm and a precision of ± 0.9 mm (N = 10) were maintainable. Instances of translational image shifting were related to the table-to-CT scanner docking mechanism. A distance scaling error when altering the table's height was detected. Initial prototype problems visible in our study causing systematic errors were resolved by repeated system calibrations between interventions. We conclude that the accuracy achieved is sufficient for a wide range of clinical applications in surgery and interventional radiology.

Photon counting spectral breast CT: effect of adaptive filtration on CT numbers, noise, and contrast to noise ratio.

PubMed

Silkwood, Justin D; Matthews, Kenneth L; Shikhaliev, Polad M

2013-05-01

Photon counting spectral (PCS) computed tomography (CT) shows promise for breast imaging. An issue with current photon-counting detectors is low count rate capabilities, artifacts resulting from nonuniform count rate across the field of view, and suboptimal spectral information. These issues are addressed in part by using tissue-equivalent adaptive filtration of the x-ray beam. The purpose of the study was to investigate the effect of adaptive filtration on different aspects of PCS breast CT. The theoretical formulation for the filter shape was derived for different filter materials and evaluated by simulation and an experimental prototype of the filter was fabricated from a tissue-like material (acrylic). The PCS CT images of a glandular breast phantom with adipose and iodine contrast elements were simulated at 40, 60, 90, and 120 kVp tube voltages, with and without adaptive filter. The CT numbers, CT noise, and contrast-to-noise ratio (CNR) were compared for spectral CT images acquired with and without adaptive filters. Similar comparison was made for material-decomposed PCS CT images. The adaptive filter improved the uniformity of CT numbers, CT noise, and CNR in both ordinary and material decomposed PCS CT images. At the same tube output the average CT noise with adaptive filter, although uniform, was higher than the average noise without adaptive filter due to x-ray absorption by the filter. Increasing tube output, so that average skin exposure with the adaptive filter was same as without filter, made the noise with adaptive filter comparable to or lower than that without adaptive filter. Similar effects were observed when energy weighting was applied, and when material decompositions were performed using energy selective CT data. An adaptive filter decreases count rate requirements to the photon counting detectors which enables PCS breast CT based on commercially available detector technologies. Adaptive filter also improves image quality in PCS breast CT by decreasing beam hardening artifacts and by eliminating spatial nonuniformities of CT numbers, noise, and CNR.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method.

PubMed

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-05-16

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

PubMed Central

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-01-01

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

Consequences of additional use of PET information for target volume delineation and radiotherapy dose distribution for esophageal cancer.

PubMed

Muijs, Christina T; Schreurs, Liesbeth M; Busz, Dianne M; Beukema, Jannet C; van der Borden, Arnout J; Pruim, Jan; Van der Jagt, Eric J; Plukker, John Th; Langendijk, Johannes A

2009-12-01

To determine the consequences of target volume (TV) modifications, based on the additional use of PET information, on radiation planning, assuming PET/CT-imaging represents the true extent of the tumour. For 21 patients with esophageal cancer, two separate TV's were retrospectively defined based on CT (CT-TV) and co-registered PET/CT images (PET/CT-TV). Two 3D-CRT plans (prescribed dose 50.4 Gy) were constructed to cover the corresponding TV's. Subsequently, these plans were compared for target coverage, normal tissue dose-volume histograms and the corresponding normal tissue complication probability (NTCP) values. The addition of PET led to the modification of CT-TV with at least 10% in 12 of 21 patients (57%) (reduction in 9, enlargement in 3). PET/CT-TV was inadequately covered by the CT-based treatment plan in 8 patients (36%). Treatment plan modifications resulted in significant changes (p<0.05) in dose distributions to heart and lungs. Corresponding changes in NTCP values ranged from -3% to +2% for radiation pneumonitis and from -0.2% to +1.2% for cardiac mortality. This study demonstrated that TV's based on CT might exclude PET-avid disease. Consequences are under dosing and thereby possibly ineffective treatment. Moreover, the addition of PET in radiation planning might result in clinical important changes in NTCP.

Quantitative Rapid Assessment of Leukoaraiosis in CT : Comparison to Gold Standard MRI.

PubMed

Hanning, Uta; Sporns, Peter Bernhard; Schmidt, Rene; Niederstadt, Thomas; Minnerup, Jens; Bier, Georg; Knecht, Stefan; Kemmling, André

2017-10-20

The severity of white matter lesions (WML) is a risk factor of hemorrhage and predictor of clinical outcome after ischemic stroke; however, in contrast to magnetic resonance imaging (MRI) reliable quantification for this surrogate marker is limited for computed tomography (CT), the leading stroke imaging technique. We aimed to present and evaluate a CT-based automated rater-independent method for quantification of microangiopathic white matter changes. Patients with suspected minor stroke (National Institutes of Health Stroke scale, NIHSS < 4) were screened for the analysis of non-contrast computerized tomography (NCCT) at admission and compared to follow-up MRI. The MRI-based WML volume and visual Fazekas scores were assessed as the gold standard reference. We employed a recently published probabilistic brain segmentation algorithm for CT images to determine the tissue-specific density of WM space. All voxel-wise densities were quantified in WM space and weighted according to partial probabilistic WM content. The resulting mean weighted density of WM space in NCCT, the surrogate of WML, was correlated with reference to MRI-based WML parameters. The process of CT-based tissue-specific segmentation was reliable in 79 cases with varying severity of microangiopathy. Voxel-wise weighted density within WM spaces showed a noticeable correlation (r = -0.65) with MRI-based WML volume. Particularly in patients with moderate or severe lesion load according to the visual Fazekas score the algorithm provided reliable prediction of MRI-based WML volume. Automated observer-independent quantification of voxel-wise WM density in CT significantly correlates with microangiopathic WM disease in gold standard MRI. This rapid surrogate of white matter lesion load in CT may support objective WML assessment and therapeutic decision-making during acute stroke triage.

SU-E-J-90: MRI-Based Treatment Simulation and Patient Setup for Radiation Therapy of Brain Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y; Cao, M; Han, F

2014-06-01

Purpose: Traditional radiation therapy of cancer is heavily dependent on CT. CT provides excellent depiction of the bones but lacks good soft tissue contrast, which makes contouring difficult. Often, MRIs are fused with CT to take advantage of its superior soft tissue contrast. Such an approach has drawbacks. It is desirable to perform treatment simulation entirely based on MRI. To achieve MR-based simulation for radiation therapy, bone imaging is an important challenge because of the low MR signal intensity from bone due to its ultra-short T2 and T1, which presents difficulty for both dose calculation and patient setup in termsmore » of digitally reconstructed radiograph (DRR) generation. Current solutions will either require manual bone contouring or multiple MR scans. We present a technique to generate DRR using MRI with an Ultra Short Echo Time (UTE) sequence which is applicable to both OBI and ExacTrac 2D patient setup. Methods: Seven brain cancer patients were scanned at 1.5 Tesla using a radial UTE sequence. The sequence acquires two images at two different echo times. The two images were processed using in-house software. The resultant bone images were subsequently loaded into commercial systems to generate DRRs. Simulation and patient clinical on-board images were used to evaluate 2D patient setup with MRI-DRRs. Results: The majority bones are well visualized in all patients. The fused image of patient CT with the MR bone image demonstrates the accuracy of automatic bone identification using our technique. The generated DRR is of good quality. Accuracy of 2D patient setup by using MRI-DRR is comparable to CT-based 2D patient setup. Conclusion: This study shows the potential of DRR generation with single MR sequence. Further work will be needed on MR sequence development and post-processing procedure to achieve robust MR bone imaging for other human sites in addition to brain.« less

In vivo spatial correlation between (18)F-BPA and (18)F-FDG uptakes in head and neck cancer.

PubMed

Kobayashi, Kazuma; Kurihara, Hiroaki; Watanabe, Yoshiaki; Murakami, Naoya; Inaba, Koji; Nakamura, Satoshi; Wakita, Akihisa; Okamoto, Hiroyuki; Umezawa, Rei; Takahashi, Kana; Igaki, Hiroshi; Ito, Yoshinori; Yoshimoto, Seiichi; Shigematsu, Naoyuki; Itami, Jun

2016-09-01

Borono-2-(18)F-fluoro-phenylalanine ((18)F-BPA) has been used to estimate the therapeutic effects of boron neutron capture therapy (BNCT), while (18)F-fluorodeoxyglucose ((18)F-FDG) is the most commonly used positron emission tomography (PET) radiopharmaceutical in a routine clinical use. The aim of the present study was to evaluate spatial correlation between (18)F-BPA and (18)F-FDG uptakes using a deformable image registration-based technique. Ten patients with head and neck cancer were recruited from January 2014 to December 2014. All patients underwent whole-body (18)F-BPA PET/computed tomography (CT) and (18)F-FDG PET/CT within a 2-week period. For each patient, (18)F-BPA PET/CT and (18)F-FDG PET/CT images were aligned based on a deformable image registration framework. The voxel-by-voxel spatial correlation of standardized uptake value (SUV) within the tumor was analyzed. Our image processing framework achieved accurate and validated registration results for each PET/CT image. In 9/10 patients, the spatial distribution of SUVs between (18)F-BPA and (18)F-FDG showed a significant, positive correlation in the tumor volume. Deformable image registration-based voxel-wise analysis demonstrated a spatial correlation between (18)F-BPA and (18)F-FDG uptakes in the head and neck cancer. A tumor sub-volume with a high (18)F-FDG uptake may predict high accumulation of (18)F-BPA. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The impact of 18 F-FET PET-CT on target definition in image-guided stereotactic radiotherapy in patients with skull base lesions.

PubMed

Badakhshi, Harun; Graf, Reinhold; Prasad, Vikas; Budach, Volker

2014-06-25

18 F-fluoro-ethyl-tyrosine PET is gaining more indications in the field of oncology. We investigated the potentials of usage of FET-PET/CT in addition to MRI for definition of gross tumor volume (GTV) in stereotactic radiotherapy of lesions of skull base. We included in a prospective setting 21 cases. An MRI was performed, completed by FET PET/CT. Different GTV's were defined based on respective imaging tools: 1. GTVMRI, 2. GTV MRI /CT, 3. GTV composit (1 + 2), and GTVPET = GTV Boost. Lesions could be visualised by MRI and FET-PET/CT in all patients. FET tracer enhancement was found in all cases. Skull base infiltration by these lesions was observed by MRI, CT (PET/CT) and FET-PET (PET/CT) in all patients. Totally, brain tissue infiltration was seen in 10 patients. While, in 7 (out 10) cases, MRI and CT (from PET/CT) were indicating brain infiltration, FET-PET could add additional information regarding infiltrative behaviour: in 3 (out 10) patients, infiltration of the brain was displayed merely in FET-PET. An enlargement of GTVMRI/CT due to the FET-PET driven information, which revealed GTVcomposite , was necessary in 7 cases,. This enlargement was significant by definition (> 10% of GTVMRI/CT). The mean PET-effect on GTV counted for 1 ± 4 cm3. The restricted boost fields were based mainly on the GTVPET volume. In mean, about 8.5 cm3 of GTVMRI/CT, which showed no FET uptake, were excluded from target volume. GTV boost driven by only-PET-activity, was in mean by 33% smaller than the initial large treatment field, GTV composite, for those cases received boost treatment. FET-PET lead to significant (>10%) changes in the initial treatment fields in 11/21 patients and showed additional tumour volume relevant for radiation planning in 6/21 cases, and led to a subsequent decrease of more than 10% of the initial volumes for the boost fields. The implementation of FET PET into the planning procedures showed a benefit in terms of accurate definition of skull base lesions as targets for Image-guided stereotactic Radiotherapy. This has to be investigated prospectively in larger cohorts.

SU-E-J-119: Head-And-Neck Digital Phantoms for Geometric and Dosimetric Uncertainty Evaluation of CT-CBCT Deformable Image Registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Z; Koyfman, S; Xia, P

2015-06-15

Purpose: To evaluate geometric and dosimetric uncertainties of CT-CBCT deformable image registration (DIR) algorithms using digital phantoms generated from real patients. Methods: We selected ten H&N cancer patients with adaptive IMRT. For each patient, a planning CT (CT1), a replanning CT (CT2), and a pretreatment CBCT (CBCT1) were used as the basis for digital phantom creation. Manually adjusted meshes were created for selected ROIs (e.g. PTVs, brainstem, spinal cord, mandible, and parotids) on CT1 and CT2. The mesh vertices were input into a thin-plate spline algorithm to generate a reference displacement vector field (DVF). The reference DVF was applied tomore » CBCT1 to create a simulated mid-treatment CBCT (CBCT2). The CT-CBCT digital phantom consisted of CT1 and CBCT2, which were linked by the reference DVF. Three DIR algorithms (Demons, B-Spline, and intensity-based) were applied to these ten digital phantoms. The images, ROIs, and volumetric doses were mapped from CT1 to CBCT2 using the DVFs computed by these three DIRs and compared to those mapped using the reference DVF. Results: The average Dice coefficients for selected ROIs were from 0.83 to 0.94 for Demons, from 0.82 to 0.95 for B-Spline, and from 0.67 to 0.89 for intensity-based DIR. The average Hausdorff distances for selected ROIs were from 2.4 to 6.2 mm for Demons, from 1.8 to 5.9 mm for B-Spline, and from 2.8 to 11.2 mm for intensity-based DIR. The average absolute dose errors for selected ROIs were from 0.7 to 2.1 Gy for Demons, from 0.7 to 2.9 Gy for B- Spline, and from 1.3 to 4.5 Gy for intensity-based DIR. Conclusion: Using clinically realistic CT-CBCT digital phantoms, Demons and B-Spline were shown to have similar geometric and dosimetric uncertainties while intensity-based DIR had the worst uncertainties. CT-CBCT DIR has the potential to provide accurate CBCT-based dose verification for H&N adaptive radiotherapy. Z Shen: None; K Bzdusek: an employee of Philips Healthcare; S Koyfman: None; P Xia: received research grants from Philips Healthcare and Siemens Healthcare.« less

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

NASA Astrophysics Data System (ADS)

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-09-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images. Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

PubMed Central

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-01-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. Methods We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 seconds. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.04375 mAs, were investigated. Both the analytical FDK algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. Results With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images. Conclusions Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode. PMID:26352168

Ultra-Low-Dose Fetal CT With Model-Based Iterative Reconstruction: A Prospective Pilot Study.

PubMed

Imai, Rumi; Miyazaki, Osamu; Horiuchi, Tetsuya; Asano, Keisuke; Nishimura, Gen; Sago, Haruhiko; Nosaka, Shunsuke

2017-06-01

Prenatal diagnosis of skeletal dysplasia by means of 3D skeletal CT examination is highly accurate. However, it carries a risk of fetal exposure to radiation. Model-based iterative reconstruction (MBIR) technology can reduce radiation exposure; however, to our knowledge, the lower limit of an optimal dose is currently unknown. The objectives of this study are to establish ultra-low-dose fetal CT as a method for prenatal diagnosis of skeletal dysplasia and to evaluate the appropriate radiation dose for ultra-low-dose fetal CT. Relationships between tube current and image noise in adaptive statistical iterative reconstruction and MBIR were examined using a 32-cm CT dose index (CTDI) phantom. On the basis of the results of this examination and the recommended methods for the MBIR option and the known relationship between noise and tube current for filtered back projection, as represented by the expression SD = (milliamperes) -0.5 , the lower limit of the optimal dose in ultra-low-dose fetal CT with MBIR was set. The diagnostic power of the CT images obtained using the aforementioned scanning conditions was evaluated, and the radiation exposure associated with ultra-low-dose fetal CT was compared with that noted in previous reports. Noise increased in nearly inverse proportion to the square root of the dose in adaptive statistical iterative reconstruction and in inverse proportion to the fourth root of the dose in MBIR. Ultra-low-dose fetal CT was found to have a volume CTDI of 0.5 mGy. Prenatal diagnosis was accurately performed on the basis of ultra-low-dose fetal CT images that were obtained using this protocol. The level of fetal exposure to radiation was 0.7 mSv. The use of ultra-low-dose fetal CT with MBIR led to a substantial reduction in radiation exposure, compared with the CT imaging method currently used at our institution, but it still enabled diagnosis of skeletal dysplasia without reducing diagnostic power.

Size effect of Au/PAMAM contrast agent on CT imaging of reticuloendothelial system and tumor tissue

NASA Astrophysics Data System (ADS)

Wang, Wei; Li, Jian; Liu, Ransheng; Zhang, Aixu; Yuan, Zhiyong

2016-09-01

Polyamidoamine (PAMAM)-entrapped Au nanoparticles were synthesized with distinct sizes to figure out the size effect of Au-based contrast agent on CT imaging of passively targeted tissues. Au/PAMAM nanoparticles were first synthesized with narrow distribution of particles size of 22.2 ± 3.1, 54.2 ± 3.7, and 104.9 ± 4.7 nm in diameters. Size effect leads no significant difference on X-ray attenuation when Au/PAMAM was ≤0.05 mol/L. For CT imaging of a tumor model, small Au/PAMAM were more easily internalized via endocytosis in the liver, leading to more obviously enhanced contrast. Similarly, contrast agents with small sizes were more effective in tumor imaging because of the enhanced permeability and retention effect. Overall, the particle size of Au/PAMAM heavily affected the efficiency of CT enhancement in imaging RES and tumors.

Deep learning for low-dose CT

NASA Astrophysics Data System (ADS)

Chen, Hu; Zhang, Yi; Zhou, Jiliu; Wang, Ge

2017-09-01

Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative reconstruction algorithms, but they need to access raw data whose formats are not transparent to most users. Due to the difficulty of modeling the statistical characteristics in the image domain, the existing methods for directly processing reconstructed images cannot eliminate image noise very well while keeping structural details. Inspired by the idea of deep learning, here we combine the autoencoder, deconvolution network, and shortcut connections into the residual encoder-decoder convolutional neural network (RED-CNN) for low-dose CT imaging. After patch-based training, the proposed RED-CNN achieves a competitive performance relative to the-state-of-art methods. Especially, our method has been favorably evaluated in terms of noise suppression and structural preservation.

Technical Note: MRI only prostate radiotherapy planning using the statistical decomposition algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siversson, Carl, E-mail: carl.siversson@med.lu.se; Nordström, Fredrik; Department of Radiation Physics, Skåne University Hospital, Lund 214 28

2015-10-15

Purpose: In order to enable a magnetic resonance imaging (MRI) only workflow in radiotherapy treatment planning, methods are required for generating Hounsfield unit (HU) maps (i.e., synthetic computed tomography, sCT) for dose calculations, directly from MRI. The Statistical Decomposition Algorithm (SDA) is a method for automatically generating sCT images from a single MR image volume, based on automatic tissue classification in combination with a model trained using a multimodal template material. This study compares dose calculations between sCT generated by the SDA and conventional CT in the male pelvic region. Methods: The study comprised ten prostate cancer patients, for whommore » a 3D T2 weighted MRI and a conventional planning CT were acquired. For each patient, sCT images were generated from the acquired MRI using the SDA. In order to decouple the effect of variations in patient geometry between imaging modalities from the effect of uncertainties in the SDA, the conventional CT was nonrigidly registered to the MRI to assure that their geometries were well aligned. For each patient, a volumetric modulated arc therapy plan was created for the registered CT (rCT) and recalculated for both the sCT and the conventional CT. The results were evaluated using several methods, including mean average error (MAE), a set of dose-volume histogram parameters, and a restrictive gamma criterion (2% local dose/1 mm). Results: The MAE within the body contour was 36.5 ± 4.1 (1 s.d.) HU between sCT and rCT. Average mean absorbed dose difference to target was 0.0% ± 0.2% (1 s.d.) between sCT and rCT, whereas it was −0.3% ± 0.3% (1 s.d.) between CT and rCT. The average gamma pass rate was 99.9% for sCT vs rCT, whereas it was 90.3% for CT vs rCT. Conclusions: The SDA enables a highly accurate MRI only workflow in prostate radiotherapy planning. The dosimetric uncertainties originating from the SDA appear negligible and are notably lower than the uncertainties introduced by variations in patient geometry between imaging sessions.« less

A Practical Cone-beam CT Scatter Correction Method with Optimized Monte Carlo Simulations for Image-Guided Radiation Therapy

PubMed Central

Xu, Yuan; Bai, Ti; Yan, Hao; Ouyang, Luo; Pompos, Arnold; Wang, Jing; Zhou, Linghong; Jiang, Steve B.; Jia, Xun

2015-01-01

Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in image-guided radiation therapy. However, due to its large illumination field, scattered photons severely degrade its image quality. While kernel-based scatter correction methods have been used routinely in the clinic, it is still desirable to develop Monte Carlo (MC) simulation-based methods due to their accuracy. However, the high computational burden of the MC method has prevented routine clinical application. This paper reports our recent development of a practical method of MC-based scatter estimation and removal for CBCT. In contrast with conventional MC approaches that estimate scatter signals using a scatter-contaminated CBCT image, our method used a planning CT image for MC simulation, which has the advantages of accurate image intensity and absence of image truncation. In our method, the planning CT was first rigidly registered with the CBCT. Scatter signals were then estimated via MC simulation. After scatter signals were removed from the raw CBCT projections, a corrected CBCT image was reconstructed. The entire workflow was implemented on a GPU platform for high computational efficiency. Strategies such as projection denoising, CT image downsampling, and interpolation along the angular direction were employed to further enhance the calculation speed. We studied the impact of key parameters in the workflow on the resulting accuracy and efficiency, based on which the optimal parameter values were determined. Our method was evaluated in numerical simulation, phantom, and real patient cases. In the simulation cases, our method reduced mean HU errors from 44 HU to 3 HU and from 78 HU to 9 HU in the full-fan and the half-fan cases, respectively. In both the phantom and the patient cases, image artifacts caused by scatter, such as ring artifacts around the bowtie area, were reduced. With all the techniques employed, we achieved computation time of less than 30 sec including the time for both the scatter estimation and CBCT reconstruction steps. The efficacy of our method and its high computational efficiency make our method attractive for clinical use. PMID:25860299

MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Q; Stanford University School of Medicine, Stanford, CA; Liu, H

Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channelmore » and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral CT. This work is partially supported by the National Natural Science Foundation of China (No. 61302136), and the Natural Science Basic Research Plan in Shaanxi Province of China (No. 2014JQ8317).« less

Evaluation of the sparse coding super-resolution method for improving image quality of up-sampled images in computed tomography

NASA Astrophysics Data System (ADS)

Ota, Junko; Umehara, Kensuke; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

2017-02-01

As the capability of high-resolution displays grows, high-resolution images are often required in Computed Tomography (CT). However, acquiring high-resolution images takes a higher radiation dose and a longer scanning time. In this study, we applied the Sparse-coding-based Super-Resolution (ScSR) method to generate high-resolution images without increasing the radiation dose. We prepared the over-complete dictionary learned the mapping between low- and highresolution patches and seek a sparse representation of each patch of the low-resolution input. These coefficients were used to generate the high-resolution output. For evaluation, 44 CT cases were used as the test dataset. We up-sampled images up to 2 or 4 times and compared the image quality of the ScSR scheme and bilinear and bicubic interpolations, which are the traditional interpolation schemes. We also compared the image quality of three learning datasets. A total of 45 CT images, 91 non-medical images, and 93 chest radiographs were used for dictionary preparation respectively. The image quality was evaluated by measuring peak signal-to-noise ratio (PSNR) and structure similarity (SSIM). The differences of PSNRs and SSIMs between the ScSR method and interpolation methods were statistically significant. Visual assessment confirmed that the ScSR method generated a high-resolution image with sharpness, whereas conventional interpolation methods generated over-smoothed images. To compare three different training datasets, there were no significance between the CT, the CXR and non-medical datasets. These results suggest that the ScSR provides a robust approach for application of up-sampling CT images and yields substantial high image quality of extended images in CT.

Improvements to image quality using hybrid and model-based iterative reconstructions: a phantom study.

PubMed

Aurumskjöld, Marie-Louise; Ydström, Kristina; Tingberg, Anders; Söderberg, Marcus

2017-01-01

The number of computed tomography (CT) examinations is increasing and leading to an increase in total patient exposure. It is therefore important to optimize CT scan imaging conditions in order to reduce the radiation dose. The introduction of iterative reconstruction methods has enabled an improvement in image quality and a reduction in radiation dose. To investigate how image quality depends on reconstruction method and to discuss patient dose reduction resulting from the use of hybrid and model-based iterative reconstruction. An image quality phantom (Catphan® 600) and an anthropomorphic torso phantom were examined on a Philips Brilliance iCT. The image quality was evaluated in terms of CT numbers, noise, noise power spectra (NPS), contrast-to-noise ratio (CNR), low-contrast resolution, and spatial resolution for different scan parameters and dose levels. The images were reconstructed using filtered back projection (FBP) and different settings of hybrid (iDose 4 ) and model-based (IMR) iterative reconstruction methods. iDose 4 decreased the noise by 15-45% compared with FBP depending on the level of iDose 4 . The IMR reduced the noise even further, by 60-75% compared to FBP. The results are independent of dose. The NPS showed changes in the noise distribution for different reconstruction methods. The low-contrast resolution and CNR were improved with iDose 4 , and the improvement was even greater with IMR. There is great potential to reduce noise and thereby improve image quality by using hybrid or, in particular, model-based iterative reconstruction methods, or to lower radiation dose and maintain image quality. © The Foundation Acta Radiologica 2016.

The dynamic micro computed tomography at SSRF

NASA Astrophysics Data System (ADS)

Chen, R.; Xu, L.; Du, G.; Deng, B.; Xie, H.; Xiao, T.

2018-05-01

Synchrotron radiation micro-computed tomography (SR-μCT) is a critical technique for quantitative characterizing the 3D internal structure of samples, recently the dynamic SR-μCT has been attracting vast attention since it can evaluate the three-dimensional structure evolution of a sample. A dynamic μCT method, which is based on monochromatic beam, was developed at the X-ray Imaging and Biomedical Application Beamline at Shanghai Synchrotron Radiation Facility, by combining the compressed sensing based CT reconstruction algorithm and hardware upgrade. The monochromatic beam based method can achieve quantitative information, and lower dose than the white beam base method in which the lower energy beam is absorbed by the sample rather than contribute to the final imaging signal. The developed method is successfully used to investigate the compression of the air sac during respiration in a bell cricket, providing new knowledge for further research on the insect respiratory system.