APPLICATION OF COMPUTER AIDED TOMOGRAPHY (CAT) TO THE STUDY OF MARINE BENTIC COMMUNITIES

EPA Science Inventory

Sediment cores were imaged using a Computer-Aided Tomography (CT) scanner at Massachusetts General Hospital, Boston, Massachusetts, United States. Procedures were developed, using the attenuation of X-rays, to differentiate between sediment and the water contained in macrobenthic...

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.

Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

NASA Astrophysics Data System (ADS)

McClatchy, David M., III; Rizzo, Elizabeth J.; Meganck, Jeff; Kempner, Josh; Vicory, Jared; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.

2017-12-01

A multimodal micro-computed tomography (CT) and multi-spectral structured light imaging (SLI) system is introduced and systematically analyzed to test its feasibility to aid in margin delineation during breast conserving surgery (BCS). Phantom analysis of the micro-CT yielded a signal-to-noise ratio of 34, a contrast of 1.64, and a minimum detectable resolution of 240 μm for a 1.2 min scan. The SLI system, spanning wavelengths 490 nm to 800 nm and spatial frequencies up to 1.37 mm-1 , was evaluated with aqueous tissue simulating phantoms having variations in particle size distribution, scatter density, and blood volume fraction. The reduced scattering coefficient, μs\\prime and phase function parameter, γ, were accurately recovered over all wavelengths independent of blood volume fractions from 0% to 4%, assuming a flat sample geometry perpendicular to the imaging plane. The resolution of the optical system was tested with a step phantom, from which the modulation transfer function was calculated yielding a maximum resolution of 3.78 cycles per mm. The three dimensional spatial co-registration between the CT and optical imaging space was tested and shown to be accurate within 0.7 mm. A freshly resected breast specimen, with lobular carcinoma, fibrocystic disease, and adipose, was imaged with the system. The micro-CT provided visualization of the tumor mass and its spiculations, and SLI yielded superficial quantification of light scattering parameters for the malignant and benign tissue types. These results appear to be the first demonstration of SLI combined with standard medical tomography for imaging excised tumor specimens. While further investigations are needed to determine and test the spectral, spatial, and CT features required to classify tissue, this study demonstrates the ability of multimodal CT/SLI to quantify, visualize, and spatially navigate breast tumor specimens, which could potentially aid in the assessment of tumor margin status during BCS.

Computer aided detection system for lung cancer using computer tomography scans

NASA Astrophysics Data System (ADS)

Mahesh, Shanthi; Rakesh, Spoorthi; Patil, Vidya C.

2018-04-01

Lung Cancer is a disease can be defined as uncontrolled cell growth in tissues of the lung. If we detect the Lung Cancer in its early stage, then that could be the key of its cure. In this work the non-invasive methods are studied for assisting in nodule detection. It supplies a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Computer Tomography (CT) images. CAD system is the one which helps to improve the diagnostic performance of radiologists in their image interpretations. The main aim of this technique is to develop a CAD system for finding the lung cancer using the lung CT images and classify the nodule as Benign or Malignant. For classifying cancer cells, SVM classifier is used. Here, image processing techniques have been used to de-noise, to enhance, for segmentation and edge detection of an image is used to extract the area, perimeter and shape of nodule. The core factors of this research are Image quality and accuracy.

Pulmonary cryptococcosis in rheumatoid arthritis (RA) patients: comparison of imaging characteristics among RA, acquired immunodeficiency syndrome, and immunocompetent patients.

PubMed

Yanagawa, Noriyo; Sakai, Fumikazu; Takemura, Tamiko; Ishikawa, Satoru; Takaki, Yasunobu; Hishima, Tsunekazu; Kamata, Noriko

2013-11-01

The imaging characteristics of cryptococcosis in rheumatoid arthritis (RA) patients were analyzed by comparing them with those of acquired immunodeficiency syndrome (AIDS) and immunocompetent patients, and the imaging findings were correlated with pathological findings. Two radiologists retrospectively compared the computed tomographic (CT) findings of 35 episodes of pulmonary cryptococcosis in 31 patients with 3 kinds of underlying states (10 RA, 12 AIDS, 13 immunocompetent), focusing on the nature, number, and distribution of lesions. The pathological findings of 18 patients (8 RA, 2 AIDS, 8 immunocompetent) were analyzed by two pathologists, and then correlated with imaging findings. The frequencies of consolidation and ground glass attenuation (GGA) were significantly higher, and the frequency of peripheral distribution was significantly lower in the RA group than in the immunocompetent group. Peripheral distribution was less common and generalized distribution was more frequent in the RA group than in the AIDS group. The pathological findings of the AIDS and immunocompetent groups reflected their immune status: There was lack of a granuloma reaction in the AIDS group, and a complete granuloma reaction in the immunocompetent group, while the findings of the RA group varied, including a complete granuloma reaction, a loose granuloma reaction and a hyper-immune reaction. Cases with the last two pathologic findings were symptomatic and showed generalized or central distribution on CT. Cryptococcosis in the RA group showed characteristic radiological and pathological findings compared with the other 2 groups. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Automatic detection of pulmonary nodules at spiral CT: first clinical experience with a computer-aided diagnosis system

NASA Astrophysics Data System (ADS)

Wormanns, Dag; Fiebich, Martin; Wietholt, Christian; Diederich, Stefan; Heindel, Walter

2000-06-01

We evaluated the practical application of a Computer-Aided Diagnosis (CAD) system for viewing spiral computed tomography (CT) of the chest low-dose screening examinations which includes an automatic detection of pulmonary nodules. A UNIX- based CAD system was developed including a detection algorithm for pulmonary nodules and a user interface providing an original axial image, the same image with nodules highlighted, a thin-slab MIP, and a cine mode. As yet, 26 CT examinations with 1625 images were reviewed in a clinical setting and reported by an experienced radiologist using both the CAD system and hardcopies. The CT studies exhibited 19 nodules found on the hardcopies in consensus reporting of 2 experienced radiologists. Viewing with the CAD system was more time consuming than using hardcopies (4.16 vs. 2.92 min) due to analyzing MIP and cine mode. The algorithm detected 49% (18/37) pulmonary nodules larger than 5 mm and 30% (21/70) of all nodules. It produced an average of 6.3 false positive findings per CT study. Most of the missed nodules were adjacent to the pleura. However, the program detected 6 nodules missed by the radiologists. Automatic nodule detection increases the radiologists's awareness of pulmonary lesions. Simultaneous display of axial image and thin-slab MIP makes the radiologist more confident in diagnosis of smaller pulmonary nodules. The CAD system improves the detection of pulmonary nodules at spiral CT. Lack of sensitivity and specificity is still an issue to be addressed but does not prevent practical use.

Automated segmentation and recognition of the bone structure in non-contrast torso CT images using implicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Zhou, X.; Hayashi, T.; Han, M.; Chen, H.; Hara, T.; Fujita, H.; Yokoyama, R.; Kanematsu, M.; Hoshi, H.

2009-02-01

X-ray CT images have been widely used in clinical diagnosis in recent years. A modern CT scanner can generate about 1000 CT slices to show the details of all the human organs within 30 seconds. However, CT image interpretations (viewing 500-1000 slices of CT images manually in front of a screen or films for each patient) require a lot of time and energy. Therefore, computer-aided diagnosis (CAD) systems that can support CT image interpretations are strongly anticipated. Automated recognition of the anatomical structures in CT images is a basic pre-processing of the CAD system. The bone structure is a part of anatomical structures and very useful to act as the landmarks for predictions of the other different organ positions. However, the automated recognition of the bone structure is still a challenging issue. This research proposes an automated scheme for segmenting the bone regions and recognizing the bone structure in noncontrast torso CT images. The proposed scheme was applied to 48 torso CT cases and a subjective evaluation for the experimental results was carried out by an anatomical expert following the anatomical definition. The experimental results showed that the bone structure in 90% CT cases have been recognized correctly. For quantitative evaluation, automated recognition results were compared to manual inputs of bones of lower limb created by an anatomical expert on 10 randomly selected CT cases. The error (maximum distance in 3D) between the recognition results and manual inputs distributed from 3-8 mm in different parts of the bone regions.

A fully automated non-external marker 4D-CT sorting algorithm using a serial cine scanning protocol.

PubMed

Carnes, Greg; Gaede, Stewart; Yu, Edward; Van Dyk, Jake; Battista, Jerry; Lee, Ting-Yim

2009-04-07

Current 4D-CT methods require external marker data to retrospectively sort image data and generate CT volumes. In this work we develop an automated 4D-CT sorting algorithm that performs without the aid of data collected from an external respiratory surrogate. The sorting algorithm requires an overlapping cine scan protocol. The overlapping protocol provides a spatial link between couch positions. Beginning with a starting scan position, images from the adjacent scan position (which spatial match the starting scan position) are selected by maximizing the normalized cross correlation (NCC) of the images at the overlapping slice position. The process was continued by 'daisy chaining' all couch positions using the selected images until an entire 3D volume was produced. The algorithm produced 16 phase volumes to complete a 4D-CT dataset. Additional 4D-CT datasets were also produced using external marker amplitude and phase angle sorting methods. The image quality of the volumes produced by the different methods was quantified by calculating the mean difference of the sorted overlapping slices from adjacent couch positions. The NCC sorted images showed a significant decrease in the mean difference (p < 0.01) for the five patients.

Use of dynamic images in radiology education: Movies of CT and MRI in the anatomy classroom.

PubMed

Jang, Hye Won; Oh, Chang-Seok; Choe, Yeon Hyeon; Jang, Dong Su

2018-04-19

Radiology education is a key component in many preclinical anatomy courses. However, the reported effectiveness of radiology education within such anatomy classrooms has varied. This study was conducted to determine if a novel educational method using dynamic images of movies of computed tomography (CT) and magnetic resonance imaging (MRI) was effective in radiology education during a preclinical anatomy course, aided by clay modeling, specific hand gestures (digit anatomy), and reports from dissection findings uploaded to the anatomy course website (digital reports). Feedback surveys using a five-point Likert scale were administered to better clarify students' opinions regarding their understanding of CT and MRI of anatomical structures, as well as to determine if such preclinical radiology education was helpful in their clinical studies. After completion of the anatomy course taught with dynamic images of CT and MRI, most students demonstrated an adequate understanding of basic CT and MR images. Additionally, students in later clinical years generally believed that their study of radiologic images during the preclinical anatomy course was helpful for their clinical studies and clerkship rotations. Moreover, student scores on imaging anatomy examinations demonstrated meaningful improvements in performance after using dynamic images from movies of CT and MRI. Anat Sci Educ. © 2018 American Association of Anatomists. © 2018 American Association of Anatomists.

The new frontiers of multimodality and multi-isotope imaging

NASA Astrophysics Data System (ADS)

Behnam Azad, Babak; Nimmagadda, Sridhar

2014-06-01

Technological advances in imaging systems and the development of target specific imaging tracers has been rapidly growing over the past two decades. Recent progress in "all-in-one" imaging systems that allow for automated image coregistration has significantly added to the growth of this field. These developments include ultra high resolution PET and SPECT scanners that can be integrated with CT or MR resulting in PET/CT, SPECT/CT, SPECT/PET and PET/MRI scanners for simultaneous high resolution high sensitivity anatomical and functional imaging. These technological developments have also resulted in drastic enhancements in image quality and acquisition time while eliminating cross compatibility issues between modalities. Furthermore, the most cutting edge technology, though mostly preclinical, also allows for simultaneous multimodality multi-isotope image acquisition and image reconstruction based on radioisotope decay characteristics. These scientific advances, in conjunction with the explosion in the development of highly specific multimodality molecular imaging agents, may aid in realizing simultaneous imaging of multiple biological processes and pave the way towards more efficient diagnosis and improved patient care.

Visualisation of the Bonebridge by means of CT and CBCT

PubMed Central

2013-01-01

Background With the Bonebridge, a new bone-anchored hearing aid has been available since March 2012. The objective of the study was to analyse the visualisation of the implant itself as well as its impact on the representation of the bony structures of the petrosal bone in CT, MRI and cone beam CT (CBCT). Methods The Bonebridge was implanted unilaterally in two completely prepared human heads. The radiological imaging by means of CBCT, 64-slice CT, 1.5-T and 3.0-T MRI was conducted both preoperatively and postoperatively. The images were subsequently evaluated from both the ENT medical and nd radiological perspectives. Results As anticipated, no visualisation of the implant or of the petrosal bones could be realised on MRI because of the interactive technology and the magnet artefact. In contrast, an excellent evaluability of the implant itself as well as of the surrounding neurovascular structures (sinus sigmoideus, skull base, middle ear, inner ear, inner auditory canal) was exhibited in both the CT and in the CBCT. Conclusion The Bonebridge can be excellently imaged with the radiological imaging technologies of CT and CBCT. In the process, CBCT shows discrete advantages in comparison with CT. No relevant restrictions in image quality in the evaluation of the bony structures of the petrosal bones could be seen. PMID:24004903

Anatomic optical coherence tomography for dynamic imaging of the upper airway

NASA Astrophysics Data System (ADS)

Bu, Ruofei; Balakrishnan, Santosh; Iftimia, Nicusor; Price, Hillel; Zdanski, Carlton; Oldenburg, Amy L.

2017-03-01

To aid in diagnosis and treatment of upper airway obstructive disorders (UAOD), we propose anatomic Optical Coherence Tomography (aOCT) for endoscopic imaging of the upper airway lumen with high speed and resolution. aOCT and CT scans are performed sequentially on in vivo swine to compare dynamic airway imaging data. The aOCT system is capable of capturing the dynamic deformation of the airway during respiration. This may lead to methods for airway elastography and aid in our understanding of dynamic collapse in UAOD.

High resolution multidetector CT aided tissue analysis and quantification of lung fibrosis

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Karwoski, Ronald A.; Bartholmai, Brian; Robb, Richard A.

2006-03-01

Idiopathic pulmonary fibrosis (IPF, also known as Idiopathic Usual Interstitial Pneumontis, pathologically) is a progressive diffuse lung disease which has a median survival rate of less than four years with a prevalence of 15-20/100,000 in the United States. Global function changes are measured by pulmonary function tests and the diagnosis and extent of pulmonary structural changes are typically assessed by acquiring two-dimensional high resolution CT (HRCT) images. The acquisition and analysis of volumetric high resolution Multi-Detector CT (MDCT) images with nearly isotropic pixels offers the potential to measure both lung function and structure. This paper presents a new approach to three dimensional lung image analysis and classification of normal and abnormal structures in lungs with IPF.

Computer-Aided Diagnostic (CAD) Scheme by Use of Contralateral Subtraction Technique

NASA Astrophysics Data System (ADS)

Nagashima, Hiroyuki; Harakawa, Tetsumi

We developed a computer-aided diagnostic (CAD) scheme for detection of subtle image findings of acute cerebral infarction in brain computed tomography (CT) by using a contralateral subtraction technique. In our computerized scheme, the lateral inclination of image was first corrected automatically by rotating and shifting. The contralateral subtraction image was then derived by subtraction of reversed image from original image. Initial candidates for acute cerebral infarctions were identified using the multiple-thresholding and image filtering techniques. As the 1st step for removing false positive candidates, fourteen image features were extracted in each of the initial candidates. Halfway candidates were detected by applying the rule-based test with these image features. At the 2nd step, five image features were extracted using the overlapping scale with halfway candidates in interest slice and upper/lower slice image. Finally, acute cerebral infarction candidates were detected by applying the rule-based test with five image features. The sensitivity in the detection for 74 training cases was 97.4% with 3.7 false positives per image. The performance of CAD scheme for 44 testing cases had an approximate result to training cases. Our CAD scheme using the contralateral subtraction technique can reveal suspected image findings of acute cerebral infarctions in CT images.

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.

Computer-aided diagnosis of lung cancer: definition and detection of ground-glass opacity type of nodules by high-resolution computed tomography.

PubMed

Okada, Tohru; Iwano, Shingo; Ishigaki, Takeo; Kitasaka, Takayuki; Hirano, Yasushi; Mori, Kensaku; Suenaga, Yasuhito; Naganawa, Shinji

2009-02-01

The ground-glass opacity (GGO) of lung cancer is identified only subjectively on computed tomography (CT) images as no quantitative characteristic has been defined for GGOs. We sought to define GGOs quantitatively and to differentiate between GGOs and solid-type lung cancers semiautomatically with a computer-aided diagnosis (CAD). High-resolution CT images of 100 pulmonary nodules (all peripheral lung cancers) were collected from our clinical records. Two radiologists traced the contours of nodules and distinguished GGOs from solid areas. The CT attenuation value of each area was measured. Differentiation between cancer types was assessed by a receiver-operating characteristic (ROC) analysis. The mean CT attenuation of the GGO areas was -618.4 +/- 212.2 HU, whereas that of solid areas was -68.1 +/- 230.3 HU. CAD differentiated between solidand GGO-type lung cancers with a sensitivity of 86.0% and specificity of 96.5% when the threshold value was -370 HU. Four nodules of mixed GGOs were incorrectly classified as the solid type. CAD detected 96.3% of GGO areas when the threshold between GGO and solid areas was 194 HU. Objective definition of GGO area by CT attenuation is feasible. This method is useful for semiautomatic differentiation between GGOs and solid types of lung cancer.

Multicenter study of quantitative computed tomography analysis using a computer-aided three-dimensional system in patients with idiopathic pulmonary fibrosis.

PubMed

Iwasawa, Tae; Kanauchi, Tetsu; Hoshi, Toshiko; Ogura, Takashi; Baba, Tomohisa; Gotoh, Toshiyuki; Oba, Mari S

2016-01-01

To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.

Infrared needle mapping to assist biopsy procedures and training.

PubMed

Shar, Bruce; Leis, John; Coucher, John

2018-04-01

A computed tomography (CT) biopsy is a radiological procedure which involves using a needle to withdraw tissue or a fluid specimen from a lesion of interest inside a patient's body. The needle is progressively advanced into the patient's body, guided by the most recent CT scan. CT guided biopsies invariably expose patients to high dosages of radiation, due to the number of scans required whilst the needle is advanced. This study details the design of a novel method to aid biopsy procedures using infrared cameras. Two cameras are used to image the biopsy needle area, from which the proposed algorithm computes an estimate of the needle endpoint, which is projected onto the CT image space. This estimated position may be used to guide the needle between scans, and results in a reduction in the number of CT scans that need to be performed during the biopsy procedure. The authors formulate a 2D augmentation system which compensates for camera pose, and show that multiple low-cost infrared imaging devices provide a promising approach.

Detection of longitudinal ulcer using roughness value for computer aided diagnosis of Crohn's disease

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kitasaka, Takayuki; Furukawa, Kazuhiro; Watanabe, Osamu; Ando, Takafumi; Goto, Hidemi; Mori, Kensaku

2011-03-01

The purpose of this paper is to present a new method to detect ulcers, which is one of the symptoms of Crohn's disease, from CT images. Crohn's disease is an inflammatory disease of the digestive tract. Crohn's disease commonly affects the small intestine. An optical or a capsule endoscope is used for small intestine examinations. However, these endoscopes cannot pass through intestinal stenosis parts in some cases. A CT image based diagnosis allows a physician to observe whole intestine even if intestinal stenosis exists. However, because of the complicated shape of the small and large intestines, understanding of shapes of the intestines and lesion positions are difficult in the CT image based diagnosis. Computer-aided diagnosis system for Crohn's disease having automated lesion detection is required for efficient diagnosis. We propose an automated method to detect ulcers from CT images. Longitudinal ulcers make rough surface of the small and large intestinal wall. The rough surface consists of combination of convex and concave parts on the intestinal wall. We detect convex and concave parts on the intestinal wall by a blob and an inverse-blob structure enhancement filters. A lot of convex and concave parts concentrate on roughed parts. We introduce a roughness value to differentiate convex and concave parts concentrated on the roughed parts from the other on the intestinal wall. The roughness value effectively reduces false positives of ulcer detection. Experimental results showed that the proposed method can detect convex and concave parts on the ulcers.

[Usefulness of imaging examinations in preoperative diagnosis of acute appendicitis].

PubMed

Nitoń, Tomasz; Górecka-Nitoń, Aleksandra

2014-01-01

Acute appendicitis (AA) is the cause one of most operations perform in department of general surgery on emergency ward. Frequency of acute appendicitis range from 6-8% of population. Clinical presentation is frequently unspecified and despite common occurence leads to many difficulties in diagnosis. Diagnosis of acute appendicitis includes clinical examination, laboratory tests, diagnostic scoring systems, computer programs as physisian aids and imaging examinations. About 30-45% patients suspected of acute appendicitis have untypical clinical presentation and here use of US or CT is very helpful. Longstanding use of US resulted in high AA evaluation accuracy with high sensitivity (75-90%) and specificity (84-100%). CT demonstrates above 95% ratio of correct diagnoses, reduces negative appendectomy rates and perforation rates as well as unnecessary observations. CT sensitivity and specificity CT is estimated between 83-100% among different authors. Expedited AA diagnosis, surgery and reduced hospitalization time are possible advantages of imaging tests. Additionally these tests can detect alternative deseases imitating acute appnedicitis. Use of imaging tests especially CT is beneficial in fertile women because of frequent genito-urinary disorders leading to the most diagnostic errors. However thera are contraindications in use of CT, for example it can not be performed in early pregnancy etc...

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.

Application of Computer-Aided Tomography (CT) Technology to Visually Compare Belowground Components of Salt Marshes in Jamaica Bay and Long Island, New York

EPA Science Inventory

Using CT imaging, we found that rapidly deteriorating marshes in Jamaica Bay had significantly less belowground mass and abundance of coarse roots and rhizomes at depth (< 10 cm) compared to more stable areas in the Jamaica Bay Estuary. In addition, the rhizome diameters and pea...

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.

Paleoradiology: advanced CT in the evaluation of nine Egyptian mummies.

PubMed

Hoffman, Heidi; Torres, William E; Ernst, Randy D

2002-01-01

Axial thin-collimation state-of-the-art spiral computed tomography (CT) was combined with sagittal and coronal reformatting, three-dimensional (3D) reconstruction, and virtual "fly-through" techniques to nondestructively study nine Egyptian mummies. These techniques provided important paleopathologic and historical information about mummification techniques, depicted anatomy in the most informative imaging plane, illustrated the soft-tissue preservation and physical appearance of mummies in superb detail, and generated an intriguing virtual tour through hollow mummified remains without harming the specimens themselves. Images generated with these methods can help archaeologists and Egyptologists understand these fascinating members of mankind and can serve as adjunct visual aids for laypersons who are interested in mummies. CT has emerged as the imaging modality of choice for the examination of Egyptian mummies due to its noninvasive cross-sectional nature and inherently superior contrast and spatial resolution. As multi-detector row CT and postprocessing tools evolve, the capabilities and applications of CT will continue to proliferate, attesting to the expanded versatility and utility of CT as a noninvasive research tool in the multidisciplinary study of Egyptian mummies. Copyright RSNA, 2002

A method of semi-quantifying β-AP in brain PET-CT 11C-PiB images.

PubMed

Jiang, Jiehui; Lin, Xiaoman; Wen, Junlin; Huang, Zhemin; Yan, Zhuangzhi

2014-01-01

Alzheimer's disease (AD) is a common health problem for elderly populations. Positron emission tomography-computed tomography (PET-CT)11C-PiB for beta-P (amyloid-β peptide, β-AP) imaging is an advanced method to diagnose AD in early stage. However, in practice radiologists lack a standardized value to semi-quantify β-AP. This paper proposes such a standardized value: SVβ-AP. This standardized value measures the mean ratio between the dimension of β-AP areas in PET and CT images. A computer aided diagnosis approach is also proposed to achieve SVβ-AP. A simulation experiment was carried out to pre-test the technical feasibility of the CAD approach and SVβ-AP. The experiment results showed that it is technically feasible.

Second cancers discovered by (18)FDG PET/CT imaging for choroidal melanoma.

PubMed

Chin, Kimberly; Finger, Paul T; Kurli, Madhavi; Tena, Lawrence B; Reddy, Shantan

2007-08-01

Positron-emission tomography/computed tomography (PET/CT) is a unique imaging tool that aids in the detection of cancerous lesions. It is currently and widely used for cancer staging (both initial and follow-up). Here we report our findings of second primary cancers incidentally discovered during PET/CT staging of patients with choroidal melanomas. We performed a retrospective case review of 139 patients with uveal melanoma who were subsequently evaluated by whole-body [18-fluorine-labeled] 2-deoxy-2-fluoro-D-glucose ((18)FDG) PET/CT imaging. In this series, 93 were scanned before treatment and 46 during the course of their follow-up systemic examinations. Their mean follow-up was 50.9 months. Six patients (4.3%) had second primary cancers revealed by PET/CT imaging. Three patients (50%) were synchronous (found at initial staging), and the remaining 3 patients (50%) were metachronous (found at follow-up staging). Second primary cancers were found in the lung, breast, uterus, colon, and thyroid. Although whole-body PET/CT scans were ordered as part of the staging process of patients with diagnosed choroidal melanoma, both synchronous and metachronous second primary cancers were found. PET/CT has become an indispensable tool for staging, diagnosis, and treatment planning for choroidal melanoma. The possibility of detecting second primary cancers should also be considered valuable.

Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network

NASA Astrophysics Data System (ADS)

Patel, Ajay; van de Leemput, Sil C.; Prokop, Mathias; van Ginneken, Bram; Manniesing, Rashindra

2017-03-01

Segmentation of anatomical structures is fundamental in the development of computer aided diagnosis systems for cerebral pathologies. Manual annotations are laborious, time consuming and subject to human error and observer variability. Accurate quantification of cerebrospinal fluid (CSF) can be employed as a morphometric measure for diagnosis and patient outcome prediction. However, segmenting CSF in non-contrast CT images is complicated by low soft tissue contrast and image noise. In this paper we propose a state-of-the-art method using a multi-scale three-dimensional (3D) fully convolutional neural network (CNN) to automatically segment all CSF within the cranial cavity. The method is trained on a small dataset comprised of four manually annotated cerebral CT images. Quantitative evaluation of a separate test dataset of four images shows a mean Dice similarity coefficient of 0.87 +/- 0.01 and mean absolute volume difference of 4.77 +/- 2.70 %. The average prediction time was 68 seconds. Our method allows for fast and fully automated 3D segmentation of cerebral CSF in non-contrast CT, and shows promising results despite a limited amount of training data.

Virtual 3-dimensional preoperative planning with the dextroscope for excision of a 4th ventricular ependymoma.

PubMed

Anil, S M; Kato, Y; Hayakawa, M; Yoshida, K; Nagahisha, S; Kanno, T

2007-04-01

Advances in computer imaging and technology have facilitated enhancement in surgical planning with a 3-dimensional model of the surgical plan of action utilizing advanced visualization tools in order to plan individual interactive operations with the aid of the dextroscope. This provides a proper 3-dimensional imaging insight to the pathological anatomy and sets a new dimension in collaboration for training and education. The case of a seventeen-year-old female, being operated with the aid of a preoperative 3-dimensional virtual reality planning and the practical application of the neurosurgical operation, is presented. This young lady presented with a two-year history of recurrent episodes of severe, global, throbbing headache with episodes of projectile vomiting associated with shoulder pain which progressively worsened. She had no obvious neurological deficits on clinical examination. CT and MRI showed a contrast-enhancing midline posterior fossa space-occupying lesion. Utilizing virtual imaging technology with the aid of a dextroscope which generates stereoscopic images, a 3-dimensional image was produced with the CT and MRI images. A preoperative planning for excision of the lesion was made and a real-time 3-dimensional volume was produced and surgical planning with the dextroscope was made and the lesion excised. Virtual reality has brought new proportions in 3-dimensional planning and management of various complex neuroanatomical problems that are faced during various operations. Integration of 3-dimensional imaging with stereoscopic vision makes understanding the complex anatomy easier and helps improve decision making in patient management.

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.

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.

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.

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.

Recent advances in imaging cancer of the kidney and urinary tract.

PubMed

Hilton, Susan; Jones, Lisa P

2014-10-01

Modern radiologic imaging is an aid to treatment planning for localized renal cancer, enabling characterization of mass lesions. For patients who present with advanced renal cancer, new imaging techniques enable a functional assessment of treatment response not possible using anatomic measurements alone. Multidetector CT urography permits simultaneous assessment of the kidneys and urinary tract for patients with unexplained hematuria. Both CT and MRI play a significant role in staging and follow up of patients treated for urothelial cancer. Newer imaging methods such as diffusion-weighted MRI have shown promising results for improving accuracy of staging and follow up of urothelial cancer. Copyright © 2014 Elsevier Inc. All rights reserved.

Computer-aided diagnosis for osteoporosis using chest 3D CT images

NASA Astrophysics Data System (ADS)

Yoneda, K.; Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2016-03-01

The patients of osteoporosis comprised of about 13 million people in Japan and it is one of the problems the aging society has. In order to prevent the osteoporosis, it is necessary to do early detection and treatment. Multi-slice CT technology has been improving the three dimensional (3-D) image analysis with higher body axis resolution and shorter scan time. The 3-D image analysis using multi-slice CT images of thoracic vertebra can be used as a support to diagnose osteoporosis and at the same time can be used for lung cancer diagnosis which may lead to early detection. We develop automatic extraction and partitioning algorithm for spinal column by analyzing vertebral body structure, and the analysis algorithm of the vertebral body using shape analysis and a bone density measurement for the diagnosis of osteoporosis. Osteoporosis diagnosis support system obtained high extraction rate of the thoracic vertebral in both normal and low doses.

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.

Improved computer-aided detection of small polyps in CT colonography using interpolation for curvature estimationa

PubMed Central

Liu, Jiamin; Kabadi, Suraj; Van Uitert, Robert; Petrick, Nicholas; Deriche, Rachid; Summers, Ronald M.

2011-01-01

Purpose: Surface curvatures are important geometric features for the computer-aided analysis and detection of polyps in CT colonography (CTC). However, the general kernel approach for curvature computation can yield erroneous results for small polyps and for polyps that lie on haustral folds. Those erroneous curvatures will reduce the performance of polyp detection. This paper presents an analysis of interpolation’s effect on curvature estimation for thin structures and its application on computer-aided detection of small polyps in CTC. Methods: The authors demonstrated that a simple technique, image interpolation, can improve the accuracy of curvature estimation for thin structures and thus significantly improve the sensitivity of small polyp detection in CTC. Results: Our experiments showed that the merits of interpolating included more accurate curvature values for simulated data, and isolation of polyps near folds for clinical data. After testing on a large clinical data set, it was observed that sensitivities with linear, quadratic B-spline and cubic B-spline interpolations significantly improved the sensitivity for small polyp detection. Conclusions: The image interpolation can improve the accuracy of curvature estimation for thin structures and thus improve the computer-aided detection of small polyps in CTC. PMID:21859029

Application of CT-PSF-based computer-simulated lung nodules for evaluating the accuracy of computer-aided volumetry.

PubMed

Funaki, Ayumu; Ohkubo, Masaki; Wada, Shinichi; Murao, Kohei; Matsumoto, Toru; Niizuma, Shinji

2012-07-01

With the wide dissemination of computed tomography (CT) screening for lung cancer, measuring the nodule volume accurately with computer-aided volumetry software is increasingly important. Many studies for determining the accuracy of volumetry software have been performed using a phantom with artificial nodules. These phantom studies are limited, however, in their ability to reproduce the nodules both accurately and in the variety of sizes and densities required. Therefore, we propose a new approach of using computer-simulated nodules based on the point spread function measured in a CT system. The validity of the proposed method was confirmed by the excellent agreement obtained between computer-simulated nodules and phantom nodules regarding the volume measurements. A practical clinical evaluation of the accuracy of volumetry software was achieved by adding simulated nodules onto clinical lung images, including noise and artifacts. The tested volumetry software was revealed to be accurate within an error of 20 % for nodules >5 mm and with the difference between nodule density and background (lung) (CT value) being 400-600 HU. Such a detailed analysis can provide clinically useful information on the use of volumetry software in CT screening for lung cancer. We concluded that the proposed method is effective for evaluating the performance of computer-aided volumetry software.

A “loop” shape descriptor and its application to automated segmentation of airways from CT scans

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

Pu, Jiantao; Jin, Chenwang, E-mail: jcw76@163.com; Yu, Nan

2015-06-15

Purpose: A novel shape descriptor is presented to aid an automated identification of the airways depicted on computed tomography (CT) images. Methods: Instead of simplifying the tubular characteristic of the airways as an ideal mathematical cylindrical or circular shape, the proposed “loop” shape descriptor exploits the fact that the cross sections of any tubular structure (regardless of its regularity) always appear as a loop. In implementation, the authors first reconstruct the anatomical structures in volumetric CT as a three-dimensional surface model using the classical marching cubes algorithm. Then, the loop descriptor is applied to locate the airways with a concavemore » loop cross section. To deal with the variation of the airway walls in density as depicted on CT images, a multiple threshold strategy is proposed. A publicly available chest CT database consisting of 20 CT scans, which was designed specifically for evaluating an airway segmentation algorithm, was used for quantitative performance assessment. Measures, including length, branch count, and generations, were computed under the aid of a skeletonization operation. Results: For the test dataset, the airway length ranged from 64.6 to 429.8 cm, the generation ranged from 7 to 11, and the branch number ranged from 48 to 312. These results were comparable to the performance of the state-of-the-art algorithms validated on the same dataset. Conclusions: The authors’ quantitative experiment demonstrated the feasibility and reliability of the developed shape descriptor in identifying lung airways.« less

Navigational ultrasound imaging: A novel imaging tool for aiding interventional therapies of equine musculoskeletal injuries.

PubMed

Lustgarten, M; Redding, W R; Schnabel, L V; Prange, T; Seiler, G S

2016-03-01

Navigational ultrasound imaging, also known as fusion imaging, is a novel technology that allows real-time ultrasound imaging to be correlated with a previously acquired computed tomography (CT) or magnetic resonance imaging (MRI) study. It has been used in man to aid interventional therapies and has been shown to be valuable for sampling and assessing lesions diagnosed with MRI or CT that are equivocal on ultrasonography. To date, there are no reports of the use of this modality in veterinary medicine. To assess whether navigational ultrasound imaging can be used to assist commonly performed interventional therapies for the treatment of equine musculoskeletal injuries diagnosed with MRI and determine the appropriateness of regional anatomical landmarks as registration sites. Retrospective, descriptive clinical study. Horses with musculoskeletal injuries of the distal limb diagnosed with MRI scheduled for ultrasound-guided interventional therapies were evaluated (n = 17 horses with a total of 29 lesions). Anatomical landmarks used for image registration for the navigational procedure were documented. Accuracy of lesion location and success of the procedure were assessed subjectively and described using a grading scale. All procedures were accurately registered using regional anatomical landmarks and considered successful based on our criteria. Anatomical landmarks were described for each lesion type. The addition of navigational imaging was considered to greatly aid the procedures in 59% of cases and added information to the remainder of the procedures. The technique was considered to improve the precision of these interventional procedures. Navigational ultrasound imaging is a complementary imaging modality that can be used for the treatment of equine soft tissue musculoskeletal injuries diagnosed with MRI. © 2015 EVJ Ltd.

Computer-aided design/computer-aided manufacturing skull base drill.

PubMed

Couldwell, William T; MacDonald, Joel D; Thomas, Charles L; Hansen, Bradley C; Lapalikar, Aniruddha; Thakkar, Bharat; Balaji, Alagar K

2017-05-01

The authors have developed a simple device for computer-aided design/computer-aided manufacturing (CAD-CAM) that uses an image-guided system to define a cutting tool path that is shared with a surgical machining system for drilling bone. Information from 2D images (obtained via CT and MRI) is transmitted to a processor that produces a 3D image. The processor generates code defining an optimized cutting tool path, which is sent to a surgical machining system that can drill the desired portion of bone. This tool has applications for bone removal in both cranial and spine neurosurgical approaches. Such applications have the potential to reduce surgical time and associated complications such as infection or blood loss. The device enables rapid removal of bone within 1 mm of vital structures. The validity of such a machining tool is exemplified in the rapid (< 3 minutes machining time) and accurate removal of bone for transtemporal (for example, translabyrinthine) approaches.

A head motion estimation algorithm for motion artifact correction in dental CT imaging

NASA Astrophysics Data System (ADS)

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

2018-03-01

A small head motion of the patient can compromise the image quality in a dental CT, in which a slow cone-beam scan is adopted. We introduce a retrospective head motion estimation method by which we can estimate the motion waveform from the projection images without employing any external motion monitoring devices. We compute the cross-correlation between every two successive projection images, which results in a sinusoid-like displacement curve over the projection view when there is no patient motion. However, the displacement curve deviates from the sinusoid-like form when patient motion occurs. We develop a method to estimate the motion waveform with a single parameter derived from the displacement curve with aid of image entropy minimization. To verify the motion estimation method, we use a lab-built micro-CT that can emulate major head motions during dental CT scans, such as tilting and nodding, in a controlled way. We find that the estimated motion waveform conforms well to the actual motion waveform. To further verify the motion estimation method, we correct the motion artifacts with the estimated motion waveform. After motion artifact correction, the corrected images look almost identical to the reference images, with structural similarity index values greater than 0.81 in the phantom and rat imaging studies.

Combined endeavor of Neutrosophic Set and Chan-Vese model to extract accurate liver image from CT scan.

PubMed

Siri, Sangeeta K; Latte, Mrityunjaya V

2017-11-01

Many different diseases can occur in the liver, including infections such as hepatitis, cirrhosis, cancer and over effect of medication or toxins. The foremost stage for computer-aided diagnosis of liver is the identification of liver region. Liver segmentation algorithms extract liver image from scan images which helps in virtual surgery simulation, speedup the diagnosis, accurate investigation and surgery planning. The existing liver segmentation algorithms try to extort exact liver image from abdominal Computed Tomography (CT) scan images. It is an open problem because of ambiguous boundaries, large variation in intensity distribution, variability of liver geometry from patient to patient and presence of noise. A novel approach is proposed to meet challenges in extracting the exact liver image from abdominal CT scan images. The proposed approach consists of three phases: (1) Pre-processing (2) CT scan image transformation to Neutrosophic Set (NS) and (3) Post-processing. In pre-processing, the noise is removed by median filter. The "new structure" is designed to transform a CT scan image into neutrosophic domain which is expressed using three membership subset: True subset (T), False subset (F) and Indeterminacy subset (I). This transform approximately extracts the liver image structure. In post processing phase, morphological operation is performed on indeterminacy subset (I) and apply Chan-Vese (C-V) model with detection of initial contour within liver without user intervention. This resulted in liver boundary identification with high accuracy. Experiments show that, the proposed method is effective, robust and comparable with existing algorithm for liver segmentation of CT scan images. Copyright © 2017 Elsevier B.V. All rights reserved.

An application of Chan-Vese method used to determine the ROI area in CT lung screening

NASA Astrophysics Data System (ADS)

Prokop, Paweł; Surtel, Wojciech

2016-09-01

The article presents two approaches of determining the ROI area in CT lung screening. First approach is based on a classic method of framing the image in order to determine the ROI by using a MaZda tool. Second approach is based on segmentation of CT images of the lungs and reducing the redundant information from the image. Of the two approaches of an Active Contour, it was decided to choose the Chan-Vese method. In order to determine the effectiveness of the approach, it was performed an analysis of received ROI texture and extraction of textural features. In order to determine the effectiveness of the method, it was performed an analysis of the received ROI textures and extraction of the texture features, by using a Mazda tool. The results were compared and presented in the form of the radar graphs. The second approach proved to be effective and appropriate and consequently it is used for further analysis of CT images, in the computer-aided diagnosis of sarcoidosis.

Computer-aided assessment of pulmonary disease in novel swine-origin H1N1 influenza on CT

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Dwyer, Andrew J.; Summers, Ronald M.; Mollura, Daniel J.

2011-03-01

The 2009 pandemic is a global outbreak of novel H1N1 influenza. Radiologic images can be used to assess the presence and severity of pulmonary infection. We develop a computer-aided assessment system to analyze the CT images from Swine-Origin Influenza A virus (S-OIV) novel H1N1 cases. The technique is based on the analysis of lung texture patterns and classification using a support vector machine (SVM). Pixel-wise tissue classification is computed from the SVM value. The method was validated on four H1N1 cases and ten normal cases. We demonstrated that the technique can detect regions of pulmonary abnormality in novel H1N1 patients and differentiate these regions from visually normal lung (area under the ROC curve is 0.993). This technique can also be applied to differentiate regions infected by different pulmonary diseases.

Quantitative CT analysis of honeycombing area in idiopathic pulmonary fibrosis: Correlations with pulmonary function tests.

PubMed

Nakagawa, Hiroaki; Nagatani, Yukihiro; Takahashi, Masashi; Ogawa, Emiko; Tho, Nguyen Van; Ryujin, Yasushi; Nagao, Taishi; Nakano, Yasutaka

2016-01-01

The 2011 official statement of idiopathic pulmonary fibrosis (IPF) mentions that the extent of honeycombing and the worsening of fibrosis on high-resolution computed tomography (HRCT) in IPF are associated with the increased risk of mortality. However, there are few reports about the quantitative computed tomography (CT) analysis of honeycombing area. In this study, we first proposed a computer-aided method for quantitative CT analysis of honeycombing area in patients with IPF. We then evaluated the correlations between honeycombing area measured by the proposed method with that estimated by radiologists or with parameters of PFTs. Chest HRCTs and pulmonary function tests (PFTs) of 36 IPF patients, who were diagnosed using HRCT alone, were retrospectively evaluated. Two thoracic radiologists independently estimated the honeycombing area as Identified Area (IA) and the percentage of honeycombing area to total lung area as Percent Area (PA) on 3 axial CT slices for each patient. We also developed a computer-aided method to measure the honeycombing area on CT images of those patients. The total honeycombing area as CT honeycombing area (HA) and the percentage of honeycombing area to total lung area as CT %honeycombing area (%HA) were derived from the computer-aided method for each patient. HA derived from three CT slices was significantly correlated with IA (ρ=0.65 for Radiologist 1 and ρ=0.68 for Radiologist 2). %HA derived from three CT slices was also significantly correlated with PA (ρ=0.68 for Radiologist 1 and ρ=0.70 for Radiologist 2). HA and %HA derived from all CT slices were significantly correlated with FVC (%pred.), DLCO (%pred.), and the composite physiologic index (CPI) (HA: ρ=-0.43, ρ=-0.56, ρ=0.63 and %HA: ρ=-0.60, ρ=-0.49, ρ=0.69, respectively). The honeycombing area measured by the proposed computer-aided method was correlated with that estimated by expert radiologists and with parameters of PFTs. This quantitative CT analysis of honeycombing area may be useful and reliable in patients with IPF. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Computed tomography-assisted laparoscopic removal of intraabdominally migrated levonorgestrel-releasing intrauterine systems.

PubMed

Mahmoud, Mohamad S; Merhi, Zaher O

2010-04-01

To report three cases of migrated levonorgestrel intrauterine device (LNG-IUS) into the pelvic/abdominal cavity removed laparoscopically with the aid of preoperative computed tomography (CT) scan imaging. Three patients presenting with a missing LNG-IUS on examination and pelvic ultrasound are presented. A preoperative CT scan was performed, what helped in a successful removal of the LNG-IUS. The patients were discharged home the same day of the procedure. Our cases reinforce, besides the diagnosis of a migrated LNG-IUS by ultrasound, the fact that preoperative CT scan imaging assists in the diagnosis of the precise location of a migrated LNG-IUS into the pelvic/abdominal cavity and helps the physician in the prediction of the difficulty of the laparoscopic removal.

Use of CT imaging to examine the coarse roots, rhizomes, and peat associated with creek bank Spartina alterniflora in fertilized and control creeks in Plum Island (MA)

EPA Science Inventory

We used computer-aided tomography (CT) to quantify the wet mass, abundance, and diameter of coarse roots and rhizomes as well as the wet mass and particle density of marsh peat in 7-year fertilized and control creeks in Plum Island (MA). In shallow soils (0 – 10 cm) and at dep...

Texture classification of lung computed tomography images

NASA Astrophysics Data System (ADS)

Pheng, Hang See; Shamsuddin, Siti M.

2013-03-01

Current development of algorithms in computer-aided diagnosis (CAD) scheme is growing rapidly to assist the radiologist in medical image interpretation. Texture analysis of computed tomography (CT) scans is one of important preliminary stage in the computerized detection system and classification for lung cancer. Among different types of images features analysis, Haralick texture with variety of statistical measures has been used widely in image texture description. The extraction of texture feature values is essential to be used by a CAD especially in classification of the normal and abnormal tissue on the cross sectional CT images. This paper aims to compare experimental results using texture extraction and different machine leaning methods in the classification normal and abnormal tissues through lung CT images. The machine learning methods involve in this assessment are Artificial Immune Recognition System (AIRS), Naive Bayes, Decision Tree (J48) and Backpropagation Neural Network. AIRS is found to provide high accuracy (99.2%) and sensitivity (98.0%) in the assessment. For experiments and testing purpose, publicly available datasets in the Reference Image Database to Evaluate Therapy Response (RIDER) are used as study cases.

The Application of Contrast Media for In Vivo Feature Enhancement in X-Ray Computed Tomography of Soil-Grown Plant Roots.

PubMed

Keyes, Samuel D; Gostling, Neil J; Cheung, Jessica H; Roose, Tiina; Sinclair, Ian; Marchant, Alan

2017-06-01

The use of in vivo X-ray microcomputed tomography (μCT) to study plant root systems has become routine, but is often hampered by poor contrast between roots, soil, soil water, and soil organic matter. In clinical radiology, imaging of poorly contrasting regions is frequently aided by the use of radio-opaque contrast media. In this study, we present evidence for the utility of iodinated contrast media (ICM) in the study of plant root systems using μCT. Different dilutions of an ionic and nonionic ICM (Gastrografin 370 and Niopam 300) were perfused into the aerial vasculature of juvenile pea plants via a leaf flap (Pisum sativum). The root systems were imaged via μCT, and a variety of image-processing approaches used to quantify and compare the magnitude of the contrast enhancement between different regions. Though the treatment did not appear to significantly aid extraction of full root system architectures from the surrounding soil, it did allow the xylem and phloem units of seminal roots and the vascular morphology within rhizobial nodules to be clearly visualized. The nonionic, low-osmolality contrast agent Niopam appeared to be well tolerated by the plant, whereas Gastrografin showed evidence of toxicity. In summary, the use of iodine-based contrast media allows usually poorly contrasting root structures to be visualized nondestructively using X-ray μCT. In particular, the vascular structures of roots and rhizobial nodules can be clearly visualized in situ.

[Experience of Fusion image guided system in endonasal endoscopic surgery].

PubMed

Wen, Jingying; Zhen, Hongtao; Shi, Lili; Cao, Pingping; Cui, Yonghua

2015-08-01

To review endonasal endoscopic surgeries aided by Fusion image guided system, and to explore the application value of Fusion image guided system in endonasal endoscopic surgeries. Retrospective research. Sixty cases of endonasal endoscopic surgeries aided by Fusion image guided system were analysed including chronic rhinosinusitis with polyp (n = 10), fungus sinusitis (n = 5), endoscopic optic nerve decompression (n = 16), inverted papilloma of the paranasal sinus (n = 9), ossifying fibroma of sphenoid bone (n = 1), malignance of the paranasal sinus (n = 9), cerebrospinal fluid leak (n = 5), hemangioma of orbital apex (n = 2) and orbital reconstruction (n = 3). Sixty cases of endonasal endoscopic surgeries completed successfully without any complications. Fusion image guided system can help to identify the ostium of paranasal sinus, lamina papyracea and skull base. Fused CT-CTA images, or fused MR-MRA images can help to localize the optic nerve or internal carotid arteiy . Fused CT-MR images can help to detect the range of the tumor. It spent (7.13 ± 1.358) minutes for image guided system to do preoperative preparation and the surgical navigation accuracy reached less than 1mm after proficient. There was no device localization problem because of block or head set loosed. Fusion image guided system make endonasal endoscopic surgery to be a true microinvasive and exact surgery. It spends less preoperative preparation time, has high surgical navigation accuracy, improves the surgical safety and reduces the surgical complications.

A web-based procedure for liver segmentation in CT images

NASA Astrophysics Data System (ADS)

Yuan, Rong; Luo, Ming; Wang, Luyao; Xie, Qingguo

2015-03-01

Liver segmentation in CT images has been acknowledged as a basic and indispensable part in systems of computer aided liver surgery for operation design and risk evaluation. In this paper, we will introduce and implement a web-based procedure for liver segmentation to help radiologists and surgeons get an accurate result efficiently and expediently. Several clinical datasets are used to evaluate the accessibility and the accuracy. This procedure seems a promising approach for extraction of liver volumetry of various shapes. Moreover, it is possible for user to access the segmentation wherever the Internet is available without any specific machine.

Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

PubMed

Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

2015-06-01

The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kiryu, Takuji; Hoshi, Hiroaki

2004-05-01

We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.

Computer aided segmentation of kidneys using locally shape constrained deformable models on CT images

NASA Astrophysics Data System (ADS)

Erdt, Marius; Sakas, Georgios

2010-03-01

This work presents a novel approach for model based segmentation of the kidney in images acquired by Computed Tomography (CT). The developed computer aided segmentation system is expected to support computer aided diagnosis and operation planning. We have developed a deformable model based approach based on local shape constraints that prevents the model from deforming into neighboring structures while allowing the global shape to adapt freely to the data. Those local constraints are derived from the anatomical structure of the kidney and the presence and appearance of neighboring organs. The adaptation process is guided by a rule-based deformation logic in order to improve the robustness of the segmentation in areas of diffuse organ boundaries. Our work flow consists of two steps: 1.) a user guided positioning and 2.) an automatic model adaptation using affine and free form deformation in order to robustly extract the kidney. In cases which show pronounced pathologies, the system also offers real time mesh editing tools for a quick refinement of the segmentation result. Evaluation results based on 30 clinical cases using CT data sets show an average dice correlation coefficient of 93% compared to the ground truth. The results are therefore in most cases comparable to manual delineation. Computation times of the automatic adaptation step are lower than 6 seconds which makes the proposed system suitable for an application in clinical practice.

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.

Sci-Thur AM: YIS – 08: Automated Imaging Quality Assurance for Image-Guided Small Animal Irradiators

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

Johnstone, Chris; Bazalova-Carter, Magdalena

Purpose: To develop quality assurance (QA) standards and tolerance levels for image quality of small animal irradiators. Methods: A fully automated in-house QA software for image analysis of a commercial microCT phantom was created. Quantitative analyses of CT linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, modulation transfer function (MTF), and CT number evaluation was performed. Phantom microCT scans from seven institutions acquired with varying parameters (kVp, mA, time, voxel size, and frame rate) and five irradiator units (Xstrahl SARRP, PXI X-RAD 225Cx, PXI X-RAD SmART, GE explore CT/RT 140, and GE Explore CT 120) were analyzed. Multi-institutional datamore » sets were compared using our in-house software to establish pass/fail criteria for each QA test. Results: CT linearity (R2>0.996) was excellent at all but Institution 2. Acceptable SNR (>35) and noise levels (<55HU) were obtained at four of the seven institutions, where failing scans were acquired with less than 120mAs. Acceptable MTF (>1.5 lp/mm for MTF=0.2) was obtained at all but Institution 6 due to the largest scan voxel size (0.35mm). The geometric accuracy passed (<1.5%) at five of the seven institutions. Conclusion: Our QA software can be used to rapidly perform quantitative imaging QA for small animal irradiators, accumulate results over time, and display possible changes in imaging functionality from its original performance and/or from the recommended tolerance levels. This tool will aid researchers in maintaining high image quality, enabling precise conformal dose delivery to small animals.« less

Dictionary learning-based CT detection of pulmonary nodules

NASA Astrophysics Data System (ADS)

Wu, Panpan; Xia, Kewen; Zhang, Yanbo; Qian, Xiaohua; Wang, Ge; Yu, Hengyong

2016-10-01

Segmentation of lung features is one of the most important steps for computer-aided detection (CAD) of pulmonary nodules with computed tomography (CT). However, irregular shapes, complicated anatomical background and poor pulmonary nodule contrast make CAD a very challenging problem. Here, we propose a novel scheme for feature extraction and classification of pulmonary nodules through dictionary learning from training CT images, which does not require accurately segmented pulmonary nodules. Specifically, two classification-oriented dictionaries and one background dictionary are learnt to solve a two-category problem. In terms of the classification-oriented dictionaries, we calculate sparse coefficient matrices to extract intrinsic features for pulmonary nodule classification. The support vector machine (SVM) classifier is then designed to optimize the performance. Our proposed methodology is evaluated with the lung image database consortium and image database resource initiative (LIDC-IDRI) database, and the results demonstrate that the proposed strategy is promising.

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

Deformable anatomical templates for brachytherapy treatment planning in radiotherapy of cervical cancer

NASA Astrophysics Data System (ADS)

Christensen, Gary E.; Williamson, Jeffrey F.; Chao, K. S. C.; Miller, Michael I.; So, F. B.; Vannier, Michael W.

1997-10-01

This paper describes a new method to register serial, volumetric x-ray computed tomography (CT) data sets for tracking soft-tissue deformation caused by insertion of intracavity brachytherapy applicators to treat cervical cancer. 3D CT scans collected from the same patient with and without a brachytherapy applicator are registered to aid in computation of the radiation dose to tumor and normal tissue. The 3D CT image volume of pelvic anatomy with the applicator. Initial registration is accomplished by rigid alignment of the pelvic bones and non-rigid alignment of gray scale CT data and hand segmentations of the vagina, cervix, bladder, and rectum. A viscous fluid transformation model is used for non-rigid registration to allow for local, non-linear registration of the vagina, cervix, bladder, and rectum without disturbing the rigid registration of the bony pelvis and adjacent structures. Results are presented in which two 3D CT data sets of the same patient - imaged with and without a brachytherapy applicator - are registered.

A web-based computer aided system for liver surgery planning: initial implementation on RayPlus

NASA Astrophysics Data System (ADS)

Luo, Ming; Yuan, Rong; Sun, Zhi; Li, Tianhong; Xie, Qingguo

2016-03-01

At present, computer aided systems for liver surgery design and risk evaluation are widely used in clinical all over the world. However, most systems are local applications that run on high-performance workstations, and the images have to processed offline. Compared with local applications, a web-based system is accessible anywhere and for a range of regardless of relative processing power or operating system. RayPlus (http://rayplus.life.hust.edu.cn), a B/S platform for medical image processing, was developed to give a jump start on web-based medical image processing. In this paper, we implement a computer aided system for liver surgery planning on the architecture of RayPlus. The system consists of a series of processing to CT images including filtering, segmentation, visualization and analyzing. Each processing is packaged into an executable program and runs on the server side. CT images in DICOM format are processed step by to interactive modeling on browser with zero-installation and server-side computing. The system supports users to semi-automatically segment the liver, intrahepatic vessel and tumor from the pre-processed images. Then, surface and volume models are built to analyze the vessel structure and the relative position between adjacent organs. The results show that the initial implementation meets satisfactorily its first-order objectives and provide an accurate 3D delineation of the liver anatomy. Vessel labeling and resection simulation are planned to add in the future. The system is available on Internet at the link mentioned above and an open username for testing is offered.

Image-guided tissue engineering of anatomically shaped implants via MRI and micro-CT using injection molding.

PubMed

Ballyns, Jeffery J; Gleghorn, Jason P; Niebrzydowski, Vicki; Rawlinson, Jeremy J; Potter, Hollis G; Maher, Suzanne A; Wright, Timothy M; Bonassar, Lawrence J

2008-07-01

This study demonstrates for the first time the development of engineered tissues based on anatomic geometries derived from widely used medical imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). Computer-aided design and tissue injection molding techniques have demonstrated the ability to generate living implants of complex geometry. Due to its complex geometry, the meniscus of the knee was used as an example of this technique's capabilities. MRI and microcomputed tomography (microCT) were used to design custom-printed molds that enabled the generation of anatomically shaped constructs that retained shape throughout 8 weeks of culture. Engineered constructs showed progressive tissue formation indicated by increases in extracellular matrix content and mechanical properties. The paradigm of interfacing tissue injection molding technology can be applied to other medical imaging techniques that render 3D models of anatomy, demonstrating the potential to apply the current technique to engineering of many tissues and organs.

Microstructural characterization of multiphase chocolate using X-ray microtomography.

PubMed

Frisullo, Pierangelo; Licciardello, Fabio; Muratore, Giuseppe; Del Nobile, Matteo Alessandro

2010-09-01

In this study, X-ray microtomography (μCT) was used for the image analysis of the microstructure of 12 types of Italian aerated chocolate chosen to exhibit variability in terms of cocoa mass content. Appropriate quantitative 3-dimensional parameters describing the microstructure were calculated, for example, the structure thickness (ST), object structure volume ratio (OSVR), and the percentage object volume (POV). Chemical analysis was also performed to correlate the microstructural data to the chemical composition of the samples. Correlation between the μCT parameters acquired for the pore microstructure evaluation and the chemical analysis revealed that the sugar crystals content does not influence the pore structure and content. On the other hand, it revealed that there is a strong correlation between the POV and the sugar content obtained by chemical analysis. The results from this study show that μCT is a suitable technique for the microstructural analysis of confectionary products such as chocolates and not only does it provide an accurate analysis of the pores and microstructure but the data obtained could also be used to aid in the assessment of its composition and consistency with label specifications. X-ray microtomography (μCT) is a noninvasive and nondestructive 3-D imaging technique that has several advantages over other methods, including the ability to image low-moisture materials. Given the enormous success of μCT in medical applications, material science, chemical engineering, geology, and biology, it is not surprising that in recent years much attention has been focused on extending this imaging technique to food science as a useful technique to aid in the study of food microstructure. X-ray microtomography provides in-depth information on the microstructure of the food product being tested; therefore, a better understanding of the physical structure of the product and from an engineering perspective, knowledge about the microstructure of foods can be used to identify the important processing parameters that affect the quality of a product.

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.

Computer aided diagnosis and treatment planning for developmental dysplasia of the hip

NASA Astrophysics Data System (ADS)

Li, Bin; Lu, Hongbing; Cai, Wenli; Li, Xiang; Meng, Jie; Liang, Zhengrong

2005-04-01

The developmental dysplasia of the hip (DDH) is a congenital malformation affecting the proximal femurs and acetabulum that are subluxatable, dislocatable, and dislocated. Early diagnosis and treatment is important because failure to diagnose and improper treatment can result in significant morbidity. In this paper, we designed and implemented a computer aided system for the diagnosis and treatment planning of this disease. With the design, the patient received CT (computed tomography) or MRI (magnetic resonance imaging) scan first. A mixture-based PV partial-volume algorithm was applied to perform bone segmentation on CT image, followed by three-dimensional (3D) reconstruction and display of the segmented image, demonstrating the special relationship between the acetabulum and femurs for visual judgment. Several standard procedures, such as Salter procedure, Pemberton procedure and Femoral Shortening osteotomy, were simulated on the screen to rehearse a virtual treatment plan. Quantitative measurement of Acetabular Index (AI) and Femoral Neck Anteversion (FNA) were performed on the 3D image for evaluation of DDH and treatment plans. PC graphics-card GPU architecture was exploited to accelerate the 3D rendering and geometric manipulation. The prototype system was implemented on PC/Windows environment and is currently under clinical trial on patient datasets.

A convolutional neural network for intracranial hemorrhage detection in non-contrast CT

NASA Astrophysics Data System (ADS)

Patel, Ajay; Manniesing, Rashindra

2018-02-01

The assessment of the presence of intracranial hemorrhage is a crucial step in the work-up of patients requiring emergency care. Fast and accurate detection of intracranial hemorrhage can aid treating physicians by not only expediting and guiding diagnosis, but also supporting choices for secondary imaging, treatment and intervention. However, the automatic detection of intracranial hemorrhage is complicated by the variation in appearance on non-contrast CT images as a result of differences in etiology and location. We propose a method using a convolutional neural network (CNN) for the automatic detection of intracranial hemorrhage. The method is trained on a dataset comprised of cerebral CT studies for which the presence of hemorrhage has been labeled for each axial slice. A separate test dataset of 20 images is used for quantitative evaluation and shows a sensitivity of 0.87, specificity of 0.97 and accuracy of 0.95. The average processing time for a single three-dimensional (3D) CT volume was 2.7 seconds. The proposed method is capable of fast and automated detection of intracranial hemorrhages in non-contrast CT without being limited to a specific subtype of pathology.

Computer-Aided Diagnosis of Splenic Enlargement Using Wave Pattern of Spleen in Abdominal CT Images: Initial Observations

NASA Astrophysics Data System (ADS)

Seong, Won; Cho, June-Sik; Noh, Seung-Moo; Park, Jong-Won

In general, the spleen accompanied by abnormal abdomen is hypertrophied. However, if the spleen size is originally small, it is hard to detect the splenic enlargement due to abnormal abdomen by simply measure the size. On the contrary, the spleen size of a person having a normal abdomen may be large by nature. Therefore, measuring the size of spleen is not a reliable diagnostic measure of its enlargement or the abdomen abnormality. This paper proposes an automatic method to diagnose the splenic enlargement due to abnormality, by examining the boundary pattern of spleen in abdominal CT images.

Technical Note: Image filtering to make computer-aided detection robust to image reconstruction kernel choice in lung cancer CT screening

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

Ohkubo, Masaki, E-mail: mook@clg.niigata-u.ac.jp

Purpose: In lung cancer computed tomography (CT) screening, the performance of a computer-aided detection (CAD) system depends on the selection of the image reconstruction kernel. To reduce this dependence on reconstruction kernels, the authors propose a novel application of an image filtering method previously proposed by their group. Methods: The proposed filtering process uses the ratio of modulation transfer functions (MTFs) of two reconstruction kernels as a filtering function in the spatial-frequency domain. This method is referred to as MTF{sub ratio} filtering. Test image data were obtained from CT screening scans of 67 subjects who each had one nodule. Imagesmore » were reconstructed using two kernels: f{sub STD} (for standard lung imaging) and f{sub SHARP} (for sharp edge-enhancement lung imaging). The MTF{sub ratio} filtering was implemented using the MTFs measured for those kernels and was applied to the reconstructed f{sub SHARP} images to obtain images that were similar to the f{sub STD} images. A mean filter and a median filter were applied (separately) for comparison. All reconstructed and filtered images were processed using their prototype CAD system. Results: The MTF{sub ratio} filtered images showed excellent agreement with the f{sub STD} images. The standard deviation for the difference between these images was very small, ∼6.0 Hounsfield units (HU). However, the mean and median filtered images showed larger differences of ∼48.1 and ∼57.9 HU from the f{sub STD} images, respectively. The free-response receiver operating characteristic (FROC) curve for the f{sub SHARP} images indicated poorer performance compared with the FROC curve for the f{sub STD} images. The FROC curve for the MTF{sub ratio} filtered images was equivalent to the curve for the f{sub STD} images. However, this similarity was not achieved by using the mean filter or median filter. Conclusions: The accuracy of MTF{sub ratio} image filtering was verified and the method was demonstrated to be effective for reducing the kernel dependence of CAD performance.« less

Dual-energy CT revisited with multidetector CT: review of principles and clinical applications.

PubMed

Karçaaltıncaba, Muşturay; Aktaş, Aykut

2011-09-01

Although dual-energy CT (DECT) was first conceived in the 1970s, it was not widely used for CT indications. Recently, the simultaneous acquisition of volumetric dual-energy data has been introduced using multidetector CT (MDCT) with two X-ray tubes and rapid kVp switching (gemstone spectral imaging). Two major advantages of DECT are material decomposition by acquiring two image series with different kVp and the elimination of misregistration artifacts. Hounsfield unit measurements by DECT are not absolute and can change depending on the kVp used for an acquisition. Typically, a combination of 80/140 kVp is used for DECT, but for some applications, 100/140 kVp is preferred. In this study, we summarized the clinical applications of DECT and included images that were acquired using the dual-source CT and rapid kVp switching. In general, unenhanced images can be avoided by using DECT for body and neurological applications; iodine can be removed from the image, and a virtual, non-contrast (water) image can be obtained. Neuroradiological applications allow for the removal of bone and calcium from the carotid and brain CT angiography. Thorax applications include perfusion imaging in patients with pulmonary thromboemboli and other chest diseases, xenon ventilation-perfusion imaging and solitary nodule characterization. Cardiac applications include dual-energy cardiac perfusion, viability and cardiac iron detection. The removal of calcific plaques from arteries, bone removal and aortic stent graft evaluation may be achieved in the vascular system. Abdominal applications include the detection and characterization of liver and pancreas masses, the diagnosis of steatosis and iron overload, DECT colonoscopy and CT cholangiography. Urinary system applications are urinary calculi characterization (uric acid vs. non-uric acid), renal cyst characterization and mass characterization. Musculoskeletal applications permit the differentiation of gout from pseudogout and a reduction of metal artifacts. Recent introduction of iterative reconstruction techniques can increase the use of DECT techniques; the use of dual energy in patients with a high BMI is limited due to noise and the radiation dose. DECT may be a good alternative to PET-CT. Iodine map images can quantify iodine uptake, and this approach may be more effective than obtaining non-contrast and post-contrast images for the diagnosis of a solid mass. Thus, computer-aided detection may be used more effectively in CT applications. DECT is a promising technique with potential clinical applications.

Computer-Aided Classification of Visual Ventilation Patterns in Patients with Chronic Obstructive Pulmonary Disease at Two-Phase Xenon-Enhanced CT

PubMed Central

Yoon, Soon Ho; Jung, Julip; Hong, Helen; Park, Eun Ah; Lee, Chang Hyun; Lee, Youkyung; Jin, Kwang Nam; Choo, Ji Yung; Lee, Nyoung Keun

2014-01-01

Objective To evaluate the technical feasibility, performance, and interobserver agreement of a computer-aided classification (CAC) system for regional ventilation at two-phase xenon-enhanced CT in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods Thirty-eight patients with COPD underwent two-phase xenon ventilation CT with resulting wash-in (WI) and wash-out (WO) xenon images. The regional ventilation in structural abnormalities was visually categorized into four patterns by consensus of two experienced radiologists who compared the xenon attenuation of structural abnormalities with that of adjacent normal parenchyma in the WI and WO images, and it served as the reference. Two series of image datasets of structural abnormalities were randomly extracted for optimization and validation. The proportion of agreement on a per-lesion basis and receiver operating characteristics on a per-pixel basis between CAC and reference were analyzed for optimization. Thereafter, six readers independently categorized the regional ventilation in structural abnormalities in the validation set without and with a CAC map. Interobserver agreement was also compared between assessments without and with CAC maps using multirater κ statistics. Results Computer-aided classification maps were successfully generated in 31 patients (81.5%). The proportion of agreement and the average area under the curve of optimized CAC maps were 94% (75/80) and 0.994, respectively. Multirater κ value was improved from moderate (κ = 0.59; 95% confidence interval [CI], 0.56-0.62) at the initial assessment to excellent (κ = 0.82; 95% CI, 0.79-0.85) with the CAC map. Conclusion Our proposed CAC system demonstrated the potential for regional ventilation pattern analysis and enhanced interobserver agreement on visual classification of regional ventilation. PMID:24843245

Computer-aided classification of visual ventilation patterns in patients with chronic obstructive pulmonary disease at two-phase xenon-enhanced CT.

PubMed

Yoon, Soon Ho; Goo, Jin Mo; Jung, Julip; Hong, Helen; Park, Eun Ah; Lee, Chang Hyun; Lee, Youkyung; Jin, Kwang Nam; Choo, Ji Yung; Lee, Nyoung Keun

2014-01-01

To evaluate the technical feasibility, performance, and interobserver agreement of a computer-aided classification (CAC) system for regional ventilation at two-phase xenon-enhanced CT in patients with chronic obstructive pulmonary disease (COPD). Thirty-eight patients with COPD underwent two-phase xenon ventilation CT with resulting wash-in (WI) and wash-out (WO) xenon images. The regional ventilation in structural abnormalities was visually categorized into four patterns by consensus of two experienced radiologists who compared the xenon attenuation of structural abnormalities with that of adjacent normal parenchyma in the WI and WO images, and it served as the reference. Two series of image datasets of structural abnormalities were randomly extracted for optimization and validation. The proportion of agreement on a per-lesion basis and receiver operating characteristics on a per-pixel basis between CAC and reference were analyzed for optimization. Thereafter, six readers independently categorized the regional ventilation in structural abnormalities in the validation set without and with a CAC map. Interobserver agreement was also compared between assessments without and with CAC maps using multirater κ statistics. Computer-aided classification maps were successfully generated in 31 patients (81.5%). The proportion of agreement and the average area under the curve of optimized CAC maps were 94% (75/80) and 0.994, respectively. Multirater κ value was improved from moderate (κ = 0.59; 95% confidence interval [CI], 0.56-0.62) at the initial assessment to excellent (κ = 0.82; 95% CI, 0.79-0.85) with the CAC map. Our proposed CAC system demonstrated the potential for regional ventilation pattern analysis and enhanced interobserver agreement on visual classification of regional ventilation.

Computer-aided diagnosis and artificial intelligence in clinical imaging.

PubMed

Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Doi, Kunio

2011-11-01

Computer-aided diagnosis (CAD) is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work for the detection of breast cancer with mammograms. The computer output is used as a "second opinion" in assisting radiologists' image interpretations. The computer algorithm generally consists of several steps that may include image processing, image feature analysis, and data classification via the use of tools such as artificial neural networks (ANN). In this article, we will explore these and other current processes that have come to be referred to as "artificial intelligence." One element of CAD, temporal subtraction, has been applied for enhancing interval changes and for suppressing unchanged structures (eg, normal structures) between 2 successive radiologic images. To reduce misregistration artifacts on the temporal subtraction images, a nonlinear image warping technique for matching the previous image to the current one has been developed. Development of the temporal subtraction method originated with chest radiographs, with the method subsequently being applied to chest computed tomography (CT) and nuclear medicine bone scans. The usefulness of the temporal subtraction method for bone scans was demonstrated by an observer study in which reading times and diagnostic accuracy improved significantly. An additional prospective clinical study verified that the temporal subtraction image could be used as a "second opinion" by radiologists with negligible detrimental effects. ANN was first used in 1990 for computerized differential diagnosis of interstitial lung diseases in CAD. Since then, ANN has been widely used in CAD schemes for the detection and diagnosis of various diseases in different imaging modalities, including the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography, CT, and position emission tomography/CT. It is likely that CAD will be integrated into picture archiving and communication systems and will become a standard of care for diagnostic examinations in daily clinical work. Copyright © 2011 Elsevier Inc. All rights reserved.

Multi-institutional MicroCT image comparison of image-guided small animal irradiators

NASA Astrophysics Data System (ADS)

Johnstone, Chris D.; Lindsay, Patricia; E Graves, Edward; Wong, Eugene; Perez, Jessica R.; Poirier, Yannick; Ben-Bouchta, Youssef; Kanesalingam, Thilakshan; Chen, Haijian; E Rubinstein, Ashley; Sheng, Ke; Bazalova-Carter, Magdalena

2017-07-01

To recommend imaging protocols and establish tolerance levels for microCT image quality assurance (QA) performed on conformal image-guided small animal irradiators. A fully automated QA software SAPA (small animal phantom analyzer) for image analysis of the commercial Shelley micro-CT MCTP 610 phantom was developed, in which quantitative analyses of CT number linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, spatial resolution by means of modulation transfer function (MTF), and CT contrast were performed. Phantom microCT scans from eleven institutions acquired with four image-guided small animal irradiator units (including the commercial PXi X-RAD SmART and Xstrahl SARRP systems) with varying parameters used for routine small animal imaging were analyzed. Multi-institutional data sets were compared using SAPA, based on which tolerance levels for each QA test were established and imaging protocols for QA were recommended. By analyzing microCT data from 11 institutions, we established image QA tolerance levels for all image quality tests. CT number linearity set to R 2  >  0.990 was acceptable in microCT data acquired at all but three institutions. Acceptable SNR  >  36 and noise levels  <55 HU were obtained at five of the eleven institutions, where failing scans were acquired with current-exposure time of less than 120 mAs. Acceptable spatial resolution (>1.5 lp mm-1 for MTF  =  0.2) was obtained at all but four institutions due to their large image voxel size used (>0.275 mm). Ten of the eleven institutions passed the set QA tolerance for geometric accuracy (<1.5%) and nine of the eleven institutions passed the QA tolerance for contrast (>2000 HU for 30 mgI ml-1). We recommend performing imaging QA with 70 kVp, 1.5 mA, 120 s imaging time, 0.20 mm voxel size, and a frame rate of 5 fps for the PXi X-RAD SmART. For the Xstrahl SARRP, we recommend using 60 kVp, 1.0 mA, 240 s imaging time, 0.20 mm voxel size, and 6 fps. These imaging protocols should result in high quality images that pass the set tolerance levels on all systems. Average SAPA computation time for complete QA analysis for a 0.20 mm voxel, 400 slice Shelley phantom microCT data set was less than 20 s. We present image quality assurance recommendations for image-guided small animal radiotherapy systems that can aid researchers in maintaining high image quality, allowing for spatially precise conformal dose delivery to small animals.

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.

Optical imaging: new tools for arthritis.

PubMed

Chamberland, David; Jiang, Yebin; Wang, Xueding

2010-10-01

Conventional radiography, ultrasound, CT, MRI, and nuclear imaging are the current imaging modalities used for clinical evaluation of arthritis which is highly prevalent and a leading cause of disability. Some of these types of imaging are also used for monitoring disease progression and treatment response of arthritis. However, their disadvantages limit their utilities, such as ionizing radiation for radiography, CT, and nuclear imaging; suboptimal tissue contrast resolution for radiography, CT, ultrasound, and nuclear imaging; high cost for CT and MRI and nuclear imaging; and long data-acquisition time with ensuing patient discomfort for MRI. Recently, there have been considerable advances in nonionizing noninvasive optical imaging which has demonstrated promise for early diagnosis, monitoring therapeutic interventions and disease progression of arthritis. Optical based molecular imaging modalities such as fluorescence imaging have shown high sensitivity in detection of optical contrast agents and can aid early diagnosis and ongoing evaluation of chronic inflammatory arthritis. Optical transillumination imaging or diffuse optical tomography may differentiate normal joint clear synovial fluid from turbid and pink medium early in the inflammatory process. Fourier transform infrared spectroscopy has been used to evaluate fluid composition from joints affected by arthritis. Hemodynamic changes such as angiogenesis, hypervascularization, and hypoxia in arthritic articular tissue can potentially be observed by diffuse optical tomography and photoacoustic tomography. Optical measurements could also facilitate quantification of hemodynamic properties such as blood volume and oxygenation levels at early stages of inflammatory arthritis. Optical imaging provides methodologies which should contribute to detection of early changes and monitoring of progression in pathological characteristics of arthritis, with relatively simple instrumentation.

The bone scan.

PubMed

Brenner, Arnold I; Koshy, June; Morey, Jose; Lin, Cheryl; DiPoce, Jason

2012-01-01

Bone imaging continues to be the second greatest-volume nuclear imaging procedure, offering the advantage of total body examination, low cost, and high sensitivity. Its power rests in the physiological uptake and pathophysiologic behavior of 99m technetium (99m-Tc) diphosphonates. The diagnostic utility, sensitivity, specificity, and predictive value of 99m-Tc bone imaging for benign conditions and tumors was established when only planar imaging was available. Currently, nearly all bone scans are performed as a planar study (whole-body, 3-phase, or regional), with the radiologist often adding single-photon emission computed tomography (SPECT) imaging. Here we review many current indications for planar bone imaging, highlighting indications in which the planar data are often diagnostically sufficient, although diagnosis may be enhanced by SPECT. (18)F sodium fluoride positron emission tomography (PET) is also re-emerging as a bone agent, and had been considered interchangeable with 99m-Tc diphosphonates in the past. In addition to SPECT, new imaging modalities, including (18)F fluorodeoxyglucose, PET/CT, CT, magnetic resonance, and SPECT/CT, have been developed and can aid in evaluating benign and malignant bone disease. Because (18)F fluorodeoxyglucose is taken up by tumor cells and Tc diphosphonates are taken up in osteoblastic activity or osteoblastic healing reaction, both modalities are complementary. CT and magnetic resonance may supplement, but do not replace, bone imaging, which often detects pathology before anatomic changes are appreciated. We also stress the importance of dose reduction by reducing the dose of 99m-Tc diphosphonates and avoiding unnecessary CT acquisitions. In addition, we describe an approach to image interpretation that emphasizes communication with referring colleagues and correlation with appropriate history to significantly improve our impact on patient care. Copyright © 2012 Elsevier Inc. All rights reserved.

Molecular Imaging of Influenza and Other Emerging Respiratory Viral Infections

PubMed Central

Lawler, James; Paragas, Jason; Jahrling, Peter B.; Mollura, Daniel J.

2011-01-01

Research on the pathogenesis and therapy of influenza and other emerging respiratory viral infections would be aided by methods that directly visualize pathophysiologic processes in patients and laboratory animals. At present, imaging of diseases, such as swine-origin H1N1 influenza, is largely restricted to chest radiograph and computed tomography (CT), which can detect pulmonary structural changes in severely ill patients but are more limited in characterizing the early stages of illness, differentiating inflammation from infection or tracking immune responses. In contrast, imaging modalities, such as positron emission tomography, single photon emission CT, magnetic resonance imaging, and bioluminescence imaging, which have become useful tools for investigating the pathogenesis of a range of disease processes, could be used to advance in vivo studies of respiratory viral infections in patients and animals. Molecular techniques might also be used to identify novel biomarkers of disease progression and to evaluate new therapies. PMID:21422476

The Added Value of a Single-photon Emission Computed Tomography-Computed Tomography in Sentinel Lymph Node Mapping in Patients with Breast Cancer and Malignant Melanoma.

PubMed

Bennie, George; Vorster, Mariza; Buscombe, John; Sathekge, Mike

2015-01-01

Single-photon emission computed tomography-computed tomography (SPECT-CT) allows for physiological and anatomical co-registration in sentinel lymph node (SLN) mapping and offers additional benefits over conventional planar imaging. However, the clinical relevance when considering added costs and radiation burden of these reported benefits remains somewhat uncertain. This study aimed to evaluate the possible added value of SPECT-CT and intra-operative gamma-probe use over planar imaging alone in the South African setting. 80 patients with breast cancer or malignant melanoma underwent both planar and SPECT-CT imaging for SLN mapping. We assessed and compared the number of nodes detected on each study, false positive and negative findings, changes in surgical approach and or patient management. In all cases where a sentinel node was identified, SPECT-CT was more accurate anatomically. There was a significant change in surgical approach in 30 cases - breast cancer (n = 13; P 0.001) and malignant melanoma (n = 17; P 0.0002). In 4 cases a node not identified on planar imaging was seen on SPECT-CT. In 16 cases additional echelon nodes were identified. False positives were excluded by SPECT-CT in 12 cases. The addition of SPECT-CT and use of intra-operative gamma-probe to planar imaging offers important benefits in patients who present with breast cancer and melanoma. These benefits include increased nodal detection, elimination of false positives and negatives and improved anatomical localization that ultimately aids and expedites surgical management. This has been demonstrated in the context of industrialized country previously and has now also been confirmed in the setting of a emerging-market nation.

Benefit from NASA

NASA Image and Video Library

2001-09-01

The high-tech art of digital signal processing (DSP) was pioneered at NASA's Jet Propulsion Laboratory (JPL) in the mid-1960s for use in the Apollo Lunar Landing Program. Designed to computer enhance pictures of the Moon, this technology became the basis for the Landsat Earth resources satellites and subsequently has been incorporated into a broad range of Earthbound medical and diagnostic tools. DSP is employed in advanced body imaging techniques including Computer-Aided Tomography, also known as CT and CATScan, and Magnetic Resonance Imaging (MRI). CT images are collected by irradiating a thin slice of the body with a fan-shaped x-ray beam from a number of directions around the body's perimeter. A tomographic (slice-like) picture is reconstructed from these multiple views by a computer. MRI employs a magnetic field and radio waves, rather than x-rays, to create images.

Segmentation, surface rendering, and surface simplification of 3-D skull images for the repair of a large skull defect

NASA Astrophysics Data System (ADS)

Wan, Weibing; Shi, Pengfei; Li, Shuguang

2009-10-01

Given the potential demonstrated by research into bone-tissue engineering, the use of medical image data for the rapid prototyping (RP) of scaffolds is a subject worthy of research. Computer-aided design and manufacture and medical imaging have created new possibilities for RP. Accurate and efficient design and fabrication of anatomic models is critical to these applications. We explore the application of RP computational methods to the repair of a pediatric skull defect. The focus of this study is the segmentation of the defect region seen in computerized tomography (CT) slice images of this patient's skull and the three-dimensional (3-D) surface rendering of the patient's CT-scan data. We see if our segmentation and surface rendering software can improve the generation of an implant model to fill a skull defect.

Self-assembled gold coating enhances X-ray imaging of alginate microcapsules

NASA Astrophysics Data System (ADS)

Qie, Fengxiang; Astolfo, Alberto; Wickramaratna, Malsha; Behe, Martin; Evans, Margaret D. M.; Hughes, Timothy C.; Hao, Xiaojuan; Tan, Tianwei

2015-01-01

Therapeutic biomolecules produced from cells encapsulated within alginate microcapsules (MCs) offer a potential treatment for a number of diseases. However the fate of such MCs once implanted into the body is difficult to establish. Labelling the MCs with medical imaging contrast agents may aid their detection and give researchers the ability to track them over time thus aiding the development of such cellular therapies. Here we report the preparation of MCs with a self-assembled gold nanoparticle (AuNPs) coating which results in distinctive contrast and enables them to be readily identified using a conventional small animal X-ray micro-CT scanner. Cationic Reversible Addition-Fragmentation chain Transfer (RAFT) homopolymer modified AuNPs (PAuNPs) were coated onto the surface of negatively charged alginate MCs resulting in hybrids which possessed low cytotoxicity and high mechanical stability in vitro. As a result of their high localized Au concentration, the hybrid MCs exhibited a distinctive bright circular ring even with a low X-ray dose and rapid scanning in post-mortem imaging experiments facilitating their positive identification and potentially enabling them to be used for in vivo tracking experiments over multiple time-points.Therapeutic biomolecules produced from cells encapsulated within alginate microcapsules (MCs) offer a potential treatment for a number of diseases. However the fate of such MCs once implanted into the body is difficult to establish. Labelling the MCs with medical imaging contrast agents may aid their detection and give researchers the ability to track them over time thus aiding the development of such cellular therapies. Here we report the preparation of MCs with a self-assembled gold nanoparticle (AuNPs) coating which results in distinctive contrast and enables them to be readily identified using a conventional small animal X-ray micro-CT scanner. Cationic Reversible Addition-Fragmentation chain Transfer (RAFT) homopolymer modified AuNPs (PAuNPs) were coated onto the surface of negatively charged alginate MCs resulting in hybrids which possessed low cytotoxicity and high mechanical stability in vitro. As a result of their high localized Au concentration, the hybrid MCs exhibited a distinctive bright circular ring even with a low X-ray dose and rapid scanning in post-mortem imaging experiments facilitating their positive identification and potentially enabling them to be used for in vivo tracking experiments over multiple time-points. Electronic supplementary information (ESI) available: Including NMR spectra and TGA chromatogram of polymers, SEM imaging, EDS analysis, UV-Visible spectra of MCs and CT images of unlabeled MCs. See DOI: 10.1039/c4nr06692h

Hybrid detection of lung nodules on CT scan images

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

Lu, Lin; Tan, Yongqiang; Schwartz, Lawrence H.

Purpose: The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. Methods: The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithmsmore » were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. Results: The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%. Conclusions: The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.« less

Deep 3D convolution neural network for CT brain hemorrhage classification

NASA Astrophysics Data System (ADS)

Jnawali, Kamal; Arbabshirani, Mohammad R.; Rao, Navalgund; Patel, Alpen A.

2018-02-01

Intracranial hemorrhage is a critical conditional with the high mortality rate that is typically diagnosed based on head computer tomography (CT) images. Deep learning algorithms, in particular, convolution neural networks (CNN), are becoming the methodology of choice in medical image analysis for a variety of applications such as computer-aided diagnosis, and segmentation. In this study, we propose a fully automated deep learning framework which learns to detect brain hemorrhage based on cross sectional CT images. The dataset for this work consists of 40,367 3D head CT studies (over 1.5 million 2D images) acquired retrospectively over a decade from multiple radiology facilities at Geisinger Health System. The proposed algorithm first extracts features using 3D CNN and then detects brain hemorrhage using the logistic function as the last layer of the network. Finally, we created an ensemble of three different 3D CNN architectures to improve the classification accuracy. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve of the ensemble of three architectures was 0.87. Their results are very promising considering the fact that the head CT studies were not controlled for slice thickness, scanner type, study protocol or any other settings. Moreover, the proposed algorithm reliably detected various types of hemorrhage within the skull. This work is one of the first applications of 3D CNN trained on a large dataset of cross sectional medical images for detection of a critical radiological condition

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.

Quantifying Three-Dimensional Morphology and RNA from Individual Embryos

PubMed Central

Green, Rebecca M.; Leach, Courtney L.; Hoehn, Natasha; Marcucio, Ralph S.; Hallgrímsson, Benedikt

2017-01-01

Quantitative analysis of morphogenesis aids our understanding of developmental processes by providing a method to link changes in shape with cellular and molecular processes. Over the last decade many methods have been developed for 3D imaging of embryos using microCT scanning to quantify the shape of embryos during development. These methods generally involve a powerful, cross-linking fixative such as paraformaldehyde to limit shrinkage during the CT scan. However, the extended time frames that these embryos are incubated in such fixatives prevent use of the tissues for molecular analysis after microCT scanning. This is a significant problem because it limits the ability to correlate variation in molecular data with morphology at the level of individual embryos. Here, we outline a novel method that allows RNA, DNA or protein isolation following CT scan while also allowing imaging of different tissue layers within the developing embryo. We show shape differences early in craniofacial development (E11.5) between common mouse genetic backgrounds, and demonstrate that we are able to generate RNA from these embryos after CT scanning that is suitable for downstream RT-PCR and RNAseq analyses. PMID:28152580

Multi-organ segmentation from multi-phase abdominal CT via 4D graphs using enhancement, shape and location optimization.

PubMed

Linguraru, Marius George; Pura, John A; Chowdhury, Ananda S; Summers, Ronald M

2010-01-01

The interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis (CAD) applications. Diagnosis also relies on the comprehensive analysis of multiple organs and quantitative measures of soft tissue. An automated method optimized for medical image data is presented for the simultaneous segmentation of four abdominal organs from 4D CT data using graph cuts. Contrast-enhanced CT scans were obtained at two phases: non-contrast and portal venous. Intra-patient data were spatially normalized by non-linear registration. Then 4D erosion using population historic information of contrast-enhanced liver, spleen, and kidneys was applied to multi-phase data to initialize the 4D graph and adapt to patient specific data. CT enhancement information and constraints on shape, from Parzen windows, and location, from a probabilistic atlas, were input into a new formulation of a 4D graph. Comparative results demonstrate the effects of appearance and enhancement, and shape and location on organ segmentation.

Imaging of brain metastases.

PubMed

Fink, Kathleen R; Fink, James R

2013-01-01

Imaging plays a key role in the diagnosis of central nervous system (CNS) metastasis. Imaging is used to detect metastases in patients with known malignancies and new neurological signs or symptoms, as well as to screen for CNS involvement in patients with known cancer. Computed tomography (CT) and magnetic resonance imaging (MRI) are the key imaging modalities used in the diagnosis of brain metastases. In difficult cases, such as newly diagnosed solitary enhancing brain lesions in patients without known malignancy, advanced imaging techniques including proton magnetic resonance spectroscopy (MRS), contrast enhanced magnetic resonance perfusion (MRP), diffusion weighted imaging (DWI), and diffusion tensor imaging (DTI) may aid in arriving at the correct diagnosis. This image-rich review discusses the imaging evaluation of patients with suspected intracranial involvement and malignancy, describes typical imaging findings of parenchymal brain metastasis on CT and MRI, and provides clues to specific histological diagnoses such as the presence of hemorrhage. Additionally, the role of advanced imaging techniques is reviewed, specifically in the context of differentiating metastasis from high-grade glioma and other solitary enhancing brain lesions. Extra-axial CNS involvement by metastases, including pachymeningeal and leptomeningeal metastases is also briefly reviewed.

Pulmonary nodule characterization, including computer analysis and quantitative features.

PubMed

Bartholmai, Brian J; Koo, Chi Wan; Johnson, Geoffrey B; White, Darin B; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Moynagh, Michael R; Lindell, Rebecca M; Hartman, Thomas E

2015-03-01

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

Accuracy and efficiency of computer-aided anatomical analysis using 3D visualization software based on semi-automated and automated segmentations.

PubMed

An, Gao; Hong, Li; Zhou, Xiao-Bing; Yang, Qiong; Li, Mei-Qing; Tang, Xiang-Yang

2017-03-01

We investigated and compared the functionality of two 3D visualization software provided by a CT vendor and a third-party vendor, respectively. Using surgical anatomical measurement as baseline, we evaluated the accuracy of 3D visualization and verified their utility in computer-aided anatomical analysis. The study cohort consisted of 50 adult cadavers fixed with the classical formaldehyde method. The computer-aided anatomical analysis was based on CT images (in DICOM format) acquired by helical scan with contrast enhancement, using a CT vendor provided 3D visualization workstation (Syngo) and a third-party 3D visualization software (Mimics) that was installed on a PC. Automated and semi-automated segmentations were utilized in the 3D visualization workstation and software, respectively. The functionality and efficiency of automated and semi-automated segmentation methods were compared. Using surgical anatomical measurement as a baseline, the accuracy of 3D visualization based on automated and semi-automated segmentations was quantitatively compared. In semi-automated segmentation, the Mimics 3D visualization software outperformed the Syngo 3D visualization workstation. No significant difference was observed in anatomical data measurement by the Syngo 3D visualization workstation and the Mimics 3D visualization software (P>0.05). Both the Syngo 3D visualization workstation provided by a CT vendor and the Mimics 3D visualization software by a third-party vendor possessed the needed functionality, efficiency and accuracy for computer-aided anatomical analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

Impact of deep learning on the normalization of reconstruction kernel effects in imaging biomarker quantification: a pilot study in CT emphysema

NASA Astrophysics Data System (ADS)

Jin, Hyeongmin; Heo, Changyong; Kim, Jong Hyo

2018-02-01

Differing reconstruction kernels are known to strongly affect the variability of imaging biomarkers and thus remain as a barrier in translating the computer aided quantification techniques into clinical practice. This study presents a deep learning application to CT kernel conversion which converts a CT image of sharp kernel to that of standard kernel and evaluates its impact on variability reduction of a pulmonary imaging biomarker, the emphysema index (EI). Forty cases of low-dose chest CT exams obtained with 120kVp, 40mAs, 1mm thickness, of 2 reconstruction kernels (B30f, B50f) were selected from the low dose lung cancer screening database of our institution. A Fully convolutional network was implemented with Keras deep learning library. The model consisted of symmetric layers to capture the context and fine structure characteristics of CT images from the standard and sharp reconstruction kernels. Pairs of the full-resolution CT data set were fed to input and output nodes to train the convolutional network to learn the appropriate filter kernels for converting the CT images of sharp kernel to standard kernel with a criterion of measuring the mean squared error between the input and target images. EIs (RA950 and Perc15) were measured with a software package (ImagePrism Pulmo, Seoul, South Korea) and compared for the data sets of B50f, B30f, and the converted B50f. The effect of kernel conversion was evaluated with the mean and standard deviation of pair-wise differences in EI. The population mean of RA950 was 27.65 +/- 7.28% for B50f data set, 10.82 +/- 6.71% for the B30f data set, and 8.87 +/- 6.20% for the converted B50f data set. The mean of pair-wise absolute differences in RA950 between B30f and B50f is reduced from 16.83% to 1.95% using kernel conversion. Our study demonstrates the feasibility of applying the deep learning technique for CT kernel conversion and reducing the kernel-induced variability of EI quantification. The deep learning model has a potential to improve the reliability of imaging biomarker, especially in evaluating the longitudinal changes of EI even when the patient CT scans were performed with different kernels.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

NASA Astrophysics Data System (ADS)

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

PubMed

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-15

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

PubMed Central

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-01-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features. PMID:27079888

Opacity annotation of diffuse lung diseases using deep convolutional neural network with multi-channel information

NASA Astrophysics Data System (ADS)

Mabu, Shingo; Kido, Shoji; Hashimoto, Noriaki; Hirano, Yasushi; Kuremoto, Takashi

2018-02-01

This research proposes a multi-channel deep convolutional neural network (DCNN) for computer-aided diagnosis (CAD) that classifies normal and abnormal opacities of diffuse lung diseases in Computed Tomography (CT) images. Because CT images are gray scale, DCNN usually uses one channel for inputting image data. On the other hand, this research uses multi-channel DCNN where each channel corresponds to the original raw image or the images transformed by some preprocessing techniques. In fact, the information obtained only from raw images is limited and some conventional research suggested that preprocessing of images contributes to improving the classification accuracy. Thus, the combination of the original and preprocessed images is expected to show higher accuracy. The proposed method realizes region of interest (ROI)-based opacity annotation. We used lung CT images taken in Yamaguchi University Hospital, Japan, and they are divided into 32 × 32 ROI images. The ROIs contain six kinds of opacities: consolidation, ground-glass opacity (GGO), emphysema, honeycombing, nodular, and normal. The aim of the proposed method is to classify each ROI into one of the six opacities (classes). The DCNN structure is based on VGG network that secured the first and second places in ImageNet ILSVRC-2014. From the experimental results, the classification accuracy of the proposed method was better than the conventional method with single channel, and there was a significant difference between them.

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

Automated method for relating regional pulmonary structure and function: integration of dynamic multislice CT and thin-slice high-resolution CT

NASA Astrophysics Data System (ADS)

Tajik, Jehangir K.; Kugelmass, Steven D.; Hoffman, Eric A.

1993-07-01

We have developed a method utilizing x-ray CT for relating pulmonary perfusion to global and regional anatomy, allowing for detailed study of structure to function relationships. A thick slice, high temporal resolution mode is used to follow a bolus contrast agent for blood flow evaluation and is fused with a high spatial resolution, thin slice mode to obtain structure- function detail. To aid analysis of blood flow, we have developed a software module, for our image analysis package (VIDA), to produce the combined structure-function image. Color coded images representing blood flow, mean transit time, regional tissue content, regional blood volume, regional air content, etc. are generated and imbedded in the high resolution volume image. A text file containing these values along with a voxel's 3-D coordinates is also generated. User input can be minimized to identifying the location of the pulmonary artery from which the input function to a blood flow model is derived. Any flow model utilizing one input and one output function can be easily added to a user selectable list. We present examples from our physiologic based research findings to demonstrate the strengths of combining dynamic CT and HRCT relative to other scanning modalities to uniquely characterize pulmonary normal and pathophysiology.

Can computed tomography aid in diagnosis of intramural hematomas of the intestinal wall?

PubMed

Ulusan, Serife; Pekoz, Burcak; Sariturk, Cagla

2015-12-01

We sought to use computed tomography (CT) data to support the correct differential diagnosis of patients with spontaneous intramural hematomas of the gastrointestinal tract, to aid in the clinical management of those using oral anticoagulants. Patient data were retrospectively analyzed and patients were divided into two groups. The first group contained 10 patients (5 females, 5 males, median age 65 years [range 35-79 years]) who had been diagnosed with spontaneous intramural hematomas of the gastrointestinal tract. The second group contained nine patients (5 females, 4 males, median age 41 years [range 24-56 years]) who exhibited intestinal wall thickening on CT, and who had been diagnosed with ulcerative colitis, Crohn's disease, ameboma, and lymphoma. The enhancement patterns in the CT images of the two groups were compared by an experienced and inexperienced radiologist. The differences in values were subjected to ROC analysis. Inter-observer variability was excellent (0.84) when post-contrast CT images were evaluated, as were the subtraction values (0.89). The subtracted values differed significantly between the two groups (p=0.0001). A cutoff of +31.5 HU was optimal in determining whether a hematoma was or was not present. Contrast enhancement of an intestinal wall hematoma is less than that of other intestinal wall pathologies associated with increased wall thickness. If the post-contrast enhancement of a thickened intestinal wall is less than +31.5 HU, a wall hematoma is possible. © Acta Gastro-Enterologica Belgica.

A deep-learning based automatic pulmonary nodule detection system

NASA Astrophysics Data System (ADS)

Zhao, Yiyuan; Zhao, Liang; Yan, Zhennan; Wolf, Matthias; Zhan, Yiqiang

2018-02-01

Lung cancer is the deadliest cancer worldwide. Early detection of lung cancer is a promising way to lower the risk of dying. Accurate pulmonary nodule detection in computed tomography (CT) images is crucial for early diagnosis of lung cancer. The development of computer-aided detection (CAD) system of pulmonary nodules contributes to making the CT analysis more accurate and with more efficiency. Recent studies from other groups have been focusing on lung cancer diagnosis CAD system by detecting medium to large nodules. However, to fully investigate the relevance between nodule features and cancer diagnosis, a CAD that is capable of detecting nodules with all sizes is needed. In this paper, we present a deep-learning based automatic all size pulmonary nodule detection system by cascading two artificial neural networks. We firstly use a U-net like 3D network to generate nodule candidates from CT images. Then, we use another 3D neural network to refine the locations of the nodule candidates generated from the previous subsystem. With the second sub-system, we bring the nodule candidates closer to the center of the ground truth nodule locations. We evaluate our system on a public CT dataset provided by the Lung Nodule Analysis (LUNA) 2016 grand challenge. The performance on the testing dataset shows that our system achieves 90% sensitivity with an average of 4 false positives per scan. This indicates that our system can be an aid for automatic nodule detection, which is beneficial for lung cancer diagnosis.

Benefit from NASA

NASA Image and Video Library

2001-01-01

The high-tech art of digital signal processing (DSP) was pioneered at NASA's Jet Propulsion Laboratory (JPL) in the mid-1960s for use in the Apollo Lunar Landing Program. Designed to computer enhance pictures of the Moon, this technology became the basis for the Landsat Earth resources satellites and subsequently has been incorporated into a broad range of Earthbound medical and diagnostic tools. DSP is employed in advanced body imaging techniques including Computer-Aided Tomography, also known as CT and CATScan, and Magnetic Resonance Imaging (MRI). CT images are collected by irradiating a thin slice of the body with a fan-shaped x-ray beam from a number of directions around the body's perimeter. A tomographic (slice-like) picture is reconstructed from these multiple views by a computer. MRI employs a magnetic field and radio waves, rather than x-rays, to create images. In this photograph, a patient undergoes an open MRI.

Computer-aided detection of colorectal polyps: can it improve sensitivity of less-experienced readers? Preliminary findings.

PubMed

Baker, Mark E; Bogoni, Luca; Obuchowski, Nancy A; Dass, Chandra; Kendzierski, Renee M; Remer, Erick M; Einstein, David M; Cathier, Pascal; Jerebko, Anna; Lakare, Sarang; Blum, Andrew; Caroline, Dina F; Macari, Michael

2007-10-01

To determine whether computer-aided detection (CAD) applied to computed tomographic (CT) colonography can help improve sensitivity of polyp detection by less-experienced radiologist readers, with colonoscopy or consensus used as the reference standard. The release of the CT colonographic studies was approved by the individual institutional review boards of each institution. Institutions from the United States were HIPAA compliant. Written informed consent was waived at all institutions. The CT colonographic studies in 30 patients from six institutions were collected; 24 images depicted at least one confirmed polyp 6 mm or larger (39 total polyps) and six depicted no polyps. By using an investigational software package, seven less-experienced readers from two institutions evaluated the CT colonographic images and marked or scored polyps by using a five-point scale before and after CAD. The time needed to interpret the CT colonographic findings without CAD and then to re-evaluate them with CAD was recorded. For each reader, the McNemar test, adjusted for clustered data, was used to compare sensitivities for readers without and with CAD; a Wilcoxon signed-rank test was used to analyze the number of false-positive results per patient. The average sensitivity of the seven readers for polyp detection was significantly improved with CAD-from 0.810 to 0.908 (P=.0152). The number of false-positive results per patient without and with CAD increased from 0.70 to 0.96 (95% confidence interval for the increase: -0.39, 0.91). The mean total time for the readings was 17 minutes 54 seconds; for interpretation of CT colonographic findings alone, the mean time was 14 minutes 16 seconds; and for review of CAD findings, the mean time was 3 minutes 38 seconds. Results of this feasibility study suggest that CAD for CT colonography significantly improves per-polyp detection for less-experienced readers. Copyright (c) RSNA, 2007.

Myocardial strain estimation from CT: towards computer-aided diagnosis on infarction identification

NASA Astrophysics Data System (ADS)

Wong, Ken C. L.; Tee, Michael; Chen, Marcus; Bluemke, David A.; Summers, Ronald M.; Yao, Jianhua

2015-03-01

Regional myocardial strains have the potential for early quantification and detection of cardiac dysfunctions. Although image modalities such as tagged and strain-encoded MRI can provide motion information of the myocardium, they are uncommon in clinical routine. In contrary, cardiac CT images are usually available, but they only provide motion information at salient features such as the cardiac boundaries. To estimate myocardial strains from a CT image sequence, we adopted a cardiac biomechanical model with hyperelastic material properties to relate the motion on the cardiac boundaries to the myocardial deformation. The frame-to-frame displacements of the cardiac boundaries are obtained using B-spline deformable image registration based on mutual information, which are enforced as boundary conditions to the biomechanical model. The system equation is solved by the finite element method to provide the dense displacement field of the myocardium, and the regional values of the three principal strains and the six strains in cylindrical coordinates are computed in terms of the American Heart Association nomenclature. To study the potential of the estimated regional strains on identifying myocardial infarction, experiments were performed on cardiac CT image sequences of ten canines with artificially induced myocardial infarctions. The leave-one-subject-out cross validations show that, by using the optimal strain magnitude thresholds computed from ROC curves, the radial strain and the first principal strain have the best performance.

Scope for energy improvement for hospital imaging services in the USA.

PubMed

Esmaeili, Amin; Twomey, Janet M; Overcash, Michael R; Soltani, Seyed A; McGuire, Charles; Ali, Kamran

2015-04-01

To aid radiologists by measuring the carbon footprint of CT scans by quantifying in-hospital and out-of-hospital energy use and to assess public health impacts. The study followed a standard life cycle assessment protocol to measure energy from a CT scan then expanding to all hospital electrical energy related to CT usage. In addition, all the fuel energy used to generate electricity and to manufacture the CT consumables was measured. The study was conducted at two hospitals. The entire life cycle energy for a CT scan was 24-34 kWh of natural resource energy per scan. The actual active patient scan energy that produces the images is only about 1.6% of this total life cycle energy. This large multiplier to get total CT energy is a previously undocumented environmental response to the direct radiology order for a patient CT scan. The CT in-hospital energy related to idle periods, where the machine is on but no patients are being scanned and is 14-30-fold higher than the energy used for the CT image. The in-hospital electrical energy of a CT scan makes up only about 25% of the total energy footprint. The rest is generated outside the hospital: 54-62% for generation and transmission of the electricity, while 13-22% is for all the energy to make the consumables. Different CT scanners have some influences on the results and could help guide purchase of CT equipment. The transparent, detailed life cycle approach allows the data from this study to be used by radiologists to examine details of both direct and of unseen energy impacts of CT scans. The public health (outside-the-hospital) impact (including the patients receiving a CT) needs to be measured and included. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

CT, MRI, and 18F-FDG PET/CT findings of malignant peripheral nerve sheath tumor of the head and neck.

PubMed

Kim, Ha Youn; Hwang, Ji Young; Kim, Hyung-Jin; Kim, Yi Kyung; Cha, Jihoon; Park, Gyeong Min; Kim, Sung Tae

2017-10-01

Background Malignant peripheral nerve sheath tumor (MPNST) is a highly malignant tumor and rarely occurs in the head and neck. Purpose To describe the imaging features of MPNST of the head and neck. Material and Methods We retrospectively analyzed computed tomography (CT; n = 14), magnetic resonance imaging (MRI; n = 16), and 18 F-FDG PET/CT (n = 5) imaging features of 18 MPNSTs of the head and neck in 17 patients. Special attention was paid to determine the nerve of origin from which the tumor might have arisen. Results All lesions were well-defined (n = 3) or ill-defined (n = 15) masses (mean, 6.1 cm). Lesions were at various locations but most commonly the neck (n = 8), followed by the intracranial cavity (n = 3), paranasal sinus (n = 2), and orbit (n = 2). The nerve of origin was inferred for 11 lesions: seven in the neck, two in the orbit, one in the cerebellopontine angle, and one on the parietal scalp. Attenuation, signal intensity, and enhancement pattern of the lesions on CT and MRI were non-specific. Necrosis/hemorrhage/cystic change within the lesion was considered to be present on images in 13 and bone change in nine. On 18 F-FDG PET/CT images, all five lesions demonstrated various hypermetabolic foci with maximum standard uptake value (SUV max ) from 3.2 to 14.6 (mean, 7.16 ± 4.57). Conclusion MPNSTs can arise from various locations in the head and neck. Though non-specific, a mass with an ill-defined margin along the presumed course of the cranial nerves may aid the diagnosis of MPSNT in the head and neck.

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.

Electronic cleansing for CT colonography using spectral-driven iterative reconstruction

NASA Astrophysics Data System (ADS)

Nasirudin, Radin A.; Näppi, Janne J.; Hironaka, Toru; Tachibana, Rie; Yoshida, Hiroyuki

2017-03-01

Dual-energy computed tomography is used increasingly in CT colonography (CTC). The combination of computer-aided detection (CADe) and dual-energy CTC (DE-CTC) has high clinical value, because it can detect clinically significant colonic lesions automatically at higher accuracy than does conventional single-energy CTC. While CADe has demonstrated its ability to detect small polyps, its performance is highly dependent on several factors, including the quality of CTC images and electronic cleansing (EC) of the images. The presence of artifacts such as beam hardening and image noise in ultra-low-dose CTC can produce incorrectly cleansed colon images that severely degrade the detection performance of CTC for small polyps. Also, CADe methods are very dependent on the quality of input images and the information about different tissues in the colon. In this work, we developed a novel method to calculate EC images using spectral information from DE-CTC data. First, the ultra-low dose dual-energy projection data obtained from a CT scanner are decomposed into two materials, soft tissue and the orally administered fecal-tagging contrast agent, to detect the location and intensity of the contrast agent. Next, the images are iteratively reconstructed while gradually removing the presence of tagged materials from the images. Our preliminary qualitative results show that the method can cleanse the contrast agent and tagged materials correctly from DE-CTC images without affecting the appearance of surrounding tissue.

Finding glenoid surface on scapula in 3D medical images for shoulder joint implant operation planning: 3D OCR

NASA Astrophysics Data System (ADS)

Mohammad Sadeghi, Majid; Kececi, Emin Faruk; Bilsel, Kerem; Aralasmak, Ayse

2017-03-01

Medical imaging has great importance in earlier detection, better treatment and follow-up of diseases. 3D Medical image analysis with CT Scan and MRI images has also been used to aid surgeries by enabling patient specific implant fabrication, where having a precise three dimensional model of associated body parts is essential. In this paper, a 3D image processing methodology for finding the plane on which the glenoid surface has a maximum surface area is proposed. Finding this surface is the first step in designing patient specific shoulder joint implant.

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

An improved method for pancreas segmentation using SLIC and interactive region merging

NASA Astrophysics Data System (ADS)

Zhang, Liyuan; Yang, Huamin; Shi, Weili; Miao, Yu; Li, Qingliang; He, Fei; He, Wei; Li, Yanfang; Zhang, Huimao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.

CT and MRI of superficial solid tumors

PubMed Central

Zhang, Jingfeng; Li, Yanyuan; Zhao, Yilei

2018-01-01

Superficial solid masses are common conditions in clinical practice, however, some of which can be easily diagnosed and others would be difficult. Although imaging of superficial masses is not always characteristic, it would be helpful to give a definitive diagnosis or narrow a differential diagnosis. Crossing-section imaging can depicture the masses directly, find some pathognomonic signs and demonstrate their relationship with adjacent structures, which can provide decision support for clinician’s reference. Computed tomography (CT) can be used to detect calcifications and bone erosion which could not be seen on radiographs. Magnetic resonance imaging (MRI) is the preferred way for evaluating soft tissue lesions and provides information on hemorrhage, necrosis, edema, cystic and myxoid degeneration, and fibrosis. Other advantages of MRI are its superior soft tissue resolution and any profile imaging, which can aid the assessment of extension and adjacent infiltration. Positron emission tomography (PET)/CT and PET/MRI have been increasingly used in bone and soft tissue sarcomas and provides advantages in the initial tumor staging, tumor grading, therapy assessment, and recurrence detection. Therefore, imaging examination can play an important role in treatment decision making for superficial solid tumors. Here we review the important conditions presenting as superficial mass and show the imaging of typical cases diagnosed in our hospital. PMID:29675364

Letter to the Editor: Use of Publicly Available Image Resources

DOE PAGES

Armato, Samuel G.; Drukker, Karen; Li, Feng; ...

2017-05-11

Here we write with regard to the Academic Radiology article entitled, “Computer-aided Diagnosis for Lung Cancer: Usefulness of Nodule Heterogeneity” by Drs. Nishio and Nagashima (1). The authors also report on a computerized method to classify as benign or malignant lung nodules present in computed tomography (CT) scans.

Application of computer-aided three-dimensional skull model with rapid prototyping technique in repair of zygomatico-orbito-maxillary complex fracture.

PubMed

Li, Wei Zhong; Zhang, Mei Chao; Li, Shao Ping; Zhang, Lei Tao; Huang, Yu

2009-06-01

With the advent of CAD/CAM and rapid prototyping (RP), a technical revolution in oral and maxillofacial trauma was promoted to benefit treatment, repair of maxillofacial fractures and reconstruction of maxillofacial defects. For a patient with zygomatico-facial collapse deformity resulting from a zygomatico-orbito-maxillary complex (ZOMC) fracture, CT scan data were processed by using Mimics 10.0 for three-dimensional (3D) reconstruction. The reduction design was aided by 3D virtual imaging and the 3D skull model was reproduced using the RP technique. In line with the design by Mimics, presurgery was performed on the 3D skull model and the semi-coronal incision was taken for reduction of ZOMC fracture, based on the outcome from the presurgery. Postoperative CT and images revealed significantly modified zygomatic collapse and zygomatic arch rise and well-modified facial symmetry. The CAD/CAM and RP technique is a relatively useful tool that can assist surgeons with reconstruction of the maxillofacial skeleton, especially in repairs of ZOMC fracture.

Nuclear Medicine Imaging in the Dentomaxillofacial Region.

PubMed

Wassef, Heidi R; Colletti, Patrick M

2018-07-01

Nuclear medicine studies evaluate physiology on a molecular level providing earlier detection of lesions before morphologic change is evident. 99m Tc-MDP and 18 F-fluoride bone scans detect osteomyelitis earlier than radiographs and computed tomography (CT); aid in diagnosis of temporomandibular joint disorder; and evaluate activity of condylar hyperplasia, extent of Paget disease, and viability of bone grafts. 18 F-FDG PET/CT distinguish between soft tissue and bone infections and diagnose osteomyelitis complicated by fracture or surgery. FDG PET is more accurate than CT alone and has a major role in staging, restaging, and assessing response to therapy for head and neck malignancies and in detecting sequelae of therapy. Copyright © 2018 Elsevier Inc. All rights reserved.

Small Nodules Localization on CT Images of Lungs

NASA Astrophysics Data System (ADS)

Snezhko, E. V.; Kharuzhyk, S. A.; Tuzikov, A. V.; Kovalev, V. A.

2017-05-01

According to the World Health Organization (WHO) lung cancer remains the leading cause of death of men among all malignant tumors [1, 2]. One of the reasons of such a statistics is the fact that the lung cancer is hardly diagnosed on the yearly stages when it is almost asymptomatic. The purpose of this paper is to present a Computer-Aided Diagnosis (CAD) software developed for assistance of early detection of nodules in CT lung images including solitary pulmonary nodules (SPN) as well as multiple nodules. The efficiency of nodule localization was intended to be as high as the level of the best practice. The software developed supports several functions including lungs segmentation, selection of nodule candidates and nodule candidates filtering.

Contextual convolutional neural networks for lung nodule classification using Gaussian-weighted average image patches

NASA Astrophysics Data System (ADS)

Lee, Haeil; Lee, Hansang; Park, Minseok; Kim, Junmo

2017-03-01

Lung cancer is the most common cause of cancer-related death. To diagnose lung cancers in early stages, numerous studies and approaches have been developed for cancer screening with computed tomography (CT) imaging. In recent years, convolutional neural networks (CNN) have become one of the most common and reliable techniques in computer aided detection (CADe) and diagnosis (CADx) by achieving state-of-the-art-level performances for various tasks. In this study, we propose a CNN classification system for false positive reduction of initially detected lung nodule candidates. First, image patches of lung nodule candidates are extracted from CT scans to train a CNN classifier. To reflect the volumetric contextual information of lung nodules to 2D image patch, we propose a weighted average image patch (WAIP) generation by averaging multiple slice images of lung nodule candidates. Moreover, to emphasize central slices of lung nodules, slice images are locally weighted according to Gaussian distribution and averaged to generate the 2D WAIP. With these extracted patches, 2D CNN is trained to achieve the classification of WAIPs of lung nodule candidates into positive and negative labels. We used LUNA 2016 public challenge database to validate the performance of our approach for false positive reduction in lung CT nodule classification. Experiments show our approach improves the classification accuracy of lung nodules compared to the baseline 2D CNN with patches from single slice image.

Implementation of a computer-aided detection tool for quantification of intracranial radiologic markers on brain CT images

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Ross, Stephen R.; Wang, Yunzhi; Wu, Dee H.; Cornwell, Benjamin O.; Ray, Bappaditya; Zheng, Bin

2017-03-01

Aneurysmal subarachnoid hemorrhage (aSAH) is a form of hemorrhagic stroke that affects middle-aged individuals and associated with significant morbidity and/or mortality especially those presenting with higher clinical and radiologic grades at the time of admission. Previous studies suggested that blood extravasated after aneurysmal rupture was a potentially clinical prognosis factor. But all such studies used qualitative scales to predict prognosis. The purpose of this study is to develop and test a new interactive computer-aided detection (CAD) tool to detect, segment and quantify brain hemorrhage and ventricular cerebrospinal fluid on non-contrasted brain CT images. First, CAD segments brain skull using a multilayer region growing algorithm with adaptively adjusted thresholds. Second, CAD assigns pixels inside the segmented brain region into one of three classes namely, normal brain tissue, blood and fluid. Third, to avoid "black-box" approach and increase accuracy in quantification of these two image markers using CT images with large noise variation in different cases, a graphic User Interface (GUI) was implemented and allows users to visually examine segmentation results. If a user likes to correct any errors (i.e., deleting clinically irrelevant blood or fluid regions, or fill in the holes inside the relevant blood or fluid regions), he/she can manually define the region and select a corresponding correction function. CAD will automatically perform correction and update the computed data. The new CAD tool is now being used in clinical and research settings to estimate various quantitatively radiological parameters/markers to determine radiological severity of aSAH at presentation and correlate the estimations with various homeostatic/metabolic derangements and predict clinical outcome.

Minimizing the extra-oral time in autogeneous tooth transplantation: use of computer-aided rapid prototyping (CARP) as a duplicate model tooth.

PubMed

Lee, Seung-Jong; Kim, Euiseong

2012-08-01

The maintenance of the healthy periodontal ligament cells of the root surface of donor tooth and intimate surface contact between the donor tooth and the recipient bone are the key factors for successful tooth transplantation. In order to achieve these purposes, a duplicated donor tooth model can be utilized to reduce the extra-oral time using the computer-aided rapid prototyping (CARP) technique. Briefly, a three-dimensional digital imaging and communication in medicine (DICOM) image with the real dimensions of the donor tooth was obtained from a computed tomography (CT), and a life-sized resin tooth model was fabricated. Dimensional errors between real tooth, 3D CT image model and CARP model were calculated. And extra-oral time was recorded during the autotransplantation of the teeth. The average extra-oral time was 7 min 25 sec with the range of immediate to 25 min in cases which extra-oral root canal treatments were not performed while it was 9 min 15 sec when extra-oral root canal treatments were performed. The average radiographic distance between the root surface and the alveolar bone was 1.17 mm and 1.35 mm at mesial cervix and apex; they were 0.98 mm and 1.26 mm at the distal cervix and apex. When the dimensional errors between real tooth, 3D CT image model and CARP model were measured in cadavers, the average of absolute error was 0.291 mm between real teeth and CARP model. These data indicate that CARP may be of value in minimizing the extra-oral time and the gap between the donor tooth and the recipient alveolar bone in tooth transplantation.

3-D printouts of the tracheobronchial tree generated from CT images as an aid to management in a case of tracheobronchial chondromalacia caused by relapsing polychondritis.

PubMed

Tam, Matthew David; Laycock, Stephen David; Jayne, David; Babar, Judith; Noble, Brendon

2013-08-01

This report concerns a 67 year old male patient with known advanced relapsing polychondritis complicated by tracheobronchial chondromalacia who is increasingly symptomatic and therapeutic options such as tracheostomy and stenting procedures are being considered. The DICOM files from the patient's dynamic chest CT in its inspiratory and expiratory phases were used to generate stereolithography (STL) files and hence print out 3-D models of the patient's trachea and central airways. The 4 full-sized models allowed better understanding of the extent and location of any stenosis or malacic change and should aid any planned future stenting procedures. The future possibility of using the models as scaffolding to generate a new cartilaginous upper airway using regenerative medical techniques is also discussed.

Predicting tumor hypoxia in non-small cell lung cancer by combining CT, FDG PET and dynamic contrast-enhanced CT.

PubMed

Even, Aniek J G; Reymen, Bart; La Fontaine, Matthew D; Das, Marco; Jochems, Arthur; Mottaghy, Felix M; Belderbos, José S A; De Ruysscher, Dirk; Lambin, Philippe; van Elmpt, Wouter

2017-11-01

Most solid tumors contain inadequately oxygenated (i.e., hypoxic) regions, which tend to be more aggressive and treatment resistant. Hypoxia PET allows visualization of hypoxia and may enable treatment adaptation. However, hypoxia PET imaging is expensive, time-consuming and not widely available. We aimed to predict hypoxia levels in non-small cell lung cancer (NSCLC) using more easily available imaging modalities: FDG-PET/CT and dynamic contrast-enhanced CT (DCE-CT). For 34 NSCLC patients, included in two clinical trials, hypoxia HX4-PET/CT, planning FDG-PET/CT and DCE-CT scans were acquired before radiotherapy. Scans were non-rigidly registered to the planning CT. Tumor blood flow (BF) and blood volume (BV) were calculated by kinetic analysis of DCE-CT images. Within the gross tumor volume, independent clusters, i.e., supervoxels, were created based on FDG-PET/CT. For each supervoxel, tumor-to-background ratios (TBR) were calculated (median SUV/aorta SUV mean ) for HX4-PET/CT and supervoxel features (median, SD, entropy) for the other modalities. Two random forest models (cross-validated: 10 folds, five repeats) were trained to predict the hypoxia TBR; one based on CT, FDG, BF and BV, and one with only CT and FDG features. Patients were split in a training (trial NCT01024829) and independent test set (trial NCT01210378). For each patient, predicted, and observed hypoxic volumes (HV) (TBR > 1.2) were compared. Fifteen patients (3291 supervoxels) were used for training and 19 patients (1502 supervoxels) for testing. The model with all features (RMSE training: 0.19 ± 0.01, test: 0.27) outperformed the model with only CT and FDG-PET features (RMSE training: 0.20 ± 0.01, test: 0.29). All tumors of the test set were correctly classified as normoxic or hypoxic (HV > 1 cm 3 ) by the best performing model. We created a data-driven methodology to predict hypoxia levels and hypoxia spatial patterns using CT, FDG-PET and DCE-CT features in NSCLC. The model correctly classifies all tumors, and could therefore, aid tumor hypoxia classification and patient stratification.

Comparison of CT angiography with conventional arterial angiography in aortoiliac occlusive disease.

PubMed

Tins, B; Oxtoby, J; Patel, S

2001-03-01

This study compared the results of conventional and CT angiography of the aortoiliac segment in 35 patients with occlusive disease. Disease severity was graded into five categories. Two assessors independently assessed the segment from the distal abdominal aorta to the proximal superficial femoral artery and a consensus was formed. There was interobserver agreement in 87% of segments for conventional angiography and in 78% for CT angiography. Comparison of the two modalities gave identical grading in 84% of segments. Dissimilar grading was found in 16%, with a roughly equal number of undergrading and overgrading. CT angiography has the advantages of being minimally invasive, requiring only an intravenous injection of contrast medium and imaging surrounding soft tissues. Multiplanar reconstruction aids the visualization of asymmetrical stenoses, and collateral blood supply is readily appreciated. However, CT angiography may fail to demonstrate short stenoses owing to limited z-axis resolution.

Experimental flat-panel high-spatial-resolution volume CT of the temporal bone.

PubMed

Gupta, Rajiv; Bartling, Soenke H; Basu, Samit K; Ross, William R; Becker, Hartmut; Pfoh, Armin; Brady, Thomas; Curtin, Hugh D

2004-09-01

A CT scanner employing a digital flat-panel detector is capable of very high spatial resolution as compared with a multi-section CT (MSCT) scanner. Our purpose was to determine how well a prototypical volume CT (VCT) scanner with a flat-panel detector system defines fine structures in temporal bone. Four partially manipulated temporal-bone specimens were imaged by use of a prototypical cone-beam VCT scanner with a flat-panel detector system at an isometric resolution of 150 microm at the isocenter. These specimens were also depicted by state-of-the-art multisection CT (MSCT). Forty-two structures imaged by both scanners were qualitatively assessed and rated, and scores assigned to VCT findings were compared with those of MSCT. Qualitative assessment of anatomic structures, lesions, cochlear implants, and middle-ear hearing aids indicated that image quality was significantly better with VCT (P < .001). Structures near the spatial-resolution limit of MSCT (e.g., bony covering of the tympanic segment of the facial canal, the incudo-stapedial joint, the proximal vestibular aqueduct, the interscalar septum, and the modiolus) had higher contrast and less partial-volume effect with VCT. The flat-panel prototype provides better definition of fine osseous structures of temporal bone than that of currently available MSCT scanners. This study provides impetus for further research in increasing spatial resolution beyond that offered by the current state-of-the-art scanners.

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.

Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity

NASA Astrophysics Data System (ADS)

He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan

2017-07-01

While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

Comparison of computed tomography and high-field (3.0 T) magnetic resonance imaging of age-related variances in selected equine maxillary cheek teeth and adjacent tissues.

PubMed

Schoppe, Christin; Hellige, Maren; Rohn, Karl; Ohnesorge, Bernhard; Bienert-Zeit, Astrid

2017-09-06

Modern imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) have the advantage of producing images without superimposition. Whilst CT is a well-established technique for dental diagnostics, MRI examinations are rarely used for the evaluation of dental diseases in horses. Regarding equine endodontic therapies which are increasingly implemented, MRI could help to portray changes of the periodontal ligament and display gross pulpar anatomy. Knowledge of age-related changes is essential for diagnosis, as cheek teeth and surrounding structures alter with increasing age. The aim of the present study was to highlight the advantages of CT and MRI regarding age-related changes in selected equine cheek teeth and their adjacent structures. The CT and MRI appearances of the maxillary 08 s and 09 s and adjacent structures were described by evaluation of post-mortem examinations of nine horses of different ages (Group A: <6 years, B: 6-15 years, C: ≥16 years). Most of the tissues selected were imaged accurately with MRI and CT. Magnetic resonance imaging gives an excellent depiction of soft endo- and periodontal units, and CT of hard dental and bony tissues. Negative correlation between dental age and pulpar sizes was found: 71.3% of the changes in pulp dimensions can be explained by teeth aging. Pulpar sizes ranged from 14.3 to 1.3 mm and were significantly smaller in older horses (p < 0.05). A common pulp chamber was present in 33% of the teeth with a mean dental age of 2.25 years. Ninety-four percent of the 08 and 09 alveoli of all groups were in direct contact with the maxillary sinus. An age-related regression was found (R 2  = 0.88) for the distance between alveoli and the infraorbital canal. The present study provides information about the dental and periodontal age-related morphology and its visibility using different imaging techniques. These results aid in evaluating diagnostic images and in deciding which is the superior imaging modality for clinical cases.

Image calibration and registration in cone-beam computed tomogram for measuring the accuracy of computer-aided implant surgery

NASA Astrophysics Data System (ADS)

Lam, Walter Y. H.; Ngan, Henry Y. T.; Wat, Peter Y. P.; Luk, Henry W. K.; Goto, Tazuko K.; Pow, Edmond H. N.

2015-02-01

Medical radiography is the use of radiation to "see through" a human body without breaching its integrity (surface). With computed tomography (CT)/cone beam computed tomography (CBCT), three-dimensional (3D) imaging can be produced. These imagings not only facilitate disease diagnosis but also enable computer-aided surgical planning/navigation. In dentistry, the common method for transfer of the virtual surgical planning to the patient (reality) is the use of surgical stent either with a preloaded planning (static) like a channel or a real time surgical navigation (dynamic) after registration with fiducial markers (RF). This paper describes using the corner of a cube as a radiopaque fiducial marker on an acrylic (plastic) stent, this RF allows robust calibration and registration of Cartesian (x, y, z)- coordinates for linking up the patient (reality) and the imaging (virtuality) and hence the surgical planning can be transferred in either static or dynamic way. The accuracy of computer-aided implant surgery was measured with reference to coordinates. In our preliminary model surgery, a dental implant was planned virtually and placed with preloaded surgical guide. The deviation of the placed implant apex from the planning was x=+0.56mm [more right], y=- 0.05mm [deeper], z=-0.26mm [more lingual]) which was within clinically 2mm safety range. For comparison with the virtual planning, the physically placed implant was CT/CBCT scanned and errors may be introduced. The difference of the actual implant apex to the virtual apex was x=0.00mm, y=+0.21mm [shallower], z=-1.35mm [more lingual] and this should be brought in mind when interpret the results.

A novel scatter separation method for multi-energy x-ray imaging

NASA Astrophysics Data System (ADS)

Sossin, A.; Rebuffel, V.; Tabary, J.; Létang, J. M.; Freud, N.; Verger, L.

2016-06-01

X-ray imaging coupled with recently emerged energy-resolved photon counting detectors provides the ability to differentiate material components and to estimate their respective thicknesses. However, such techniques require highly accurate images. The presence of scattered radiation leads to a loss of spatial contrast and, more importantly, a bias in radiographic material imaging and artefacts in computed tomography (CT). The aim of the present study was to introduce and evaluate a partial attenuation spectral scatter separation approach (PASSSA) adapted for multi-energy imaging. This evaluation was carried out with the aid of numerical simulations provided by an internal simulation tool, Sindbad-SFFD. A simplified numerical thorax phantom placed in a CT geometry was used. The attenuation images and CT slices obtained from corrected data showed a remarkable increase in local contrast and internal structure detectability when compared to uncorrected images. Scatter induced bias was also substantially decreased. In terms of quantitative performance, the developed approach proved to be quite accurate as well. The average normalized root-mean-square error between the uncorrected projections and the reference primary projections was around 23%. The application of PASSSA reduced this error to around 5%. Finally, in terms of voxel value accuracy, an increase by a factor  >10 was observed for most inspected volumes-of-interest, when comparing the corrected and uncorrected total volumes.

A novel computer-aided detection system for pulmonary nodule identification in CT images

NASA Astrophysics Data System (ADS)

Han, Hao; Li, Lihong; Wang, Huafeng; Zhang, Hao; Moore, William; Liang, Zhengrong

2014-03-01

Computer-aided detection (CADe) of pulmonary nodules from computer tomography (CT) scans is critical for assisting radiologists to identify lung lesions at an early stage. In this paper, we propose a novel approach for CADe of lung nodules using a two-stage vector quantization (VQ) scheme. The first-stage VQ aims to extract lung from the chest volume, while the second-stage VQ is designed to extract initial nodule candidates (INCs) within the lung volume. Then rule-based expert filtering is employed to prune obvious FPs from INCs, and the commonly-used support vector machine (SVM) classifier is adopted to further reduce the FPs. The proposed system was validated on 100 CT scans randomly selected from the 262 scans that have at least one juxta-pleural nodule annotation in the publicly available database - Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The two-stage VQ only missed 2 out of the 207 nodules at agreement level 1, and the INCs detection for each scan took about 30 seconds in average. Expert filtering reduced FPs more than 18 times, while maintaining a sensitivity of 93.24%. As it is trivial to distinguish INCs attached to pleural wall versus not on wall, we investigated the feasibility of training different SVM classifiers to further reduce FPs from these two kinds of INCs. Experiment results indicated that SVM classification over the entire set of INCs was in favor of, where the optimal operating of our CADe system achieved a sensitivity of 89.4% at a specificity of 86.8%.

Higher-order scene statistics of breast images

NASA Astrophysics Data System (ADS)

Abbey, Craig K.; Sohl-Dickstein, Jascha N.; Olshausen, Bruno A.; Eckstein, Miguel P.; Boone, John M.

2009-02-01

Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural scenes. It is argued that this allows for sparse representation of the independent components of natural images [Olshausen and Field, Nature, 1996]. These theories have important implications for medical image perception. For example, will a system that is designed to represent the independent components of natural scenes, where objects occlude one another and illumination is typically reflected, be appropriate for X-ray imaging, where features superimpose on one another and illumination is transmissive? In this research we begin to examine these issues by evaluating higher-order statistical properties of breast images from X-ray projection mammography (PM) and dedicated breast computed tomography (bCT). We evaluate kurtosis in responses of octave bandwidth Gabor filters applied to PM and to coronal slices of bCT scans. We find that kurtosis in PM rises and quickly saturates for filter center frequencies with an average value above 0.95. By contrast, kurtosis in bCT peaks near 0.20 cyc/mm with kurtosis of approximately 2. Our findings suggest that the human visual system may be tuned to represent breast tissue more effectively in bCT over a specific range of spatial frequencies.

Computed Tomography of the Abdomen in Eight Clinically Normal Common Marmosets (Callithrix jacchus).

PubMed

du Plessis, W M; Groenewald, H B; Elliott, D

2017-08-01

The aim of this study was to provide a detailed anatomical description of the abdomen in the clinically normal common marmoset by means of computed tomography (CT). Eight clinically healthy mature common marmosets ranging from 12 to 48 months and 235 to 365 g bodyweight were anesthetized and pre- and post-contrast CT examinations were performed using different CT settings in dorsal recumbency. Abdominal organs were identified and visibility noted. Diagnostic quality abdominal images could be obtained of the common marmoset despite its small size using a dual-slice CT scanner. Representative cross-sectional images were chosen from different animals illustrating the abdominal CT anatomy of clinically normal common marmosets. Identification or delineation of abdominal organs greatly improved with i.v. contrast. A modified high-frequency algorithm with edge enhancement added valuable information for identification of small structures such as the ureters. The Hounsfield unit (HU) of major abdominal organs differed from that of small animals (domestic dogs and cats). Due to their size and different anatomy, standard small animal CT protocols need to be critically assessed and adapted for exotics, such as the common marmoset. The established normal reference range of HU of major abdominal organs and adapted settings for a CT protocol will aid clinical assessment of the common marmoset. © 2017 Blackwell Verlag GmbH.

Alignment of the lower extremity mechanical axis by computer-aided design and application in total knee arthroplasty.

PubMed

Zhang, Yuan Z; Lu, Sheng; Zhang, Hui Q; Jin, Zhong M; Zhao, Jian M; Huang, Jian; Zhang, Zhi F

2016-10-01

The success of total knee arthroplasty (TKA) depends on many factors. The position of a prosthesis is vitally important. The purpose of the present study was to evaluate the value of a computer-aided establishing lower extremity mechanical axis in TKA using digital technology. A total of 36 cases of patients with TKA were randomly divided into the computer-aided design of navigation template group (NT) and conventional intramedullary positioning group (CIP). Three-dimensional (3D) CT scanning images of the hip, knee, and ankle were obtained in NT group. X-ray images and CT scans were transferred into the 3D reconstruction software. A 3D bone model of the hip, knee, ankle, as well as the modified loading, was reconstructed and saved in a stereolithographic format. In the 3D reconstruction model, the mechanical axis of the lower limb was determined, and the navigational templates produced an accurate model using a rapid prototyping technique. The THA in CIP group was performed according to a routine operation. CT scans were performed postoperatively to evaluate the accuracy of the two TKA methods. The averaged operative time of the NT group procedures was [Formula: see text] min shorter than those of the conventional procedures ([Formula: see text]  min). The coronal femoral angle, coronal tibial angle, posterior tibial slope were [Formula: see text], [Formula: see text], [Formula: see text] in NT group and [Formula: see text], [Formula: see text], [Formula: see text] in CIP group, respectively. Statistically significant group differences were found. The navigation template produced through mechanical axis of lower extremity may provide a relative accurate and simple method for TKA.

Automatic lung nodule graph cuts segmentation with deep learning false positive reduction

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang Bill; Qian, Wei

2017-03-01

To automatic detect lung nodules from CT images, we designed a two stage computer aided detection (CAD) system. The first stage is graph cuts segmentation to identify and segment the nodule candidates, and the second stage is convolutional neural network for false positive reduction. The dataset contains 595 CT cases randomly selected from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) and the 305 pulmonary nodules achieved diagnosis consensus by all four experienced radiologists were our detection targets. Consider each slice as an individual sample, 2844 nodules were included in our database. The graph cuts segmentation was conducted in a two-dimension manner, 2733 lung nodule ROIs are successfully identified and segmented. With a false positive reduction by a seven-layer convolutional neural network, 2535 nodules remain detected while the false positive dropped to 31.6%. The average F-measure of segmented lung nodule tissue is 0.8501.

Computer aided stress analysis of long bones utilizing computer tomography

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

Marom, S.A.

1986-01-01

A computer aided analysis method, utilizing computed tomography (CT) has been developed, which together with a finite element program determines the stress-displacement pattern in a long bone section. The CT data file provides the geometry, the density and the material properties for the generated finite element model. A three-dimensional finite element model of a tibial shaft is automatically generated from the CT file by a pre-processing procedure for a finite element program. The developed pre-processor includes an edge detection algorithm which determines the boundaries of the reconstructed cross-sectional images of the scanned bone. A mesh generation procedure than automatically generatesmore » a three-dimensional mesh of a user-selected refinement. The elastic properties needed for the stress analysis are individually determined for each model element using the radiographic density (CT number) of each pixel with the elemental borders. The elastic modulus is determined from the CT radiographic density by using an empirical relationship from the literature. The generated finite element model, together with applied loads, determined from existing gait analysis and initial displacements, comprise a formatted input for the SAP IV finite element program. The output of this program, stresses and displacements at the model elements and nodes, are sorted and displayed by a developed post-processor to provide maximum and minimum values at selected locations in the model.« less

Development of an organ-specific insert phantom generated using a 3D printer for investigations of cardiac computed tomography protocols.

PubMed

Abdullah, Kamarul A; McEntee, Mark F; Reed, Warren; Kench, Peter L

2018-04-30

An ideal organ-specific insert phantom should be able to simulate the anatomical features with appropriate appearances in the resultant computed tomography (CT) images. This study investigated a 3D printing technology to develop a novel and cost-effective cardiac insert phantom derived from volumetric CT image datasets of anthropomorphic chest phantom. Cardiac insert volumes were segmented from CT image datasets, derived from an anthropomorphic chest phantom of Lungman N-01 (Kyoto Kagaku, Japan). These segmented datasets were converted to a virtual 3D-isosurface of heart-shaped shell, while two other removable inserts were included using computer-aided design (CAD) software program. This newly designed cardiac insert phantom was later printed by using a fused deposition modelling (FDM) process via a Creatbot DM Plus 3D printer. Then, several selected filling materials, such as contrast media, oil, water and jelly, were loaded into designated spaces in the 3D-printed phantom. The 3D-printed cardiac insert phantom was positioned within the anthropomorphic chest phantom and 30 repeated CT acquisitions performed using a multi-detector scanner at 120-kVp tube potential. Attenuation (Hounsfield Unit, HU) values were measured and compared to the image datasets of real-patient and Catphan ® 500 phantom. The output of the 3D-printed cardiac insert phantom was a solid acrylic plastic material, which was strong, light in weight and cost-effective. HU values of the filling materials were comparable to the image datasets of real-patient and Catphan ® 500 phantom. A novel and cost-effective cardiac insert phantom for anthropomorphic chest phantom was developed using volumetric CT image datasets with a 3D printer. Hence, this suggested the printing methodology could be applied to generate other phantoms for CT imaging studies. © 2018 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.

Neuroimaging in adult penetrating brain injury: a guide for radiographers

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

Temple, Nikki; Donald, Cortny; Skora, Amanda

Penetrating brain injuries (PBI) are a medical emergency, often resulting in complex damage and high mortality rates. Neuroimaging is essential to evaluate the location and extent of injuries, and to manage them accordingly. Currently, a myriad of imaging modalities are included in the diagnostic workup for adult PBI, including skull radiography, computed tomography (CT), magnetic resonance imaging (MRI) and angiography, with each modality providing their own particular benefits. This literature review explores the current modalities available for investigating PBI and aims to assist in decision making for the appropriate use of diagnostic imaging when presented with an adult PBI. Basedmore » on the current literature, the authors have developed an imaging pathway for adult penetrating brain injury that functions as both a learning tool and reference guide for radiographers and other health professionals. Currently, CT is recommended as the imaging modality of choice for the initial assessment of PBI patients, while MRI is important in the sub-acute setting where it aids prognosis prediction and rehabilitation planning, Additional follow-up imaging, such as angiography, should be dependent upon clinical findings.« less

Multi-modal anatomical optical coherence tomography and CT for in vivo dynamic upper airway imaging

NASA Astrophysics Data System (ADS)

Balakrishnan, Santosh; Bu, Ruofei; Price, Hillel; Zdanski, Carlton; Oldenburg, Amy L.

2017-02-01

We describe a novel, multi-modal imaging protocol for validating quantitative dynamic airway imaging performed using anatomical Optical Coherence Tomography (aOCT). The aOCT system consists of a catheter-based aOCT probe that is deployed via a bronchoscope, while a programmable ventilator is used to control airway pressure. This setup is employed on the bed of a Siemens Biograph CT system capable of performing respiratory-gated acquisitions. In this arrangement the position of the aOCT catheter may be visualized with CT to aid in co-registration. Utilizing this setup we investigate multiple respiratory pressure parameters with aOCT, and respiratory-gated CT, on both ex vivo porcine trachea and live, anesthetized pigs. This acquisition protocol has enabled real-time measurement of airway deformation with simultaneous measurement of pressure under physiologically relevant static and dynamic conditions- inspiratory peak or peak positive airway pressures of 10-40 cm H2O, and 20-30 breaths per minute for dynamic studies. We subsequently compare the airway cross sectional areas (CSA) obtained from aOCT and CT, including the change in CSA at different stages of the breathing cycle for dynamic studies, and the CSA at different peak positive airway pressures for static studies. This approach has allowed us to improve our acquisition methodology and to validate aOCT measurements of the dynamic airway for the first time. We believe that this protocol will prove invaluable for aOCT system development and greatly facilitate translation of OCT systems for airway imaging into the clinical setting.

Bragg peak prediction from quantitative proton computed tomography using different path estimates

PubMed Central

Wang, Dongxu; Mackie, T Rockwell

2015-01-01

This paper characterizes the performance of the straight-line path (SLP) and cubic spline path (CSP) as path estimates used in reconstruction of proton computed tomography (pCT). The GEANT4 Monte Carlo simulation toolkit is employed to simulate the imaging phantom and proton projections. SLP, CSP and the most-probable path (MPP) are constructed based on the entrance and exit information of each proton. The physical deviations of SLP, CSP and MPP from the real path are calculated. Using a conditional proton path probability map, the relative probability of SLP, CSP and MPP are calculated and compared. The depth dose and Bragg peak are predicted on the pCT images reconstructed using SLP, CSP, and MPP and compared with the simulation result. The root-mean-square physical deviations and the cumulative distribution of the physical deviations show that the performance of CSP is comparable to MPP while SLP is slightly inferior. About 90% of the SLP pixels and 99% of the CSP pixels lie in the 99% relative probability envelope of the MPP. Even at an imaging dose of ~0.1 mGy the proton Bragg peak for a given incoming energy can be predicted on the pCT image reconstructed using SLP, CSP, or MPP with 1 mm accuracy. This study shows that SLP and CSP, like MPP, are adequate path estimates for pCT reconstruction, and therefore can be chosen as the path estimation method for pCT reconstruction, which can aid the treatment planning and range prediction of proton radiation therapy. PMID:21212472

Three-dimensional automatic computer-aided evaluation of pleural effusions on chest CT images

NASA Astrophysics Data System (ADS)

Bi, Mark; Summers, Ronald M.; Yao, Jianhua

2011-03-01

The ability to estimate the volume of pleural effusions is desirable as it can provide information about the severity of the condition and the need for thoracentesis. We present here an improved version of an automated program to measure the volume of pleural effusions using regular chest CT images. First, the lungs are segmented using region growing, mathematical morphology, and anatomical knowledge. The visceral and parietal layers of the pleura are then extracted based on anatomical landmarks, curve fitting and active contour models. The liver and compressed tissues are segmented out using thresholding. The pleural space is then fitted to a Bezier surface which is subsequently projected onto the individual two-dimensional slices. Finally, the volume of the pleural effusion is quantified. Our method was tested on 15 chest CT studies and validated against three separate manual tracings. The Dice coefficients were 0.74+/-0.07, 0.74+/-0.08, and 0.75+/-0.07 respectively, comparable to the variation between two different manual tracings.

Building a medical image processing algorithm verification database

NASA Astrophysics Data System (ADS)

Brown, C. Wayne

2000-06-01

The design of a database containing head Computed Tomography (CT) studies is presented, along with a justification for the database's composition. The database will be used to validate software algorithms that screen normal head CT studies from studies that contain pathology. The database is designed to have the following major properties: (1) a size sufficient for statistical viability, (2) inclusion of both normal (no pathology) and abnormal scans, (3) inclusion of scans due to equipment malfunction, technologist error, and uncooperative patients, (4) inclusion of data sets from multiple scanner manufacturers, (5) inclusion of data sets from different gender and age groups, and (6) three independent diagnosis of each data set. Designed correctly, the database will provide a partial basis for FDA (United States Food and Drug Administration) approval of image processing algorithms for clinical use. Our goal for the database is the proof of viability of screening head CT's for normal anatomy using computer algorithms. To put this work into context, a classification scheme for 'computer aided diagnosis' systems is proposed.

Navigational Guidance and Ablation Planning Tools for Interventional Radiology.

PubMed

Sánchez, Yadiel; Anvari, Arash; Samir, Anthony E; Arellano, Ronald S; Prabhakar, Anand M; Uppot, Raul N

Image-guided biopsy and ablation relies on successful identification and targeting of lesions. Currently, image-guided procedures are routinely performed under ultrasound, fluoroscopy, magnetic resonance imaging, or computed tomography (CT) guidance. However, these modalities have their limitations including inadequate visibility of the lesion, lesion or organ or patient motion, compatibility of instruments in an magnetic resonance imaging field, and, for CT and fluoroscopy cases, radiation exposure. Recent advances in technology have resulted in the development of a new generation of navigational guidance tools that can aid in targeting lesions for biopsy or ablations. These navigational guidance tools have evolved from simple hand-held trajectory guidance tools, to electronic needle visualization, to image fusion, to the development of a body global positioning system, to growth in cone-beam CT, and to ablation volume planning. These navigational systems are promising technologies that not only have the potential to improve lesion targeting (thereby increasing diagnostic yield of a biopsy or increasing success of tumor ablation) but also have the potential to decrease radiation exposure to the patient and staff, decrease procedure time, decrease the sedation requirements, and improve patient safety. The purpose of this article is to describe the challenges in current standard image-guided techniques, provide a definition and overview for these next-generation navigational devices, and describe the current limitations of these, still evolving, next-generation navigational guidance tools. Copyright © 2017 Elsevier Inc. All rights reserved.

Survey of image-guided radiotherapy use in Australia.

PubMed

Batumalai, Vikneswary; Holloway, Lois Charlotte; Kumar, Shivani; Dundas, Kylie; Jameson, Michael Geoffrey; Vinod, Shalini Kavita; Delaney, Geoff P

2017-06-01

This study aimed to evaluate the current use of imaging technologies for planning and delivery of radiotherapy (RT) in Australia. An online survey was emailed to all Australian RT centres in August 2015. The survey inquired about imaging practices during planning and treatment delivery processes. Participants were asked about the types of image-guided RT (IGRT) technologies and the disease sites they were used for, reasons for implementation, frequency of imaging and future plans for IGRT use in their department. The survey was completed by 71% of Australian RT centres. All respondents had access to computed tomography (CT) simulators and regularly co-registered the following scans to the RT: diagnostic CT (50%), diagnostic magnetic resonance imaging (MRI) (95%), planning MRI (34%), planning positron emission tomography (PET) (26%) and diagnostic PET (97%) to aid in tumour delineation. The main reason for in-room IGRT implementation was the use of highly conformal techniques, while the most common reason for under-utilisation was lack of equipment capability. The most commonly used IGRT modalities were kilovoltage (kV) cone-beam CT (CBCT) (97%), kV electronic portal image (EPI) (89%) and megavoltage (MV) EPI (75%). Overall, participants planned to increase IGRT use in planning (33%) and treatment delivery (36%). IGRT is widely used among Australian RT centres. On the basis of future plans of respondents, the installation of new imaging modalities is expected to increase for both planning and treatment. © 2016 The Royal Australian and New Zealand College of Radiologists.

Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Moore, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2015-03-01

The purpose of this study is to identify and apply quantitative image biomarkers for early prediction of the tumor response to the chemotherapy among the ovarian cancer patients participated in the clinical trials of testing new drugs. In the experiment, we retrospectively selected 30 cases from the patients who participated in Phase I clinical trials of new drug or drug agents for ovarian cancer treatment. Each case is composed of two sets of CT images acquired pre- and post-treatment (4-6 weeks after starting treatment). A computer-aided detection (CAD) scheme was developed to extract and analyze the quantitative image features of the metastatic tumors previously tracked by the radiologists using the standard Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The CAD scheme first segmented 3-D tumor volumes from the background using a hybrid tumor segmentation scheme. Then, for each segmented tumor, CAD computed three quantitative image features including the change of tumor volume, tumor CT number (density) and density variance. The feature changes were calculated between the matched tumors tracked on the CT images acquired pre- and post-treatments. Finally, CAD predicted patient's 6-month progression-free survival (PFS) using a decision-tree based classifier. The performance of the CAD scheme was compared with the RECIST category. The result shows that the CAD scheme achieved a prediction accuracy of 76.7% (23/30 cases) with a Kappa coefficient of 0.493, which is significantly higher than the performance of RECIST prediction with a prediction accuracy and Kappa coefficient of 60% (17/30) and 0.062, respectively. This study demonstrated the feasibility of analyzing quantitative image features to improve the early predicting accuracy of the tumor response to the new testing drugs or therapeutic methods for the ovarian cancer patients.

A proposal of microtomography evaluation for restoration interface gaps.

PubMed

Meleo, Deborah; Manzon, Licia; Pecci, Raffaella; Zuppante, Francesca; Bedini, Rossella

2012-01-01

Nowadays, several adhesive systems are used in dental restoration and they are evaluated by clinical research. In vitro evaluations are often made by means of traditional observation techniques (for example scanning electron microscope (SEM), while 3D cone-beam microtomography technique (3D micro-CT), that can be able to generate 3D sample images without any sample treatment during acquisition data, is going to be used a lot in the next few years. In dental cavity restored with composite, it is possible to predict the presence of gaps due to polymerization shrinkage; that is the reason this work purpose is to reveal by 3D images and measure by micro-CT analysis the voids generated applying the most used adhesive systems at the moment. By means of microtomographic analysis is proposed an aid to overcome bidimensional SEM investigation limits like random observation of sample surface, sample sectioning (to see inside it with the relative possible structural alterations induced on the same sample) and the gold sputtering treatment. For this experimental work, human crown teeth have been selected, all restored with the same composite material, using five adhesive systems. After about 48 hours each tooth has been acquired by means of Skyscan 1072 micro-CT instrument and then processed by 3D reconstruction and micro-CT analyser software. Three adhesive systems have showed 3D micro-CT images with not as much voids as expected, with a very little extent. This kind of micro-CT in vitro evaluation proposal suggests a method to observe and quantify the voids generated after polymerization shrinkage during tooth restoration.

Metal Artifact Reduction in X-ray Computed Tomography Using Computer-Aided Design Data of Implants as Prior Information.

PubMed

Ruth, Veikko; Kolditz, Daniel; Steiding, Christian; Kalender, Willi A

2017-06-01

The performance of metal artifact reduction (MAR) methods in x-ray computed tomography (CT) suffers from incorrect identification of metallic implants in the artifact-affected volumetric images. The aim of this study was to investigate potential improvements of state-of-the-art MAR methods by using prior information on geometry and material of the implant. The influence of a novel prior knowledge-based segmentation (PS) compared with threshold-based segmentation (TS) on 2 MAR methods (linear interpolation [LI] and normalized-MAR [NORMAR]) was investigated. The segmentation is the initial step of both MAR methods. Prior knowledge-based segmentation uses 3-dimensional registered computer-aided design (CAD) data as prior knowledge to estimate the correct position and orientation of the metallic objects. Threshold-based segmentation uses an adaptive threshold to identify metal. Subsequently, for LI and NORMAR, the selected voxels are projected into the raw data domain to mark metal areas. Attenuation values in these areas are replaced by different interpolation schemes followed by a second reconstruction. Finally, the previously selected metal voxels are replaced by the metal voxels determined by PS or TS in the initial reconstruction. First, we investigated in an elaborate phantom study if the knowledge of the exact implant shape extracted from the CAD data provided by the manufacturer of the implant can improve the MAR result. Second, the leg of a human cadaver was scanned using a clinical CT system before and after the implantation of an artificial knee joint. The results were compared regarding segmentation accuracy, CT number accuracy, and the restoration of distorted structures. The use of PS improved the efficacy of LI and NORMAR compared with TS. Artifacts caused by insufficient segmentation were reduced, and additional information was made available within the projection data. The estimation of the implant shape was more exact and not dependent on a threshold value. Consequently, the visibility of structures was improved when comparing the new approach to the standard method. This was further confirmed by improved CT value accuracy and reduced image noise. The PS approach based on prior implant information provides image quality which is superior to TS-based MAR, especially when the shape of the metallic implant is complex. The new approach can be useful for improving MAR methods and dose calculations within radiation therapy based on the MAR corrected CT images.

Update on imaging techniques in oculoplastics

PubMed Central

Cetinkaya, Altug

2012-01-01

Imaging is a beneficial aid to the oculoplastic surgeon especially in orbital and lacrimal disorders when the pathology is not visible from outside. It is a powerful tool that may be benefited in not only diagnosis but also management and follow-up. The most common imaging modalities required are CT and MRI, with CT being more frequently ordered by oculoplastic surgeons. Improvements in technology enabled the acquisition times to shorten incredibly. Radiologists can now obtain images with superb resolution, and isolate the site and tissue of interest from other structures with special techniques. Better contrast agents and 3D imaging capabilities make complicated cases easier to identify. Color Doppler imaging is becoming more popular both for research and clinical purposes. Magnetic resonance angiography (MRA) added so much to the vascular system imaging recently. Although angiography is still the gold standard, new software and techniques rendered MRA as valuable as angiography in most circumstances. Stereotactic navigation, although in use for a long time, recently became the focus of interest for the oculoplastic surgeon especially in orbital decompressions. Improvements in radiology and nuclear medicine techniques of lacrimal drainage system imaging provided more detailed analysis of the system. PMID:23961020

Computer-aided detection of acute pulmonary embolism with 64-slice multi-detector row computed tomography: impact of the scanning conditions and overall image quality in the detection of peripheral clots.

PubMed

Dewailly, Marion; Rémy-Jardin, Martine; Duhamel, Alain; Faivre, Jean-Baptiste; Pontana, François; Deken, Valérie; Bakai, Anne-Marie; Remy, Jacques

2010-01-01

To evaluate the performance of a computer-aided detection (CAD) system for diagnosing peripheral acute pulmonary embolism (PE) with a 64-slice multi-detector row computed tomography (CT). Two radiologists investigated the accuracy of a software aimed at detecting peripheral clots (PECAD prototype, version 7; Siemens Medical Systems, Forchheim, Germany) by applying this tool for the analysis of the pulmonary arterial bed of 74 CT angiograms obtained with 64-slice dual-source CT (Definition; Siemens Medical Systems). These cases were retrospectively selected from a database of CT studies performed on the same CT unit, with a similar collimation (64 x 0.6 mm) and similar injection protocols. Patient selection was based on a variety of (1) scanning conditions, namely, nongated (n = 30), electrocardiography-gated (n = 30), and dual-energy CT angiograms (n = 14), and (2) image quality (IQ), namely, scans of excellent IQ (n = 53) and lower IQ due to lower levels of arterial enhancement and/or presence of noise (n = 21). The standard of truth was based on the 2 radiologists' consensus reading and the results of CAD. The software detected 80 of 93 peripheral clots present in the 21 patients (42 segmental and 38 subsegmental clots). The overall sensitivity (95% confidence interval) of the CAD tool was 86% (77%-92%) for detecting peripheral clots, 78% (64.5%-88%) at the segmental level and 97% (85.5%-99.9%) at the subsegmental level. Assuming normal vascular anatomy with 20 segmental and 40 subsegmental arteries, overall specificity and positive and negative predictive values (95% confidence interval) of the software were 91.8% (91%-92.6%), 18.4% (15%-22.4%), and 99.7% (99.5%-99.8%), respectively. A mean of 5.4 false positives was found per patient (total, 354 false positives), mainly linked to the presence of perivascular connective tissue (n = 119; 34%) and perivascular airspace consolidation (n = 97; 27%). The sensitivities (95% confidence interval) for the CAD tool were 91% (69.8%-99.3%) for dual-energy, 87% (59.3%-93.2%) for electrocardiography-gated, and 87% (73.5%-95.3%) for nongated scans (P > 0.05). No significant difference was found in the sensitivity of the CAD software when comparing the scans according to the scanning conditions and image quality. The evaluated CAD software has a good sensitivity in detecting peripheral PE, which is not influenced by the scanning conditions or the overall image quality.

Automated segmentation of murine lung tumors in x-ray micro-CT images

NASA Astrophysics Data System (ADS)

Swee, Joshua K. Y.; Sheridan, Clare; de Bruin, Elza; Downward, Julian; Lassailly, Francois; Pizarro, Luis

2014-03-01

Recent years have seen micro-CT emerge as a means of providing imaging analysis in pre-clinical study, with in-vivo micro-CT having been shown to be particularly applicable to the examination of murine lung tumors. Despite this, existing studies have involved substantial human intervention during the image analysis process, with the use of fully-automated aids found to be almost non-existent. We present a new approach to automate the segmentation of murine lung tumors designed specifically for in-vivo micro-CT-based pre-clinical lung cancer studies that addresses the specific requirements of such study, as well as the limitations human-centric segmentation approaches experience when applied to such micro-CT data. Our approach consists of three distinct stages, and begins by utilizing edge enhancing and vessel enhancing non-linear anisotropic diffusion filters to extract anatomy masks (lung/vessel structure) in a pre-processing stage. Initial candidate detection is then performed through ROI reduction utilizing obtained masks and a two-step automated segmentation approach that aims to extract all disconnected objects within the ROI, and consists of Otsu thresholding, mathematical morphology and marker-driven watershed. False positive reduction is finally performed on initial candidates through random-forest-driven classification using the shape, intensity, and spatial features of candidates. We provide validation of our approach using data from an associated lung cancer study, showing favorable results both in terms of detection (sensitivity=86%, specificity=89%) and structural recovery (Dice Similarity=0.88) when compared against manual specialist annotation.

Diagnostic and prognostic value of additional SPECT/CT in sentinel lymph node mapping in breast cancer patients.

PubMed

Stanzel, Susanne; Pernthaler, Birgit; Schwarz, Thomas; Bjelic-Radisic, Vesna; Kerschbaumer, Stefan; Aigner, Reingard M

2018-06-01

of the study was to demonstrate the diagnostic and prognostic value of SPECT/CT in sentinel lymph node mapping (SLNM) in patients with invasive breast cancer. 114 patients with invasive breast cancer with clinically negative lymph nodes were included in this retrospective study as they were referred for SLNM with 99m Tc-nanocolloid. Planar image acquisition was accomplished in a one-day or two-day protocol depending on the schedule of the surgical procedure. Low dose SPECT/CT was performed after the planar images. The sentinel lymph node biopsy (SLNB) was considered false negative if a primary recurrence developed within 12 months after SLNB in the axilla from which a tumor-free SLN had been removed. Between December 2009 and December 2011, 114 patients (pts.) underwent SLNM with additional SPECT/CT. Planar imaging identified in 109 pts. 139 SLNs, which were tumor-positive in 42 nodes (n = 41 pts.). SPECT/CT identified in 81 pts. 151 additional SLNs, of which 19 were tumor-positive and led to therapy change (axillary lymph node dissection) in 11 pts. (9.6 %). Of overall 61 tumor-positive SLNs (n = 52 pts.) SPECT/CT detected all, whereas planar imaging detected only 42 of 61 ( P < 0.0001). No patient had lymph node metastasis within 12 months after SLNB in the axilla from which a tumor-free SLN had been removed resulting in a false-negative rate of 0 %. The local relapse rate was 1.8 % leading to a 4-year disease-free survival rate of 90 %. Among patients with breast cancer, the use of SPECT/CT-aided SLNM correlated due to a better anatomical localization and identification of planar not visible SLNs with a higher detection rate of SLNs. This led to therapeutic consequences and an excellent false-negative and 4-year disease-free survival rate. Schattauer GmbH.

Emergency department imaging: are weather and calendar factors associated with imaging volume?

PubMed

Burns, K; Chernyak, V; Scheinfeld, M H

2016-12-01

To identify weather and calendar factors that would enable prediction of daily emergency department (ED) imaging volume to aid appropriate scheduling of imaging resources for efficient ED function. Daily ED triage and imaging volumes for radiography, computed tomography (CT), and ultrasound were obtained from hospital databases for the period between January 2011 and December 2013 at a large tertiary urban hospital with a Level II trauma centre. These data were tabulated alongside daily weather conditions (temperature, wind and precipitation), day of week, season, and holidays. Multivariate analysis was performed. Pearson correlations were used to measure the association between number of imaging studies performed and ED triage volume. For every additional 50 triaged patients, the odds of having high (imaging volume ≥90th percentile) radiography, CT, and ultrasound volume increased by 4.3 times (p<0.001), 1.5 times (p=0.02), and 1.4 times (p=0.02), respectively. Tuesday was an independent predictor of high radiography volume (odds ratio=2.8) and Monday was an independent predictor of high CT volume (odds ratio=3.0). Weekday status was an independent factor increasing the odds of a high US volume compared to Saturday (odds ratios ranging from 5.6-9.8). Weather factors and other calendar variables were not independent predictors of high imaging volume. Using Pearson correlations, ED triage volume correlated with number of radiographs, CT, and ultrasound examinations with r=0.73, 0.37, and 0.41, respectively (p<0.0001). As ED triage volume was found to be the only factor associated with imaging volume for all techniques, analysis of predictors of ED triage volumes at a particular healthcare facility would be useful to determine imaging needs. Although calendar and weather factors were found to be minor or non-significant independent predictors of ED imaging utilisation, these may be important in influencing the actual number of ED triages. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

A method for evaluating the performance of computer-aided detection of pulmonary nodules in lung cancer CT screening: detection limit for nodule size and density

PubMed Central

Kobayashi, Hajime; Ohkubo, Masaki; Narita, Akihiro; Marasinghe, Janaka C; Murao, Kohei; Matsumoto, Toru; Sone, Shusuke

2017-01-01

Objective: We propose the application of virtual nodules to evaluate the performance of computer-aided detection (CAD) of lung nodules in cancer screening using low-dose CT. Methods: The virtual nodules were generated based on the spatial resolution measured for a CT system used in an institution providing cancer screening and were fused into clinical lung images obtained at that institution, allowing site specificity. First, we validated virtual nodules as an alternative to artificial nodules inserted into a phantom. In addition, we compared the results of CAD analysis between the real nodules (n = 6) and the corresponding virtual nodules. Subsequently, virtual nodules of various sizes and contrasts between nodule density and background density (ΔCT) were inserted into clinical images (n = 10) and submitted for CAD analysis. Results: In the validation study, 46 of 48 virtual nodules had the same CAD results as artificial nodules (kappa coefficient = 0.913). Real nodules and the corresponding virtual nodules showed the same CAD results. The detection limits of the tested CAD system were determined in terms of size and density of peripheral lung nodules; we demonstrated that a nodule with a 5-mm diameter was detected when the nodule had a ΔCT > 220 HU. Conclusion: Virtual nodules are effective in evaluating CAD performance using site-specific scan/reconstruction conditions. Advances in knowledge: Virtual nodules can be an effective means of evaluating site-specific CAD performance. The methodology for guiding the detection limit for nodule size/density might be a useful evaluation strategy. PMID:27897029

Solid models for CT/MR image display: accuracy and utility in surgical planning

NASA Astrophysics Data System (ADS)

Mankovich, Nicholas J.; Yue, Alvin; Ammirati, Mario; Kioumehr, Farhad; Turner, Scott

1991-05-01

Medical imaging can now take wider advantage of Computer-Aided-Manufacturing through rapid prototyping technologies (RPT) such as stereolithography, laser sintering, and laminated object manufacturing to directly produce solid models of patient anatomy from processed CT and MR images. While conventional surgical planning relies on consultation with the radiologist combined with direct reading and measurement of CT and MR studies, 3-D surface and volumetric display workstations are providing a more easily interpretable view of patient anatomy. RPT can provide the surgeon with a life size model of patient anatomy constructed layer by layer with full internal detail. Although this life-size anatomic model is more easily understandable by the surgeon, its accuracy and true surgical utility remain untested. We have developed a prototype image processing and model fabrication system based on stereolithography, which provides the neurosurgeon with models of the skull base. Parallel comparison of the model with the original thresholded CT data and with a CRT displayed surface rendering showed that both have an accuracy of 99.6 percent. Because of the ease of exact voxel localization on the model, its precision was high with the standard deviation of measurement of 0.71 percent. The measurements on the surface rendered display proved more difficult to exactly locate and yielded a standard deviation of 2.37 percent. This paper presents our accuracy study and discussed ways of assessing the quality of neurosurgical plans when 3-D models a made available as planning tools.

Fracture risk assessment: improved evaluation of vertebral integrity among metastatic cancer patients to aid in surgical decision-making

NASA Astrophysics Data System (ADS)

Augustine, Kurt E.; Camp, Jon J.; Holmes, David R.; Huddleston, Paul M.; Lu, Lichun; Yaszemski, Michael J.; Robb, Richard A.

2012-03-01

Failure of the spine's structural integrity from metastatic disease can lead to both pain and neurologic deficit. Fractures that require treatment occur in over 30% of bony metastases. Our objective is to use computed tomography (CT) in conjunction with analytic techniques that have been previously developed to predict fracture risk in cancer patients with metastatic disease to the spine. Current clinical practice for cancer patients with spine metastasis often requires an empirical decision regarding spinal reconstructive surgery. Early image-based software systems used for CT analysis are time consuming and poorly suited for clinical application. The Biomedical Image Resource (BIR) at Mayo Clinic, Rochester has developed an image analysis computer program that calculates from CT scans, the residual load-bearing capacity in a vertebra with metastatic cancer. The Spine Cancer Assessment (SCA) program is built on a platform designed for clinical practice, with a workflow format that allows for rapid selection of patient CT exams, followed by guided image analysis tasks, resulting in a fracture risk report. The analysis features allow the surgeon to quickly isolate a single vertebra and obtain an immediate pre-surgical multiple parallel section composite beam fracture risk analysis based on algorithms developed at Mayo Clinic. The analysis software is undergoing clinical validation studies. We expect this approach will facilitate patient management and utilization of reliable guidelines for selecting among various treatment option based on fracture risk.

Machine Learning and Radiology

PubMed Central

Wang, Shijun; Summers, Ronald M.

2012-01-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

Classification of micro-CT images using 3D characterization of bone canal patterns in human osteogenesis imperfecta

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Jameson, John; Molthen, Robert; Wismüller, Axel

2017-03-01

Few studies have analyzed the microstructural properties of bone in cases of Osteogenenis Imperfecta (OI), or `brittle bone disease'. Current approaches mainly focus on bone mineral density measurements as an indirect indicator of bone strength and quality. It has been shown that bone strength would depend not only on composition but also structural organization. This study aims to characterize 3D structure of the cortical bone in high-resolution micro CT images. A total of 40 bone fragments from 28 subjects (13 with OI and 15 healthy controls) were imaged using micro tomography using a synchrotron light source (SRµCT). Minkowski functionals - volume, surface, curvature, and Euler characteristics - describing the topological organization of the bone were computed from the images. The features were used in a machine learning task to classify between healthy and OI bone. The best classification performance (mean AUC - 0.96) was achieved with a combined 4-dimensional feature of all Minkowski functionals. Individually, the best feature performance was seen using curvature (mean AUC - 0.85), which characterizes the edges within a binary object. These results show that quantitative analysis of cortical bone microstructure, in a computer-aided diagnostics framework, can be used to distinguish between healthy and OI bone with high accuracy.

Navigation of a robot-integrated fluorescence laparoscope in preoperative SPECT/CT and intraoperative freehand SPECT imaging data: a phantom study

NASA Astrophysics Data System (ADS)

van Oosterom, Matthias Nathanaël; Engelen, Myrthe Adriana; van den Berg, Nynke Sjoerdtje; KleinJan, Gijs Hendrik; van der Poel, Henk Gerrit; Wendler, Thomas; van de Velde, Cornelis Jan Hadde; Navab, Nassir; van Leeuwen, Fijs Willem Bernhard

2016-08-01

Robot-assisted laparoscopic surgery is becoming an established technique for prostatectomy and is increasingly being explored for other types of cancer. Linking intraoperative imaging techniques, such as fluorescence guidance, with the three-dimensional insights provided by preoperative imaging remains a challenge. Navigation technologies may provide a solution, especially when directly linked to both the robotic setup and the fluorescence laparoscope. We evaluated the feasibility of such a setup. Preoperative single-photon emission computed tomography/X-ray computed tomography (SPECT/CT) or intraoperative freehand SPECT (fhSPECT) scans were used to navigate an optically tracked robot-integrated fluorescence laparoscope via an augmented reality overlay in the laparoscopic video feed. The navigation accuracy was evaluated in soft tissue phantoms, followed by studies in a human-like torso phantom. Navigation accuracies found for SPECT/CT-based navigation were 2.25 mm (coronal) and 2.08 mm (sagittal). For fhSPECT-based navigation, these were 1.92 mm (coronal) and 2.83 mm (sagittal). All errors remained below the <1-cm detection limit for fluorescence imaging, allowing refinement of the navigation process using fluorescence findings. The phantom experiments performed suggest that SPECT-based navigation of the robot-integrated fluorescence laparoscope is feasible and may aid fluorescence-guided surgery procedures.

A graphical approach to optimizing variable-kernel smoothing parameters for improved deformable registration of CT and cone beam CT images

NASA Astrophysics Data System (ADS)

Hart, Vern; Burrow, Damon; Li, X. Allen

2017-08-01

A systematic method is presented for determining optimal parameters in variable-kernel deformable image registration of cone beam CT and CT images, in order to improve accuracy and convergence for potential use in online adaptive radiotherapy. Assessed conditions included the noise constant (symmetric force demons), the kernel reduction rate, the kernel reduction percentage, and the kernel adjustment criteria. Four such parameters were tested in conjunction with reductions of 5, 10, 15, 20, 30, and 40%. Noise constants ranged from 1.0 to 1.9 for pelvic images in ten prostate cancer patients. A total of 516 tests were performed and assessed using the structural similarity index. Registration accuracy was plotted as a function of iteration number and a least-squares regression line was calculated, which implied an average improvement of 0.0236% per iteration. This baseline was used to determine if a given set of parameters under- or over-performed. The most accurate parameters within this range were applied to contoured images. The mean Dice similarity coefficient was calculated for bladder, prostate, and rectum with mean values of 98.26%, 97.58%, and 96.73%, respectively; corresponding to improvements of 2.3%, 9.8%, and 1.2% over previously reported values for the same organ contours. This graphical approach to registration analysis could aid in determining optimal parameters for Demons-based algorithms. It also establishes expectation values for convergence rates and could serve as an indicator of non-physical warping, which often occurred in cases  >0.6% from the regression line.

In vivo longitudinal micro-CT study of bent long limb bones in rat offspring.

PubMed

De Schaepdrijver, Luc; Delille, Peter; Geys, Helena; Boehringer-Shahidi, Christian; Vanhove, Christian

2014-07-01

Micro-computed X-ray tomography (micro-CT) has been reported as a reliable method to assess ex vivo rat and rabbit fetal skeletons in embryo-fetal developmental toxicity studies. Since micro-CT is a non-invasive imaging modality it has the potential for longitudinal, in vivo investigation of postnatal skeletal development. This is the first paper using micro-CT to assess the reversibility of drug-induced bent long bones in a longitudinal study from birth to early adulthood in rat offspring. Analysis of the scans obtained on postnatal Day 0, 7, 21 and 80 showed complete recovery or repair of the bent long limb bones (including the scapula) within the first 3 weeks. When assessing risk the ability to demonstrate recovery is highly advantageous when interpreting such transient skeletal change. In summary, in vivo micro-CT of small laboratory animals can aid in non-clinical safety assessment, particularly for specific mechanistic purposes or to address a particular concern in developmental biology. Copyright © 2014 Elsevier Inc. All rights reserved.

Assessment of coronary artery calcium by chest CT compared with EKG-gated cardiac CT in the multicenter AIDS cohort study.

PubMed

Chandra, Divay; Gupta, Aman; Leader, Joseph K; Fitzpatrick, Meghan; Kingsley, Lawrence A; Kleerup, Eric; Haberlen, Sabina A; Budoff, Matthew J; Witt, Mallory; Post, Wendy S; Sciurba, Frank C; Morris, Alison

2017-01-01

Individuals with HIV are at increased risk for coronary artery disease (CAD). Early detection of subclinical CAD by assessment of coronary artery calcium (CAC) may help risk stratify and prevent CAD events in these individuals. However, the current standard to quantify CAC i.e. Agatston scoring requires EKG-gated cardiac CT imaging. To determine if the assessment of CAC using non-EKG-gated chest CT and the Weston scoring system is a useful surrogate for Agatston scores in HIV-infected and HIV-uninfected individuals. CAC was assessed by both the Weston and Agatston score in 108 men enrolled in the Multicenter AIDS Cohort Study. Participants were 55.2 (IQR 50.4; 59.9) years old and 62 (57.4%) were seropositive for HIV. Inter-observer agreement (rs = 0.94, κ = 90.0%, p<0.001, n = 21) and intra-observer agreement (rs = 0.95, κ = 95.2%, p<0.001, n = 97) for category of Weston score were excellent. Weston scores were associated with similar CAD risk factors as Agatston scores (age, race, HDL cholesterol level, all p<0.05) in our cohort. There was excellent correlation (rs = 0.92, p<0.001) and agreement (κw = 0.77, p<0.001) between Weston and Agatston scores. This study is the first to examine calcium scoring using chest CT in HIV-infected individuals and to independently validate the Weston score as a surrogate for the Agatston score. In clinical or research settings where EKG-gated cardiac CT is not feasible for the assessment of coronary calcium, Weston scoring by using chest CT should be considered.

Assessment of coronary artery calcium by chest CT compared with EKG-gated cardiac CT in the multicenter AIDS cohort study

PubMed Central

Chandra, Divay; Gupta, Aman; Leader, Joseph K.; Fitzpatrick, Meghan; Kingsley, Lawrence A.; Kleerup, Eric; Haberlen, Sabina A.; Budoff, Matthew J.; Witt, Mallory; Post, Wendy S.; Sciurba, Frank C.; Morris, Alison

2017-01-01

Rationale Individuals with HIV are at increased risk for coronary artery disease (CAD). Early detection of subclinical CAD by assessment of coronary artery calcium (CAC) may help risk stratify and prevent CAD events in these individuals. However, the current standard to quantify CAC i.e. Agatston scoring requires EKG-gated cardiac CT imaging. Objective To determine if the assessment of CAC using non-EKG-gated chest CT and the Weston scoring system is a useful surrogate for Agatston scores in HIV-infected and HIV-uninfected individuals. Methods and measurements CAC was assessed by both the Weston and Agatston score in 108 men enrolled in the Multicenter AIDS Cohort Study. Results Participants were 55.2 (IQR 50.4; 59.9) years old and 62 (57.4%) were seropositive for HIV. Inter-observer agreement (rs = 0.94, κ = 90.0%, p<0.001, n = 21) and intra-observer agreement (rs = 0.95, κ = 95.2%, p<0.001, n = 97) for category of Weston score were excellent. Weston scores were associated with similar CAD risk factors as Agatston scores (age, race, HDL cholesterol level, all p<0.05) in our cohort. There was excellent correlation (rs = 0.92, p<0.001) and agreement (κw = 0.77, p<0.001) between Weston and Agatston scores. Conclusions This study is the first to examine calcium scoring using chest CT in HIV-infected individuals and to independently validate the Weston score as a surrogate for the Agatston score. In clinical or research settings where EKG-gated cardiac CT is not feasible for the assessment of coronary calcium, Weston scoring by using chest CT should be considered. PMID:28453572

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

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

NONE

2011-02-15

Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.more » Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule{>=}3 mm,''''nodule<3 mm,'' and ''non-nodule{>=}3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule{>=}3 mm'' by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.« less

MO-FG-CAMPUS-JeP1-05: Water Equivalent Path Length Calculations Using Scatter-Corrected Head and Neck CBCT Images to Evaluate Patients for Adaptive Proton Therapy

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

Kim, J; Park, Y; Sharp, G

Purpose: To establish a method to evaluate the dosimetric impact of anatomic changes in head and neck patients during proton therapy by using scatter-corrected cone-beam CT (CBCT) images. Methods: The water equivalent path length (WEPL) was calculated to the distal edge of PTV contours by using tomographic images available for six head and neck patients received photon therapy. The proton range variation was measured by calculating the difference between the distal WEPLs calculated with the planning CT and weekly treatment CBCT images. By performing an automatic rigid registration, six degrees-of-freedom (DOF) correction was made to the CBCT images to accountmore » for the patient setup uncertainty. For accurate WEPL calculations, an existing CBCT scatter correction algorithm, whose performance was already proven for phantom images, was calibrated for head and neck patient images. Specifically, two different image similarity measures, mutual information (MI) and mean square error (MSE), were tested for the deformable image registration (DIR) in the CBCT scatter correction algorithm. Results: The impact of weight loss was reflected in the distal WEPL differences with the aid of the automatic rigid registration reducing the influence of patient setup uncertainty on the WEPL calculation results. The WEPL difference averaged over distal area was 2.9 ± 2.9 (mm) across all fractions of six patients and its maximum, mostly found at the last available fraction, was 6.2 ± 3.4 (mm). The MSE-based DIR successfully registered each treatment CBCT image to the planning CT image. On the other hand, the MI-based DIR deformed the skin voxels in the planning CT image to the immobilization mask in the treatment CBCT image, most of which was cropped out of the planning CT image. Conclusion: The dosimetric impact of anatomic changes was evaluated by calculating the distal WEPL difference with the existing scatter-correction algorithm appropriately calibrated. Jihun Kim, Yang-Kyun Park, Gregory Sharp, and Brian Winey have received grant support from the NCI Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center.« less

SU-E-J-224: Multimodality Segmentation of Head and Neck Tumors

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

Aristophanous, M; Yang, J; Beadle, B

2014-06-01

Purpose: Develop an algorithm that is able to automatically segment tumor volume in Head and Neck cancer by integrating information from CT, PET and MR imaging simultaneously. Methods: Twenty three patients that were recruited under an adaptive radiotherapy protocol had MR, CT and PET/CT scans within 2 months prior to start of radiotherapy. The patients had unresectable disease and were treated either with chemoradiotherapy or radiation therapy alone. Using the Velocity software, the PET/CT and MR (T1 weighted+contrast) scans were registered to the planning CT using deformable and rigid registration respectively. The PET and MR images were then resampled accordingmore » to the registration to match the planning CT. The resampled images, together with the planning CT, were fed into a multi-channel segmentation algorithm, which is based on Gaussian mixture models and solved with the expectation-maximization algorithm and Markov random fields. A rectangular region of interest (ROI) was manually placed to identify the tumor area and facilitate the segmentation process. The auto-segmented tumor contours were compared with the gross tumor volume (GTV) manually defined by the physician. The volume difference and Dice similarity coefficient (DSC) between the manual and autosegmented GTV contours were calculated as the quantitative evaluation metrics. Results: The multimodality segmentation algorithm was applied to all 23 patients. The volumes of the auto-segmented GTV ranged from 18.4cc to 32.8cc. The average (range) volume difference between the manual and auto-segmented GTV was −42% (−32.8%–63.8%). The average DSC value was 0.62, ranging from 0.39 to 0.78. Conclusion: An algorithm for the automated definition of tumor volume using multiple imaging modalities simultaneously was successfully developed and implemented for Head and Neck cancer. This development along with more accurate registration algorithms can aid physicians in the efforts to interpret the multitude of imaging information available in radiotherapy today. This project was supported by a grant by Varian Medical Systems.« less

Precise segmentation of multiple organs in CT volumes using learning-based approach and information theory.

PubMed

Lu, Chao; Zheng, Yefeng; Birkbeck, Neil; Zhang, Jingdan; Kohlberger, Timo; Tietjen, Christian; Boettger, Thomas; Duncan, James S; Zhou, S Kevin

2012-01-01

In this paper, we present a novel method by incorporating information theory into the learning-based approach for automatic and accurate pelvic organ segmentation (including the prostate, bladder and rectum). We target 3D CT volumes that are generated using different scanning protocols (e.g., contrast and non-contrast, with and without implant in the prostate, various resolution and position), and the volumes come from largely diverse sources (e.g., diseased in different organs). Three key ingredients are combined to solve this challenging segmentation problem. First, marginal space learning (MSL) is applied to efficiently and effectively localize the multiple organs in the largely diverse CT volumes. Second, learning techniques, steerable features, are applied for robust boundary detection. This enables handling of highly heterogeneous texture pattern. Third, a novel information theoretic scheme is incorporated into the boundary inference process. The incorporation of the Jensen-Shannon divergence further drives the mesh to the best fit of the image, thus improves the segmentation performance. The proposed approach is tested on a challenging dataset containing 188 volumes from diverse sources. Our approach not only produces excellent segmentation accuracy, but also runs about eighty times faster than previous state-of-the-art solutions. The proposed method can be applied to CT images to provide visual guidance to physicians during the computer-aided diagnosis, treatment planning and image-guided radiotherapy to treat cancers in pelvic region.

Pulmonary embolism detection using localized vessel-based features in dual energy CT

NASA Astrophysics Data System (ADS)

Dicente Cid, Yashin; Depeursinge, Adrien; Foncubierta Rodríguez, Antonio; Platon, Alexandra; Poletti, Pierre-Alexandre; Müller, Henning

2015-03-01

Pulmonary embolism (PE) affects up to 600,000 patients and contributes to at least 100,000 deaths every year in the United States alone. Diagnosis of PE can be difficult as most symptoms are unspecific and early diagnosis is essential for successful treatment. Computed Tomography (CT) images can show morphological anomalies that suggest the existence of PE. Various image-based procedures have been proposed for improving computer-aided diagnosis of PE. We propose a novel method for detecting PE based on localized vessel-based features computed in Dual Energy CT (DECT) images. DECT provides 4D data indexed by the three spatial coordinates and the energy level. The proposed features encode the variation of the Hounsfield Units across the different levels and the CT attenuation related to the amount of iodine contrast in each vessel. A local classification of the vessels is obtained through the classification of these features. Moreover, the localization of the vessel in the lung provides better comparison between patients. Results show that the simple features designed are able to classify pulmonary embolism patients with an AUC (area under the receiver operating curve) of 0.71 on a lobe basis. Prior segmentation of the lung lobes is not necessary because an automatic atlas-based segmentation obtains similar AUC levels (0.65) for the same dataset. The automatic atlas reaches 0.80 AUC in a larger dataset with more control cases.

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

PubMed

Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing

2017-03-01

Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.

SparseBeads data: benchmarking sparsity-regularized computed tomography

NASA Astrophysics Data System (ADS)

Jørgensen, Jakob S.; Coban, Sophia B.; Lionheart, William R. B.; McDonald, Samuel A.; Withers, Philip J.

2017-12-01

Sparsity regularization (SR) such as total variation (TV) minimization allows accurate image reconstruction in x-ray computed tomography (CT) from fewer projections than analytical methods. Exactly how few projections suffice and how this number may depend on the image remain poorly understood. Compressive sensing connects the critical number of projections to the image sparsity, but does not cover CT, however empirical results suggest a similar connection. The present work establishes for real CT data a connection between gradient sparsity and the sufficient number of projections for accurate TV-regularized reconstruction. A collection of 48 x-ray CT datasets called SparseBeads was designed for benchmarking SR reconstruction algorithms. Beadpacks comprising glass beads of five different sizes as well as mixtures were scanned in a micro-CT scanner to provide structured datasets with variable image sparsity levels, number of projections and noise levels to allow the systematic assessment of parameters affecting performance of SR reconstruction algorithms6. Using the SparseBeads data, TV-regularized reconstruction quality was assessed as a function of numbers of projections and gradient sparsity. The critical number of projections for satisfactory TV-regularized reconstruction increased almost linearly with the gradient sparsity. This establishes a quantitative guideline from which one may predict how few projections to acquire based on expected sample sparsity level as an aid in planning of dose- or time-critical experiments. The results are expected to hold for samples of similar characteristics, i.e. consisting of few, distinct phases with relatively simple structure. Such cases are plentiful in porous media, composite materials, foams, as well as non-destructive testing and metrology. For samples of other characteristics the proposed methodology may be used to investigate similar relations.

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

NASA Astrophysics Data System (ADS)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-09-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 × 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver ( p < 0.05). Furthermore, the F-value, which was used as a scale for the difference in recognition rates, was highest in the average gray level, relatively high in the skewness and the entropy, and relatively low in the uniformity, the relative smoothness and the average contrast. The recognition rate for a fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Exploring a new quantitative image marker to assess benefit of chemotherapy to ovarian cancer patients

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Patil, Omkar; Aghaei, Faranak; Wang, Yunzhi; Zheng, Bin

2017-03-01

Accurately assessing the potential benefit of chemotherapy to cancer patients is an important prerequisite to developing precision medicine in cancer treatment. The previous study has shown that total psoas area (TPA) measured on preoperative cross-section CT image might be a good image marker to predict long-term outcome of pancreatic cancer patients after surgery. However, accurate and automated segmentation of TPA from the CT image is difficult due to the fuzzy boundary or connection of TPA to other muscle areas. In this study, we developed a new interactive computer-aided detection (ICAD) scheme aiming to segment TPA from the abdominal CT images more accurately and assess the feasibility of using this new quantitative image marker to predict the benefit of ovarian cancer patients receiving Bevacizumab-based chemotherapy. ICAD scheme was applied to identify a CT image slice of interest, which is located at the level of L3 (vertebral spines). The cross-sections of the right and left TPA are segmented using a set of adaptively adjusted boundary conditions. TPA is then quantitatively measured. In addition, recent studies have investigated that muscle radiation attenuation which reflects fat deposition in the tissue might be a good image feature for predicting the survival rate of cancer patients. The scheme and TPA measurement task were applied to a large national clinical trial database involving 1,247 ovarian cancer patients. By comparing with manual segmentation results, we found that ICAD scheme could yield higher accuracy and consistency for this task. Using a new ICAD scheme can provide clinical researchers a useful tool to more efficiently and accurately extract TPA as well as muscle radiation attenuation as new image makers, and allow them to investigate the discriminatory power of it to predict progression-free survival and/or overall survival of the cancer patients before and after taking chemotherapy.

Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

PubMed

Ferreira Junior, José Raniery; Oliveira, Marcelo Costa; de Azevedo-Marques, Paulo Mazzoncini

2016-12-01

Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

The predictive value of single-photon emission computed tomography/computed tomography for sentinel lymph node localization in head and neck cutaneous malignancy.

PubMed

Remenschneider, Aaron K; Dilger, Amanda E; Wang, Yingbing; Palmer, Edwin L; Scott, James A; Emerick, Kevin S

2015-04-01

Preoperative localization of sentinel lymph nodes in head and neck cutaneous malignancies can be aided by single-photon emission computed tomography/computed tomography (SPECT/CT); however, its true predictive value for identifying lymph nodes intraoperatively remains unquantified. This study aims to understand the sensitivity, specificity, and positive and negative predictive values of SPECT/CT in sentinel lymph node biopsy for cutaneous malignancies of the head and neck. Blinded retrospective imaging review with comparison to intraoperative gamma probe confirmed sentinel lymph nodes. A consecutive series of patients with a head and neck cutaneous malignancy underwent preoperative SPECT/CT followed by sentinel lymph node biopsy with a gamma probe. Two nuclear medicine physicians, blinded to clinical data, independently reviewed each SPECT/CT. Activity within radiographically defined nodal basins was recorded and compared to intraoperative gamma probe findings. Sensitivity, specificity, and negative and positive predictive values were calculated with subgroup stratification by primary tumor site. Ninety-two imaging reads were performed on 47 patients with cutaneous malignancy who underwent SPECT/CT followed by sentinel lymph node biopsy. Overall sensitivity was 73%, specificity 92%, positive predictive value 54%, and negative predictive value 96%. The predictive ability of SPECT/CT to identify the basin or an adjacent basin containing the single hottest node was 92%. SPECT/CT overestimated uptake by an average of one nodal basin. In the head and neck, SPECT/CT has higher reliability for primary lesions of the eyelid, scalp, and cheek. SPECT/CT has high sensitivity, specificity, and negative predictive value, but may overestimate relevant nodal basins in sentinel lymph node biopsy. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Inter- and Intraobserver Agreement of 18F-FDG PET/CT Image Interpretation in Patients Referred for Assessment of Cardiac Sarcoidosis.

PubMed

Ohira, Hiroshi; Ardle, Brian Mc; deKemp, Robert A; Nery, Pablo; Juneau, Daniel; Renaud, Jennifer M; Klein, Ran; Clarkin, Owen; MacDonald, Karen; Leung, Eugene; Nair, Girish; Beanlands, Rob; Birnie, David

2017-08-01

Recent studies have reported the usefulness of 18 F-FDG PET in aiding with the diagnosis and management of patients with cardiac sarcoidosis (CS). However, image interpretation of 18 F-FDG PET for CS is sometimes challenging. We sought to investigate the inter- and intraobserver agreement and explore factors that led to important discrepancies between readers. Methods: We studied consecutive patients with no significant coronary artery disease who were referred for assessment of CS. Two experienced readers masked to clinical information, imaging reports, independently reviewed 18 F-FDG PET/CT images. 18 F-FDG PET/CT images were interpreted according to a predefined standard operating procedure, with cardiac 18 F-FDG uptake patterns categorized into 5 patterns: none, focal, focal on diffuse, diffuse, and isolated lateral wall or basal uptake. Overall image assessment was classified as either consistent with active CS or not. Results: One hundred scans were included from 71 patients. Of these, 46 underwent 18 F-FDG PET/CT with a no-restriction diet (no-restriction group), and 54 underwent 18 F-FDG PET/CT with a low-carbohydrate, high-fat and protein-permitted diet (low-carb group). There was agreement of the interpretation category in 74 of 100 scans. The κ-value of agreement among all 5 categories was 0.64, indicating moderate agreement. For overall clinical interpretation, there was agreement in 93 of 100 scans (κ = 0.85). When scans were divided into the preparation groups, there was a trend toward higher agreement in the low-carb group versus the no-restriction group (80% vs. 67%, P = 0.08). Regarding the overall clinical interpretation, there was also a trend toward greater agreement in the low-carb group versus the no-restriction group (96% vs. 89%, P = 0.08). Conclusion : The interobserver agreement of cardiac 18 F-FDG uptake image patterns was moderate. However, agreement was better regarding overall interpretation of CS. Detailed prescan dietary preparation seemed to improve interobserver agreement. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Automated noninvasive classification of renal cancer on multiphase CT

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

Linguraru, Marius George; Wang, Shijun; Shah, Furhawn

2011-10-15

Purpose: To explore the added value of the shape of renal lesions for classifying renal neoplasms. To investigate the potential of computer-aided analysis of contrast-enhanced computed-tomography (CT) to quantify and classify renal lesions. Methods: A computer-aided clinical tool based on adaptive level sets was employed to analyze 125 renal lesions from contrast-enhanced abdominal CT studies of 43 patients. There were 47 cysts and 78 neoplasms: 22 Von Hippel-Lindau (VHL), 16 Birt-Hogg-Dube (BHD), 19 hereditary papillary renal carcinomas (HPRC), and 21 hereditary leiomyomatosis and renal cell cancers (HLRCC). The technique quantified the three-dimensional size and enhancement of lesions. Intrapatient and interphasemore » registration facilitated the study of lesion serial enhancement. The histograms of curvature-related features were used to classify the lesion types. The areas under the curve (AUC) were calculated for receiver operating characteristic curves. Results: Tumors were robustly segmented with 0.80 overlap (0.98 correlation) between manual and semi-automated quantifications. The method further identified morphological discrepancies between the types of lesions. The classification based on lesion appearance, enhancement and morphology between cysts and cancers showed AUC = 0.98; for BHD + VHL (solid cancers) vs. HPRC + HLRCC AUC = 0.99; for VHL vs. BHD AUC = 0.82; and for HPRC vs. HLRCC AUC = 0.84. All semi-automated classifications were statistically significant (p < 0.05) and superior to the analyses based solely on serial enhancement. Conclusions: The computer-aided clinical tool allowed the accurate quantification of cystic, solid, and mixed renal tumors. Cancer types were classified into four categories using their shape and enhancement. Comprehensive imaging biomarkers of renal neoplasms on abdominal CT may facilitate their noninvasive classification, guide clinical management, and monitor responses to drugs or interventions.« less

A role for 11C-methionine PET imaging in ACTH-dependent Cushing's syndrome.

PubMed

Koulouri, Olympia; Steuwe, Andrea; Gillett, Daniel; Hoole, Andrew C; Powlson, Andrew S; Donnelly, Neil A; Burnet, Neil G; Antoun, Nagui M; Cheow, Heok; Mannion, Richard J; Pickard, John D; Gurnell, Mark

2015-10-01

We report our experience of functional imaging with (11)C-methionine positron emission tomography-computed tomography (PET-CT) co-registered with 3D gradient echo (spoiled gradient recalled (SPGR)) magnetic resonance imaging (MRI) in the investigation of ACTH-dependent Cushing's syndrome. Twenty patients with i) de novo Cushing's disease (CD, n=10), ii) residual or recurrent hypercortisolism following first pituitary surgery (±radiotherapy; n=8) or iii) ectopic Cushing's syndrome (n=2) were referred to our centre for functional imaging studies between 2010 and 2015. Six of the patients with de novo CD and five of those with persistent/relapsed disease had a suspected abnormality on conventional MRI. All patients underwent (11)C-methionine PET-CT. For pituitary imaging, co-registration of PET-CT images with contemporaneous SPGR MRI (1 mm slice thickness) was performed, followed by detailed mapping of (11)C-methionine uptake across the sella in three planes (coronal, sagittal and axial). This allowed us to determine whether suspected adenomas seen on structural imaging exhibited focal tracer uptake on functional imaging. In seven of ten patients with de novo CD, asymmetric (11)C-methionine uptake was observed within the sella, which co-localized with the suspected site of a corticotroph microadenoma visualised on SPGR MRI (and which was subsequently confirmed histologically following successful transsphenoidal surgery (TSS)). Focal (11)C-methionine uptake that correlated with a suspected abnormality on pituitary MRI was seen in five of eight patients with residual or recurrent Cushing's syndrome following first TSS (and pituitary radiotherapy in two cases). Two patients elected to undergo repeat TSS with histology confirming a corticotroph tumour in each case. In two patients with the ectopic ACTH syndrome, (11)C-methionine was concentrated in sites of distant metastases, with minimal uptake in the sellar region. (11)C-methionine PET-CT can aid the detection of ACTH-secreting tumours in Cushing's syndrome and facilitate targeted therapy. © 2015 European Society of Endocrinology.

Diagnostic imaging of trabecular bone microstructure for oral implants: a literature review.

PubMed

Ibrahim, N; Parsa, A; Hassan, B; van der Stelt, P; Wismeijer, D

2013-01-01

Several dental implant studies have reported that radiographic evaluation of bone quality can aid in reducing implant failure. Bone quality is assessed in terms of its quantity, density, trabecular characteristics and cells. Current imaging modalities vary widely in their efficiency in assessing trabecular structures, especially in a clinical setting. Most are very costly, require an extensive scanning procedure coupled with a high radiation dose and are only partially suitable for patient use. This review examines the current literature regarding diagnostic imaging assessment of trabecular microstructure prior to oral implant placement and suggests cone beam CT as a method of choice for evaluating trabecular bone microstructure.

Intraoperative imaging for patient safety and QA: detection of intracranial hemorrhage using C-arm cone-beam CT

NASA Astrophysics Data System (ADS)

Schafer, Sebastian; Wang, Adam; Otake, Yoshito; Stayman, J. W.; Zbijewski, Wojciech; Kleinszig, Gerhard; Xia, Xuewei; Gallia, Gary L.; Siewerdsen, Jeffrey H.

2013-03-01

Intraoperative imaging could improve patient safety and quality assurance (QA) via the detection of subtle complications that might otherwise only be found hours after surgery. Such capability could therefore reduce morbidity and the need for additional intervention. Among the severe adverse events that could be more quickly detected by high-quality intraoperative imaging is acute intracranial hemorrhage (ICH), conventionally assessed using post-operative CT. A mobile C-arm capable of high-quality cone-beam CT (CBCT) in combination with advanced image reconstruction techniques is reported as a means of detecting ICH in the operating room. The system employs an isocentric C-arm with a flat-panel detector in dual gain mode, correction of x-ray scatter and beam-hardening, and a penalized likelihood (PL) iterative reconstruction method. Performance in ICH detection was investigated using a quantitative phantom focusing on (non-contrast-enhanced) blood-brain contrast, an anthropomorphic head phantom, and a porcine model with injection of fresh blood bolus. The visibility of ICH was characterized in terms of contrast-to-noise ratio (CNR) and qualitative evaluation of images by a neurosurgeon. Across a range of size and contrast of the ICH as well as radiation dose from the CBCT scan, the CNR was found to increase from ~2.2-3.7 for conventional filtered backprojection (FBP) to ~3.9-5.4 for PL at equivalent spatial resolution. The porcine model demonstrated superior ICH detectability for PL. The results support the role of high-quality mobile C-arm CBCT employing advanced reconstruction algorithms for detecting subtle complications in the operating room at lower radiation dose and lower cost than intraoperative CT scanners and/or fixedroom C-arms. Such capability could present a potentially valuable aid to patient safety and QA.

Analysis of 3D Prints by X-ray Computed Microtomography and Terahertz Pulsed Imaging.

PubMed

Markl, Daniel; Zeitler, J Axel; Rasch, Cecilie; Michaelsen, Maria Høtoft; Müllertz, Anette; Rantanen, Jukka; Rades, Thomas; Bøtker, Johan

2017-05-01

A 3D printer was used to realise compartmental dosage forms containing multiple active pharmaceutical ingredient (API) formulations. This work demonstrates the microstructural characterisation of 3D printed solid dosage forms using X-ray computed microtomography (XμCT) and terahertz pulsed imaging (TPI). Printing was performed with either polyvinyl alcohol (PVA) or polylactic acid (PLA). The structures were examined by XμCT and TPI. Liquid self-nanoemulsifying drug delivery system (SNEDDS) formulations containing saquinavir and halofantrine were incorporated into the 3D printed compartmentalised structures and in vitro drug release determined. A clear difference in terms of pore structure between PVA and PLA prints was observed by extracting the porosity (5.5% for PVA and 0.2% for PLA prints), pore length and pore volume from the XμCT data. The print resolution and accuracy was characterised by XμCT and TPI on the basis of the computer-aided design (CAD) models of the dosage form (compartmentalised PVA structures were 7.5 ± 0.75% larger than designed; n = 3). The 3D printer can reproduce specific structures very accurately, whereas the 3D prints can deviate from the designed model. The microstructural information extracted by XμCT and TPI will assist to gain a better understanding about the performance of 3D printed dosage forms.

Brain abscesses as a metastatic manifestation of strangles: symptomatology and the use of magnetic resonance imaging as a diagnostic aid.

PubMed

Spoormakers, T J P; Ensink, J M; Goehring, L S; Koeman, J P; Ter Braake, F; van der Vlugt-Meijer, R H; van den Belt, A J M

2003-03-01

The occurrence of unexpectedly high numbers of horses with neurological signs during two outbreaks of strangles required prompt in-depth researching of these cases, including the exploration of magnetic resonance imaging (MRI) as a possible diagnostic technique. To describe the case series and assess the usefulness of MRI as an imaging modality for cases suspected of space-occupying lesions in the cerebral cavity. Four cases suspected of suffering from cerebral damage due to Streptococcus equi subsp. equi infection were examined clinically, pathologically, bacteriologically, by clinical chemistry (3 cases) and MRI (2 cases). In one case, MRI findings were compared to images acquired using computer tomography (CT). In all cases, cerebral abscesses positive for Streptococcus equi subsp. equi were found, which explained the clinical signs. Although the lesions could be visualised with CT, MRI images were superior in representing the exact anatomic reality of the soft tissue lesions. The diagnosis of bastard strangles characterised by metastatic brain abscesses was confirmed. MRI appeared to be an excellent tool for the imaging of cerebral lesions in the horse. The high incidence of neurological complications could not be explained but possibly indicated a change in virulence of certain strains of Streptococcus equi subsp. equi. MRI images were very detailed, permitting visualisation of much smaller lesions than demonstrated in this study and this could allow prompt clinical intervention in less advanced cases with a better prognosis. Further, MRI could assist in the surgical treatment of brain abscesses, as has been described earlier for CT.

Computer-based analysis of microvascular alterations in a mouse model for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Heinzer, Stefan; Müller, Ralph; Stampanoni, Marco; Abela, Rafael; Meyer, Eric P.; Ulmann-Schuler, Alexandra; Krucker, Thomas

2007-03-01

Vascular factors associated with Alzheimer's disease (AD) have recently gained increased attention. To investigate changes in vascular, particularly microvascular architecture, we developed a hierarchical imaging framework to obtain large-volume, high-resolution 3D images from brains of transgenic mice modeling AD. In this paper, we present imaging and data analysis methods which allow compiling unique characteristics from several hundred gigabytes of image data. Image acquisition is based on desktop micro-computed tomography (µCT) and local synchrotron-radiation µCT (SRµCT) scanning with a nominal voxel size of 16 µm and 1.4 µm, respectively. Two visualization approaches were implemented: stacks of Z-buffer projections for fast data browsing, and progressive-mesh based surface rendering for detailed 3D visualization of the large datasets. In a first step, image data was assessed visually via a Java client connected to a central database. Identified characteristics of interest were subsequently quantified using global morphometry software. To obtain even deeper insight into microvascular alterations, tree analysis software was developed providing local morphometric parameters such as number of vessel segments or vessel tortuosity. In the context of ever increasing image resolution and large datasets, computer-aided analysis has proven both powerful and indispensable. The hierarchical approach maintains the context of local phenomena, while proper visualization and morphometry provide the basis for detailed analysis of the pathology related to structure. Beyond analysis of microvascular changes in AD this framework will have significant impact considering that vascular changes are involved in other neurodegenerative diseases as well as in cancer, cardiovascular disease, asthma, and arthritis.

Radiomics-based features for pattern recognition of lung cancer histopathology and metastases.

PubMed

Ferreira Junior, José Raniery; Koenigkam-Santos, Marcel; Cipriano, Federico Enrique Garcia; Fabro, Alexandre Todorovic; Azevedo-Marques, Paulo Mazzoncini de

2018-06-01

lung cancer is the leading cause of cancer-related deaths in the world, and its poor prognosis varies markedly according to tumor staging. Computed tomography (CT) is the imaging modality of choice for lung cancer evaluation, being used for diagnosis and clinical staging. Besides tumor stage, other features, like histopathological subtype, can also add prognostic information. In this work, radiomics-based CT features were used to predict lung cancer histopathology and metastases using machine learning models. local image datasets of confirmed primary malignant pulmonary tumors were retrospectively evaluated for testing and validation. CT images acquired with same protocol were semiautomatically segmented. Tumors were characterized by clinical features and computer attributes of intensity, histogram, texture, shape, and volume. Three machine learning classifiers used up to 100 selected features to perform the analysis. radiomics-based features yielded areas under the receiver operating characteristic curve of 0.89, 0.97, and 0.92 at testing and 0.75, 0.71, and 0.81 at validation for lymph nodal metastasis, distant metastasis, and histopathology pattern recognition, respectively. the radiomics characterization approach presented great potential to be used in a computational model to aid lung cancer histopathological subtype diagnosis as a "virtual biopsy" and metastatic prediction for therapy decision support without the necessity of a whole-body imaging scanning. Copyright © 2018 Elsevier B.V. All rights reserved.

Computed tomography-magnetic resonance image fusion: a clinical evaluation of an innovative approach for improved tumor localization in primary central nervous system lesions.

PubMed

Lattanzi, J P; Fein, D A; McNeeley, S W; Shaer, A H; Movsas, B; Hanks, G E

1997-01-01

We describe our initial experience with the AcQSim (Picker International, St. David, PA) computed tomography-magnetic resonance imaging (CT-MRI) fusion software in eight patients with intracranial lesions. MRI data are electronically integrated into the CT-based treatment planning system. Since MRI is superior to CT in identifying intracranial abnormalities, we evaluated the precision and feasibility of this new localization method. Patients initially underwent CT simulation from C2 to the most superior portion of the scalp. T2 and post-contrast T1-weighted MRI of this area was then performed. Patient positioning was duplicated utilizing a head cup and bridge of nose to forehead angle measurements. First, a gross tumor volume (GTV) was identified utilizing the CT (CT/GTV). The CT and MRI scans were subsequently fused utilizing a point pair matching method and a second GTV (CT-MRI/GTV) was contoured with the aid of both studies. The fusion process was uncomplicated and completed in a timely manner. Volumetric analysis revealed the CT-MRI/GTV to be larger than the CT/GTV in all eight cases. The mean CT-MRI/GTV was 28.7 cm3 compared to 16.7 cm3 by CT alone. This translated into a 72% increase in the radiographic tumor volume by CT-MRI. A simulated dose-volume histogram in two patients revealed that marginal portions of the lesion, as identified by CT and MRI, were not included in the high dose treatment volume as contoured with the use of CT alone. Our initial experience with the fusion software demonstrated an improvement in tumor localization with this technique. Based on these patients the use of CT alone for treatment planning purposes in central nervous system (CNS) lesions is inadequate and would result in an unacceptable rate of marginal misses. The importation of MRI data into three-dimensional treatment planning is therefore crucial to accurate tumor localization. The fusion process simplifies and improves precision of this task.

Machine learning and radiology.

PubMed

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Texture-based CAD improves diagnosis for low-dose CT colonography

NASA Astrophysics Data System (ADS)

Liang, Zhengrong; Cohen, Harris; Posniak, Erica; Fiore, Eddie; Wang, Zigang; Li, Bin; Andersen, Joseph; Harrington, Donald

2008-03-01

Computed tomography (CT)-based virtual colonoscopy or CT colonography (CTC) currently utilizes oral contrast solutions to tag the colonic fluid and possibly residual stool for differentiation from the colon wall and polyps. The enhanced image density of the tagged colonic materials causes a significant partial volume (PV) effect into the colon wall as well as the lumen space (filled with air or CO II). The PV effect on the colon wall can "bury" polyps of size as large as 5mm by increasing their image densities to a noticeable level, resulting in false negatives. It can also create false positives when PV effect goes into the lumen space. We have been modeling the PV effect for mixture-based image segmentation and developing text-based computer-aided detection of polyp (CADpolyp) by utilizing the PV mixture-based image segmentation. This work presents some preliminary results of developing and applying texture-based CADpolyp technique to low-dose CTC studies. A total of 114 studies of asymptomatic patients older than 50, who underwent CTC and then optical colonoscopy (OC) on the same day, were selected from a database, which was accumulated in the past decade and contains various bowel preparations and CT scanning protocols. The participating radiologists found ten polyps of greater than 5 mm from a total of 16 OC proved polyps, i.e., a detection sensitivity of 63%. They scored 23 false positives from the database, i.e., a 20% false positive rate. Approximately 70% of the datasets were marked as imperfect bowel cleansing and/or presence of image artifacts. The impact of imperfect bowel cleansing and image artifacts on VC performance is significant. The texture-based CADpolyp detected all the polyps with an average of 2.68 false positives per patient. This indicates that texture-based CADpolyp can improve the CTC performance in the cases of imperfect cleansed bowels and presence of image artifacts.

Dynamic MRI-based computer aided diagnostic systems for early detection of kidney transplant rejection: A survey

NASA Astrophysics Data System (ADS)

Mostapha, Mahmoud; Khalifa, Fahmi; Alansary, Amir; Soliman, Ahmed; Gimel'farb, Georgy; El-Baz, Ayman

2013-10-01

Early detection of renal transplant rejection is important to implement appropriate medical and immune therapy in patients with transplanted kidneys. In literature, a large number of computer-aided diagnostic (CAD) systems using different image modalities, such as ultrasound (US), magnetic resonance imaging (MRI), computed tomography (CT), and radionuclide imaging, have been proposed for early detection of kidney diseases. A typical CAD system for kidney diagnosis consists of a set of processing steps including: motion correction, segmentation of the kidney and/or its internal structures (e.g., cortex, medulla), construction of agent kinetic curves, functional parameter estimation, diagnosis, and assessment of the kidney status. In this paper, we survey the current state-of-the-art CAD systems that have been developed for kidney disease diagnosis using dynamic MRI. In addition, the paper addresses several challenges that researchers face in developing efficient, fast and reliable CAD systems for the early detection of kidney diseases.

PET imaging of β-glucuronidase activity by an activity-based 124I-trapping probe for the personalized glucuronide prodrug targeted therapy.

PubMed

Su, Yu-Cheng; Cheng, Ta-Chun; Leu, Yu-Ling; Roffler, Steve R; Wang, Jaw-Yuan; Chuang, Chih-Hung; Kao, Chien-Han; Chen, Kai-Chuan; Wang, Hsin-Ell; Cheng, Tian-Lu

2014-12-01

Beta-glucuronidase (βG) is a potential biomarker for cancer diagnosis and prodrug therapy. The ability to image βG activity in patients would assist in personalized glucuronide prodrug cancer therapy. However, whole-body imaging of βG activity for medical usage is not yet available. Here, we developed a radioactive βG activity-based trapping probe for positron emission tomography (PET). We generated a (124)I-tyramine-conjugated difluoromethylphenol beta-glucuronide probe (TrapG) to form (124)I-TrapG that could be selectively activated by βG for subsequent attachment of (124)I-tyramine to nucleophilic moieties near βG-expressing sites. We estimated the specificity of a fluorescent FITC-TrapG, the cytotoxicity of tyramine-TrapG, and the serum half-life of (124)I-TrapG. βG targeting of (124)I-TrapG in vivo was examined by micro-PET. The biodistribution of (131)I-TrapG was investigated in different organs. Finally, we imaged the endogenous βG activity and assessed its correlation with therapeutic efficacy of 9-aminocamptothecin glucuronide (9ACG) prodrug in native tumors. FITC-TrapG showed specific trapping at βG-expressing CT26 (CT26/mβG) cells but not in CT26 cells. The native TrapG probe possessed low cytotoxicity. (124)I-TrapG preferentially accumulated in CT26/mβG but not CT26 cells. Meanwhile, micro-PET and whole-body autoradiography results demonstrated that (124)I-TrapG signals in CT26/mβG tumors were 141.4-fold greater than in CT26 tumors. Importantly, Colo205 xenografts in nude mice that express elevated endogenous βG can be monitored by using infrared glucuronide trapping probes (NIR-TrapG) and suppressed by 9ACG prodrug treatment. (124)I-TrapG exhibited low cytotoxicity allowing long-term monitoring of βG activity in vivo to aid in the optimization of prodrug targeted therapy. ©2014 American Association for Cancer Research.

Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.

PubMed

Madero Orozco, Hiram; Vergara Villegas, Osslan Osiris; Cruz Sánchez, Vianey Guadalupe; Ochoa Domínguez, Humberto de Jesús; Nandayapa Alfaro, Manuel de Jesús

2015-02-12

Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung nodule is a round lesion which can be either non-cancerous or cancerous. In the CT, the lung cancer is observed as round white shadow nodules. The possibility to obtain a manually accurate interpretation from CT scans demands a big effort by the radiologist and might be a fatiguing process. Therefore, the design of a computer-aided diagnosis (CADx) system would be helpful as a second opinion tool. The stages of the proposed CADx are: a supervised extraction of the region of interest to eliminate the shape differences among CT images. The Daubechies db1, db2, and db4 wavelet transforms are computed with one and two levels of decomposition. After that, 19 features are computed from each wavelet sub-band. Then, the sub-band and attribute selection is performed. As a result, 11 features are selected and combined in pairs as inputs to the support vector machine (SVM), which is used to distinguish CT images containing cancerous nodules from those not containing nodules. The clinical data set used for experiments consists of 45 CT scans from ELCAP and LIDC. For the training stage 61 CT images were used (36 with cancerous lung nodules and 25 without lung nodules). The system performance was tested with 45 CT scans (23 CT scans with lung nodules and 22 without nodules), different from that used for training. The results obtained show that the methodology successfully classifies cancerous nodules with a diameter from 2 mm to 30 mm. The total preciseness obtained was 82%; the sensitivity was 90.90%, whereas the specificity was 73.91%. The CADx system presented is competitive with other literature systems in terms of sensitivity. The system reduces the complexity of classification by not performing the typical segmentation stage of most CADx systems. Additionally, the novelty of the algorithm is the use of a wavelet feature descriptor.

Organ dose measurements from multiple-detector computed tomography using a commercial dosimetry system and tomographic, physical phantoms

NASA Astrophysics Data System (ADS)

Lavoie, Lindsey K.

The technology of computed tomography (CT) imaging has soared over the last decade with the use of multi-detector CT (MDCT) scanners that are capable of performing studies in a matter of seconds. While the diagnostic information obtained from MDCT imaging is extremely valuable, it is important to ensure that the radiation doses resulting from these studies are at acceptably safe levels. This research project focused on the measurement of organ doses resulting from modern MDCT scanners. A commercially-available dosimetry system was used to measure organ doses. Small dosimeters made of optically-stimulated luminescent (OSL) material were analyzed with a portable OSL reader. Detailed verification of this system was performed. Characteristics studied include energy, scatter, and angular responses; dose linearity, ability to erase the exposed dose and ability to reuse dosimeters multiple times. The results of this verification process were positive. While small correction factors needed to be applied to the dose reported by the OSL reader, these factors were small and expected. Physical, tomographic pediatric and adult phantoms were used to measure organ doses. These phantoms were developed from CT images and are composed of tissue-equivalent materials. Because the adult phantom is comprised of numerous segments, dosimeters were placed in the phantom at several organ locations, and doses to select organs were measured using three clinical protocols: pediatric craniosynostosis, adult brain perfusion and adult cardiac CT angiography (CTA). A wide-beam, 320-slice, volumetric CT scanner and a 64-slice, MDCT scanner were used for organ dose measurements. Doses ranged from 1 to 26 mGy for the pediatric protocol, 1 to 1241 mGy for the brain perfusion protocol, and 2-100 mGy for the cardiac protocol. In most cases, the doses measured on the 64-slice scanner were higher than those on the 320-slice scanner. A methodology to measure organ doses with OSL dosimeters received from CT imaging has been presented. These measurements are especially important in keeping with the ALARA (as low as reasonably achievable) principle. While diagnostic information from CT imaging is valuable and necessary, the dose to patients is always a consideration. This methodology aids in this important task. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)

MO-G-9A-01: Imaging Refresher for Standard of Care Radiation Therapy

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

Labby, Z; Sensakovic, W; Hipp, E

2014-06-15

Imaging techniques and technology which were previously the domain of diagnostic medicine are becoming increasingly integrated and utilized in radiation therapy (RT) clinical practice. As such, there are a number of specific imaging topics that are highly applicable to modern radiation therapy physics. As imaging becomes more widely integrated into standard clinical radiation oncology practice, the impetus is on RT physicists to be informed and up-to-date on those imaging modalities relevant to the design and delivery of therapeutic radiation treatments. For example, knowing that, for a given situation, a fluid attenuated inversion recovery (FLAIR) image set is most likely whatmore » the physician would like to import and contour is helpful, but may not be sufficient to providing the best quality of care. Understanding the physics of how that pulse sequence works and why it is used could help assess its utility and determine if it is the optimal sequence for aiding in that specific clinical situation. It is thus important that clinical medical physicists be able to understand and explain the physics behind the imaging techniques used in all aspects of clinical radiation oncology practice. This session will provide the basic physics for a variety of imaging modalities for applications that are highly relevant to radiation oncology practice: computed tomography (CT) (including kV, MV, cone beam CT [CBCT], and 4DCT), positron emission tomography (PET)/CT, magnetic resonance imaging (MRI), and imaging specific to brachytherapy (including ultrasound and some brachytherapy specific topics in MR). For each unique modality, the image formation process will be reviewed, trade-offs between image quality and other factors (e.g. imaging time or radiation dose) will be clarified, and typically used cases for each modality will be introduced. The current and near-future uses of these modalities and techniques in radiation oncology clinical practice will also be discussed. Learning Objectives: To review the basic physical science principles of CT, PET, MR, and ultrasound imaging. To understand how the images are created, and present their specific role in patient management and treatment planning for therapeutic radiation (both external beam and brachytherapy). To discuss when and how each specific imaging modality is currently used in clinical practice, as well as how they may come to be used in the near future.« less

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.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.

PubMed

Shin, Hoo-Chang; Roth, Holger R; Gao, Mingchen; Lu, Le; Xu, Ziyue; Nogues, Isabella; Yao, Jianhua; Mollura, Daniel; Summers, Ronald M

2016-05-01

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models pre-trained from natural image dataset to medical image tasks. In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computer-aided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks.

The Utility of PET/CT in the Planning of External Radiation Therapy for Prostate Cancer.

PubMed

Calais, Jeremie; Cao, Minsong; Nickols, Nicholas G

2018-04-01

Radiotherapy and radical prostatectomy are the definitive treatment options for patients with localized prostate cancer. A rising level of prostate-specific antigen after radical prostatectomy indicates prostate cancer recurrence, and these patients may still be cured with salvage radiotherapy. To maximize chance for cure, the irradiated volumes should completely encompass the extent of disease. Therefore, accurate estimation of the location of disease is critical for radiotherapy planning in both the definitive and the salvage settings. Current first-line imaging for prostate cancer has limited sensitivity for detection of disease both at initial staging and at biochemical recurrence. Integration of PET into routine evaluation of prostate cancer patients may improve both staging accuracy and radiotherapy planning. 18 F-FDG PET/CT is now routinely used in radiation planning for several cancer types. However, 18 F-FDG PET/CT has low sensitivity for prostate cancer. Additional PET probes evaluated in prostate cancer include 18 F-sodium fluoride, 11 C-acetate, 11 C- or 18 F-choline, 18 F-fluciclovine, and 68 Ga- or 18 F-labeled ligands that bind prostate-specific membrane antigen (PSMA). PSMA ligands appear to be the most sensitive and specific but have not yet received Food and Drug Administration New Drug Application approval for use in the United States. Retrospective and prospective investigations suggest a potential major impact of PET/CT on prostate radiation treatment planning. Prospective trials randomizing patients to routine radiotherapy planning versus PET/CT-aided planning may show meaningful clinical outcomes. Prospective clinical trials evaluating the addition of 18 F-fluciclovine PET/CT for planning of salvage radiotherapy with clinical endpoints are under way. Prospective trials evaluating the clinical impact of PSMA PET/CT on prostate radiation planning are indicated. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Wide field of view CT and acromioclavicular joint instability: A technical innovation.

PubMed

Dyer, David R; Troupis, John M; Kamali Moaveni, Afshin

2015-06-01

A 21-year-old female with a traumatic shoulder injury is investigated and managed for symptoms relating to this injury. Pathology at the acromioclavicular joint is detected clinically; however, clinical examination and multiple imaging modalities do not reach a unified diagnosis on the grading of this acromioclavicular joint injury. When management appropriate to that suggested injury grading fail to help the patient's symptoms, further investigation methods were utilised. Wide field of view, dynamic CT (4D CT) is conducted on the patient's affected shoulder using a 320 × 0.5 mm detector multislice CT. Scans were conducted with a static table as the patient completed three movements of the affected shoulder. Capturing multiple data sets per second over a z-axis of 16 cm, measurements of the acromioclavicular joint were made, to show dynamic changes at the joint. Acromioclavicular (AC) joint translations were witnessed in three planes (a previously unrecognised pathology in the grading of acromioclavicular joint injuries). Translation in multiple planes was also not evident on careful clinical examination of this patient. AC joint width, anterior-posterior translation, superior-inferior translation and coracoclavicular width were measured with planar reconstructions while volume-rendered images and dynamic sequences aiding visual understanding of the pathology. Wide field of view dynamic CT (4D CT) is an accurate and quick modality to diagnose complex acromioclavicular joint injury. It provides dynamic information that no other modality can; 4D CT shows future benefits for clinical approach to diagnosis and management of acromioclavicular joint injury, and other musculoskeletal pathologies. © 2015 The Royal Australian and New Zealand College of Radiologists.

Design and Development of a Megavoltage CT Scanner for Radiation Therapy.

NASA Astrophysics Data System (ADS)

Chen, Ching-Tai

A Varian 4 MeV isocentric therapy accelerator has been modified to perform also as a CT scanner. The goal is to provide low cost computed tomography capability for use in radiotherapy. The system will have three principal uses. These are (i) to provide 2- and 3-dimensional maps of electron density distribution for CT assisted therapy planning, (ii) to aid in patient set up by providing sectional views of the treatment volume and high contrast scout-mode verification images and (iii) to provide a means for periodically checking the patients anatomical conformation against what was used to generate the original therapy plan. The treatment machine was modified by mounting an array of detectors on a frame bolted to the counter weight end of the gantry in such a manner as to define a 'third generation' CT Scanner geometry. The data gathering is controlled by a Z-80 based microcomputer system which transfers the x-ray transmission data to a general purpose PDP 11/34 for processing. There a series of calibration processes and a logarithmic conversion are performed to get projection data. After reordering the projection data to an equivalent parallel beam sinogram format a convolution algorithm is employed to construct the image from the equivalent parallel projection data. Results of phantom studies have shown a spatial resolution of 2.6 mm and an electron density discrimination of less than 1% which are sufficiently good for accurate therapy planning. Results also show that the system is linear to within the precision of our measurement ((DBLTURN).75%) over a wide range of electron densities corresponding to those found in body tissues. Animal and human images are also presented to demonstrate that the system's imaging capability is sufficient to allow the necessary visualization of anatomy.

A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging.

PubMed

Bagci, Ulas; Foster, Brent; Miller-Jaster, Kirsten; Luna, Brian; Dey, Bappaditya; Bishai, William R; Jonsson, Colleen B; Jain, Sanjay; Mollura, Daniel J

2013-07-23

Infectious diseases are the second leading cause of death worldwide. In order to better understand and treat them, an accurate evaluation using multi-modal imaging techniques for anatomical and functional characterizations is needed. For non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), there have been many engineering improvements that have significantly enhanced the resolution and contrast of the images, but there are still insufficient computational algorithms available for researchers to use when accurately quantifying imaging data from anatomical structures and functional biological processes. Since the development of such tools may potentially translate basic research into the clinic, this study focuses on the development of a quantitative and qualitative image analysis platform that provides a computational radiology perspective for pulmonary infections in small animal models. Specifically, we designed (a) a fast and robust automated and semi-automated image analysis platform and a quantification tool that can facilitate accurate diagnostic measurements of pulmonary lesions as well as volumetric measurements of anatomical structures, and incorporated (b) an image registration pipeline to our proposed framework for volumetric comparison of serial scans. This is an important investigational tool for small animal infectious disease models that can help advance researchers' understanding of infectious diseases. We tested the utility of our proposed methodology by using sequentially acquired CT and PET images of rabbit, ferret, and mouse models with respiratory infections of Mycobacterium tuberculosis (TB), H1N1 flu virus, and an aerosolized respiratory pathogen (necrotic TB) for a total of 92, 44, and 24 scans for the respective studies with half of the scans from CT and the other half from PET. Institutional Administrative Panel on Laboratory Animal Care approvals were obtained prior to conducting this research. First, the proposed computational framework registered PET and CT images to provide spatial correspondences between images. Second, the lungs from the CT scans were segmented using an interactive region growing (IRG) segmentation algorithm with mathematical morphology operations to avoid false positive (FP) uptake in PET images. Finally, we segmented significant radiotracer uptake from the PET images in lung regions determined from CT and computed metabolic volumes of the significant uptake. All segmentation processes were compared with expert radiologists' delineations (ground truths). Metabolic and gross volume of lesions were automatically computed with the segmentation processes using PET and CT images, and percentage changes in those volumes over time were calculated. (Continued on next page)(Continued from previous page) Standardized uptake value (SUV) analysis from PET images was conducted as a complementary quantitative metric for disease severity assessment. Thus, severity and extent of pulmonary lesions were examined through both PET and CT images using the aforementioned quantification metrics outputted from the proposed framework. Each animal study was evaluated within the same subject class, and all steps of the proposed methodology were evaluated separately. We quantified the accuracy of the proposed algorithm with respect to the state-of-the-art segmentation algorithms. For evaluation of the segmentation results, dice similarity coefficient (DSC) as an overlap measure and Haussdorf distance as a shape dissimilarity measure were used. Significant correlations regarding the estimated lesion volumes were obtained both in CT and PET images with respect to the ground truths (R2=0.8922,p<0.01 and R2=0.8664,p<0.01, respectively). The segmentation accuracy (DSC (%)) was 93.4±4.5% for normal lung CT scans and 86.0±7.1% for pathological lung CT scans. Experiments showed excellent agreements (all above 85%) with expert evaluations for both structural and functional imaging modalities. Apart from quantitative analysis of each animal, we also qualitatively showed how metabolic volumes were changing over time by examining serial PET/CT scans. Evaluation of the registration processes was based on precisely defined anatomical landmark points by expert clinicians. An average of 2.66, 3.93, and 2.52 mm errors was found in rabbit, ferret, and mouse data (all within the resolution limits), respectively. Quantitative results obtained from the proposed methodology were visually related to the progress and severity of the pulmonary infections as verified by the participating radiologists. Moreover, we demonstrated that lesions due to the infections were metabolically active and appeared multi-focal in nature, and we observed similar patterns in the CT images as well. Consolidation and ground glass opacity were the main abnormal imaging patterns and consistently appeared in all CT images. We also found that the gross and metabolic lesion volume percentage follow the same trend as the SUV-based evaluation in the longitudinal analysis. We explored the feasibility of using PET and CT imaging modalities in three distinct small animal models for two diverse pulmonary infections. We concluded from the clinical findings, derived from the proposed computational pipeline, that PET-CT imaging is an invaluable hybrid modality for tracking pulmonary infections longitudinally in small animals and has great potential to become routinely used in clinics. Our proposed methodology showed that automated computed-aided lesion detection and quantification of pulmonary infections in small animal models are efficient and accurate as compared to the clinical standard of manual and semi-automated approaches. Automated analysis of images in pre-clinical applications can increase the efficiency and quality of pre-clinical findings that ultimately inform downstream experimental design in human clinical studies; this innovation will allow researchers and clinicians to more effectively allocate study resources with respect to research demands without compromising accuracy.

Computer-aided diagnosis of liver tumors on computed tomography images.

PubMed

Chang, Chin-Chen; Chen, Hong-Hao; Chang, Yeun-Chung; Yang, Ming-Yang; Lo, Chung-Ming; Ko, Wei-Chun; Lee, Yee-Fan; Liu, Kao-Lang; Chang, Ruey-Feng

2017-07-01

Liver cancer is the tenth most common cancer in the USA, and its incidence has been increasing for several decades. Early detection, diagnosis, and treatment of the disease are very important. Computed tomography (CT) is one of the most common and robust imaging techniques for the detection of liver cancer. CT scanners can provide multiple-phase sequential scans of the whole liver. In this study, we proposed a computer-aided diagnosis (CAD) system to diagnose liver cancer using the features of tumors obtained from multiphase CT images. A total of 71 histologically-proven liver tumors including 49 benign and 22 malignant lesions were evaluated with the proposed CAD system to evaluate its performance. Tumors were identified by the user and then segmented using a region growing algorithm. After tumor segmentation, three kinds of features were obtained for each tumor, including texture, shape, and kinetic curve. The texture was quantified using 3 dimensional (3-D) texture data of the tumor based on the grey level co-occurrence matrix (GLCM). Compactness, margin, and an elliptic model were used to describe the 3-D shape of the tumor. The kinetic curve was established from each phase of tumor and represented as variations in density between each phase. Backward elimination was used to select the best combination of features, and binary logistic regression analysis was used to classify the tumors with leave-one-out cross validation. The accuracy and sensitivity for the texture were 71.82% and 68.18%, respectively, which were better than for the shape and kinetic curve under closed specificity. Combining all of the features achieved the highest accuracy (58/71, 81.69%), sensitivity (18/22, 81.82%), and specificity (40/49, 81.63%). The Az value of combining all features was 0.8713. Combining texture, shape, and kinetic curve features may be able to differentiate benign from malignant tumors in the liver using our proposed CAD system. Copyright © 2017 Elsevier B.V. All rights reserved.

Single element ultrasonic imaging of limb geometry: an in-vivo study with comparison to MRI

NASA Astrophysics Data System (ADS)

Zhang, Xiang; Fincke, Jonathan R.; Anthony, Brian W.

2016-04-01

Despite advancements in medical imaging, current prosthetic fitting methods remain subjective, operator dependent, and non-repeatable. The standard plaster casting method relies on prosthetist experience and tactile feel of the limb to design the prosthetic socket. Often times, many fitting iterations are required to achieve an acceptable fit. Use of improper socket fittings can lead to painful pathologies including neuromas, inflammation, soft tissue calcification, and pressure sores, often forcing the wearer to into a wheelchair and reducing mobility and quality of life. Computer software along with MRI/CT imaging has already been explored to aid the socket design process. In this paper, we explore the use of ultrasound instead of MRI/CT to accurately obtain the underlying limb geometry to assist the prosthetic socket design process. Using a single element ultrasound system, multiple subjects' proximal limbs were imaged using 1, 2.25, and 5 MHz single element transducers. Each ultrasound transducer was calibrated to ensure acoustic exposure within the limits defined by the FDA. To validate image quality, each patient was also imaged in an MRI. Fiducial markers visible in both MRI and ultrasound were used to compare the same limb cross-sectional image for each patient. After applying a migration algorithm, B-mode ultrasound cross-sections showed sufficiently high image resolution to characterize the skin and bone boundaries along with the underlying tissue structures.

A new approach of objective quality evaluation on JPEG2000 lossy-compressed lung cancer CT images

NASA Astrophysics Data System (ADS)

Cai, Weihua; Tan, Yongqiang; Zhang, Jianguo

2007-03-01

Image compression has been used to increase the communication efficiency and storage capacity. JPEG 2000 compression, based on the wavelet transformation, has its advantages comparing to other compression methods, such as ROI coding, error resilience, adaptive binary arithmetic coding and embedded bit-stream. However it is still difficult to find an objective method to evaluate the image quality of lossy-compressed medical images so far. In this paper, we present an approach to evaluate the image quality by using a computer aided diagnosis (CAD) system. We selected 77 cases of CT images, bearing benign and malignant lung nodules with confirmed pathology, from our clinical Picture Archiving and Communication System (PACS). We have developed a prototype of CAD system to classify these images into benign ones and malignant ones, the performance of which was evaluated by the receiver operator characteristics (ROC) curves. We first used JPEG 2000 to compress these cases of images with different compression ratio from lossless to lossy, and used the CAD system to classify the cases with different compressed ratio, then compared the ROC curves from the CAD classification results. Support vector machine (SVM) and neural networks (NN) were used to classify the malignancy of input nodules. In each approach, we found that the area under ROC (AUC) decreases with the increment of compression ratio with small fluctuations.

Single-centre experience of radiation exposure in acute surgical patients: assessment of therapeutic impact and future recommendations.

PubMed

Fitzmaurice, Gerard J; Brown, Robin; Cranley, Brian; Conlon, Enda F; Todd, R Alan J; O'Donnell, Mark E

2010-09-01

Radiological investigations have become a key adjunct in patient management and consequently radiation exposure to patients is increasing. The study objectives were to examine the use of radiological investigations in the management of acute surgical patients and to assess whether a guideline-based radiation exposure risk/benefit analysis can aid in the choice of radiological investigation used. A prospective observational study was completed over a 12-week period from April to July 2008 for all acute surgical admissions. Data recorded included demographics, clinical presentation, differential diagnosis, investigations, surgical interventions, and final clinical outcome. The use of radiological investigative modalities as an adjunct to clinical assessment was then evaluated against The Royal College of Radiologists (RCR) guidelines. A total of 380 acute surgical admissions (M = 174, F = 185, children = 21) were assessed during the study period. Seven hundred thirty-four radiological investigations were performed with a mean of 1.93 investigations per patient. Based on the RCR guidelines, 680 (92.6%) radiological investigations were warranted and included 142 CT scans (19.3%), 129 chest X-rays (17.6%), and 85 abdominal X-rays (11.6%). Clinically, radiological imaging complemented surgical management in 326 patients (85.8%) and the management plan remained unchanged for the remaining 54 patients (14.2%). This accounted for an average radiation dose of 4.18 millisievert (mSv) per patient or 626 days of background radiation exposure. CT imaging was responsible for the majority of the radiation exposure, with a total of 1310 mSv (82.6%) of the total radiation exposure being attributed to CT imaging in 20.8% of acute admissions. Subgroup analysis demonstrated that 92.8% of the CT scans performed were appropriate. Radiation exposure was generally low for the majority of acute surgical admissions. However, it is recommended that CT imaging requests be evaluated carefully, particularly for patients with clinically confirmed pathologies and in younger women.

Automated detection of pulmonary nodules in CT images with support vector machines

NASA Astrophysics Data System (ADS)

Liu, Lu; Liu, Wanyu; Sun, Xiaoming

2008-10-01

Many methods have been proposed to avoid radiologists fail to diagnose small pulmonary nodules. Recently, support vector machines (SVMs) had received an increasing attention for pattern recognition. In this paper, we present a computerized system aimed at pulmonary nodules detection; it identifies the lung field, extracts a set of candidate regions with a high sensitivity ratio and then classifies candidates by the use of SVMs. The Computer Aided Diagnosis (CAD) system presented in this paper supports the diagnosis of pulmonary nodules from Computed Tomography (CT) images as inflammation, tuberculoma, granuloma..sclerosing hemangioma, and malignant tumor. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of SVMs classifiers. The achieved classification performance was 100%, 92.75% and 90.23% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

A case of boomerang dysplasia with a novel causative mutation in filamin B: identification of typical imaging findings on ultrasonography and 3D-CT imaging.

PubMed

Tsutsumi, Seiji; Maekawa, Ayako; Obata, Miyuki; Morgan, Timothy; Robertson, Stephen P; Kurachi, Hirohisa

2012-01-01

Boomerang dysplasia is a rare lethal osteochondrodysplasia characterized by disorganized mineralization of the skeleton, leading to complete nonossification of some limb bones and vertebral elements, and a boomerang-like aspect to some of the long tubular bones. Like many short-limbed skeletal dysplasias with accompanying thoracic hypoplasia, the potential lethality of the phenotype can be difficult to ascertain prenatally. We report a case of boomerang dysplasia prenatally diagnosed by use of ultrasonography and 3D-CT imaging, and identified a novel mutation in the gene encoding the cytoskeletal protein filamin B (FLNB) postmortem. Findings that aided the radiological diagnosis of this condition in utero included absent ossification of two out of three long bones in each limb and elements of the vertebrae and a boomerang-like shape to the ulnae. The identified mutation is the third described for this disorder and is predicted to lead to amino acid substitution in the actin-binding domain of the filamin B molecule. Copyright © 2012 S. Karger AG, Basel.

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

Normal Lung Quantification in Usual Interstitial Pneumonia Pattern: The Impact of Threshold-based Volumetric CT Analysis for the Staging of Idiopathic Pulmonary Fibrosis.

PubMed

Ohkubo, Hirotsugu; Kanemitsu, Yoshihiro; Uemura, Takehiro; Takakuwa, Osamu; Takemura, Masaya; Maeno, Ken; Ito, Yutaka; Oguri, Tetsuya; Kazawa, Nobutaka; Mikami, Ryuji; Niimi, Akio

2016-01-01

Although several computer-aided computed tomography (CT) analysis methods have been reported to objectively assess the disease severity and progression of idiopathic pulmonary fibrosis (IPF), it is unclear which method is most practical. A universal severity classification system has not yet been adopted for IPF. The purpose of this study was to test the correlation between quantitative-CT indices and lung physiology variables and to determine the ability of such indices to predict disease severity in IPF. A total of 27 IPF patients showing radiological UIP pattern on high-resolution (HR) CT were retrospectively enrolled. Staging of IPF was performed according to two classification systems: the Japanese and GAP (gender, age, and physiology) staging systems. CT images were assessed using a commercially available CT imaging analysis workstation, and the whole-lung mean CT value (MCT), the normally attenuated lung volume as defined from -950 HU to -701 Hounsfield unit (NL), the volume of the whole lung (WL), and the percentage of NL to WL (NL%), were calculated. CT indices (MCT, WL, and NL) closely correlated with lung physiology variables. Among them, NL strongly correlated with forced vital capacity (FVC) (r = 0.92, P <0.0001). NL% showed a large area under the receiver operating characteristic curve for detecting patients in the moderate or advanced stages of IPF. Multivariable logistic regression analyses showed that NL% is significantly more useful than the percentages of predicted FVC and predicted diffusing capacity of the lungs for carbon monoxide (Japanese stage II/III/IV [odds ratio, 0.73; 95% confidence intervals (CI), 0.48 to 0.92; P < 0.01]; III/IV [odds ratio. 0.80; 95% CI 0.59 to 0.96; P < 0.01]; GAP stage II/III [odds ratio, 0.79; 95% CI, 0.56 to 0.97; P < 0.05]). The measurement of NL% by threshold-based volumetric CT analysis may help improve IPF staging.

A novel 3D template for mandible and maxilla reconstruction: Rapid prototyping using stereolithography

PubMed Central

Kumta, Samir; Kumta, Monica; Jain, Leena; Purohit, Shrirang; Ummul, Rani

2015-01-01

Introduction: Replication of the exact three-dimensional (3D) structure of the maxilla and mandible is now a priority whilst attempting reconstruction of these bones to attain a complete functional and aesthetic rehabilitation. We hereby present the process of rapid prototyping using stereolithography to produce templates for modelling bone grafts and implants for maxilla/mandible reconstructions, its applications in tumour/trauma, and outcomes for primary and secondary reconstruction. Materials and Methods: Stereolithographic template-assisted reconstruction was used on 11 patients for the reconstruction of the mandible/maxilla primarily following tumour excision and secondarily for the realignment of post-traumatic malunited fractures or deformity corrections. Data obtained from the computed tomography (CT) scans with 1-mm resolution were converted into a computer-aided design (CAD) using the CT Digital Imaging and Communications in Medicine (DICOM) data. Once a CAD model was constructed, it was converted into a stereolithographic format and then processed by the rapid prototyping technology to produce the physical anatomical model using a resin. This resin model replicates the native mandible, which can be thus used off table as a guide for modelling the bone grafts. Discussion: This conversion of two-dimensional (2D) data from CT scan into 3D models is a very precise guide to shaping the bone grafts. Further, this CAD can reconstruct the defective half of the mandible using the mirror image principle, and the normal anatomical model can be created to aid secondary reconstructions. Conclusion: This novel approach allows a precise translation of the treatment plan directly to the surgical field. It is also an important teaching tool for implant moulding and fixation, and helps in patient counselling. PMID:26933279

A novel 3D template for mandible and maxilla reconstruction: Rapid prototyping using stereolithography.

PubMed

Kumta, Samir; Kumta, Monica; Jain, Leena; Purohit, Shrirang; Ummul, Rani

2015-01-01

Replication of the exact three-dimensional (3D) structure of the maxilla and mandible is now a priority whilst attempting reconstruction of these bones to attain a complete functional and aesthetic rehabilitation. We hereby present the process of rapid prototyping using stereolithography to produce templates for modelling bone grafts and implants for maxilla/mandible reconstructions, its applications in tumour/trauma, and outcomes for primary and secondary reconstruction. Stereolithographic template-assisted reconstruction was used on 11 patients for the reconstruction of the mandible/maxilla primarily following tumour excision and secondarily for the realignment of post-traumatic malunited fractures or deformity corrections. Data obtained from the computed tomography (CT) scans with 1-mm resolution were converted into a computer-aided design (CAD) using the CT Digital Imaging and Communications in Medicine (DICOM) data. Once a CAD model was constructed, it was converted into a stereolithographic format and then processed by the rapid prototyping technology to produce the physical anatomical model using a resin. This resin model replicates the native mandible, which can be thus used off table as a guide for modelling the bone grafts. This conversion of two-dimensional (2D) data from CT scan into 3D models is a very precise guide to shaping the bone grafts. Further, this CAD can reconstruct the defective half of the mandible using the mirror image principle, and the normal anatomical model can be created to aid secondary reconstructions. This novel approach allows a precise translation of the treatment plan directly to the surgical field. It is also an important teaching tool for implant moulding and fixation, and helps in patient counselling.

The Power of Computer-aided Tomography to Investigate Marine Benthic Communities

EPA Science Inventory

Utilization of Computer-aided-Tomography (CT) technology is a powerful tool to investigate benthic communities in aquatic systems. In this presentation, we will attempt to summarize our 15 years of experience in developing specific CT methods and applications to marine benthic co...

Rapid prototyping to create vascular replicas from CT scan data: making tools to teach, rehearse, and choose treatment strategies.

PubMed

Knox, K; Kerber, Charles W; Singel, S A; Bailey, M J; Imbesi, S G

2005-05-01

Our goal was to develop and prove the accuracy of a system that would allow us to re-create live patient arterial pathology. Anatomically accurate replicas of blood vessels could allow physicians to teach and practice dangerous interventional techniques and might also be used to gather basic physiologic information. The preparation of replicas has, until now, depended on acquisition of fresh cadaver material. Using rapid prototyping, it should be able to replicate vascular pathology in a live patient. We obtained CT angiographic scan data from two patients with known arterial abnormalities. We took such data and, using proprietary software, created a 3D replica using a commercially available rapid prototyping machine. From the prototypes, using a lost wax technique, we created vessel replicas, placed those replicas in the CT scanner, then compared those images with the original scans. Comparison of the images made directly from the patient and from the replica showed that with each step, the relationships were maintained, remaining within 3% of the original, but some smoothing occurred in the final computer manipulation. From routinely obtainable CT angiographic data, it is possible to create accurate replicas of human vascular pathology with the aid of commercially available stereolithography equipment. Visual analysis of the images appeared to be as important as the measurements. With 64 and 128 slice detector scanners becoming available, acquisition times fall enough that we should be able to model rapidly moving structures such as the aortic root. (c) 2005 Wiley-Liss, Inc.

A method for visualizing high-density porous polyethylene (medpor, porex) with computed tomographic scanning.

PubMed

Vendemia, Nicholas; Chao, Jerry; Ivanidze, Jana; Sanelli, Pina; Spinelli, Henry M

2011-01-01

Medpor (Porex Surgical, Inc, Newnan, GA) is composed of porous polyethylene and is commonly used in craniofacial reconstruction. When complications such as seroma or abscess formation arise, diagnostic modalities are limited because Medpor is radiolucent on conventional radiologic studies. This poses a problem in situations where imaging is necessary to distinguish the implant from surrounding tissues. To present a clinically useful method for imaging Medpor with conventional computed tomographic (CT) scanning. Eleven patients (12 total implants) who have undergone reconstructive surgery with Medpor were included in the study. A retrospective review of CT scans done between 1 and 16 months postoperatively was performed using 3 distinct CT window settings. Measurements of implant dimensions and Hounsfield units were recorded and qualitatively assessed. Of the 3 distinct window settings studied, namely, "bone" (W1100/L450), "soft tissue"; (W500/L50), and "implant" (W800/L200), the implant window proved the most ideal, allowing the investigators to visualize and evaluate Medpor in all cases. Qualitative analysis revealed that Medpor implants were able to be distinguished from surrounding tissue in both the implant and soft tissue windows, with a density falling between that of fat and fluid. In 1 case, Medpor could not be visualized in the soft tissue window, although it could be visualized in the implant window. Quantitative analysis demonstrated a mean (SD) density of -38.7 (7.4) Hounsfield units. Medpor may be optimally visualized on conventional CT scans using the implant window settings W800/L200, which can aid in imaging Medpor and diagnosing implant-related complications.

Semi-automated segmentation of solid and GGO nodules in lung CT images using vessel-likelihood derived from local foreground structure

NASA Astrophysics Data System (ADS)

Yaguchi, Atsushi; Okazaki, Tomoya; Takeguchi, Tomoyuki; Matsumoto, Sumiaki; Ohno, Yoshiharu; Aoyagi, Kota; Yamagata, Hitoshi

2015-03-01

Reflecting global interest in lung cancer screening, considerable attention has been paid to automatic segmentation and volumetric measurement of lung nodules on CT. Ground glass opacity (GGO) nodules deserve special consideration in this context, since it has been reported that they are more likely to be malignant than solid nodules. However, due to relatively low contrast and indistinct boundaries of GGO nodules, segmentation is more difficult for GGO nodules compared with solid nodules. To overcome this difficulty, we propose a method for accurately segmenting not only solid nodules but also GGO nodules without prior information about nodule types. First, the histogram of CT values in pre-extracted lung regions is modeled by a Gaussian mixture model and a threshold value for including high-attenuation regions is computed. Second, after setting up a region of interest around the nodule seed point, foreground regions are extracted by using the threshold and quick-shift-based mode seeking. Finally, for separating vessels from the nodule, a vessel-likelihood map derived from elongatedness of foreground regions is computed, and a region growing scheme starting from the seed point is applied to the map with the aid of fast marching method. Experimental results using an anthropomorphic chest phantom showed that our method yielded generally lower volumetric measurement errors for both solid and GGO nodules compared with other methods reported in preceding studies conducted using similar technical settings. Also, our method allowed reasonable segmentation of GGO nodules in low-dose images and could be applied to clinical CT images including part-solid nodules.

LORENZ: a system for planning long-bone fracture reduction

NASA Astrophysics Data System (ADS)

Birkfellner, Wolfgang; Burgstaller, Wolfgang; Wirth, Joachim; Baumann, Bernard; Jacob, Augustinus L.; Bieri, Kurt; Traud, Stefan; Strub, Michael; Regazzoni, Pietro; Messmer, Peter

2003-05-01

Long bone fractures belong to the most common injuries encountered in clinical routine trauma surgery. Preoperative assessment and decision making is usually based on standard 2D radiographs of the injured limb. Taking into account that a 3D - imaging modality such as computed tomography (CT) is not used for diagnosis in clinical routine, we have designed LORENZ, a fracture reduction planning tool based on such standard radiographs. Taking into account the considerable success of so-called image free navigation systems for total knee replacement in orthopaedic surgery, we assume that a similar tool for long bone fracture reposition should have considerable impact on computer-aided trauma surgery in a standard clinical routine setup. The case for long bone fracture reduction is, however, somewhat more complicated since not only scale independent angles indicating biomechanical measures such as varus and valgus are involved. Reduction path planning requires that the individual anatomy and the classification of the fracture is taken into account. In this paper, we present the basic ideas of this planning tool, it's current state, and the methodology chosen. LORENZ takes one or more conventional radiographs of the broken limb as input data. In addition, one or more x-rays of the opposite healthy bone are taken and mirrored if necessary. A most adequate CT model is being selected from a database; currently, this is achieved by using a scale space approach on the digitized x-ray images and comparing standard perspective renderings to these x-rays. After finding a CT-volume with a similar bone, a triangulated surface model is generated, and the surgeon can break the bone and arrange the fragments in 3D according to the x-ray images of the broken bone. Common osteosynthesis plates and implants can be loaded from CAD-datasets and are visualized as well. In addition, LORENZ renders virtual x-ray views of the fracture reduction process. The hybrid surface/voxel rendering engine of LORENZ also features full collision detection of fragments and implants by using the RAPID collision detection library. The reduction path is saved, and a TCP/IP interface to a robot for executing the reduction was added. LORENZ is platform independent and was programmed using Qt, AVW and OpenGL. We present a prototype for computer-aided fracture reduction planning based on standard radiographs. First test on clinical CT-Xray image pairs showed good performance; a current effort focuses on improving the speed of model retrieval by using orthonormal image moment decomposition, and on clinical evaluation for both training and surgical planning purposes. Furthermore, user-interface aspects are currently under evaluation and will be discussed.

A study on automated anatomical labeling to arteries concerning with colon from 3D abdominal CT images

NASA Astrophysics Data System (ADS)

Hoang, Bui Huy; Oda, Masahiro; Jiang, Zhengang; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku

2011-03-01

This paper presents an automated anatomical labeling method of arteries extracted from contrasted 3D CT images based on multi-class AdaBoost. In abdominal surgery, understanding of vasculature related to a target organ such as the colon is very important. Therefore, the anatomical structure of blood vessels needs to be understood by computers in a system supporting abdominal surgery. There are several researches on automated anatomical labeling, but there is no research on automated anatomical labeling to arteries concerning with the colon. The proposed method obtains a tree structure of arteries from the artery region and calculates features values of each branch. These feature values are thickness, curvature, direction, and running vectors of branch. Then, candidate arterial names are computed by classifiers that are trained to output artery names. Finally, a global optimization process is applied to the candidate arterial names to determine final names. Target arteries of this paper are nine lower abdominal arteries (AO, LCIA, RCIA, LEIA, REIA, SMA, IMA, LIIA, RIIA). We applied the proposed method to 14 cases of 3D abdominal contrasted CT images, and evaluated the results by leave-one-out scheme. The average precision and recall rates of the proposed method were 87.9% and 93.3%, respectively. The results of this method are applicable for anatomical name display of surgical simulation and computer aided surgery.

Fuzzy pulmonary vessel segmentation in contrast enhanced CT data

NASA Astrophysics Data System (ADS)

Kaftan, Jens N.; Kiraly, Atilla P.; Bakai, Annemarie; Das, Marco; Novak, Carol L.; Aach, Til

2008-03-01

Pulmonary vascular tree segmentation has numerous applications in medical imaging and computer-aided diagnosis (CAD), including detection and visualization of pulmonary emboli (PE), improved lung nodule detection, and quantitative vessel analysis. We present a novel approach to pulmonary vessel segmentation based on a fuzzy segmentation concept, combining the strengths of both threshold and seed point based methods. The lungs of the original image are first segmented and a threshold-based approach identifies core vessel components with a high specificity. These components are then used to automatically identify reliable seed points for a fuzzy seed point based segmentation method, namely fuzzy connectedness. The output of the method consists of the probability of each voxel belonging to the vascular tree. Hence, our method provides the possibility to adjust the sensitivity/specificity of the segmentation result a posteriori according to application-specific requirements, through definition of a minimum vessel-probability required to classify a voxel as belonging to the vascular tree. The method has been evaluated on contrast-enhanced thoracic CT scans from clinical PE cases and demonstrates overall promising results. For quantitative validation we compare the segmentation results to randomly selected, semi-automatically segmented sub-volumes and present the resulting receiver operating characteristic (ROC) curves. Although we focus on contrast enhanced chest CT data, the method can be generalized to other regions of the body as well as to different imaging modalities.

Deep convolutional networks for pancreas segmentation in CT imaging

NASA Astrophysics Data System (ADS)

Roth, Holger R.; Farag, Amal; Lu, Le; Turkbey, Evrim B.; Summers, Ronald M.

2015-03-01

Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to state-of-the-art segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible for "deep learning" methods such as convolutional networks (ConvNets) to succeed in image classification tasks. These methods have the advantage that used classification features are trained directly from the imaging data. We present a fully-automated bottom-up method for pancreas segmentation in computed tomography (CT) images of the abdomen. The method is based on hierarchical coarse-to-fine classification of local image regions (superpixels). Superpixels are extracted from the abdominal region using Simple Linear Iterative Clustering (SLIC). An initial probability response map is generated, using patch-level confidences and a two-level cascade of random forest classifiers, from which superpixel regions with probabilities larger 0.5 are retained. These retained superpixels serve as a highly sensitive initial input of the pancreas and its surroundings to a ConvNet that samples a bounding box around each superpixel at different scales (and random non-rigid deformations at training time) in order to assign a more distinct probability of each superpixel region being pancreas or not. We evaluate our method on CT images of 82 patients (60 for training, 2 for validation, and 20 for testing). Using ConvNets we achieve maximum Dice scores of an average 68% +/- 10% (range, 43-80%) in testing. This shows promise for accurate pancreas segmentation, using a deep learning approach and compares favorably to state-of-the-art methods.

3D marker-controlled watershed for kidney segmentation in clinical CT exams.

PubMed

Wieclawek, Wojciech

2018-02-27

Image segmentation is an essential and non trivial task in computer vision and medical image analysis. Computed tomography (CT) is one of the most accessible medical examination techniques to visualize the interior of a patient's body. Among different computer-aided diagnostic systems, the applications dedicated to kidney segmentation represent a relatively small group. In addition, literature solutions are verified on relatively small databases. The goal of this research is to develop a novel algorithm for fully automated kidney segmentation. This approach is designed for large database analysis including both physiological and pathological cases. This study presents a 3D marker-controlled watershed transform developed and employed for fully automated CT kidney segmentation. The original and the most complex step in the current proposition is an automatic generation of 3D marker images. The final kidney segmentation step is an analysis of the labelled image obtained from marker-controlled watershed transform. It consists of morphological operations and shape analysis. The implementation is conducted in a MATLAB environment, Version 2017a, using i.a. Image Processing Toolbox. 170 clinical CT abdominal studies have been subjected to the analysis. The dataset includes normal as well as various pathological cases (agenesis, renal cysts, tumors, renal cell carcinoma, kidney cirrhosis, partial or radical nephrectomy, hematoma and nephrolithiasis). Manual and semi-automated delineations have been used as a gold standard. Wieclawek Among 67 delineated medical cases, 62 cases are 'Very good', whereas only 5 are 'Good' according to Cohen's Kappa interpretation. The segmentation results show that mean values of Sensitivity, Specificity, Dice, Jaccard, Cohen's Kappa and Accuracy are 90.29, 99.96, 91.68, 85.04, 91.62 and 99.89% respectively. All 170 medical cases (with and without outlines) have been classified by three independent medical experts as 'Very good' in 143-148 cases, as 'Good' in 15-21 cases and as 'Moderate' in 6-8 cases. An automatic kidney segmentation approach for CT studies to compete with commonly known solutions was developed. The algorithm gives promising results, that were confirmed during validation procedure done on a relatively large database, including 170 CTs with both physiological and pathological cases.

Advances in Pancreatic CT Imaging.

PubMed

Almeida, Renata R; Lo, Grace C; Patino, Manuel; Bizzo, Bernardo; Canellas, Rodrigo; Sahani, Dushyant V

2018-07-01

The purpose of this article is to discuss the advances in CT acquisition and image postprocessing as they apply to imaging the pancreas and to conceptualize the role of radiogenomics and machine learning in pancreatic imaging. CT is the preferred imaging modality for assessment of pancreatic diseases. Recent advances in CT (dual-energy CT, CT perfusion, CT volumetry, and radiogenomics) and emerging computational algorithms (machine learning) have the potential to further increase the value of CT in pancreatic imaging.

SU-E-J-251: Incorporation of Pre-Therapy 18F-FDG Uptake with CT Texture Features in a Predictive Model for Radiation Pneumonitis Development

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

Anthony, G; Cunliffe, A; Armato, S

2015-06-15

Purpose: To determine whether the addition of standardized uptake value (SUV) statistical variables to CT lung texture features can improve a predictive model of radiation pneumonitis (RP) development in patients undergoing radiation therapy. Methods: Anonymized data from 96 esophageal cancer patients (18 RP-positive cases of Grade ≥ 2) were retrospectively collected including pre-therapy PET/CT scans, pre-/posttherapy diagnostic CT scans and RP status. Twenty texture features (firstorder, fractal, Laws’ filter and gray-level co-occurrence matrix) were calculated from diagnostic CT scans and compared in anatomically matched regions of the lung. The mean, maximum, standard deviation, and 50th–95th percentiles of the SUV valuesmore » for all lung voxels in the corresponding PET scans were acquired. For each texture feature, a logistic regression-based classifier consisting of (1) the average change in that texture feature value between the pre- and post-therapy CT scans and (2) the pre-therapy SUV standard deviation (SUV{sub SD}) was created. The RP-classification performance of each logistic regression model was compared to the performance of its texture feature alone by computing areas under the receiver operating characteristic curves (AUCs). T-tests were performed to determine whether the mean AUC across texture features changed significantly when SUV{sub SD} was added to the classifier. Results: The AUC for single-texturefeature classifiers ranged from 0.58–0.81 in high-dose (≥ 30 Gy) regions of the lungs and from 0.53–0.71 in low-dose (< 10 Gy) regions. Adding SUVSD in a logistic regression model using a 50/50 data partition for training and testing significantly increased the mean AUC by 0.08, 0.06 and 0.04 in the low-, medium- and high-dose regions, respectively. Conclusion: Addition of SUVSD from a pre-therapy PET scan to a single CT-based texture feature improves RP-classification performance on average. These findings demonstrate the potential for more accurate prediction of RP using information from multiple imaging modalities. Supported, in part, by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under grant number T32 EB002103; SGA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. HA receives royalties through the University of Chicago for computer-aided diagnosis technology.« less

Strategies for Improved Interpretation of Computer-Aided Detections for CT Colonography Utilizing Distributed Human Intelligence

PubMed Central

McKenna, Matthew T.; Wang, Shijun; Nguyen, Tan B.; Burns, Joseph E.; Petrick, Nicholas; Summers, Ronald M.

2012-01-01

Computer-aided detection (CAD) systems have been shown to improve the diagnostic performance of CT colonography (CTC) in the detection of premalignant colorectal polyps. Despite the improvement, the overall system is not optimal. CAD annotations on true lesions are incorrectly dismissed, and false positives are misinterpreted as true polyps. Here, we conduct an observer performance study utilizing distributed human intelligence in the form of anonymous knowledge workers (KWs) to investigate human performance in classifying polyp candidates under different presentation strategies. We evaluated 600 polyp candidates from 50 patients, each case having at least one polyp • 6 mm, from a large database of CTC studies. Each polyp candidate was labeled independently as a true or false polyp by 20 KWs and an expert radiologist. We asked each labeler to determine whether the candidate was a true polyp after looking at a single 3D-rendered image of the candidate and after watching a video fly-around of the candidate. We found that distributed human intelligence improved significantly when presented with the additional information in the video fly-around. We noted that performance degraded with increasing interpretation time and increasing difficulty, but distributed human intelligence performed better than our CAD classifier for “easy” and “moderate” polyp candidates. Further, we observed numerous parallels between the expert radiologist and the KWs. Both showed similar improvement in classification moving from single-image to video interpretation. Additionally, difficulty estimates obtained from the KWs using an expectation maximization algorithm correlated well with the difficulty rating assigned by the expert radiologist. Our results suggest that distributed human intelligence is a powerful tool that will aid in the development of CAD for CTC. PMID:22705287

Strategies for improved interpretation of computer-aided detections for CT colonography utilizing distributed human intelligence.

PubMed

McKenna, Matthew T; Wang, Shijun; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Summers, Ronald M

2012-08-01

Computer-aided detection (CAD) systems have been shown to improve the diagnostic performance of CT colonography (CTC) in the detection of premalignant colorectal polyps. Despite the improvement, the overall system is not optimal. CAD annotations on true lesions are incorrectly dismissed, and false positives are misinterpreted as true polyps. Here, we conduct an observer performance study utilizing distributed human intelligence in the form of anonymous knowledge workers (KWs) to investigate human performance in classifying polyp candidates under different presentation strategies. We evaluated 600 polyp candidates from 50 patients, each case having at least one polyp ≥6 mm, from a large database of CTC studies. Each polyp candidate was labeled independently as a true or false polyp by 20 KWs and an expert radiologist. We asked each labeler to determine whether the candidate was a true polyp after looking at a single 3D-rendered image of the candidate and after watching a video fly-around of the candidate. We found that distributed human intelligence improved significantly when presented with the additional information in the video fly-around. We noted that performance degraded with increasing interpretation time and increasing difficulty, but distributed human intelligence performed better than our CAD classifier for "easy" and "moderate" polyp candidates. Further, we observed numerous parallels between the expert radiologist and the KWs. Both showed similar improvement in classification moving from single-image to video interpretation. Additionally, difficulty estimates obtained from the KWs using an expectation maximization algorithm correlated well with the difficulty rating assigned by the expert radiologist. Our results suggest that distributed human intelligence is a powerful tool that will aid in the development of CAD for CTC. Copyright © 2012. Published by Elsevier B.V.

Automated recognition of the pericardium contour on processed CT images using genetic algorithms.

PubMed

Rodrigues, É O; Rodrigues, L O; Oliveira, L S N; Conci, A; Liatsis, P

2017-08-01

This work proposes the use of Genetic Algorithms (GA) in tracing and recognizing the pericardium contour of the human heart using Computed Tomography (CT) images. We assume that each slice of the pericardium can be modelled by an ellipse, the parameters of which need to be optimally determined. An optimal ellipse would be one that closely follows the pericardium contour and, consequently, separates appropriately the epicardial and mediastinal fats of the human heart. Tracing and automatically identifying the pericardium contour aids in medical diagnosis. Usually, this process is done manually or not done at all due to the effort required. Besides, detecting the pericardium may improve previously proposed automated methodologies that separate the two types of fat associated to the human heart. Quantification of these fats provides important health risk marker information, as they are associated with the development of certain cardiovascular pathologies. Finally, we conclude that GA offers satisfiable solutions in a feasible amount of processing time. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular imaging of malignant tumor metabolism: whole-body image fusion of DWI/CT vs. PET/CT.

PubMed

Reiner, Caecilia S; Fischer, Michael A; Hany, Thomas; Stolzmann, Paul; Nanz, Daniel; Donati, Olivio F; Weishaupt, Dominik; von Schulthess, Gustav K; Scheffel, Hans

2011-08-01

To prospectively investigate the technical feasibility and performance of image fusion for whole-body diffusion-weighted imaging (wbDWI) and computed tomography (CT) to detect metastases using hybrid positron emission tomography/computed tomography (PET/CT) as reference standard. Fifty-two patients (60 ± 14 years; 18 women) with different malignant tumor disease examined by PET/CT for clinical reasons consented to undergo additional wbDWI at 1.5 Tesla. WbDWI was performed using a diffusion-weighted single-shot echo-planar imaging during free breathing. Images at b = 0 s/mm(2) and b = 700 s/mm(2) were acquired and apparent diffusion coefficient (ADC) maps were generated. Image fusion of wbDWI and CT (from PET/CT scan) was performed yielding for wbDWI/CT fused image data. One radiologist rated the success of image fusion and diagnostic image quality. The presence or absence of metastases on wbDWI/CT fused images was evaluated together with the separate wbDWI and CT images by two different, independent radiologists blinded to results from PET/CT. Detection rate and positive predictive values for diagnosing metastases was calculated. PET/CT examinations were used as reference standard. PET/CT identified 305 malignant lesions in 39 of 52 (75%) patients. WbDWI/CT image fusion was technically successful and yielded diagnostic image quality in 73% and 92% of patients, respectively. Interobserver agreement for the evaluation of wbDWI/CT images was κ = 0.78. WbDWI/CT identified 270 metastases in 43 of 52 (83%) patients. Overall detection rate and positive predictive value of wbDWI/CT was 89% (95% CI, 0.85-0.92) and 94% (95% CI, 0.92-0.97), respectively. WbDWI/CT image fusion is technically feasible in a clinical setting and allows the diagnostic assessment of metastatic tumor disease detecting nine of 10 lesions as compared with PET/CT. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

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.

Multidetector CT of blunt traumatic venous injuries in the chest, abdomen, and pelvis.

PubMed

Holly, Brian P; Steenburg, Scott D

2011-01-01

Venous injuries as a result of blunt trauma are rare. Even though current protocols for multidetector computed tomography (CT) of patients with trauma are designed to evaluate primarily the solid organs and arteries, blunt venous injuries may nevertheless be identified, or at least suspected, on the basis of the multidetector CT findings. Venous injuries are associated with high morbidity and mortality rates. Diagnosis of a possible venous injury is crucial because the physical findings of a venous injury are nonspecific and may be absent. This article aims to make the radiologist aware of various venous injuries caused by blunt trauma and to provide helpful hints to aid in the identification of venous injuries. Multidetector CT technology, in combination with interactive manipulation of the raw dataset, can be useful in the creation of multiplanar reconstructed images and in the identification of a venous injury caused by blunt trauma. Familiarity with direct and indirect signs of venous injuries, as well as with examples of blunt traumatic venous injuries in the chest, abdomen, and pelvis, will help in the diagnosis of these injuries.

An Engineering View on Megatrends in Radiology: Digitization to Quantitative Tools of Medicine

PubMed Central

Choi, Jaesoon; Yi, Jaeyoun; Choi, Seungwook; Park, Seyoun; Chang, Yongjun; Seo, Joon Beom

2013-01-01

Within six months of the discovery of X-ray in 1895, the technology was used to scan the interior of the human body, paving the way for many innovations in the field of medicine, including an ultrasound device in 1950, a CT scanner in 1972, and MRI in 1980. More recent decades have witnessed developments such as digital imaging using a picture archiving and communication system, computer-aided detection/diagnosis, organ-specific workstations, and molecular, functional, and quantitative imaging. One of the latest technical breakthrough in the field of radiology has been imaging genomics and robotic interventions for biopsy and theragnosis. This review provides an engineering perspective on these developments and several other megatrends in radiology. PMID:23482650

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.

A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging

PubMed Central

2013-01-01

Background Infectious diseases are the second leading cause of death worldwide. In order to better understand and treat them, an accurate evaluation using multi-modal imaging techniques for anatomical and functional characterizations is needed. For non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), there have been many engineering improvements that have significantly enhanced the resolution and contrast of the images, but there are still insufficient computational algorithms available for researchers to use when accurately quantifying imaging data from anatomical structures and functional biological processes. Since the development of such tools may potentially translate basic research into the clinic, this study focuses on the development of a quantitative and qualitative image analysis platform that provides a computational radiology perspective for pulmonary infections in small animal models. Specifically, we designed (a) a fast and robust automated and semi-automated image analysis platform and a quantification tool that can facilitate accurate diagnostic measurements of pulmonary lesions as well as volumetric measurements of anatomical structures, and incorporated (b) an image registration pipeline to our proposed framework for volumetric comparison of serial scans. This is an important investigational tool for small animal infectious disease models that can help advance researchers’ understanding of infectious diseases. Methods We tested the utility of our proposed methodology by using sequentially acquired CT and PET images of rabbit, ferret, and mouse models with respiratory infections of Mycobacterium tuberculosis (TB), H1N1 flu virus, and an aerosolized respiratory pathogen (necrotic TB) for a total of 92, 44, and 24 scans for the respective studies with half of the scans from CT and the other half from PET. Institutional Administrative Panel on Laboratory Animal Care approvals were obtained prior to conducting this research. First, the proposed computational framework registered PET and CT images to provide spatial correspondences between images. Second, the lungs from the CT scans were segmented using an interactive region growing (IRG) segmentation algorithm with mathematical morphology operations to avoid false positive (FP) uptake in PET images. Finally, we segmented significant radiotracer uptake from the PET images in lung regions determined from CT and computed metabolic volumes of the significant uptake. All segmentation processes were compared with expert radiologists’ delineations (ground truths). Metabolic and gross volume of lesions were automatically computed with the segmentation processes using PET and CT images, and percentage changes in those volumes over time were calculated. (Continued on next page)(Continued from previous page) Standardized uptake value (SUV) analysis from PET images was conducted as a complementary quantitative metric for disease severity assessment. Thus, severity and extent of pulmonary lesions were examined through both PET and CT images using the aforementioned quantification metrics outputted from the proposed framework. Results Each animal study was evaluated within the same subject class, and all steps of the proposed methodology were evaluated separately. We quantified the accuracy of the proposed algorithm with respect to the state-of-the-art segmentation algorithms. For evaluation of the segmentation results, dice similarity coefficient (DSC) as an overlap measure and Haussdorf distance as a shape dissimilarity measure were used. Significant correlations regarding the estimated lesion volumes were obtained both in CT and PET images with respect to the ground truths (R2=0.8922,p<0.01 and R2=0.8664,p<0.01, respectively). The segmentation accuracy (DSC (%)) was 93.4±4.5% for normal lung CT scans and 86.0±7.1% for pathological lung CT scans. Experiments showed excellent agreements (all above 85%) with expert evaluations for both structural and functional imaging modalities. Apart from quantitative analysis of each animal, we also qualitatively showed how metabolic volumes were changing over time by examining serial PET/CT scans. Evaluation of the registration processes was based on precisely defined anatomical landmark points by expert clinicians. An average of 2.66, 3.93, and 2.52 mm errors was found in rabbit, ferret, and mouse data (all within the resolution limits), respectively. Quantitative results obtained from the proposed methodology were visually related to the progress and severity of the pulmonary infections as verified by the participating radiologists. Moreover, we demonstrated that lesions due to the infections were metabolically active and appeared multi-focal in nature, and we observed similar patterns in the CT images as well. Consolidation and ground glass opacity were the main abnormal imaging patterns and consistently appeared in all CT images. We also found that the gross and metabolic lesion volume percentage follow the same trend as the SUV-based evaluation in the longitudinal analysis. Conclusions We explored the feasibility of using PET and CT imaging modalities in three distinct small animal models for two diverse pulmonary infections. We concluded from the clinical findings, derived from the proposed computational pipeline, that PET-CT imaging is an invaluable hybrid modality for tracking pulmonary infections longitudinally in small animals and has great potential to become routinely used in clinics. Our proposed methodology showed that automated computed-aided lesion detection and quantification of pulmonary infections in small animal models are efficient and accurate as compared to the clinical standard of manual and semi-automated approaches. Automated analysis of images in pre-clinical applications can increase the efficiency and quality of pre-clinical findings that ultimately inform downstream experimental design in human clinical studies; this innovation will allow researchers and clinicians to more effectively allocate study resources with respect to research demands without compromising accuracy. PMID:23879987

Network-based reading system for lung cancer screening CT

NASA Astrophysics Data System (ADS)

Fujino, Yuichi; Fujimura, Kaori; Nomura, Shin-ichiro; Kawashima, Harumi; Tsuchikawa, Megumu; Matsumoto, Toru; Nagao, Kei-ichi; Uruma, Takahiro; Yamamoto, Shinji; Takizawa, Hotaka; Kuroda, Chikazumi; Nakayama, Tomio

2006-03-01

This research aims to support chest computed tomography (CT) medical checkups to decrease the death rate by lung cancer. We have developed a remote cooperative reading system for lung cancer screening over the Internet, a secure transmission function, and a cooperative reading environment. It is called the Network-based Reading System. A telemedicine system involves many issues, such as network costs and data security if we use it over the Internet, which is an open network. In Japan, broadband access is widespread and its cost is the lowest in the world. We developed our system considering human machine interface and security. It consists of data entry terminals, a database server, a computer aided diagnosis (CAD) system, and some reading terminals. It uses a secure Digital Imaging and Communication in Medicine (DICOM) encrypting method and Public Key Infrastructure (PKI) based secure DICOM image data distribution. We carried out an experimental trial over the Japan Gigabit Network (JGN), which is the testbed for the Japanese next-generation network, and conducted verification experiments of secure screening image distribution, some kinds of data addition, and remote cooperative reading. We found that network bandwidth of about 1.5 Mbps enabled distribution of screening images and cooperative reading and that the encryption and image distribution methods we proposed were applicable to the encryption and distribution of general DICOM images via the Internet.

Radiology case of the month. Nausea, vomiting, and diarrhea in a patient with hepatitis C and acquired immunodeficiency syndrome (AIDS). Diffuse, severe gastric-wall thickening, consistent with edema.

PubMed

Mabry, Christian; Hutchings, John; Sanders, Charles; Neitzschman, Harold

2012-01-01

The patient is a 42-year-old male with a past medical history of HIV/AIDS (his most recent CD4 count, four months before admission, was 19) and hepatitis C who presented to the Emergency Department complaining of one week of persistent nausea, vomiting, and diarrhea. His admit labs were as follows: hemoglobin of 11.8, hematocrit of 35, total protein of 6.0, albumin of 1.6, total bilirubin of 2.3, aspartate aminotransferase (AST) of 141, alkaline phosphatase (ALP) of 146, and alanine aminotransferase (ALT) of 31. Computed tomography (CT) images of the abdomen and pelvis with contrast were obtained (Figures 1 - 4).

Automated Quantification of Pneumothorax in CT

PubMed Central

Do, Synho; Salvaggio, Kristen; Gupta, Supriya; Kalra, Mannudeep; Ali, Nabeel U.; Pien, Homer

2012-01-01

An automated, computer-aided diagnosis (CAD) algorithm for the quantification of pneumothoraces from Multidetector Computed Tomography (MDCT) images has been developed. Algorithm performance was evaluated through comparison to manual segmentation by expert radiologists. A combination of two-dimensional and three-dimensional processing techniques was incorporated to reduce required processing time by two-thirds (as compared to similar techniques). Volumetric measurements on relative pneumothorax size were obtained and the overall performance of the automated method shows an average error of just below 1%. PMID:23082091

Age and sex based reference values for incidental coronary artery and thoracic aorta calcifications on routine clinical chest CT: a powerful tool to appreciate available imaging findings.

PubMed

Jairam, Pushpa M; de Jong, Pim A; Mali, Willem P Th M; Gondrie, Martijn J A; Jacobs, Peter C A; van der Graaf, Yolanda

2014-08-01

To establish age and gender specific reference values for incidental coronary artery and thoracic aorta calcification scores on routine diagnostic CT scans. These reference values can aid in structured reporting and interpretation of readily available imaging data by chest CT readers in routine practice. A random sample of 1572 (57% male, median age 61 years) was taken from a study population of 12,063 subjects who underwent diagnostic chest CT for non-cardiovascular indications between January 2002 and December 2005. Coronary artery and thoracic aorta calcifications were graded using a validated ordinal score. The 25th, 50th and 75th percentile cut points were calculated for the coronary artery and thoracic aorta calcification scores within each age/gender stratum. The 75th percentile cut points for coronary artery calcification scores were higher for men than for women across all age groups, with the exception of the lowest age group. The 75th percentile cut points for thoracic aorta calcifications scores were comparable for both genders across all age groups. Based on the obtained age and gender reference values a calculation tool is provided, that allows one to enter an individual's age, gender and calcification scores to obtain the corresponding estimated percentiles. The calculation tool as provided in this study can be used in daily practice by CT readers to examine whether a subject has high calcifications scores relative to others with the same age and gender. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

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

Examination of the dental cone-beam CT equipped with flat-panel-detector (FPD)

NASA Astrophysics Data System (ADS)

Ito, Rieko; Fujita, Naotoshi; Kodera, Yoshie

2011-03-01

In dentistry, computed tomography (CT) is essential for diagnosis. Recently, cone-beam CT has come into use. We used an "Alphard 3030" cone-beam CT equipped with an FPD system. This system can obtain fluoroscopic and CT images. Moreover, the Alphard has 4 exposure modes for CT, and each mode has a different field of view (FOV) and voxel size. We examined the image quality of kinetic and CT images obtained using the cone-beam CT system. To evaluate kinetic image quality, we calculated the Wiener spectrum (WS) and modulation transfer function (MTF). We then analyzed the lag images and exposed a phantom. To evaluate CT image quality, we calculated WS and MTF at various places in the FOV and examined the influence of extension of the cone beam X-ray on voxel size. Furthermore, we compared the WS and MTF values of cone-beam CT to those of another CT system. Evaluation of the kinetic images showed that cone-beam CT is sufficient for clinical diagnosis and provides better image quality than the other system tested. However, during exposure of a CT image, the distance from the center influences image quality (especially MTF). Further, differences in voxel size affect image quality. It is therefore necessary to carefully position the region of interest and select an appropriate mode.

Evaluation of correlation between CT image features and ERCC1 protein expression in assessing lung cancer prognosis

NASA Astrophysics Data System (ADS)

Tan, Maxine; Emaminejad, Nastaran; Qian, Wei; Sun, Shenshen; Kang, Yan; Guan, Yubao; Lure, Fleming; Zheng, Bin

2014-03-01

Stage I non-small-cell lung cancers (NSCLC) usually have favorable prognosis. However, high percentage of NSCLC patients have cancer relapse after surgery. Accurately predicting cancer prognosis is important to optimally treat and manage the patients to minimize the risk of cancer relapse. Studies have shown that an excision repair crosscomplementing 1 (ERCC1) gene was a potentially useful genetic biomarker to predict prognosis of NSCLC patients. Meanwhile, studies also found that chronic obstructive pulmonary disease (COPD) was highly associated with lung cancer prognosis. In this study, we investigated and evaluated the correlations between COPD image features and ERCC1 gene expression. A database involving 106 NSCLC patients was used. Each patient had a thoracic CT examination and ERCC1 genetic test. We applied a computer-aided detection scheme to segment and quantify COPD image features. A logistic regression method and a multilayer perceptron network were applied to analyze the correlation between the computed COPD image features and ERCC1 protein expression. A multilayer perceptron network (MPN) was also developed to test performance of using COPD-related image features to predict ERCC1 protein expression. A nine feature based logistic regression analysis showed the average COPD feature values in the low and high ERCC1 protein expression groups are significantly different (p < 0.01). Using a five-fold cross validation method, the MPN yielded an area under ROC curve (AUC = 0.669±0.053) in classifying between the low and high ERCC1 expression cases. The study indicates that CT phenotype features are associated with the genetic tests, which may provide supplementary information to help improve accuracy in assessing prognosis of NSCLC patients.

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Non-rigid registration of serial dedicated breast CT, longitudinal dedicated breast CT and PET/CT images using the diffeomorphic demons method.

PubMed

Santos, Jonathan; Chaudhari, Abhijit J; Joshi, Anand A; Ferrero, Andrea; Yang, Kai; Boone, John M; Badawi, Ramsey D

2014-09-01

Dedicated breast CT and PET/CT scanners provide detailed 3D anatomical and functional imaging data sets and are currently being investigated for applications in breast cancer management such as diagnosis, monitoring response to therapy and radiation therapy planning. Our objective was to evaluate the performance of the diffeomorphic demons (DD) non-rigid image registration method to spatially align 3D serial (pre- and post-contrast) dedicated breast computed tomography (CT), and longitudinally-acquired dedicated 3D breast CT and positron emission tomography (PET)/CT images. The algorithmic parameters of the DD method were optimized for the alignment of dedicated breast CT images using training data and fixed. The performance of the method for image alignment was quantitatively evaluated using three separate data sets; (1) serial breast CT pre- and post-contrast images of 20 women, (2) breast CT images of 20 women acquired before and after repositioning the subject on the scanner, and (3) dedicated breast PET/CT images of 7 women undergoing neo-adjuvant chemotherapy acquired pre-treatment and after 1 cycle of therapy. The DD registration method outperformed no registration (p < 0.001) and conventional affine registration (p ≤ 0.002) for serial and longitudinal breast CT and PET/CT image alignment. In spite of the large size of the imaging data, the computational cost of the DD method was found to be reasonable (3-5 min). Co-registration of dedicated breast CT and PET/CT images can be performed rapidly and reliably using the DD method. This is the first study evaluating the DD registration method for the alignment of dedicated breast CT and PET/CT images. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Radiographic considerations for the regional anatomy in the posterior mandible.

PubMed

Yashar, Natasha; Engeland, Christopher G; Rosenfeld, Alan L; Walsh, Timothy P; Califano, Joseph V

2012-01-01

Previous studies of the inferior alveolar nerve have used cadaveric specimens in small patient groups. The purpose of this study was to describe the anatomy in the posterior mandible with respect to the inferior alveolar nerve (IAN) using computed tomography (CT) images in a large patient population. We hypothesize that CT scans are an important component of a thorough treatment plan for minimizing risk to the IAN and optimizing surgical outcomes. CT scans of 195 patients (62 males and 133 females; age range: 22 to 88 years) were evaluated retrospectively. With the aid of computer software, cross-sectional images were examined at 5-mm increments distal to the mental foramen to the ascending ramus. Four measurements were made at each cross-sectional image. The distances from the IAN to the: 1) alveolar crest (CN); 2) buccal cortical plate (BN); 3) lingual cortical plate (LN); and 4) inferior border (IN) were measured. Most measurements for males and females were significantly different. Mean values were as follows (males/females): CN, 13.85 ± 0.43/11.98 ± 0.40 mm (P <0.01); BN, 4.98 ± 0.15/4.47 ± 0.11 mm (P <0.01); LN, 2.93 ± 0.12/3.19 ± 0.10 mm (P <0.10); and IN, 7.76 ± 0.16/7.00 ± 0.15 mm (P <0.01). The 95% confidence intervals indicated that many patients had limited bone volume in the buccal shelf or ascending ramus. Given the high degree of variability in mandibular bone volume surrounding the IAN and the position of the IAN, the use of CT scans should be considered for surgical procedures in the posterior mandible when there is risk of injury to the IAN.

Computerized organ localization in abdominal CT volume with context-driven generalized Hough transform

NASA Astrophysics Data System (ADS)

Liu, Jing; Li, Qiang

2014-03-01

Fast localization of organs is a key step in computer-aided detection of lesions and in image guided radiation therapy. We developed a context-driven Generalized Hough Transform (GHT) for robust localization of organ-of-interests (OOIs) in a CT volume. Conventional GHT locates the center of an organ by looking-up center locations of pre-learned organs with "matching" edges. It often suffers from mislocalization because "similar" edges in vicinity may attract the prelearned organs towards wrong places. The proposed method not only uses information from organ's own shape but also takes advantage of nearby "similar" edge structures. First, multiple GHT co-existing look-up tables (cLUT) were constructed from a set of training shapes of different organs. Each cLUT represented the spatial relationship between the center of the OOI and the shape of a co-existing organ. Second, the OOI center in a test image was determined using GHT with each cLUT separately. Third, the final localization of OOI was based on weighted combination of the centers obtained in the second stage. The training set consisted of 10 CT volumes with manually segmented OOIs including liver, spleen and kidneys. The method was tested on a set of 25 abdominal CT scans. Context-driven GHT correctly located all OOIs in the test image and gave localization errors of 19.5±9.0, 12.8±7.3, 9.4±4.6 and 8.6±4.1 mm for liver, spleen, left and right kidney respectively. Conventional GHT mis-located 8 out of 100 organs and its localization errors were 26.0±32.6, 14.1±10.6, 30.1±42.6 and 23.6±39.7mm for liver, spleen, left and right kidney respectively.

Prior image constrained image reconstruction in emerging computed tomography applications

NASA Astrophysics Data System (ADS)

Brunner, Stephen T.

Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation dose efficiency improvement in multi-energy photon-counting CT, and can mitigate scatter-induced shading artifacts in cone-beam CT in full-fan and half-fan modes.

Segmentation of pulmonary nodules in three-dimensional CT images by use of a spiral-scanning technique

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

Wang Jiahui; Engelmann, Roger; Li Qiang

2007-12-15

Accurate segmentation of pulmonary nodules in computed tomography (CT) is an important and difficult task for computer-aided diagnosis of lung cancer. Therefore, the authors developed a novel automated method for accurate segmentation of nodules in three-dimensional (3D) CT. First, a volume of interest (VOI) was determined at the location of a nodule. To simplify nodule segmentation, the 3D VOI was transformed into a two-dimensional (2D) image by use of a key 'spiral-scanning' technique, in which a number of radial lines originating from the center of the VOI spirally scanned the VOI from the 'north pole' to the 'south pole'. Themore » voxels scanned by the radial lines provided a transformed 2D image. Because the surface of a nodule in the 3D image became a curve in the transformed 2D image, the spiral-scanning technique considerably simplified the segmentation method and enabled reliable segmentation results to be obtained. A dynamic programming technique was employed to delineate the 'optimal' outline of a nodule in the 2D image, which corresponded to the surface of the nodule in the 3D image. The optimal outline was then transformed back into 3D image space to provide the surface of the nodule. An overlap between nodule regions provided by computer and by the radiologists was employed as a performance metric for evaluating the segmentation method. The database included two Lung Imaging Database Consortium (LIDC) data sets that contained 23 and 86 CT scans, respectively, with 23 and 73 nodules that were 3 mm or larger in diameter. For the two data sets, six and four radiologists manually delineated the outlines of the nodules as reference standards in a performance evaluation for nodule segmentation. The segmentation method was trained on the first and was tested on the second LIDC data sets. The mean overlap values were 66% and 64% for the nodules in the first and second LIDC data sets, respectively, which represented a higher performance level than those of two existing segmentation methods that were also evaluated by use of the LIDC data sets. The segmentation method provided relatively reliable results for pulmonary nodule segmentation and would be useful for lung cancer quantification, detection, and diagnosis.« less

Computer-aided diagnosis in phase contrast imaging X-ray computed tomography for quantitative characterization of ex vivo human patellar cartilage.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismuller, Axel

2013-10-01

Visualization of ex vivo human patellar cartilage matrix through the phase contrast imaging X-ray computed tomography (PCI-CT) has been previously demonstrated. Such studies revealed osteoarthritis-induced changes to chondrocyte organization in the radial zone. This study investigates the application of texture analysis to characterizing such chondrocyte patterns in the presence and absence of osteoarthritic damage. Texture features derived from Minkowski functionals (MF) and gray-level co-occurrence matrices (GLCM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These texture features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). The best classification performance was observed with the MF features perimeter (AUC: 0.94 ±0.08 ) and "Euler characteristic" (AUC: 0.94 ±0.07 ), and GLCM-derived feature "Correlation" (AUC: 0.93 ±0.07). These results suggest that such texture features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix, enabling classification of cartilage as healthy or osteoarthritic with high accuracy.

Reduced dose CT with model-based iterative reconstruction compared to standard dose CT of the chest, abdomen, and pelvis in oncology patients: intra-individual comparison study on image quality and lesion conspicuity.

PubMed

Morimoto, Linda Nayeli; Kamaya, Aya; Boulay-Coletta, Isabelle; Fleischmann, Dominik; Molvin, Lior; Tian, Lu; Fisher, George; Wang, Jia; Willmann, Jürgen K

2017-09-01

To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging. Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales. Median radiation dose reduction was 46% using RD CT (P < 0.01). Median image noise across all measured tissue types was lower (P < 0.01) in RD CT. Subjective image quality for RD CT was higher (P < 0.01) in regard to image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P < 0.01). Lesion conspicuity was subjectively better in RD CT (P < 0.01). Repeated target lesion size measurements were highly reproducible both on SD CT (ICC = 0.987) and RD CT (ICC = 0.97). RD CT imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.

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.

[Basic concept in computer assisted surgery].

PubMed

Merloz, Philippe; Wu, Hao

2006-03-01

To investigate application of medical digital imaging systems and computer technologies in orthopedics. The main computer-assisted surgery systems comprise the four following subcategories. (1) A collection and recording process for digital data on each patient, including preoperative images (CT scans, MRI, standard X-rays), intraoperative visualization (fluoroscopy, ultrasound), and intraoperative position and orientation of surgical instruments or bone sections (using 3D localises). Data merging based on the matching of preoperative imaging (CT scans, MRI, standard X-rays) and intraoperative visualization (anatomical landmarks, or bone surfaces digitized intraoperatively via 3D localiser; intraoperative ultrasound images processed for delineation of bone contours). (2) In cases where only intraoperative images are used for computer-assisted surgical navigation, the calibration of the intraoperative imaging system replaces the merged data system, which is then no longer necessary. (3) A system that provides aid in decision-making, so that the surgical approach is planned on basis of multimodal information: the interactive positioning of surgical instruments or bone sections transmitted via pre- or intraoperative images, display of elements to guide surgical navigation (direction, axis, orientation, length and diameter of a surgical instrument, impingement, etc. ). And (4) A system that monitors the surgical procedure, thereby ensuring that the optimal strategy defined at the preoperative stage is taken into account. It is possible that computer-assisted orthopedic surgery systems will enable surgeons to better assess the accuracy and reliability of the various operative techniques, an indispensable stage in the optimization of surgery.

Finding of Correction Factor and Dimensional Error in Bio-AM Model by FDM Technique

NASA Astrophysics Data System (ADS)

Manmadhachary, Aiamunoori; Ravi Kumar, Yennam; Krishnanand, Lanka

2018-06-01

Additive Manufacturing (AM) is the swift manufacturing process, in which input data can be provided from various sources like 3-Dimensional (3D) Computer Aided Design (CAD), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and 3D scanner data. From the CT/MRI data can be manufacture Biomedical Additive Manufacturing (Bio-AM) models. The Bio-AM model gives a better lead on preplanning of oral and maxillofacial surgery. However manufacturing of the accurate Bio-AM model is one of the unsolved problems. The current paper demonstrates error between the Standard Triangle Language (STL) model to Bio-AM model of dry mandible and found correction factor in Bio-AM model with Fused Deposition Modelling (FDM) technique. In the present work dry mandible CT images are acquired by CT scanner and supplied into a 3D CAD model in the form of STL model. Further the data is sent to FDM machine for fabrication of Bio-AM model. The difference between Bio-AM to STL model dimensions is considered as dimensional error and the ratio of STL to Bio-AM model dimensions considered as a correction factor. This correction factor helps to fabricate the AM model with accurate dimensions of the patient anatomy. These true dimensional Bio-AM models increasing the safety and accuracy in pre-planning of oral and maxillofacial surgery. The correction factor for Dimension SST 768 FDM AM machine is 1.003 and dimensional error is limited to 0.3 %.

Finding of Correction Factor and Dimensional Error in Bio-AM Model by FDM Technique

NASA Astrophysics Data System (ADS)

Manmadhachary, Aiamunoori; Ravi Kumar, Yennam; Krishnanand, Lanka

2016-06-01

Additive Manufacturing (AM) is the swift manufacturing process, in which input data can be provided from various sources like 3-Dimensional (3D) Computer Aided Design (CAD), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and 3D scanner data. From the CT/MRI data can be manufacture Biomedical Additive Manufacturing (Bio-AM) models. The Bio-AM model gives a better lead on preplanning of oral and maxillofacial surgery. However manufacturing of the accurate Bio-AM model is one of the unsolved problems. The current paper demonstrates error between the Standard Triangle Language (STL) model to Bio-AM model of dry mandible and found correction factor in Bio-AM model with Fused Deposition Modelling (FDM) technique. In the present work dry mandible CT images are acquired by CT scanner and supplied into a 3D CAD model in the form of STL model. Further the data is sent to FDM machine for fabrication of Bio-AM model. The difference between Bio-AM to STL model dimensions is considered as dimensional error and the ratio of STL to Bio-AM model dimensions considered as a correction factor. This correction factor helps to fabricate the AM model with accurate dimensions of the patient anatomy. These true dimensional Bio-AM models increasing the safety and accuracy in pre-planning of oral and maxillofacial surgery. The correction factor for Dimension SST 768 FDM AM machine is 1.003 and dimensional error is limited to 0.3 %.

Computerized methodology for micro-CT and histological data inflation using an IVUS based translation map.

PubMed

Athanasiou, Lambros S; Rigas, George A; Sakellarios, Antonis I; Exarchos, Themis P; Siogkas, Panagiotis K; Naka, Katerina K; Panetta, Daniele; Pelosi, Gualtiero; Vozzi, Federico; Michalis, Lampros K; Parodi, Oberdan; Fotiadis, Dimitrios I

2015-10-01

A framework for the inflation of micro-CT and histology data using intravascular ultrasound (IVUS) images, is presented. The proposed methodology consists of three steps. In the first step the micro-CT/histological images are manually co-registered with IVUS by experts using fiducial points as landmarks. In the second step the lumen of both the micro-CT/histological images and IVUS images are automatically segmented. Finally, in the third step the micro-CT/histological images are inflated by applying a transformation method on each image. The transformation method is based on the IVUS and micro-CT/histological contour difference. In order to validate the proposed image inflation methodology, plaque areas in the inflated micro-CT and histological images are compared with the ones in the IVUS images. The proposed methodology for inflating micro-CT/histological images increases the sensitivity of plaque area matching between the inflated and the IVUS images (7% and 22% in histological and micro-CT images, respectively). Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer-aided diagnosis workstation and teleradiology network system for chest diagnosis using the web medical image conference system with a new information security solution

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kaneko, Masahiro; Kakinuma, Ryutaro; Moriyama, Noriyuki

2010-03-01

Diagnostic MDCT imaging requires a considerable number of images to be read. Moreover, the doctor who diagnoses a medical image is insufficient in Japan. Because of such a background, 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. We also have developed the teleradiology network system by using web medical image conference system. In the teleradiology network system, the security of information network is very important subjects. Our teleradiology network system can perform Web medical image conference in the medical institutions of a remote place using the web medical image conference system. We completed the basic proof experiment of the web medical image conference system with information security solution. 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 the workstation that builds in some diagnostic assistance methods. Biometric face authentication used on site of teleradiology makes "Encryption of file" and "Success in login" effective. Our Privacy and information security technology of information security solution ensures compliance with Japanese regulations. 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 teleradiology 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 teleradiology network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

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.

Cartwheel projections of segmented pulmonary vasculature for the detection of pulmonary embolism

NASA Astrophysics Data System (ADS)

Kiraly, Atilla P.; Naidich, David P.; Novak, Carol L.

2005-04-01

Pulmonary embolism (PE) detection via contrast-enhanced computed tomography (CT) images is an increasingly important topic of research. Accurate identification of PE is of critical importance in determining the need for further treatment. However, current multi-slice CT scanners provide datasets typically containing 600 or more images per patient, making it desirable to have a visualization method to help radiologists focus directly on potential candidates that might otherwise have been overlooked. This is especially important when assessing the ability of CT to identify smaller, sub-segmental emboli. We propose a cartwheel projection approach to PE visualization that computes slab projections of the original data aided by vessel segmentation. Previous research on slab visualization for PE has utilized the entire volumetric dataset, requiring thin slabs and necessitating the use of maximum intensity projection (MIP). Our use of segmentation within the projection computation allows the use of thicker slabs than previous methods, as well as the ability to employ visualization variations that are only possible with segmentation. Following automatic segmentation of the pulmonary vessels, slabs may be rotated around the X-, Y- or Z-axis. These slabs are rendered by preferentially using voxels within the lung vessels. This effectively eliminates distracting information not relevant to diagnosis, lessening both the chance of overlooking a subtle embolus and minimizing time on spent evaluating false positives. The ability to employ thicker slabs means fewer images need to be evaluated, yielding a more efficient workflow.

Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismüller, Axel

2014-02-01

Phase-contrast computed tomography (PCI-CT) has shown tremendous potential as an imaging modality for visualizing human cartilage with high spatial resolution. Previous studies have demonstrated the ability of PCI-CT to visualize (1) structural details of the human patellar cartilage matrix and (2) changes to chondrocyte organization induced by osteoarthritis. This study investigates the use of high-dimensional geometric features in characterizing such chondrocyte patterns in the presence or absence of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and statistical features derived from gray-level co-occurrence matrices were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic curve (AUC). SIM-derived geometrical features exhibited the best classification performance (AUC, 0.95 ± 0.06) and were most robust to changes in ROI size. These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated and non-subjective manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

High-performance computer aided detection system for polyp detection in CT colonography with fluid and fecal tagging

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Wang, Shijun; Kabadi, Suraj; Summers, Ronald M.

2009-02-01

CT colonography (CTC) is a feasible and minimally invasive method for the detection of colorectal polyps and cancer screening. Computer-aided detection (CAD) of polyps has improved consistency and sensitivity of virtual colonoscopy interpretation and reduced interpretation burden. A CAD system typically consists of four stages: (1) image preprocessing including colon segmentation; (2) initial detection generation; (3) feature selection; and (4) detection classification. In our experience, three existing problems limit the performance of our current CAD system. First, highdensity orally administered contrast agents in fecal-tagging CTC have scatter effects on neighboring tissues. The scattering manifests itself as an artificial elevation in the observed CT attenuation values of the neighboring tissues. This pseudo-enhancement phenomenon presents a problem for the application of computer-aided polyp detection, especially when polyps are submerged in the contrast agents. Second, general kernel approach for surface curvature computation in the second stage of our CAD system could yield erroneous results for thin structures such as small (6-9 mm) polyps and for touching structures such as polyps that lie on haustral folds. Those erroneous curvatures will reduce the sensitivity of polyp detection. The third problem is that more than 150 features are selected from each polyp candidate in the third stage of our CAD system. These high dimensional features make it difficult to learn a good decision boundary for detection classification and reduce the accuracy of predictions. Therefore, an improved CAD system for polyp detection in CTC data is proposed by introducing three new techniques. First, a scale-based scatter correction algorithm is applied to reduce pseudo-enhancement effects in the image pre-processing stage. Second, a cubic spline interpolation method is utilized to accurately estimate curvatures for initial detection generation. Third, a new dimensionality reduction classifier, diffusion map and local linear embedding (DMLLE), is developed for classification and false positives (FP) reduction. Performance of the improved CAD system is evaluated and compared with our existing CAD system (without applying those techniques) using CT scans of 1186 patients. These scans are divided into a training set and a test set. The sensitivity of the improved CAD system increased 18% on training data at a rate of 5 FPs per patient and 15% on test data at a rate of 5 FPs per patient. Our results indicated that the improved CAD system achieved significantly better performance on medium-sized colonic adenomas with higher sensitivity and lower FP rate in CTC.

GPU-accelerated depth map generation for X-ray simulations of complex CAD geometries

NASA Astrophysics Data System (ADS)

Grandin, Robert J.; Young, Gavin; Holland, Stephen D.; Krishnamurthy, Adarsh

2018-04-01

Interactive x-ray simulations of complex computer-aided design (CAD) models can provide valuable insights for better interpretation of the defect signatures such as porosity from x-ray CT images. Generating the depth map along a particular direction for the given CAD geometry is the most compute-intensive step in x-ray simulations. We have developed a GPU-accelerated method for real-time generation of depth maps of complex CAD geometries. We preprocess complex components designed using commercial CAD systems using a custom CAD module and convert them into a fine user-defined surface tessellation. Our CAD module can be used by different simulators as well as handle complex geometries, including those that arise from complex castings and composite structures. We then make use of a parallel algorithm that runs on a graphics processing unit (GPU) to convert the finely-tessellated CAD model to a voxelized representation. The voxelized representation can enable heterogeneous modeling of the volume enclosed by the CAD model by assigning heterogeneous material properties in specific regions. The depth maps are generated from this voxelized representation with the help of a GPU-accelerated ray-casting algorithm. The GPU-accelerated ray-casting method enables interactive (> 60 frames-per-second) generation of the depth maps of complex CAD geometries. This enables arbitrarily rotation and slicing of the CAD model, leading to better interpretation of the x-ray images by the user. In addition, the depth maps can be used to aid directly in CT reconstruction algorithms.

Deep learning of contrast-coated serrated polyps for computer-aided detection in CT colonography

NASA Astrophysics Data System (ADS)

Näppi, Janne J.; Pickhardt, Perry; Kim, David H.; Hironaka, Toru; Yoshida, Hiroyuki

2017-03-01

Serrated polyps were previously believed to be benign lesions with no cancer potential. However, recent studies have revealed a novel molecular pathway where also serrated polyps can develop into colorectal cancer. CT colonography (CTC) can detect serrated polyps using the radiomic biomarker of contrast coating, but this requires expertise from the reader and current computer-aided detection (CADe) systems have not been designed to detect the contrast coating. The purpose of this study was to develop a novel CADe method that makes use of deep learning to detect serrated polyps based on their contrast-coating biomarker in CTC. In the method, volumetric shape-based features are used to detect polyp sites over soft-tissue and fecal-tagging surfaces of the colon. The detected sites are imaged using multi-angular 2D image patches. A deep convolutional neural network (DCNN) is used to review the image patches for the presence of polyps. The DCNN-based polyp-likelihood estimates are merged into an aggregate likelihood index where highest values indicate the presence of a polyp. For pilot evaluation, the proposed DCNN-CADe method was evaluated with a 10-fold cross-validation scheme using 101 colonoscopy-confirmed cases with 144 biopsy-confirmed serrated polyps from a CTC screening program, where the patients had been prepared for CTC with saline laxative and fecal tagging by barium and iodine-based diatrizoate. The average per-polyp sensitivity for serrated polyps >=6 mm in size was 93+/-7% at 0:8+/-1:8 false positives per patient on average. The detection accuracy was substantially higher that of a conventional CADe system. Our results indicate that serrated polyps can be detected automatically at high accuracy in CTC.

Reducing Head CT Use for Children With Head Injuries in a Community Emergency Department.

PubMed

Jennings, Rebecca M; Burtner, Jennifer J; Pellicer, Joseph F; Nair, Deepthi K; Bradford, Miranda C; Shaffer, Michele; Uspal, Neil G; Tieder, Joel S

2017-04-01

Clinical decision rules have reduced use of computed tomography (CT) to evaluate minor pediatric head injury in pediatric emergency departments (EDs). CT use remains high in community EDs, where the majority of children seek medical care. We sought to reduce the rate of CT scans used to evaluate pediatric head injury from 29% to 20% in a community ED. We evaluated a quality improvement (QI) project in a community ED aimed at decreasing the use of head CT scans in children by implementing a validated head trauma prediction rule for traumatic brain injury. A multidisciplinary team identified key drivers of CT use and implemented decision aids to improve the use of prediction rules. The team identified and mitigated barriers. An affiliated children's hospital offered Maintenance of Certification credit and QI coaching to participants. We used statistical process control charts to evaluate the effect of the intervention on monthly CT scan rates and performed a Wald test of equivalence to compare preintervention and postintervention CT scan proportions. The baseline period (February 2013-July 2014) included 695 patients with a CT scan rate of 29.2% (95% confidence interval, 25.8%-32.6%). The postintervention period (August 2014-October 2015) included 651 patients with a CT scan rate of 17.4% (95% confidence interval, 14.5%-20.2%, P < .01). Barriers included targeting providers with variable pediatric experience and parental imaging expectations. We demonstrate that a Maintenance of Certification QI project sponsored by a children's hospital can facilitate evidence-based pediatric care and decrease the rate of unnecessary CT use in a community setting. Copyright © 2017 by the American Academy of Pediatrics.

Comparison of image features calculated in different dimensions for computer-aided diagnosis of lung nodules

NASA Astrophysics Data System (ADS)

Xu, Ye; Lee, Michael C.; Boroczky, Lilla; Cann, Aaron D.; Borczuk, Alain C.; Kawut, Steven M.; Powell, Charles A.

2009-02-01

Features calculated from different dimensions of images capture quantitative information of the lung nodules through one or multiple image slices. Previously published computer-aided diagnosis (CADx) systems have used either twodimensional (2D) or three-dimensional (3D) features, though there has been little systematic analysis of the relevance of the different dimensions and of the impact of combining different dimensions. The aim of this study is to determine the importance of combining features calculated in different dimensions. We have performed CADx experiments on 125 pulmonary nodules imaged using multi-detector row CT (MDCT). The CADx system computed 192 2D, 2.5D, and 3D image features of the lesions. Leave-one-out experiments were performed using five different combinations of features from different dimensions: 2D, 3D, 2.5D, 2D+3D, and 2D+3D+2.5D. The experiments were performed ten times for each group. Accuracy, sensitivity and specificity were used to evaluate the performance. Wilcoxon signed-rank tests were applied to compare the classification results from these five different combinations of features. Our results showed that 3D image features generate the best result compared with other combinations of features. This suggests one approach to potentially reducing the dimensionality of the CADx data space and the computational complexity of the system while maintaining diagnostic accuracy.

Advanced imaging in acute and chronic deep vein thrombosis

PubMed Central

Karande, Gita Yashwantrao; Sanchez, Yadiel; Baliyan, Vinit; Mishra, Vishala; Ganguli, Suvranu; Prabhakar, Anand M.

2016-01-01

Deep venous thrombosis (DVT) affecting the extremities is a common clinical problem. Prompt imaging aids in rapid diagnosis and adequate treatment. While ultrasound (US) remains the workhorse of detection of extremity venous thrombosis, CT and MRI are commonly used as the problem-solving tools either to visualize the thrombosis in central veins like superior or inferior vena cava (IVC) or to test for the presence of complications like pulmonary embolism (PE). The cross-sectional modalities also offer improved visualization of venous collaterals. The purpose of this article is to review the established modalities used for characterization and diagnosis of DVT, and further explore promising innovations and recent advances in this field. PMID:28123971

PET/CT imaging of clear cell renal cell carcinoma with 124I labeled chimeric antibody

PubMed Central

Bahnson, Eamonn E.; Murrey, Douglas A.; Mojzisik, Cathy M.; Hall, Nathan C.; Martinez-Suarez, Humberto J.; Knopp, Michael V.; Martin, Edward W.; Povoski, Stephen P.; Bahnson, Robert R.

2009-01-01

Clear cell renal cell carcinoma (ccRCC) presents problems for urologists in diagnosis, treatment selection, intraoperative surgical margin analysis, and long term monitoring. In this paper we describe the development of a radiolabeled antibody specific to ccRCC (124I-cG250) and its potential to help urologists manage each of these problems. We believe 124I-cG250, in conjunction with perioperative Positron emission tomography/computed tomography imaging and intraoperative handheld gamma probe use, has the potential to diagnose ccRCC, aid in determining a proper course of treatment (operative or otherwise), confirm complete resection of malignant tissue in real time, and monitor patients post-operatively. PMID:21789055

Radiotherapy treatment planning: benefits of CT-MR image registration and fusion in tumor volume delineation.

PubMed

Djan, Igor; Petrović, Borislava; Erak, Marko; Nikolić, Ivan; Lucić, Silvija

2013-08-01

Development of imaging techniques, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), made great impact on radiotherapy treatment planning by improving the localization of target volumes. Improved localization allows better local control of tumor volumes, but also minimizes geographical misses. Mutual information is obtained by registration and fusion of images achieved manually or automatically. The aim of this study was to validate the CT-MRI image fusion method and compare delineation obtained by CT versus CT-MRI image fusion. The image fusion software (XIO CMS 4.50.0) was applied to delineate 16 patients. The patients were scanned on CT and MRI in the treatment position within an immobilization device before the initial treatment. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on CT alone and on CT+MRI images consecutively and image fusion was obtained. Image fusion showed that CTV delineated on a CT image study set is mainly inadequate for treatment planning, in comparison with CTV delineated on CT-MRI fused image study set. Fusion of different modalities enables the most accurate target volume delineation. This study shows that registration and image fusion allows precise target localization in terms of GTV and CTV and local disease control.

SU-E-P-10: Imaging in the Cardiac Catheterization Lab - Technologies and Clinical Applications

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

Fetterly, K

2014-06-01

Purpose: Diagnosis and treatment of cardiovascular disease in the cardiac catheterization laboratory is often aided by a multitude of imaging technologies. The purpose of this work is to highlight the contributions to patient care offered by the various imaging systems used during cardiovascular interventional procedures. Methods: Imaging technologies used in the cardiac catheterization lab were characterized by their fundamental technology and by the clinical applications for which they are used. Whether the modality is external to the patient, intravascular, or intracavity was specified. Specific clinical procedures for which multiple modalities are routinely used will be highlighted. Results: X-ray imaging modalitiesmore » include fluoroscopy/angiography and angiography CT. Ultrasound imaging is performed with external, trans-esophageal echocardiography (TEE), and intravascular (IVUS) transducers. Intravascular infrared optical coherence tomography (IVOCT) is used to assess vessel endothelium. Relatively large (>0.5 mm) anatomical structures are imaged with x-ray and ultrasound. IVUS and IVOCT provide high resolution images of vessel walls. Cardiac CT and MRI images are used to plan complex cardiovascular interventions. Advanced applications are used to spatially and temporally merge images from different technologies. Diagnosis and treatment of coronary artery disease frequently utilizes angiography and intra-vascular imaging, and treatment of complex structural heart conditions routinely includes use of multiple imaging modalities. Conclusion: There are several imaging modalities which are routinely used in the cardiac catheterization laboratory to diagnose and treat both coronary artery and structural heart disease. Multiple modalities are frequently used to enhance the quality and safety of procedures. The cardiac catheterization laboratory includes many opportunities for medical physicists to contribute substantially toward advancing patient care.« less

Multilevel image recognition using discriminative patches and kernel covariance descriptor

NASA Astrophysics Data System (ADS)

Lu, Le; Yao, Jianhua; Turkbey, Evrim; Summers, Ronald M.

2014-03-01

Computer-aided diagnosis of medical images has emerged as an important tool to objectively improve the performance, accuracy and consistency for clinical workflow. To computerize the medical image diagnostic recognition problem, there are three fundamental problems: where to look (i.e., where is the region of interest from the whole image/volume), image feature description/encoding, and similarity metrics for classification or matching. In this paper, we exploit the motivation, implementation and performance evaluation of task-driven iterative, discriminative image patch mining; covariance matrix based descriptor via intensity, gradient and spatial layout; and log-Euclidean distance kernel for support vector machine, to address these three aspects respectively. To cope with often visually ambiguous image patterns for the region of interest in medical diagnosis, discovery of multilabel selective discriminative patches is desired. Covariance of several image statistics summarizes their second order interactions within an image patch and is proved as an effective image descriptor, with low dimensionality compared with joint statistics and fast computation regardless of the patch size. We extensively evaluate two extended Gaussian kernels using affine-invariant Riemannian metric or log-Euclidean metric with support vector machines (SVM), on two medical image classification problems of degenerative disc disease (DDD) detection on cortical shell unwrapped CT maps and colitis detection on CT key images. The proposed approach is validated with promising quantitative results on these challenging tasks. Our experimental findings and discussion also unveil some interesting insights on the covariance feature composition with or without spatial layout for classification and retrieval, and different kernel constructions for SVM. This will also shed some light on future work using covariance feature and kernel classification for medical image analysis.

Diagnosing Appendicitis: Evidence-Based Review of the Diagnostic Approach in 2014

PubMed Central

Shogilev, Daniel J.; Duus, Nicolaj; Odom, Stephen R.; Shapiro, Nathan I.

2014-01-01

Introduction Acute appendicitis is the most common abdominal emergency requiring emergency surgery. However, the diagnosis is often challenging and the decision to operate, observe or further work-up a patient is often unclear. The utility of clinical scoring systems (namely the Alvarado score), laboratory markers, and the development of novel markers in the diagnosis of appendicitis remains controversial. This article presents an update on the diagnostic approach to appendicitis through an evidence-based review. Methods We performed a broad Medline search of radiological imaging, the Alvarado score, common laboratory markers, and novel markers in patients with suspected appendicitis. Results Computed tomography (CT) is the most accurate mode of imaging for suspected cases of appendicitis, but the associated increase in radiation exposure is problematic. The Alvarado score is a clinical scoring system that is used to predict the likelihood of appendicitis based on signs, symptoms and laboratory data. It can help risk stratify patients with suspected appendicitis and potentially decrease the use of CT imaging in patients with certain Alvarado scores. White blood cell (WBC), C-reactive protein (CRP), granulocyte count and proportion of polymorphonuclear (PMN) cells are frequently elevated in patients with appendicitis, but are insufficient on their own as a diagnostic modality. When multiple markers are used in combination their diagnostic utility is greatly increased. Several novel markers have been proposed to aid in the diagnosis of appendicitis; however, while promising, most are only in the preliminary stages of being studied. Conclusion While CT is the most accurate mode of imaging in suspected appendicitis, the accompanying radiation is a concern. Ultrasound may help in the diagnosis while decreasing the need for CT in certain circumstances. The Alvarado Score has good diagnostic utility at specific cutoff points. Laboratory markers have very limited diagnostic utility on their own but show promise when used in combination. Further studies are warranted for laboratory markers in combination and to validate potential novel markers. PMID:25493136

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.

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.

Development of proton CT imaging system using plastic scintillator and CCD camera

NASA Astrophysics Data System (ADS)

Tanaka, Sodai; Nishio, Teiji; Matsushita, Keiichiro; Tsuneda, Masato; Kabuki, Shigeto; Uesaka, Mitsuru

2016-06-01

A proton computed tomography (pCT) imaging system was constructed for evaluation of the error of an x-ray CT (xCT)-to-WEL (water-equivalent length) conversion in treatment planning for proton therapy. In this system, the scintillation light integrated along the beam direction is obtained by photography using the CCD camera, which enables fast and easy data acquisition. The light intensity is converted to the range of the proton beam using a light-to-range conversion table made beforehand, and a pCT image is reconstructed. An experiment for demonstration of the pCT system was performed using a 70 MeV proton beam provided by the AVF930 cyclotron at the National Institute of Radiological Sciences. Three-dimensional pCT images were reconstructed from the experimental data. A thin structure of approximately 1 mm was clearly observed, with spatial resolution of pCT images at the same level as that of xCT images. The pCT images of various substances were reconstructed to evaluate the pixel value of pCT images. The image quality was investigated with regard to deterioration including multiple Coulomb scattering.

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.

A computationally inexpensive model for estimating dimensional measurement uncertainty due to x-ray computed tomography instrument misalignments

NASA Astrophysics Data System (ADS)

Ametova, Evelina; Ferrucci, Massimiliano; Chilingaryan, Suren; Dewulf, Wim

2018-06-01

The recent emergence of advanced manufacturing techniques such as additive manufacturing and an increased demand on the integrity of components have motivated research on the application of x-ray computed tomography (CT) for dimensional quality control. While CT has shown significant empirical potential for this purpose, there is a need for metrological research to accelerate the acceptance of CT as a measuring instrument. The accuracy in CT-based measurements is vulnerable to the instrument geometrical configuration during data acquisition, namely the relative position and orientation of x-ray source, rotation stage, and detector. Consistency between the actual instrument geometry and the corresponding parameters used in the reconstruction algorithm is critical. Currently available procedures provide users with only estimates of geometrical parameters. Quantification and propagation of uncertainty in the measured geometrical parameters must be considered to provide a complete uncertainty analysis and to establish confidence intervals for CT dimensional measurements. In this paper, we propose a computationally inexpensive model to approximate the influence of errors in CT geometrical parameters on dimensional measurement results. We use surface points extracted from a computer-aided design (CAD) model to model discrepancies in the radiographic image coordinates assigned to the projected edges between an aligned system and a system with misalignments. The efficacy of the proposed method was confirmed on simulated and experimental data in the presence of various geometrical uncertainty contributors.

Validation of the Pediatric NEXUS II Head CT Decision Instrument for Selective Imaging of Pediatric Patients with Blunt Head Trauma.

PubMed

Gupta, Malkeet; Mower, William R; Rodriguez, Robert M; Hendey, Gregory W

2018-04-17

Data suggests that clinicians, when evaluating pediatric patients with blunt head trauma, may be over-ordering head computed tomography. Prior decision instruments aimed at aiding clinicians in safely forgoing CTs may be paradoxically increasing CT utilization. This study evaluated a novel decision instrument that aims for high sensitivity while also improving specificity over prior instruments. We conducted a planned secondary analysis of the NEXUS Head CT decision instrument (DI) among patients less than 18 years old. The rule required patients satisfy seven criteria to achieve "low-risk" classification. Patients were assigned "high risk" status if they fail to meet one or more criteria. Our primary outcome was the ability of the rule to identify all patients requiring neurosurgical intervention. The study enrolled 1,018 blunt head injury pediatric patients. The DI assigned high-risk status to 27 of 27 patients requiring neurosurgical intervention (sensitivity, 100.0% [95% confidence interval [CI]: 87.2% - 100%]). The instrument assigned low-risk status to 330 of 991 patients who did not require neurosurgical intervention (specificity, 33.3% [95% CI: 30.3% - 36.3%]). None of the 991 low-risk patients required neurosurgical intervention (NPV, 100% [95% CI: 99.6% - 100%]). The DI correctly assigned high-risk status to 48 of the 49 patients with significant intracranial injuries, yielding a sensitivity of 98.0% (95% CI: 89.1% - 99.9%). The instrument assigned low-risk status to 329 of 969 patients who did not have significant injuries to yield a specificity of 34.0% (95% CI: 31.0% - 37.0%). Significant injuries were absent in 329 of the 330 patients assigned low-risk status to yield a NPV of 99.7% (95% CI: 98.3% - 100%). The Pediatric NEXUS Head CT DI reliably identifies blunt trauma patients who require head CT imaging, and could significantly reduce the use of CT imaging This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Artefacts of PET/CT images

PubMed Central

Pettinato, C; Nanni, C; Farsad, M; Castellucci, P; Sarnelli, A; Civollani, S; Franchi, R; Fanti, S; Marengo, M; Bergamini, C

2006-01-01

Positron emission tomography (PET) is a non-invasive imaging modality, which is clinically widely used both for diagnosis and accessing therapy response in oncology, cardiology and neurology. Fusing PET and CT images in a single dataset would be useful for physicians who could read the functional and the anatomical aspects of a disease in a single shot. The use of fusion software has been replaced in the last few years by integrated PET/CT systems, which combine a PET and a CT scanner in the same gantry. CT images have the double function to correct PET images for attenuation and can fuse with PET for a better visualization and localization of lesions. The use of CT for attenuation correction yields several advantages in terms of accuracy and patient comfort, but can also introduce several artefacts on PET-corrected images. PET/CT image artefacts are due primarily to metallic implants, respiratory motion, use of contrast media and image truncation. This paper reviews different types artefacts and their correction methods. PET/CT improves image quality and image accuracy. However, to avoid possible pitfalls the simultaneous display of both Computed Tomography Attenuation Corrected (CTAC) and non corrected PET images, side by side with CT images is strongly recommended. PMID:21614340

SU-C-207A-03: Development of Proton CT Imaging System Using Thick Scintillator and CCD Camera

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

Tanaka, S; Uesaka, M; Nishio, T

2016-06-15

Purpose: In the treatment planning of proton therapy, Water Equivalent Length (WEL), which is the parameter for the calculation of dose and the range of proton, is derived by X-ray CT (xCT) image and xCT-WEL conversion. However, about a few percent error in the accuracy of proton range calculation through this conversion has been reported. The purpose of this study is to construct a proton CT (pCT) imaging system for an evaluation of the error. Methods: The pCT imaging system was constructed with a thick scintillator and a cooled CCD camera, which acquires the two-dimensional image of integrated value ofmore » the scintillation light toward the beam direction. The pCT image is reconstructed by FBP method using a correction between the light intensity and residual range of proton beam. An experiment for the demonstration of this system was performed with 70-MeV proton beam provided by NIRS cyclotron. The pCT image of several objects reconstructed from the experimental data was evaluated quantitatively. Results: Three-dimensional pCT images of several objects were reconstructed experimentally. A finestructure of approximately 1 mm was clearly observed. The position resolution of pCT image was almost the same as that of xCT image. And the error of proton CT pixel value was up to 4%. The deterioration of image quality was caused mainly by the effect of multiple Coulomb scattering. Conclusion: We designed and constructed the pCT imaging system using a thick scintillator and a CCD camera. And the system was evaluated with the experiment by use of 70-MeV proton beam. Three-dimensional pCT images of several objects were acquired by the system. This work was supported by JST SENTAN Grant Number 13A1101 and JSPS KAKENHI Grant Number 15H04912.« less

SU-E-J-89: Comparative Analysis of MIM and Velocity’s Image Deformation Algorithm Using Simulated KV-CBCT Images for Quality Assurance

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

Cline, K; Narayanasamy, G; Obediat, M

Purpose: Deformable image registration (DIR) is used routinely in the clinic without a formalized quality assurance (QA) process. Using simulated deformations to digitally deform images in a known way and comparing to DIR algorithm predictions is a powerful technique for DIR QA. This technique must also simulate realistic image noise and artifacts, especially between modalities. This study developed an algorithm to create simulated daily kV cone-beam computed-tomography (CBCT) images from CT images for DIR QA between these modalities. Methods: A Catphan and physical head-and-neck phantom, with known deformations, were used. CT and kV-CBCT images of the Catphan were utilized tomore » characterize the changes in Hounsfield units, noise, and image cupping that occur between these imaging modalities. The algorithm then imprinted these changes onto a CT image of the deformed head-and-neck phantom, thereby creating a simulated-CBCT image. CT and kV-CBCT images of the undeformed and deformed head-and-neck phantom were also acquired. The Velocity and MIM DIR algorithms were applied between the undeformed CT image and each of the deformed CT, CBCT, and simulated-CBCT images to obtain predicted deformations. The error between the known and predicted deformations was used as a metric to evaluate the quality of the simulated-CBCT image. Ideally, the simulated-CBCT image registration would produce the same accuracy as the deformed CBCT image registration. Results: For Velocity, the mean error was 1.4 mm for the CT-CT registration, 1.7 mm for the CT-CBCT registration, and 1.4 mm for the CT-simulated-CBCT registration. These same numbers were 1.5, 4.5, and 5.9 mm, respectively, for MIM. Conclusion: All cases produced similar accuracy for Velocity. MIM produced similar values of accuracy for CT-CT registration, but was not as accurate for CT-CBCT registrations. The MIM simulated-CBCT registration followed this same trend, but overestimated MIM DIR errors relative to the CT-CBCT registration.« less

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

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.

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.

Unusual Radiographic Presentation of Pneumocystis Pneumonia in a Patient with AIDS.

PubMed

Block, Brian L; Mehta, Tejas; Ortiz, Gabriel M; Ferris, Sean P; Vu, Thienkhai H; Huang, Laurence; Cattamanchi, Adithya

2017-01-01

Pneumocystis jirovecii pneumonia (PCP) typically presents as an interstitial and alveolar process with ground glass opacities on chest computed tomography (CT). The absence of ground glass opacities on chest CT is thought to have a high negative predictive value for PCP in individuals with AIDS. Here, we report a case of PCP in a man with AIDS who presented to our hospital with subacute shortness of breath and a nonproductive cough. While his chest CT revealed diffuse nodular rather than ground glass opacities, bronchoscopy with bronchoalveolar lavage and transbronchial biopsies confirmed the diagnosis of PCP and did not identify additional pathogens. PCP was not the expected diagnosis based on chest CT, but it otherwise fit well with the patient's clinical and laboratory presentation. In the era of combination antiretroviral therapy, routine prophylaxis for PCP, and increased use of computed tomography, it may be that PCP will increasingly present with nonclassical chest radiographic patterns. Clinicians should be aware of this presentation when selecting diagnostic and management strategies.

Unusual Radiographic Presentation of Pneumocystis Pneumonia in a Patient with AIDS

PubMed Central

Mehta, Tejas; Ortiz, Gabriel M.; Ferris, Sean P.; Vu, Thienkhai H.; Huang, Laurence; Cattamanchi, Adithya

2017-01-01

Pneumocystis jirovecii pneumonia (PCP) typically presents as an interstitial and alveolar process with ground glass opacities on chest computed tomography (CT). The absence of ground glass opacities on chest CT is thought to have a high negative predictive value for PCP in individuals with AIDS. Here, we report a case of PCP in a man with AIDS who presented to our hospital with subacute shortness of breath and a nonproductive cough. While his chest CT revealed diffuse nodular rather than ground glass opacities, bronchoscopy with bronchoalveolar lavage and transbronchial biopsies confirmed the diagnosis of PCP and did not identify additional pathogens. PCP was not the expected diagnosis based on chest CT, but it otherwise fit well with the patient's clinical and laboratory presentation. In the era of combination antiretroviral therapy, routine prophylaxis for PCP, and increased use of computed tomography, it may be that PCP will increasingly present with nonclassical chest radiographic patterns. Clinicians should be aware of this presentation when selecting diagnostic and management strategies. PMID:29362681

Evaluation of an attenuation correction method for PET/MR imaging of the head based on substitute CT images.

PubMed

Larsson, Anne; Johansson, Adam; Axelsson, Jan; Nyholm, Tufve; Asklund, Thomas; Riklund, Katrine; Karlsson, Mikael

2013-02-01

The aim of this study was to evaluate MR-based attenuation correction of PET emission data of the head, based on a previously described technique that calculates substitute CT (sCT) images from a set of MR images. Images from eight patients, examined with (18)F-FLT PET/CT and MRI, were included. sCT images were calculated and co-registered to the corresponding CT images, and transferred to the PET/CT scanner for reconstruction. The new reconstructions were then compared with the originals. The effect of replacing bone with soft tissue in the sCT-images was also evaluated. The average relative difference between the sCT-corrected PET images and the CT-corrected PET images was 1.6% for the head and 1.9% for the brain. The average standard deviations of the relative differences within the head were relatively high, at 13.2%, primarily because of large differences in the nasal septa region. For the brain, the average standard deviation was lower, 4.1%. The global average difference in the head when replacing bone with soft tissue was 11%. The method presented here has a high rate of accuracy, but high-precision quantitative imaging of the nasal septa region is not possible at the moment.

Mixed spine metastasis detection through positron emission tomography/computed tomography synthesis and multiclassifier

PubMed Central

Yao, Jianhua; Burns, Joseph E.; Sanoria, Vic; Summers, Ronald M.

2017-01-01

Abstract. Bone metastases are a frequent occurrence with cancer, and early detection can guide the patient’s treatment regimen. Metastatic bone disease can present in density extremes as sclerotic (high density) and lytic (low density) or in a continuum with an admixture of both sclerotic and lytic components. We design a framework to detect and characterize the varying spectrum of presentation of spine metastasis on positron emission tomography/computed tomography (PET/CT) data. A technique is proposed to synthesize CT and PET images to enhance the lesion appearance for computer detection. A combination of watershed, graph cut, and level set algorithms is first run to obtain the initial detections. Detections are then sent to multiple classifiers for sclerotic, lytic, and mixed lesions. The system was tested on 44 cases with 225 sclerotic, 139 lytic, and 92 mixed lesions. The results showed that sensitivity (false positive per patient) was 0.81 (2.1), 0.81 (1.3), and 0.76 (2.1) for sclerotic, lytic, and mixed lesions, respectively. It also demonstrates that using PET/CT data significantly improves the computer aided detection performance over using CT alone. PMID:28612036

Computed tomography: a powerful imaging technique in the fields of dimensional metrology and quality control

NASA Astrophysics Data System (ADS)

Probst, Gabriel; Boeckmans, Bart; Dewulf, Wim; Kruth, Jean-Pierre

2016-05-01

X-ray computed tomography (CT) is slowly conquering its space in the manufacturing industry for dimensional metrology and quality control purposes. The main advantage is its non-invasive and non-destructive character. Currently, CT is the only measurement technique that allows full 3D visualization of both inner and outer features of an object through a contactless probing system. Using hundreds of radiographs, acquired while rotating the object, a 3D representation is generated and dimensions can be verified. In this research, this non-contact technique was used for the inspection of assembled components. A dental cast model with 8 implants, connected by a screwed retained bar made of titanium. The retained bar includes a mating interface connection that should ensure a perfect fitting without residual stresses when the connection is fixed with screws. CT was used to inspect the mating interfaces between these two components. Gaps at the connections can lead to bacterial growth and potential inconvenience for the patient who would have to face a new surgery to replace his/hers prosthesis. With the aid of CT, flaws in the design or manufacturing process that could lead to gaps at the connections could be assessed.

Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging

PubMed Central

Danad, Ibrahim; Fayad, Zahi A.; Willemink, Martin J.; Min, James K.

2015-01-01

Computed tomography (CT) evolved into a powerful diagnostic tool and it is impossible to imagine current clinical practice without CT imaging. Due to its widespread availability, ease of clinical application, superb sensitivity for detection of CAD, and non-invasive nature, CT has become a valuable tool within the armamentarium of the cardiologist. In the last few years, numerous technological advances in CT have occurred—including dual energy CT (DECT), spectral CT and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging modality tool that permits accurate plaque characterization, assessment of myocardial perfusion and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging. PMID:26068288

Computer aided lung cancer diagnosis with deep learning algorithms

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Zheng, Bin; Qian, Wei

2016-03-01

Deep learning is considered as a popular and powerful method in pattern recognition and classification. However, there are not many deep structured applications used in medical imaging diagnosis area, because large dataset is not always available for medical images. In this study we tested the feasibility of using deep learning algorithms for lung cancer diagnosis with the cases from Lung Image Database Consortium (LIDC) database. The nodules on each computed tomography (CT) slice were segmented according to marks provided by the radiologists. After down sampling and rotating we acquired 174412 samples with 52 by 52 pixel each and the corresponding truth files. Three deep learning algorithms were designed and implemented, including Convolutional Neural Network (CNN), Deep Belief Networks (DBNs), Stacked Denoising Autoencoder (SDAE). To compare the performance of deep learning algorithms with traditional computer aided diagnosis (CADx) system, we designed a scheme with 28 image features and support vector machine. The accuracies of CNN, DBNs, and SDAE are 0.7976, 0.8119, and 0.7929, respectively; the accuracy of our designed traditional CADx is 0.7940, which is slightly lower than CNN and DBNs. We also noticed that the mislabeled nodules using DBNs are 4% larger than using traditional CADx, this might be resulting from down sampling process lost some size information of the nodules.

3D SPECT/CT fusion using image data projection of bone SPECT onto 3D volume-rendered CT images: feasibility and clinical impact in the diagnosis of bone metastasis.

PubMed

Ogata, Yuji; Nakahara, Tadaki; Ode, Kenichi; Matsusaka, Yohji; Katagiri, Mari; Iwabuchi, Yu; Itoh, Kazunari; Ichimura, Akira; Jinzaki, Masahiro

2017-05-01

We developed a method of image data projection of bone SPECT into 3D volume-rendered CT images for 3D SPECT/CT fusion. The aims of our study were to evaluate its feasibility and clinical usefulness. Whole-body bone scintigraphy (WB) and SPECT/CT scans were performed in 318 cancer patients using a dedicated SPECT/CT systems. Volume data of bone SPECT and CT were fused to obtain 2D SPECT/CT images. To generate our 3D SPECT/CT images, colored voxel data of bone SPECT were projected onto the corresponding location of the volume-rendered CT data after a semi-automatic bone extraction. Then, the resultant 3D images were blended with conventional volume-rendered CT images, allowing to grasp the three-dimensional relationship between bone metabolism and anatomy. WB and SPECT (WB + SPECT), 2D SPECT/CT fusion, and 3D SPECT/CT fusion were evaluated by two independent reviewers in the diagnosis of bone metastasis. The inter-observer variability and diagnostic accuracy in these three image sets were investigated using a four-point diagnostic scale. Increased bone metabolism was found in 744 metastatic sites and 1002 benign changes. On a per-lesion basis, inter-observer agreements in the diagnosis of bone metastasis were 0.72 for WB + SPECT, 0.90 for 2D SPECT/CT, and 0.89 for 3D SPECT/CT. Receiver operating characteristic analyses for the diagnostic accuracy of bone metastasis showed that WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT had an area under the curve of 0.800, 0.983, and 0.983 for reader 1, 0.865, 0.992, and 0.993 for reader 2, respectively (WB + SPECT vs. 2D or 3D SPECT/CT, p < 0.001; 2D vs. 3D SPECT/CT, n.s.). The durations of interpretation of WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT images were 241 ± 75, 225 ± 73, and 182 ± 71 s for reader 1 and 207 ± 72, 190 ± 73, and 179 ± 73 s for reader 2, respectively. As a result, it took shorter time to read 3D SPECT/CT images than 2D SPECT/CT (p < 0.0001) or WB + SPECT images (p < 0.0001). 3D SPECT/CT fusion offers comparable diagnostic accuracy to 2D SPECT/CT fusion. The visual effect of 3D SPECT/CT fusion facilitates reduction of reading time compared to 2D SPECT/CT fusion.

A visualization system for CT based pulmonary fissure analysis

NASA Astrophysics Data System (ADS)

Pu, Jiantao; Zheng, Bin; Park, Sang Cheol

2009-02-01

In this study we describe a visualization system of pulmonary fissures depicted on CT images. The purpose is to provide clinicians with an intuitive perception of a patient's lung anatomy through an interactive examination of fissures, enhancing their understanding and accurate diagnosis of lung diseases. This system consists of four key components: (1) region-of-interest segmentation; (2) three-dimensional surface modeling; (3) fissure type classification; and (4) an interactive user interface, by which the extracted fissures are displayed flexibly in different space domains including image space, geometric space, and mixed space using simple toggling "on" and "off" operations. In this system, the different visualization modes allow users not only to examine the fissures themselves but also to analyze the relationship between fissures and their surrounding structures. In addition, the users can adjust thresholds interactively to visualize the fissure surface under different scanning and processing conditions. Such a visualization tool is expected to facilitate investigation of structures near the fissures and provide an efficient "visual aid" for other applications such as treatment planning and assessment of therapeutic efficacy as well as education of medical professionals.

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed

K, Jalal Deen; R, Ganesan; A, Merline

2017-07-27

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. Creative Commons Attribution License

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed Central

K, Jalal Deen; R, Ganesan; A, Merline

2017-01-01

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. PMID:28749127

Integrated computer-aided forensic case analysis, presentation, and documentation based on multimodal 3D data.

PubMed

Bornik, Alexander; Urschler, Martin; Schmalstieg, Dieter; Bischof, Horst; Krauskopf, Astrid; Schwark, Thorsten; Scheurer, Eva; Yen, Kathrin

2018-06-01

Three-dimensional (3D) crime scene documentation using 3D scanners and medical imaging modalities like computed tomography (CT) and magnetic resonance imaging (MRI) are increasingly applied in forensic casework. Together with digital photography, these modalities enable comprehensive and non-invasive recording of forensically relevant information regarding injuries/pathologies inside the body and on its surface. Furthermore, it is possible to capture traces and items at crime scenes. Such digitally secured evidence has the potential to similarly increase case understanding by forensic experts and non-experts in court. Unlike photographs and 3D surface models, images from CT and MRI are not self-explanatory. Their interpretation and understanding requires radiological knowledge. Findings in tomography data must not only be revealed, but should also be jointly studied with all the 2D and 3D data available in order to clarify spatial interrelations and to optimally exploit the data at hand. This is technically challenging due to the heterogeneous data representations including volumetric data, polygonal 3D models, and images. This paper presents a novel computer-aided forensic toolbox providing tools to support the analysis, documentation, annotation, and illustration of forensic cases using heterogeneous digital data. Conjoint visualization of data from different modalities in their native form and efficient tools to visually extract and emphasize findings help experts to reveal unrecognized correlations and thereby enhance their case understanding. Moreover, the 3D case illustrations created for case analysis represent an efficient means to convey the insights gained from case analysis to forensic non-experts involved in court proceedings like jurists and laymen. The capability of the presented approach in the context of case analysis, its potential to speed up legal procedures and to ultimately enhance legal certainty is demonstrated by introducing a number of representative forensic cases. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.

Treatment response assessment of radiofrequency ablation for hepatocellular carcinoma: usefulness of virtual CT sonography with magnetic navigation.

PubMed

Minami, Yasunori; Kitai, Satoshi; Kudo, Masatoshi

2012-03-01

Virtual CT sonography using magnetic navigation provides cross sectional images of CT volume data corresponding to the angle of the transducer in the magnetic field in real-time. The purpose of this study was to clarify the value of this virtual CT sonography for treatment response of radiofrequency ablation for hepatocellular carcinoma. Sixty-one patients with 88 HCCs measuring 0.5-1.3 cm (mean±SD, 1.0±0.3 cm) were treated by radiofrequency ablation. For early treatment response, dynamic CT was performed 1-5 days (median, 2 days). We compared early treatment response between axial CT images and multi-angle CT images using virtual CT sonography. Residual tumor stains on axial CT images and multi-angle CT images were detected in 11.4% (10/88) and 13.6% (12/88) after the first session of RFA, respectively (P=0.65). Two patients were diagnosed as showing hyperemia enhancement after the initial radiofrequency ablation on axial CT images and showed local tumor progression shortly because of unnoticed residual tumors. Only virtual CT sonography with magnetic navigation retrospectively showed the residual tumor as circular enhancement. In safety margin analysis, 10 patients were excluded because of residual tumors. The safety margin more than 5 mm by virtual CT sonographic images and transverse CT images were determined in 71.8% (56/78) and 82.1% (64/78), respectively (P=0.13). The safety margin should be overestimated on axial CT images in 8 nodules. Virtual CT sonography with magnetic navigation was useful in evaluating the treatment response of radiofrequency ablation therapy for hepatocellular carcinoma. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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.

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.

Rapid Prototyping Integrated With Nondestructive Evaluation and Finite Element Analysis

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Baaklini, George Y.

2001-01-01

Most reverse engineering approaches involve imaging or digitizing an object then creating a computerized reconstruction that can be integrated, in three dimensions, into a particular design environment. Rapid prototyping (RP) refers to the practical ability to build high-quality physical prototypes directly from computer aided design (CAD) files. Using rapid prototyping, full-scale models or patterns can be built using a variety of materials in a fraction of the time required by more traditional prototyping techniques (refs. 1 and 2). Many software packages have been developed and are being designed to tackle the reverse engineering and rapid prototyping issues just mentioned. For example, image processing and three-dimensional reconstruction visualization software such as Velocity2 (ref. 3) are being used to carry out the construction process of three-dimensional volume models and the subsequent generation of a stereolithography file that is suitable for CAD applications. Producing three-dimensional models of objects from computed tomography (CT) scans is becoming a valuable nondestructive evaluation methodology (ref. 4). Real components can be rendered and subjected to temperature and stress tests using structural engineering software codes. For this to be achieved, accurate high-resolution images have to be obtained via CT scans and then processed, converted into a traditional file format, and translated into finite element models. Prototyping a three-dimensional volume of a composite structure by reading in a series of two-dimensional images generated via CT and by using and integrating commercial software (e.g. Velocity2, MSC/PATRAN (ref. 5), and Hypermesh (ref. 6)) is being applied successfully at the NASA Glenn Research Center. The building process from structural modeling to the analysis level is outlined in reference 7. Subsequently, a stress analysis of a composite cooling panel under combined thermomechanical loading conditions was performed to validate this process.

In vivo and ex vivo measurement of polyethylene wear in total hip arthroplasty: comparison of measurements using a CT algorithm, a coordinate-measuring machine, and a micrometer.

PubMed

Goldvasser, Dov; Hansen, Viktor J; Noz, Marilyn E; Maguire, Gerald Q; Zeleznik, Michael P; Olivecrona, Henrik; Bragdon, Charles R; Weidenhielm, Lars; Malchau, Henrik

2014-06-01

Determination of the amount of wear in a polyethylene liner following total hip arthroplasty (THA) is important for both the clinical care of individual patients and the development of new types of liners. We measured in vivo wear of the polyethylene liner using computed tomography (CT) (obtained in the course of regular clinical care) and compared it to coordinate-measuring machine (CMM) readings. Also, changes in liner thickness of the same retrieved polyethylene liner were measured using a micrometer, and were compared to CT and CMM measurements. The distance between the centers of the acetabular cup and femoral head component was measured in 3D CT, using a semi-automatic analysis method. CMM readings were performed on each acetabular liner and data were analyzed using 3D computer-aided design software. Micrometer readings compared the thickest and thinnest regions of the liner. We analyzed 10 THA CTs and retrievals that met minimal requirements for CT slice thickness and explanted cup condition. RESULTS - For the 10 cups, the mean difference between the CT readings and the CMM readings was -0.09 (-0.38 to 0.20) mm. This difference was not statistically significant (p = 0.6). Between CT and micrometer, the mean difference was 0.11 (-0.33 to 0.55) mm. This difference was not statistically significant (p = 0.6). INTERPRETATION - Our results show that CT imaging is ready to be used as a tool in clinical wear measurement of polyethylene liners used in THA.

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

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

SU-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET

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

Cui, Y; Bowsher, J; Yan, S

2014-06-01

Purpose: To evaluate the appropriateness of using 3D non-gated CT image for attenuation correction (AC) in a 4D-PET (gated PET) imaging protocol used in radiotherapy treatment planning simulation. Methods: The 4D-PET imaging protocol in a Siemens PET/CT simulator (Biograph mCT, Siemens Medical Solutions, Hoffman Estates, IL) was evaluated. CIRS Dynamic Thorax Phantom (CIRS Inc., Norfolk, VA) with a moving glass sphere (8 mL) in the middle of its thorax portion was used in the experiments. The glass was filled with {sup 18}F-FDG and was in a longitudinal motion derived from a real patient breathing pattern. Varian RPM system (Varian Medicalmore » Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.« less

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.

Impact of the Adaptive Statistical Iterative Reconstruction Technique on Radiation Dose and Image Quality in Bone SPECT/CT.

PubMed

Sibille, Louis; Chambert, Benjamin; Alonso, Sandrine; Barrau, Corinne; D'Estanque, Emmanuel; Al Tabaa, Yassine; Collombier, Laurent; Demattei, Christophe; Kotzki, Pierre-Olivier; Boudousq, Vincent

2016-07-01

The purpose of this study was to compare a routine bone SPECT/CT protocol using CT reconstructed with filtered backprojection (FBP) with an optimized protocol using low-dose CT images reconstructed with adaptive statistical iterative reconstruction (ASiR). In this prospective study, enrolled patients underwent bone SPECT/CT, with 1 SPECT acquisition followed by 2 randomized CT acquisitions: FBP CT (FBP; noise index, 25) and ASiR CT (70% ASiR; noise index, 40). The image quality of both attenuation-corrected SPECT and CT images was visually (5-point Likert scale, 2 interpreters) and quantitatively (contrast ratio [CR] and signal-to-noise ratio [SNR]) estimated. The CT dose index volume, dose-length product, and effective dose were compared. Seventy-five patients were enrolled in the study. Quantitative attenuation-corrected SPECT evaluation showed no inferiority for contrast ratio and SNR issued from FBP CT or ASiR CT (respectively, 13.41 ± 7.83 vs. 13.45 ± 7.99 and 2.33 ± 0.83 vs. 2.32 ± 0.84). Qualitative image analysis showed no difference between attenuation-corrected SPECT images issued from FBP CT or ASiR CT for both interpreters (respectively, 3.5 ± 0.6 vs. 3.5 ± 0.6 and 3.6 ± 0.5 vs. 3.6 ± 0.5). Quantitative CT evaluation showed no inferiority for SNR between FBP and ASiR CT images (respectively, 0.93 ± 0.16 and 1.07 ± 0.17). Qualitative image analysis showed no quality difference between FBP and ASiR CT images for both interpreters (respectively, 3.8 ± 0.5 vs. 3.6 ± 0.5 and 4.0 ± 0.1 vs. 4.0 ± 0.2). Mean CT dose index volume, dose-length product, and effective dose for ASiR CT (3.0 ± 2.0 mGy, 148 ± 85 mGy⋅cm, and 2.2 ± 1.3 mSv) were significantly lower than for FBP CT (8.5 ± 3.7 mGy, 365 ± 160 mGy⋅cm, and 5.5 ± 2.4 mSv). The use of 70% ASiR blending in bone SPECT/CT can reduce the CT radiation dose by 60%, with no sacrifice in attenuation-corrected SPECT and CT image quality, compared with the conventional protocol using FBP CT reconstruction technique. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Intraoperative cone-beam computed tomography and multi-slice computed tomography in temporal bone imaging for surgical treatment.

PubMed

Erovic, Boban M; Chan, Harley H L; Daly, Michael J; Pothier, David D; Yu, Eugene; Coulson, Chris; Lai, Philip; Irish, Jonathan C

2014-01-01

Conventional computed tomography (CT) imaging is the standard imaging technique for temporal bone diseases, whereas cone-beam CT (CBCT) imaging is a very fast imaging tool with a significant less radiation dose compared with conventional CT. We hypothesize that a system for intraoperative cone-beam CT provides comparable image quality to diagnostic CT for identifying temporal bone anatomical landmarks in cadaveric specimens. Cross-sectional study. University tertiary care facility. Twenty cadaveric temporal bones were affixed into a head phantom and scanned with both a prototype cone-beam CT C-arm and multislice helical CT. Imaging performance was evaluated by 3 otologic surgeons and 1 head and neck radiologist. Participants were presented images in a randomized order and completed landmark identification questionnaires covering 21 structures. CBCT and multislice CT have comparable performance in identifying temporal structures. Three otologic surgeons indicated that CBCT provided statistically equivalent performance for 19 of 21 landmarks, with CBCT superior to CT for the chorda tympani and inferior for the crura of the stapes. Subgroup analysis showed that CBCT performed superiorly for temporal bone structures compared with CT. The radiologist rated CBCT and CT as statistically equivalent for 18 of 21 landmarks, with CT superior to CBCT for the crura of stapes, chorda tympani, and sigmoid sinus. CBCT provides comparable image quality to conventional CT for temporal bone anatomical sites in cadaveric specimens. Clinical applications of low-dose CBCT imaging in surgical planning, intraoperative guidance, and postoperative assessment are promising but require further investigation.

Video bioinformatics analysis of human embryonic stem cell colony growth.

PubMed

Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue

2010-05-20

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion.

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.

Physics of cardiac imaging with multiple-row detector CT.

PubMed

Mahesh, Mahadevappa; Cody, Dianna D

2007-01-01

Cardiac imaging with multiple-row detector computed tomography (CT) has become possible due to rapid advances in CT technologies. Images with high temporal and spatial resolution can be obtained with multiple-row detector CT scanners; however, the radiation dose associated with cardiac imaging is high. Understanding the physics of cardiac imaging with multiple-row detector CT scanners allows optimization of cardiac CT protocols in terms of image quality and radiation dose. Knowledge of the trade-offs between various scan parameters that affect image quality--such as temporal resolution, spatial resolution, and pitch--is the key to optimized cardiac CT protocols, which can minimize the radiation risks associated with these studies. Factors affecting temporal resolution include gantry rotation time, acquisition mode, and reconstruction method; factors affecting spatial resolution include detector size and reconstruction interval. Cardiac CT has the potential to become a reliable tool for noninvasive diagnosis and prevention of cardiac and coronary artery disease. (c) RSNA, 2007.

CT artifact recognition for the nuclear technologist.

PubMed

Popilock, Robert; Sandrasagaren, Kumar; Harris, Lowell; Kaser, Keith A

2008-06-01

The goal of this article is to make the PET/CT and SPECT/CT operator aware of common artifacts found in CT. In diagnostic imaging, the ability to render an accurate diagnosis requires the technologist to take steps to optimize image quality and recognize when image quality has been compromised-that is, when there is an image artifact. One way these artifacts occur is through the inability of the CT linear attenuation image to precisely represent the linear attenuation map of a 2-dimensional section through the body. The reasons for this inability are multifold. First, CT is subject to the laws of x-ray quantum physics resulting in noise in all CT images. Moreover, all current CT x-ray systems generate a spectrum of energies. Also, CT scanners use detectors of finite dimension, as are the x-ray focal spots; reconstruct images from a finite number of samples distributed over a finite number of views; and acquire the data for each reconstruction over a finite period.

Post-processing methods of rendering and visualizing 3-D reconstructed tomographic images

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

Wong, S.T.C.

The purpose of this presentation is to discuss the computer processing techniques of tomographic images, after they have been generated by imaging scanners, for volume visualization. Volume visualization is concerned with the representation, manipulation, and rendering of volumetric data. Since the first digital images were produced from computed tomography (CT) scanners in the mid 1970s, applications of visualization in medicine have expanded dramatically. Today, three-dimensional (3D) medical visualization has expanded from using CT data, the first inherently digital source of 3D medical data, to using data from various medical imaging modalities, including magnetic resonance scanners, positron emission scanners, digital ultrasound,more » electronic and confocal microscopy, and other medical imaging modalities. We have advanced from rendering anatomy to aid diagnosis and visualize complex anatomic structures to planning and assisting surgery and radiation treatment. New, more accurate and cost-effective procedures for clinical services and biomedical research have become possible by integrating computer graphics technology with medical images. This trend is particularly noticeable in current market-driven health care environment. For example, interventional imaging, image-guided surgery, and stereotactic and visualization techniques are now stemming into surgical practice. In this presentation, we discuss only computer-display-based approaches of volumetric medical visualization. That is, we assume that the display device available is two-dimensional (2D) in nature and all analysis of multidimensional image data is to be carried out via the 2D screen of the device. There are technologies such as holography and virtual reality that do provide a {open_quotes}true 3D screen{close_quotes}. To confine the scope, this presentation will not discuss such approaches.« less

Comparison of the Diagnostic Image Quality of the Canine Maxillary Dentoalveolar Structures Obtained by Cone Beam Computed Tomography and 64-Multidetector Row Computed Tomography

PubMed Central

Soukup, Jason W.; Drees, Randi; Koenig, Lisa J.; Snyder, Christopher J.; Hetzel, Scott; Miles, Chanda R.; Schwarz, Tobias

2016-01-01

Summary The objective of this blinded study was to validate the use of cone beam computed tomography (CT) for imaging of the canine maxillary dentoalveolar structures by comparing its diagnostic image quality with that of 64-multidetector row CT. Sagittal slices of a tooth-bearing segment of the maxilla of a commercially purchased dog skull embedded in methyl methacrylate were obtained along a line parallel with the dental arch using a commercial histology diamond saw. The slice of tooth-bearing bone that best depicted the dentoalveolar structures was chosen and photographed. The maxilla segment was imaged with cone beam CT and 64-multidetector row CT. Four blinded evaluators compared the cone beam CT and 64-multidetector row CT images and image quality was scored as it related to the anatomy of dentoalveolar structures. Trabecular bone, enamel, dentin, pulp cavity, periodontal ligament space, and lamina dura were scored. In addition, a score depicting the evaluators overall impression of the image was recorded. Images acquired with cone beam CT were found to be significantly superior in image quality to images acquired with 64-multidetector row CT overall, and in all scored categories. In our study setting, cone beam CT was found to be a valid and clinically superior imaging modality for the canine maxillary dentoalveolar structures when compared to 64-multidetector row CT. PMID:26415384

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

Synthetic Hounsfield units from spectral CT data

NASA Astrophysics Data System (ADS)

Bornefalk, Hans

2012-04-01

Beam-hardening-free synthetic images with absolute CT numbers that radiologists are used to can be constructed from spectral CT data by forming ‘dichromatic’ images after basis decomposition. The CT numbers are accurate for all tissues and the method does not require additional reconstruction. This method prevents radiologists from having to relearn new rules-of-thumb regarding absolute CT numbers for various organs and conditions as conventional CT is replaced by spectral CT. Displaying the synthetic Hounsfield unit images side-by-side with images reconstructed for optimal detectability for a certain task can ease the transition from conventional to spectral CT.

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.

Application of fluence field modulation to proton computed tomography for proton therapy imaging.

PubMed

Dedes, G; De Angelis, L; Rit, S; Hansen, D; Belka, C; Bashkirov, V; Johnson, R P; Coutrakon, G; Schubert, K E; Schulte, R W; Parodi, K; Landry, G

2017-07-12

This simulation study presents the application of fluence field modulated computed tomography, initially developed for x-ray CT, to proton computed tomography (pCT). By using pencil beam (PB) scanning, fluence modulated pCT (FMpCT) may achieve variable image quality in a pCT image and imaging dose reduction. Three virtual phantoms, a uniform cylinder and two patients, were studied using Monte Carlo simulations of an ideal list-mode pCT scanner. Regions of interest (ROI) were selected for high image quality and only PBs intercepting them preserved full fluence (FF). Image quality was investigated in terms of accuracy (mean) and noise (standard deviation) of the reconstructed proton relative stopping power compared to reference values. Dose calculation accuracy on FMpCT images was evaluated in terms of dose volume histograms (DVH), range difference (RD) for beam-eye-view (BEV) dose profiles and gamma evaluation. Pseudo FMpCT scans were created from broad beam experimental data acquired with a list-mode pCT prototype. FMpCT noise in ROIs was equivalent to FF images and accuracy better than  -1.3%(-0.7%) by using 1% of FF for the cylinder (patients). Integral imaging dose reduction of 37% and 56% was achieved for the two patients for that level of modulation. Corresponding DVHs from proton dose calculation on FMpCT images agreed to those from reference images and 96% of BEV profiles had RD below 2 mm, compared to only 1% for uniform 1% of FF. Gamma pass rates (2%, 2 mm) were 98% for FMpCT while for uniform 1% of FF they were as low as 59%. Applying FMpCT to preliminary experimental data showed that low noise levels and accuracy could be preserved in a ROI, down to 30% modulation. We have shown, using both virtual and experimental pCT scans, that FMpCT is potentially feasible and may allow a means of imaging dose reduction for a pCT scanner operating in PB scanning mode. This may be of particular importance to proton therapy given the low integral dose found outside the target.

Accuracy of volume measurement using 3D ultrasound and development of CT-3D US image fusion algorithm for prostate cancer radiotherapy.

PubMed

Baek, Jihye; Huh, Jangyoung; Kim, Myungsoo; Hyun An, So; Oh, Yoonjin; Kim, DongYoung; Chung, Kwangzoo; Cho, Sungho; Lee, Rena

2013-02-01

To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Volume measurement, using 3D US, shows a 2.8 ± 1.5% error, 4.4 ± 3.0% error for CT, and 3.1 ± 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.

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.

Diagnostic Performance of Ultrafast Brain MRI for Evaluation of Abusive Head Trauma.

PubMed

Kralik, S F; Yasrebi, M; Supakul, N; Lin, C; Netter, L G; Hicks, R A; Hibbard, R A; Ackerman, L L; Harris, M L; Ho, C Y

2017-04-01

MR imaging with sedation is commonly used to detect intracranial traumatic pathology in the pediatric population. Our purpose was to compare nonsedated ultrafast MR imaging, noncontrast head CT, and standard MR imaging for the detection of intracranial trauma in patients with potential abusive head trauma. A prospective study was performed in 24 pediatric patients who were evaluated for potential abusive head trauma. All patients received noncontrast head CT, ultrafast brain MR imaging without sedation, and standard MR imaging with general anesthesia or an immobilizer, sequentially. Two pediatric neuroradiologists independently reviewed each technique blinded to other modalities for intracranial trauma. We performed interreader agreement and consensus interpretation for standard MR imaging as the criterion standard. Diagnostic accuracy was calculated for ultrafast MR imaging, noncontrast head CT, and combined ultrafast MR imaging and noncontrast head CT. Interreader agreement was moderate for ultrafast MR imaging (κ = 0.42), substantial for noncontrast head CT (κ = 0.63), and nearly perfect for standard MR imaging (κ = 0.86). Forty-two percent of patients had discrepancies between ultrafast MR imaging and standard MR imaging, which included detection of subarachnoid hemorrhage and subdural hemorrhage. Sensitivity, specificity, and positive and negative predictive values were obtained for any traumatic pathology for each examination: ultrafast MR imaging (50%, 100%, 100%, 31%), noncontrast head CT (25%, 100%, 100%, 21%), and a combination of ultrafast MR imaging and noncontrast head CT (60%, 100%, 100%, 33%). Ultrafast MR imaging was more sensitive than noncontrast head CT for the detection of intraparenchymal hemorrhage ( P = .03), and the combination of ultrafast MR imaging and noncontrast head CT was more sensitive than noncontrast head CT alone for intracranial trauma ( P = .02). In abusive head trauma, ultrafast MR imaging, even combined with noncontrast head CT, demonstrated low sensitivity compared with standard MR imaging for intracranial traumatic pathology, which may limit its utility in this patient population. © 2017 by American Journal of Neuroradiology.

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.

In vivo 3D PIXE-micron-CT imaging of Drosophila melanogaster using a contrast agent

NASA Astrophysics Data System (ADS)

Matsuyama, Shigeo; Hamada, Naoki; Ishii, Keizo; Nozawa, Yuichiro; Ohkura, Satoru; Terakawa, Atsuki; Hatori, Yoshinobu; Fujiki, Kota; Fujiwara, Mitsuhiro; Toyama, Sho

2015-04-01

In this study, we developed a three-dimensional (3D) computed tomography (CT) in vivo imaging system for imaging small insects with micrometer resolution. The 3D CT imaging system, referred to as 3D PIXE-micron-CT (PIXEμCT), uses characteristic X-rays produced by ion microbeam bombardment of a metal target. PIXEμCT was used to observe the body organs and internal structure of a living Drosophila melanogaster. Although the organs of the thorax were clearly imaged, the digestive organs in the abdominal cavity could not be clearly discerned initially, with the exception of the rectum and the Malpighian tubule. To enhance the abdominal images, a barium sulfate powder radiocontrast agent was added. For the first time, 3D images of the ventriculus of a living D. melanogaster were obtained. Our results showed that PIXEμCT can provide in vivo 3D-CT images that reflect correctly the structure of individual living organs, which is expected to be very useful in biological research.

Neural network fusion: a novel CT-MR aortic aneurysm image segmentation method

NASA Astrophysics Data System (ADS)

Wang, Duo; Zhang, Rui; Zhu, Jin; Teng, Zhongzhao; Huang, Yuan; Spiga, Filippo; Du, Michael Hong-Fei; Gillard, Jonathan H.; Lu, Qingsheng; Liò, Pietro

2018-03-01

Medical imaging examination on patients usually involves more than one imaging modalities, such as Computed Tomography (CT), Magnetic Resonance (MR) and Positron Emission Tomography(PET) imaging. Multimodal imaging allows examiners to benefit from the advantage of each modalities. For example, for Abdominal Aortic Aneurysm, CT imaging shows calcium deposits in the aorta clearly while MR imaging distinguishes thrombus and soft tissues better.1 Analysing and segmenting both CT and MR images to combine the results will greatly help radiologists and doctors to treat the disease. In this work, we present methods on using deep neural network models to perform such multi-modal medical image segmentation. As CT image and MR image of the abdominal area cannot be well registered due to non-affine deformations, a naive approach is to train CT and MR segmentation network separately. However, such approach is time-consuming and resource-inefficient. We propose a new approach to fuse the high-level part of the CT and MR network together, hypothesizing that neurons recognizing the high level concepts of Aortic Aneurysm can be shared across multiple modalities. Such network is able to be trained end-to-end with non-registered CT and MR image using shorter training time. Moreover network fusion allows a shared representation of Aorta in both CT and MR images to be learnt. Through experiments we discovered that for parts of Aorta showing similar aneurysm conditions, their neural presentations in neural network has shorter distances. Such distances on the feature level is helpful for registering CT and MR image.

Application of oral contrast media in coregistered positron emission tomography-CT.

PubMed

Dizendorf, Elena V; Treyer, Valerie; Von Schulthess, Gustav K; Hany, Thomas F

2002-08-01

Coregistration of positron emission tomography (PET) and CT images results in significantly improved localization of abnormal FDG uptake compared with PET images alone. For delineation of intestinal structures, application of oral contrast media is a standard procedure in CT. The influence of oral contrast agents in PET imaging using CT data for attenuation correction was evaluated in a comparative study on an in-line PET-CT system. Sixty patients referred for PET-CT were evaluated in two groups. One group of 30 patients received oral Gastrografin 45 min before data acquisition. The second group received no contrast medium. PET images were reconstructed, using CT data for attenuation correction. Image analysis was performed by two reviewers in consensus, using a 4-point scale comparing FDG-uptake in the gastrointestinal tract in PET images of both groups. Furthermore, correlation of FDG uptake and localization of contrast media in the intestinal tract in CT images were determined. No significant difference in FDG uptake in PET images in all regions of the gastrointestinal tract except the ascending colon was seen in both groups. No correlation was found in the location of increased FDG uptake and contrast media in the CT images. An oral contrast agent can be used for coregistered PET-CT without the introduction of artifacts in PET.

Application of modern computer-aided technologies in the production of individual bone graft: A case report.

PubMed

Mirković, Sinisa; Budak, Igor; Puskar, Tatjana; Tadić, Ana; Sokac, Mario; Santosi, Zeljko; Djurdjević-Mirković, Tatjana

2015-12-01

An autologous bone (bone derived from the patient himself) is considered to be a "golden standard" in the treatment of bone defects and partial atrophic alveolar ridge. However, large defects and bone losses are difficult to restore in this manner, because extraction of large amounts of autologous tissue can cause donor-site problems. Alternatively, data from computed tomographic (CT) scan can be used to shape a precise 3D homologous bone block using a computer-aided design-computer-aided manufacturing (CAD-CAM) system. A 63-year old male patient referred to the Clinic of Dentistry of Vojvodina in Novi Sad, because of teeth loss in the right lateral region of the lower jaw. Clinical examination revealed a pronounced resorption of the residual ridge of the lower jaw in the aforementioned region, both horizontal and vertical. After clinical examination, the patient was referred for 3D cone beam (CB)CT scan that enables visualization of bony structures and accurate measurement of dimensions of the residual alveolar ridge. Considering the large extent of bone resorption, the required ridge augmentation was more than 3 mm in height and 2 mm in width along the length of some 2 cm, thus the use of granular material was excluded. After consulting prosthodontists and engineers from the Faculty of Technical Sciences in Novi Sad we decided to fabricate an individual (custom) bovine-derived bone graft designed according to the obtained-3D CBCT scan. Application of 3D CBCT images, computer-aided systems and software in manufacturing custom bone grafts represents the most recent method of guided bone regeneration. This method substantially reduces time of recovery and carries minimum risk of postoperative complications, yet the results fully satisfy the requirements of both the patient and the therapist.

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.

Morphology filter bank for extracting nodular and linear patterns in medical images.

PubMed

Hashimoto, Ryutaro; Uchiyama, Yoshikazu; Uchimura, Keiichi; Koutaki, Gou; Inoue, Tomoki

2017-04-01

Using image processing to extract nodular or linear shadows is a key technique of computer-aided diagnosis schemes. This study proposes a new method for extracting nodular and linear patterns of various sizes in medical images. We have developed a morphology filter bank that creates multiresolution representations of an image. Analysis bank of this filter bank produces nodular and linear patterns at each resolution level. Synthesis bank can then be used to perfectly reconstruct the original image from these decomposed patterns. Our proposed method shows better performance based on a quantitative evaluation using a synthesized image compared with a conventional method based on a Hessian matrix, often used to enhance nodular and linear patterns. In addition, experiments show that our method can be applied to the followings: (1) microcalcifications of various sizes in mammograms can be extracted, (2) blood vessels of various sizes in retinal fundus images can be extracted, and (3) thoracic CT images can be reconstructed while removing normal vessels. Our proposed method is useful for extracting nodular and linear shadows or removing normal structures in medical images.

Lung Nodule Detection via Deep Reinforcement Learning.

PubMed

Ali, Issa; Hart, Gregory R; Gunabushanam, Gowthaman; Liang, Ying; Muhammad, Wazir; Nartowt, Bradley; Kane, Michael; Ma, Xiaomei; Deng, Jun

2018-01-01

Lung cancer is the most common cause of cancer-related death globally. As a preventive measure, the United States Preventive Services Task Force (USPSTF) recommends annual screening of high risk individuals with low-dose computed tomography (CT). The resulting volume of CT scans from millions of people will pose a significant challenge for radiologists to interpret. To fill this gap, computer-aided detection (CAD) algorithms may prove to be the most promising solution. A crucial first step in the analysis of lung cancer screening results using CAD is the detection of pulmonary nodules, which may represent early-stage lung cancer. The objective of this work is to develop and validate a reinforcement learning model based on deep artificial neural networks for early detection of lung nodules in thoracic CT images. Inspired by the AlphaGo system, our deep learning algorithm takes a raw CT image as input and views it as a collection of states, and output a classification of whether a nodule is present or not. The dataset used to train our model is the LIDC/IDRI database hosted by the lung nodule analysis (LUNA) challenge. In total, there are 888 CT scans with annotations based on agreement from at least three out of four radiologists. As a result, there are 590 individuals having one or more nodules, and 298 having none. Our training results yielded an overall accuracy of 99.1% [sensitivity 99.2%, specificity 99.1%, positive predictive value (PPV) 99.1%, negative predictive value (NPV) 99.2%]. In our test, the results yielded an overall accuracy of 64.4% (sensitivity 58.9%, specificity 55.3%, PPV 54.2%, and NPV 60.0%). These early results show promise in solving the major issue of false positives in CT screening of lung nodules, and may help to save unnecessary follow-up tests and expenditures.

Lung Nodule Detection via Deep Reinforcement Learning

PubMed Central

Ali, Issa; Hart, Gregory R.; Gunabushanam, Gowthaman; Liang, Ying; Muhammad, Wazir; Nartowt, Bradley; Kane, Michael; Ma, Xiaomei; Deng, Jun

2018-01-01

Lung cancer is the most common cause of cancer-related death globally. As a preventive measure, the United States Preventive Services Task Force (USPSTF) recommends annual screening of high risk individuals with low-dose computed tomography (CT). The resulting volume of CT scans from millions of people will pose a significant challenge for radiologists to interpret. To fill this gap, computer-aided detection (CAD) algorithms may prove to be the most promising solution. A crucial first step in the analysis of lung cancer screening results using CAD is the detection of pulmonary nodules, which may represent early-stage lung cancer. The objective of this work is to develop and validate a reinforcement learning model based on deep artificial neural networks for early detection of lung nodules in thoracic CT images. Inspired by the AlphaGo system, our deep learning algorithm takes a raw CT image as input and views it as a collection of states, and output a classification of whether a nodule is present or not. The dataset used to train our model is the LIDC/IDRI database hosted by the lung nodule analysis (LUNA) challenge. In total, there are 888 CT scans with annotations based on agreement from at least three out of four radiologists. As a result, there are 590 individuals having one or more nodules, and 298 having none. Our training results yielded an overall accuracy of 99.1% [sensitivity 99.2%, specificity 99.1%, positive predictive value (PPV) 99.1%, negative predictive value (NPV) 99.2%]. In our test, the results yielded an overall accuracy of 64.4% (sensitivity 58.9%, specificity 55.3%, PPV 54.2%, and NPV 60.0%). These early results show promise in solving the major issue of false positives in CT screening of lung nodules, and may help to save unnecessary follow-up tests and expenditures. PMID:29713615

Comparison of SPECT/CT, MRI and CT in diagnosis of skull base bone invasion in nasopharyngeal carcinoma.

PubMed

Zhang, Shu-xu; Han, Peng-hui; Zhang, Guo-qian; Wang, Rui-hao; Ge, Yong-bin; Ren, Zhi-gang; Li, Jian-sheng; Fu, Wen-hai

2014-01-01

Early detection of skull base invasion in nasopharyngeal carcinoma (NPC) is crucial for correct staging, assessing treatment response and contouring the tumor target in radiotherapy planning, as well as improving the patient's prognosis. To compare the diagnostic efficacy of single photon emission computed tomography/computed tomography (SPECT/CT) imaging, magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of skull base invasion in NPC. Sixty untreated patients with histologically proven NPC underwent SPECT/CT imaging, contrast-enhanced MRI and CT. Of the 60 patients, 30 had skull base invasion confirmed by the final results of contrast-enhanced MRI, CT and six-month follow-up imaging (MRI and CT). The diagnostic efficacy of the three imaging modalities in detecting skull base invasion was evaluated. The rates of positive findings of skull base invasion for SPECT/CT, MRI and CT were 53.3%, 48.3% and 33.3%, respectively. The sensitivity, specificity and accuracy were 93.3%, 86.7% and 90.0% for SPECT/CT fusion imaging, 96.7%, 100.0% and 98.3% for contrast-enhanced MRI, and 66.7%, 100.0% and 83.3% for contrast-enhanced CT. MRI showed the best performance for the diagnosis of skull base invasion in nasopharyngeal carcinoma, followed closely by SPECT/CT. SPECT/CT had poorer specificity than that of both MRI and CT, while CT had the lowest sensitivity.

Structural Anomalies Detected in Ceramic Matrix Composites Using Combined Nondestructive Evaluation and Finite Element Analysis (NDE and FEA)

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Baaklini, George Y.; Bhatt, Ramakrishna T.

2003-01-01

Most reverse engineering approaches involve imaging or digitizing an object and then creating a computerized reconstruction that can be integrated, in three dimensions, into a particular design environment. The rapid prototyping technique builds high-quality physical prototypes directly from computer-aided design files. This fundamental technique for interpreting and interacting with large data sets is being used here via Velocity2 (an integrated image-processing software, ref. 1) using computed tomography (CT) data to produce a prototype three-dimensional test specimen model for analyses. A study at the NASA Glenn Research Center proposes to use these capabilities to conduct a combined nondestructive evaluation (NDE) and finite element analysis (FEA) to screen pretest and posttest structural anomalies in structural components. A tensile specimen made of silicon nitrite (Si3N4) ceramic matrix composite was considered to evaluate structural durability and deformity. Ceramic matrix composites are being sought as candidate materials to replace nickel-base superalloys for turbine engine applications. They have the unique characteristics of being able to withstand higher operating temperatures and harsh combustion environments. In addition, their low densities relative to metals help reduce component mass (ref. 2). Detailed three-dimensional volume rendering of the tensile test specimen was successfully carried out with Velocity2 (ref. 1) using two-dimensional images that were generated via computed tomography. Subsequent, three-dimensional finite element analyses were performed, and the results obtained were compared with those predicted by NDE-based calculations and experimental tests. It was shown that Velocity2 software can be used to render a three-dimensional object from a series of CT scan images with a minimum level of complexity. The analytical results (ref. 3) show that the high-stress regions correlated well with the damage sites identified by the CT scans and the experimental data. Furthermore, modeling of the voids collected via NDE offered an analytical advantage that resulted in more accurate assessments of the material s structural strength. The top figure shows a CT scan image of the specimen test section illustrating various hidden structural entities in the material and an optical image of the test specimen considered in this study. The bottom figure represents the stress response predicted from the finite element analyses (ref .3 ) for a selected CT slice where it clearly illustrates the correspondence of the high stress risers due to voids in the material with those predicted by the NDE. This study is continuing, and efforts are concentrated on improving the modeling capabilities to imitate the structural anomalies as detected.

TH-C-BRD-06: A Novel MRI Based CT Artifact Correction Method for Improving Proton Range Calculation in the Presence of Severe CT Artifacts

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

Park, P; Schreibmann, E; Fox, T

2014-06-15

Purpose: Severe CT artifacts can impair our ability to accurately calculate proton range thereby resulting in a clinically unacceptable treatment plan. In this work, we investigated a novel CT artifact correction method based on a coregistered MRI and investigated its ability to estimate CT HU and proton range in the presence of severe CT artifacts. Methods: The proposed method corrects corrupted CT data using a coregistered MRI to guide the mapping of CT values from a nearby artifact-free region. First patient MRI and CT images were registered using 3D deformable image registration software based on B-spline and mutual information. Themore » CT slice with severe artifacts was selected as well as a nearby slice free of artifacts (e.g. 1cm away from the artifact). The two sets of paired MRI and CT images at different slice locations were further registered by applying 2D deformable image registration. Based on the artifact free paired MRI and CT images, a comprehensive geospatial analysis was performed to predict the correct CT HU of the CT image with severe artifact. For a proof of concept, a known artifact was introduced that changed the ground truth CT HU value up to 30% and up to 5cm error in proton range. The ability of the proposed method to recover the ground truth was quantified using a selected head and neck case. Results: A significant improvement in image quality was observed visually. Our proof of concept study showed that 90% of area that had 30% errors in CT HU was corrected to 3% of its ground truth value. Furthermore, the maximum proton range error up to 5cm was reduced to 4mm error. Conclusion: MRI based CT artifact correction method can improve CT image quality and proton range calculation for patients with severe CT artifacts.« less

Somatostatin Receptor SPECT/CT using 99mTc Labeled HYNIC-TOC Aids in Diagnosis of Primary Optic Nerve Sheath Meningioma.

PubMed

Chandra, Piyush; Purandare, Nilendu; Shah, Sneha; Agrawal, Archi; Rangarajan, Venkatesh

2017-01-01

Primary optic nerve sheath meningiomas (ONSM) are rare, benign and slow growing tumor involving the intra-orbital/intra-canalicular segment of the optic nerve. Untreated, they can potentially lead to visual deterioration. Magnetic resonance (MR) is the gold standard imaging modality for diagnosing the entity. Often, a clinical dilemma exists to narrow the differential diagnosis of an enhancing intra-orbital mass on MR. Molecular imaging provides a high degree of precision in diagnosing meningioma in view of relatively high levels of somatostatin receptor expression by these tumors. The following case demonstrates the potential clinical utility of somatostatin receptor SPECT using 99m Tc- labeled HYNIC-TOC in clinical diagnosis of ONSM.

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

Evaluation of a metal artifact reduction algorithm applied to post-interventional flat detector CT in comparison to pre-treatment CT in patients with acute subarachnoid haemorrhage.

PubMed

Mennecke, Angelika; Svergun, Stanislav; Scholz, Bernhard; Royalty, Kevin; Dörfler, Arnd; Struffert, Tobias

2017-01-01

Metal artefacts can impair accurate diagnosis of haemorrhage using flat detector CT (FD-CT), especially after aneurysm coiling. Within this work we evaluate a prototype metal artefact reduction algorithm by comparison of the artefact-reduced and the non-artefact-reduced FD-CT images to pre-treatment FD-CT and multi-slice CT images. Twenty-five patients with acute aneurysmal subarachnoid haemorrhage (SAH) were selected retrospectively. FD-CT and multi-slice CT before endovascular treatment as well as FD-CT data sets after treatment were available for all patients. The algorithm was applied to post-treatment FD-CT. The effect of the algorithm was evaluated utilizing the pre-post concordance of a modified Fisher score, a subjective image quality assessment, the range of the Hounsfield units within three ROIs, and the pre-post slice-wise Pearson correlation. The pre-post concordance of the modified Fisher score, the subjective image quality, and the pre-post correlation of the ranges of the Hounsfield units were significantly higher for artefact-reduced than for non-artefact-reduced images. Within the metal-affected slices, the pre-post slice-wise Pearson correlation coefficient was higher for artefact-reduced than for non-artefact-reduced images. The overall diagnostic quality of the artefact-reduced images was improved and reached the level of the pre-interventional FD-CT images. The metal-unaffected parts of the image were not modified. • After coiling subarachnoid haemorrhage, metal artefacts seriously reduce FD-CT image quality. • This new metal artefact reduction algorithm is feasible for flat-detector CT. • After coiling, MAR is necessary for diagnostic quality of affected slices. • Slice-wise Pearson correlation is introduced to evaluate improvement of MAR in future studies. • Metal-unaffected parts of image are not modified by this MAR algorithm.

Design and fabrication of facial prostheses for cancer patient applying computer aided method and manufacturing (CADCAM)

NASA Astrophysics Data System (ADS)

Din, Tengku Noor Daimah Tengku; Jamayet, Nafij; Rajion, Zainul Ahmad; Luddin, Norhayati; Abdullah, Johari Yap; Abdullah, Abdul Manaf; Yahya, Suzana

2016-12-01

Facial defects are either congenital or caused by trauma or cancer where most of them affect the person appearance. The emotional pressure and low self-esteem are problems commonly related to patient with facial defect. To overcome this problem, silicone prosthesis was designed to cover the defect part. This study describes the techniques in designing and fabrication for facial prosthesis applying computer aided method and manufacturing (CADCAM). The steps of fabricating the facial prosthesis were based on a patient case. The patient was diagnosed for Gorlin Gotz syndrome and came to Hospital Universiti Sains Malaysia (HUSM) for prosthesis. The 3D image of the patient was reconstructed from CT data using MIMICS software. Based on the 3D image, the intercanthal and zygomatic measurements of the patient were compared with available data in the database to find the suitable nose shape. The normal nose shape for the patient was retrieved from the nasal digital library. Mirror imaging technique was used to mirror the facial part. The final design of facial prosthesis including eye, nose and cheek was superimposed to see the result virtually. After the final design was confirmed, the mould design was created. The mould of nasal prosthesis was printed using Objet 3D printer. Silicone casting was done using the 3D print mould. The final prosthesis produced from the computer aided method was acceptable to be used for facial rehabilitation to provide better quality of life.

SU-E-J-109: Accurate Contour Transfer Between Different Image Modalities Using a Hybrid Deformable Image Registration and Fuzzy Connected Image Segmentation Method.

PubMed

Yang, C; Paulson, E; Li, X

2012-06-01

To develop and evaluate a tool that can improve the accuracy of contour transfer between different image modalities under challenging conditions of low image contrast and large image deformation, comparing to a few commonly used methods, for radiation treatment planning. The software tool includes the following steps and functionalities: (1) accepting input of images of different modalities, (2) converting existing contours on reference images (e.g., MRI) into delineated volumes and adjusting the intensity within the volumes to match target images (e.g., CT) intensity distribution for enhanced similarity metric, (3) registering reference and target images using appropriate deformable registration algorithms (e.g., B-spline, demons) and generate deformed contours, (4) mapping the deformed volumes on target images, calculating mean, variance, and center of mass as the initialization parameters for consecutive fuzzy connectedness (FC) image segmentation on target images, (5) generate affinity map from FC segmentation, (6) achieving final contours by modifying the deformed contours using the affinity map with a gradient distance weighting algorithm. The tool was tested with the CT and MR images of four pancreatic cancer patients acquired at the same respiration phase to minimize motion distortion. Dice's Coefficient was calculated against direct delineation on target image. Contours generated by various methods, including rigid transfer, auto-segmentation, deformable only transfer and proposed method, were compared. Fuzzy connected image segmentation needs careful parameter initialization and user involvement. Automatic contour transfer by multi-modality deformable registration leads up to 10% of accuracy improvement over the rigid transfer. Two extra proposed steps of adjusting intensity distribution and modifying the deformed contour with affinity map improve the transfer accuracy further to 14% averagely. Deformable image registration aided by contrast adjustment and fuzzy connectedness segmentation improves the contour transfer accuracy between multi-modality images, particularly with large deformation and low image contrast. © 2012 American Association of Physicists in Medicine.

Contrast-enhanced computed tomography of the gastrointestinal tract in clinically normal alpacas and llamas.

PubMed

Stieger-Vanegas, Susanne M; Cebra, Christopher K

2013-01-15

To assess the feasibility and usefulness of CT enterography to evaluate the gastrointestinal tract in clinically normal llamas and alpacas. Prospective observational study. 7 clinically normal alpacas and 8 clinically normal llamas. The imaging protocol included orogastric administration of iodinated contrast material mixed with water. Three hours later, helical CT scanning was performed of the entire abdomen with transverse and multiplanar sagittal and dorsal projections before and after IV iodinated contrast agent injection. Both oral and IV contrast agents were well tolerated, and no adverse reactions were observed. Transverse images depicted the gastrointestinal tract and pancreas in the short axis; however, dorsal and sagittal projections aided in localizing and differentiating the various gastrointestinal segments, including the pancreas. In all camelids, the wall of the gastrointestinal tract was well differentiated. In all but 2 camelids, all gastrointestinal segments were well visualized and differentiated. In those 2 animals, the cecum was difficult to identify. Good distention of the small intestine was achieved by use of the oral contrast agent. The dorsal projections were useful to identify the pancreas in its entire length. The present study supplied new information about gastrointestinal wall thickness, intestinal diameter, and location of the pancreas and ileocecocolic junction in alpacas and llamas. Multiplanar contrast-enhanced CT was useful to reveal the various segments of the gastrointestinal tract, pancreas, and abdominal lymph nodes. The shorter time delay before imaging, compared with the delay with conventional barium studies, makes this technique complementary or superior to conventional radiographic or ultrasonographic studies for evaluation of the gastrointestinal tract.

Pulmonary nodules: effect of adaptive statistical iterative reconstruction (ASIR) technique on performance of a computer-aided detection (CAD) system-comparison of performance between different-dose CT scans.

PubMed

Yanagawa, Masahiro; Honda, Osamu; Kikuyama, Ayano; Gyobu, Tomoko; Sumikawa, Hiromitsu; Koyama, Mitsuhiro; Tomiyama, Noriyuki

2012-10-01

To evaluate the effects of ASIR on CAD system of pulmonary nodules using clinical routine-dose CT and lower-dose CT. Thirty-five patients (body mass index, 22.17 ± 4.37 kg/m(2)) were scanned by multidetector-row CT with tube currents (clinical routine-dose CT, automatically adjusted mA; lower-dose CT, 10 mA) and X-ray voltage (120 kVp). Each 0.625-mm-thick image was reconstructed at 0%-, 50%-, and 100%-ASIR: 0%-ASIR is reconstructed using only the filtered back-projection algorithm (FBP), while 100%-ASIR is reconstructed using the maximum ASIR and 50%-ASIR implies a blending of 50% FBP and ASIR. CAD output was compared retrospectively with the results of the reference standard which was established using a consensus panel of three radiologists. Data were analyzed using Bonferroni/Dunn's method. Radiation dose was calculated by multiplying dose-length product by conversion coefficient of 0.021. The consensus panel found 265 non-calcified nodules ≤ 30 mm (ground-glass opacity [GGO], 103; part-solid, 34; and solid, 128). CAD sensitivity was significantly higher at 100%-ASIR [clinical routine-dose CT, 71% (overall), 49% (GGO); lower-dose CT, 52% (overall), 67% (solid)] than at 0%-ASIR [clinical routine-dose CT, 54% (overall), 25% (GGO); lower-dose CT, 36% (overall), 50% (solid)] (p<0.001). Mean number of false-positive findings per examination was significantly higher at 100%-ASIR (clinical routine-dose CT, 8.5; lower-dose CT, 6.2) than at 0%-ASIR (clinical routine-dose CT, 4.6; lower-dose CT, 3.5; p<0.001). Effective doses were 10.77 ± 3.41 mSv in clinical routine-dose CT and 2.67 ± 0.17 mSv in lower-dose CT. CAD sensitivity at 100%-ASIR on lower-dose CT is almost equal to that at 0%-ASIR on clinical routine-dose CT. ASIR can increase CAD sensitivity despite increased false-positive findings. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Phase-contrast x-ray computed tomography for observing biological specimens and organic materials

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

1995-02-01

A novel three-dimensional x-ray imaging method has been developed by combining a phase-contrast x-ray imaging technique with x-ray computed tomography. This phase-contrast x-ray computed tomography (PCX-CT) provides sectional images of organic specimens that would produce absorption-contrast x-ray CT images with little contrast. Comparing PCX-CT images of rat cerebellum and cancerous rabbit liver specimens with corresponding absorption-contrast CT images shows that PCX-CT is much more sensitive to the internal structure of organic specimens.

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

Evaluation of image registration in PET/CT of the liver and recommendations for optimized imaging.

PubMed

Vogel, Wouter V; van Dalen, Jorn A; Wiering, Bas; Huisman, Henkjan; Corstens, Frans H M; Ruers, Theo J M; Oyen, Wim J G

2007-06-01

Multimodality PET/CT of the liver can be performed with an integrated (hybrid) PET/CT scanner or with software fusion of dedicated PET and CT. Accurate anatomic correlation and good image quality of both modalities are important prerequisites, regardless of the applied method. Registration accuracy is influenced by breathing motion differences on PET and CT, which may also have impact on (attenuation correction-related) artifacts, especially in the upper abdomen. The impact of these issues was evaluated for both hybrid PET/CT and software fusion, focused on imaging of the liver. Thirty patients underwent hybrid PET/CT, 20 with CT during expiration breath-hold (EB) and 10 with CT during free breathing (FB). Ten additional patients underwent software fusion of dedicated PET and dedicated expiration breath-hold CT (SF). The image registration accuracy was evaluated at the location of liver borders on CT and uncorrected PET images and at the location of liver lesions. Attenuation-correction artifacts were evaluated by comparison of liver borders on uncorrected and attenuation-corrected PET images. CT images were evaluated for the presence of breathing artifacts. In EB, 40% of patients had an absolute registration error of the diaphragm in the craniocaudal direction of >1 cm (range, -16 to 44 mm), and 45% of lesions were mispositioned >1 cm. In 50% of cases, attenuation-correction artifacts caused a deformation of the liver dome on PET of >1 cm. Poor compliance to breath-hold instructions caused CT artifacts in 55% of cases. In FB, 30% had registration errors of >1 cm (range, -4 to 16 mm) and PET artifacts were less extensive, but all CT images had breathing artifacts. As SF allows independent alignment of PET and CT, no registration errors or artifacts of >1 cm of the diaphragm occurred. Hybrid PET/CT of the liver may have significant registration errors and artifacts related to breathing motion. The extent of these issues depends on the selected breathing protocol and the speed of the CT scanner. No protocol or scanner can guarantee perfect image fusion. On the basis of these findings, recommendations were formulated with regard to scanner requirements, breathing protocols, and reporting.

Thoracic-abdominal imaging with a novel dual-layer spectral detector CT: intra-individual comparison of image quality and radiation dose with 128-row single-energy acquisition.

PubMed

Haneder, Stefan; Siedek, Florian; Doerner, Jonas; Pahn, Gregor; Grosse Hokamp, Nils; Maintz, David; Wybranski, Christian

2018-01-01

Background A novel, multi-energy, dual-layer spectral detector computed tomography (SDCT) is commercially available now with the vendor's claim that it yields the same or better quality of polychromatic, conventional CT images like modern single-energy CT scanners without any radiation dose penalty. Purpose To intra-individually compare the quality of conventional polychromatic CT images acquired with a dual-layer spectral detector (SDCT) and the latest generation 128-row single-energy-detector (CT128) from the same manufacturer. Material and Methods Fifty patients underwent portal-venous phase, thoracic-abdominal CT scans with the SDCT and prior CT128 imaging. The SDCT scanning protocol was adapted to yield a similar estimated dose length product (DLP) as the CT128. Patient dose optimization by automatic tube current modulation and CT image reconstruction with a state-of-the-art iterative algorithm were identical on both scanners. CT image contrast-to-noise ratio (CNR) was compared between the SDCT and CT128 in different anatomic structures. Image quality and noise were assessed independently by two readers with 5-point-Likert-scales. Volume CT dose index (CTDI vol ), and DLP were recorded and normalized to 68 cm acquisition length (DLP 68 ). Results The SDCT yielded higher mean CNR values of 30.0% ± 2.0% (26.4-32.5%) in all anatomic structures ( P < 0.001) and excellent scores for qualitative parameters surpassing the CT128 (all P < 0.0001) with substantial inter-rater agreement (κ ≥ 0.801). Despite adapted scan protocols the SDCT yielded lower values for CTDI vol (-10.1 ± 12.8%), DLP (-13.1 ± 13.9%), and DLP 68 (-15.3 ± 16.9%) than the CT128 (all P < 0.0001). Conclusion The SDCT scanner yielded better CT image quality compared to the CT128 and lower radiation dose parameters.

High dose microCT does not contribute towards improved microPET/CT image quantitative accuracy and can limit longitudinal scanning of small animals

NASA Astrophysics Data System (ADS)

McDougald, Wendy A.; Collins, Richard; Green, Mark; Tavares, Adriana A. S.

2017-10-01

Obtaining accurate quantitative measurements in preclinical Positron Emission Tomography/Computed Tomography (PET/CT) imaging is of paramount importance in biomedical research and helps supporting efficient translation of preclinical results to the clinic. The purpose of this study was two-fold: (1) to investigate the effects of different CT acquisition protocols on PET/CT image quality and data quantification; and (2) to evaluate the absorbed dose associated with varying CT parameters. Methods: An air/water quality control CT phantom, tissue equivalent material phantom, an in-house 3D printed phantom and an image quality PET/CT phantom were imaged using a Mediso nanoPET/CT scanner. Collected data was analyzed using PMOD software, VivoQuant software and National Electric Manufactures Association (NEMA) software implemented by Mediso. Measured Hounsfield Unit (HU) in collected CT images were compared to the known HU values and image noise was quantified. PET recovery coefficients (RC), uniformity and quantitative bias were also measured. Results: Only less than 2% and 1% of CT acquisition protocols yielded water HU values < -80 and air HU values < -840, respectively. Four out of eleven CT protocols resulted in more than 100 mGy absorbed dose. Different CT protocols did not impact PET uniformity and RC, and resulted in <4% overall bias relative to expected radioactive concentration. Conclusion: Preclinical CT protocols with increased exposure times can result in high absorbed doses to the small animals. These should be avoided, as they do not contributed towards improved microPET/CT image quantitative accuracy and could limit longitudinal scanning of small animals.

Time-resolved computed tomography of the liver: retrospective, multi-phase image reconstruction derived from volumetric perfusion imaging.

PubMed

Fischer, Michael A; Leidner, Bertil; Kartalis, Nikolaos; Svensson, Anders; Aspelin, Peter; Albiin, Nils; Brismar, Torkel B

2014-01-01

To assess feasibility and image quality (IQ) of a new post-processing algorithm for retrospective extraction of an optimised multi-phase CT (time-resolved CT) of the liver from volumetric perfusion imaging. Sixteen patients underwent clinically indicated perfusion CT using 4D spiral mode of dual-source 128-slice CT. Three image sets were reconstructed: motion-corrected and noise-reduced (MCNR) images derived from 4D raw data; maximum and average intensity projections (time MIP/AVG) of the arterial/portal/portal-venous phases and all phases (total MIP/ AVG) derived from retrospective fusion of dedicated MCNR split series. Two readers assessed the IQ, detection rate and evaluation time; one reader assessed image noise and lesion-to-liver contrast. Time-resolved CT was feasible in all patients. Each post-processing step yielded a significant reduction of image noise and evaluation time, maintaining lesion-to-liver contrast. Time MIPs/AVGs showed the highest overall IQ without relevant motion artefacts and best depiction of arterial and portal/portal-venous phases respectively. Time MIPs demonstrated a significantly higher detection rate for arterialised liver lesions than total MIPs/AVGs and the raw data series. Time-resolved CT allows data from volumetric perfusion imaging to be condensed into an optimised multi-phase liver CT, yielding a superior IQ and higher detection rate for arterialised liver lesions than the raw data series. • Four-dimensional computed tomography is limited by motion artefacts and poor image quality. • Time-resolved-CT facilitates 4D-CT data visualisation, segmentation and analysis by condensing raw data. • Time-resolved CT demonstrates better image quality than raw data images. • Time-resolved CT improves detection of arterialised liver lesions in cirrhotic patients.

Computer-aided diagnosis in radiological imaging: current status and future challenges

NASA Astrophysics Data System (ADS)

Doi, Kunio

2009-10-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. Many different types of CAD schemes are being developed for detection and/or characterization of various lesions in medical imaging, including conventional projection radiography, CT, MRI, and ultrasound imaging. Commercial systems for detection of breast lesions on mammograms have been developed and have received FDA approval for clinical use. CAD may be defined as a diagnosis made by a physician who takes into account the computer output as a "second opinion". The purpose of CAD is to improve the quality and productivity of physicians in their interpretation of radiologic images. The quality of their work can be improved in terms of the accuracy and consistency of their radiologic diagnoses. In addition, the productivity of radiologists is expected to be improved by a reduction in the time required for their image readings. The computer output is derived from quantitative analysis of radiologic images by use of various methods and techniques in computer vision, artificial intelligence, and artificial neural networks (ANNs). The computer output may indicate a number of important parameters, for example, the locations of potential lesions such as lung cancer and breast cancer, the likelihood of malignancy of detected lesions, and the likelihood of various diseases based on differential diagnosis in a given image and clinical parameters. In this review article, the basic concept of CAD is first defined, and the current status of CAD research is then described. In addition, the potential of CAD in the future is discussed and predicted.

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.

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

PubMed

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

Implementation of combined SVM-algorithm and computer-aided perception feedback for pulmonary nodule detection

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Rannou, Didier; Brennan, Patrick C.

2012-02-01

This pilot study examines the effect of a novel decision support system in medical image interpretation. This system is based on combining image spatial frequency properties and eye-tracking data in order to recognize over and under calling errors. Thus, before it can be implemented as a detection aided schema, training is required during which SVMbased algorithm learns to recognize FP from all reported outcomes, and, FN from all unreported prolonged dwelled regions. Eight radiologists inspected 50 PA chest radiographs with the specific task of identifying lung nodules. Twentyfive cases contained CT proven subtle malignant lesions (5-20mm), but prevalence was not known by the subjects, who took part in two sequential reading sessions, the second, without and with support system feedback. MCMR ROC DBM and JAFROC analyses were conducted and demonstrated significantly higher scores following feedback with p values of 0.04, and 0.03 respectively, highlighting significant improvements in radiology performance once feedback was used. This positive effect on radiologists' performance might have important implications for future CAD-system development.

[The application of computer aided design and computer aided engineering technique in separation of Pygopagus conjoined twins].

PubMed

Zhang, Zhi-cheng; Sun, Tian-sheng; Li, Fang; Tang, Guo-lin

2009-05-19

To explore the effect of CAD and CAE related technique in separation of Pygopagus Conjoined Twins. CT images of Pygopagus conjoined twins were obtained and reconstructed in three-dimensional by Mimics software. 3D entity model of skin and spine of conjoined twins were made by fast plastic technique and equipment according to 3D data model. The circumference and area of fused and independent dural sac were measured by software of AutoCAD. The entity model is real reflection of skin and spine of Pygopagus. It was used in the procedures of discussion, sham operation, skin flap design and informed consent. In the measure of MRI, the circumference and area of fused dural sac was more than of independent dural sac, that is to say, the defect of dural sac can be repaired by direct suture. The intraoperative finding match with imaging measure results. The application of CAD and CAE in the procedure of preoperative plan have gave big help to successful separation of Pygopagus Conjoined Twins.

Radiation dose reduction through combining positron emission tomography/computed tomography (PET/CT) and diagnostic CT in children and young adults with lymphoma.

PubMed

Qi, Zhihua; Gates, Erica L; O'Brien, Maureen M; Trout, Andrew T

2018-02-01

Both [F-18]2-fluoro-2-deoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) and diagnostic CT are at times required for lymphoma staging. This means some body segments are exposed twice to X-rays for generation of CT data (diagnostic CT + localization CT). To describe a combined PET/diagnostic CT approach that modulates CT tube current along the z-axis, providing diagnostic CT of some body segments and localization CT of the remaining body segments, thereby reducing patient radiation dose. We retrospectively compared total patient radiation dose between combined PET/diagnostic CT and separately acquired PET/CT and diagnostic CT exams. When available, we calculated effective doses for both approaches in the same patient; otherwise, we used data from patients of similar size. To confirm image quality, we compared image noise (Hounsfield unit [HU] standard deviation) as measured in the liver on both combined and separately acquired diagnostic CT images. We used t-tests for dose comparisons and two one-sided tests for image-quality equivalence testing. Mean total effective dose for the CT component of the combined and separately acquired diagnostic CT exams were 6.20±2.69 and 8.17±2.61 mSv, respectively (P<0.0001). Average dose savings with the combined approach was 24.8±17.8% (2.60±2.51 mSv [range: 0.32-4.72 mSv]) of total CT effective dose. Image noise was not statistically significantly different between approaches (12.2±1.8 HU vs. 11.7±1.5 HU for the combined and separately acquired diagnostic CT images, respectively). A combined PET/diagnostic CT approach as described offers dose savings at similar image quality for children and young adults with lymphoma who have indications for both PET and diagnostic CT examinations.

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

Comparison of the Diagnostic Image Quality of the Canine Maxillary Dentoalveolar Structures Obtained by Cone Beam Computed Tomography and 64-Multidetector Row Computed Tomography.

PubMed

Soukup, Jason W; Drees, Randi; Koenig, Lisa J; Snyder, Christopher J; Hetzel, Scott; Miles, Chanda R; Schwarz, Tobias

2015-01-01

The objective of this blinded study was to validate the use of cone beam computed tomography (C) for imaging of the canine maxillary dentoalveolar structures by comparing its diagnostic image quality with that of 64-multidetector row CT Sagittal slices of a tooth-bearing segment of the maxilla of a commercially purchased dog skull embedded in methylmethacrylate were obtained along a line parallel with the dental arch using a commercial histology diamond saw. The slice of tooth-bearing bone that best depicted the dentoalveolar structures was chosen and photographed. The maxillary segment was imaged with cone beam CT and 64-multidetector row CT. Four blinded evaluators compared the cone beam CT and 64-multidetector row CT images and image quality was scored as it related to the anatomy of dentoalveolar structures. Trabecular bone, enamel, dentin, pulp cavity, periodontal ligament space, and lamina dura were scored In addition, a score depicting the evaluators overall impression of the image was recorded. Images acquired with cone beam CT were found to be significantly superior in image quality to images acquired with 64-multidetector row CT overall, and in all scored categories. In our study setting cone beam CT was found to be a valid and clinically superior imaging modality for the canine maxillary dentoalveolar structures when compared to 64-multidetector row CT.

Can CT imaging of the chest, abdomen, and pelvis identify all vertebral injuries of the thoracolumbar spine without dedicated reformatting?

PubMed

Imran, Jonathan B; Madni, Tarik D; Pruitt, Jeffrey H; Cornelius, Canon; Subramanian, Madhu; Clark, Audra T; Mokdad, Ali A; Rizk, Paul; Minei, Joseph P; Cripps, Michael W; Eastman, Alexander L

2018-07-01

The main objective of this study was to compare detection rates of clinically significant thoracolumbar spine (TLS) fracture between computed tomography (CT) imaging of the chest, abdomen, and spine (CT CAP) and CT for the thoracolumbar spine (CT TL). We retrospectively identified patients at our institution with a TLS fracture over a two-year period that had both CT CAP and reformatted CT TL imaging. The sensitivity of CT CAP to identify fracture was calculated for each fracture type. A total of 516 TLS fractures were identified in 125 patients using reformatted CT TL spine imaging. Overall, 69 of 512 fractures (13%) were missed on CT CAP that were identified on CT TL. Of those, there were no clinically significant missed fractures. CT CAP could potentially be used as a screening tool for clinically significant TLS injuries. Copyright © 2017 Elsevier Inc. All rights reserved.

Automatic lesion tracking for a PET/CT based computer aided cancer therapy monitoring system

NASA Astrophysics Data System (ADS)

Opfer, Roland; Brenner, Winfried; Carlsen, Ingwer; Renisch, Steffen; Sabczynski, Jörg; Wiemker, Rafael

2008-03-01

Response assessment of cancer therapy is a crucial component towards a more effective and patient individualized cancer therapy. Integrated PET/CT systems provide the opportunity to combine morphologic with functional information. However, dealing simultaneously with several PET/CT scans poses a serious workflow problem. It can be a difficult and tedious task to extract response criteria based upon an integrated analysis of PET and CT images and to track these criteria over time. In order to improve the workflow for serial analysis of PET/CT scans we introduce in this paper a fast lesion tracking algorithm. We combine a global multi-resolution rigid registration algorithm with a local block matching and a local region growing algorithm. Whenever the user clicks on a lesion in the base-line PET scan the course of standardized uptake values (SUV) is automatically identified and shown to the user as a graph plot. We have validated our method by a data collection from 7 patients. Each patient underwent two or three PET/CT scans during the course of a cancer therapy. An experienced nuclear medicine physician manually measured the courses of the maximum SUVs for altogether 18 lesions. As a result we obtained that the automatic detection of the corresponding lesions resulted in SUV measurements which are nearly identical to the manually measured SUVs. Between 38 measured maximum SUVs derived from manual and automatic detected lesions we observed a correlation of 0.9994 and a average error of 0.4 SUV units.

Evaluation of the impact of metal artifacts in CT-based attenuation correction of positron emission tomography scans

NASA Astrophysics Data System (ADS)

Wu, Jay; Shih, Cheng-Ting; Chang, Shu-Jun; Huang, Tzung-Chi; Chen, Chuan-Lin; Wu, Tung Hsin

2011-08-01

The quantitative ability of PET/CT allows the widespread use in clinical research and cancer staging. However, metal artifacts induced by high-density metal objects degrade the quality of CT images. These artifacts also propagate to the corresponding PET image and cause a false increase of 18F-FDG uptake near the metal implants when the CT-based attenuation correction (AC) is performed. In this study, we applied a model-based metal artifact reduction (MAR) algorithm to reduce the dark and bright streaks in the CT image and compared the differences between PET images with the general CT-based AC (G-AC) and the MAR-corrected-CT AC (MAR-AC). Results showed that the MAR algorithm effectively reduced the metal artifacts in the CT images of the ACR flangeless phantom and two clinical cases. The MAR-AC also removed the false-positive hot spot near the metal implants of the PET images. We conclude that the MAR-AC could be applied in clinical practice to improve the quantitative accuracy of PET images. Additionally, further use of PET/CT fusion images with metal artifact correction could be more valuable for diagnosis.

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.

Dual-Energy CT: New Horizon in Medical Imaging

PubMed Central

Goo, Jin Mo

2017-01-01

Dual-energy CT has remained underutilized over the past decade probably due to a cumbersome workflow issue and current technical limitations. Clinical radiologists should be made aware of the potential clinical benefits of dual-energy CT over single-energy CT. To accomplish this aim, the basic principle, current acquisition methods with advantages and disadvantages, and various material-specific imaging methods as clinical applications of dual-energy CT should be addressed in detail. Current dual-energy CT acquisition methods include dual tubes with or without beam filtration, rapid voltage switching, dual-layer detector, split filter technique, and sequential scanning. Dual-energy material-specific imaging methods include virtual monoenergetic or monochromatic imaging, effective atomic number map, virtual non-contrast or unenhanced imaging, virtual non-calcium imaging, iodine map, inhaled xenon map, uric acid imaging, automatic bone removal, and lung vessels analysis. In this review, we focus on dual-energy CT imaging including related issues of radiation exposure to patients, scanning and post-processing options, and potential clinical benefits mainly to improve the understanding of clinical radiologists and thus, expand the clinical use of dual-energy CT; in addition, we briefly describe the current technical limitations of dual-energy CT and the current developments of photon-counting detector. PMID:28670151

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

[Registration technology for mandibular angle osteotomy based on augmented reality].

PubMed

Zhu, Ming; Chai, Gang; Zhang, Yan; Ma, Xiao-Fei; Yu, Zhe-Yuan; Zhu, Yi-Jia

2010-12-01

To establish an effective path to register the operative plan to the real model of mandible made by rapid prototyping (RP) technology. Computerize tomography (CT) was performed on 20 patients to create 3D images, and computer aided operation planning information can be merged with the 3D images. Then dental cast was used to fix the signal which can be recognized by the software. The dental cast was transformed to 3D data with a laser scanner and a programmer that run on a personal computer named Rapidform matching the dental cast and the mandible image to generate the virtual image. Then the registration was achieved by video monitoring system. By using this technology, the virtual image of mandible and the cutting planes both can overlay the real model of mandible made by RP. This study found an effective way for registration by using dental cast, and this way might be a powerful option for the registration of augmented reality. Supported by Program for Innovation Research Team of Shanghai Municipal Education Commission.

Optimising μCT imaging of the middle and inner cat ear.

PubMed

Seifert, H; Röher, U; Staszyk, C; Angrisani, N; Dziuba, D; Meyer-Lindenberg, A

2012-04-01

This study's aim was to determine the optimal scan parameters for imaging the middle and inner ear of the cat with micro-computertomography (μCT). Besides, the study set out to assess whether adequate image quality can be obtained to use μCT in diagnostics and research on cat ears. For optimisation, μCT imaging of two cat skull preparations was performed using 36 different scanning protocols. The μCT-scans were evaluated by four experienced experts with regard to the image quality and detail detectability. By compiling a ranking of the results, the best possible scan parameters could be determined. From a third cat's skull, a μCT-scan, using these optimised scan parameters, and a comparative clinical CT-scan were acquired. Afterwards, histological specimens of the ears were produced which were compared to the μCT-images. The comparison shows that the osseous structures are depicted in detail. Although soft tissues cannot be differentiated, the osseous structures serve as valuable spatial orientation of relevant nerves and muscles. Clinical CT can depict many anatomical structures which can also be seen on μCT-images, but these appear a lot less sharp and also less detailed than with μCT. © 2011 Blackwell Verlag GmbH.

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

Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

NASA Astrophysics Data System (ADS)

McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

2006-03-01

To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the spatial resolution bar patterns demonstrated that the BONE (GE) and B46f (Siemens) showed higher spatial resolution compared to the STANDARD (GE) or B30f (Siemens) reconstruction algorithms typically used for routine body CT imaging. Only the sharper images were deemed clinically acceptable for the evaluation of diffuse lung disease (e.g. emphysema). Quantitative analyses of the extent of emphysema in patient data showed the percent volumes above the -950 HU threshold as 9.4% for the BONE reconstruction, 5.9% for the STANDARD reconstruction, and 4.7% for the BONE filtered images. Contrary to the practice of using standard resolution CT images for the quantitation of diffuse lung disease, these data demonstrate that a single sharp reconstruction (BONE/B46f) should be used for both the qualitative and quantitative evaluation of diffuse lung disease. The sharper reconstruction images, which are required for diagnostic interpretation, provide accurate CT numbers over the range of -1000 to +900 HU and preserve the fidelity of small structures in the reconstructed images. A filtered version of the sharper images can be accurately substituted for images reconstructed with smoother kernels for comparison to previously published results.

Synergistic Role of Newer Techniques for Forensic and Postmortem CT Examinations.

PubMed

Blum, Alain; Kolopp, Martin; Teixeira, Pedro Gondim; Stroud, Tyler; Noirtin, Philippe; Coudane, Henry; Martrille, Laurent

2018-04-30

The aim of this article is to provide an overview of newer techniques and postprocessing tools that improve the potential impact of CT in forensic situations. CT has become a standard tool in medicolegal practice. Postmortem CT is an essential aid to the pathologist during autopsies. Advances in technology and software are constantly leading to advances in its performance.

The accuracy of three-dimensional fused deposition modeling (FDM) compared with three-dimensional CT-Scans on the measurement of the mandibular ramus vertical length, gonion-menton length, and gonial angle

NASA Astrophysics Data System (ADS)

Savitri, I. T.; Badri, C.; Sulistyani, L. D.

2017-08-01

Presurgical treatment planning plays an important role in the reconstruction and correction of defects in the craniomaxillofacial region. The advance of solid freeform fabrication techniques has significantly improved the process of preparing a biomodel using computer-aided design and data from medical imaging. Many factors are implicated in the accuracy of the 3D model. To determine the accuracy of three-dimensional fused deposition modeling (FDM) models compared with three-dimensional CT scans in the measurement of the mandibular ramus vertical length, gonion-menton length, and gonial angle. Eight 3D models were produced from the CT scan data (DICOM file) of eight patients at the Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, University of Indonesia, Cipto Mangunkusumo Hospital. Three measurements were done three times by two examiners. The measurements of the 3D CT scans were made using OsiriX software, while the measurements of the 3D models were made using a digital caliper and goniometry. The measurement results were then compared. There is no significant difference between the measurements of the mandibular ramus vertical length, gonion-menton length, and gonial angle using 3D CT scans and FDM 3D models. FDM 3D models are considered accurate and are acceptable for clinical applications in dental and craniomaxillofacial surgery.

Interactive dual-volume rendering visualization with real-time fusion and transfer function enhancement

NASA Astrophysics Data System (ADS)

Macready, Hugh; Kim, Jinman; Feng, David; Cai, Weidong

2006-03-01

Dual-modality imaging scanners combining functional PET and anatomical CT constitute a challenge in volumetric visualization that can be limited by the high computational demand and expense. This study aims at providing physicians with multi-dimensional visualization tools, in order to navigate and manipulate the data running on a consumer PC. We have maximized the utilization of pixel-shader architecture of the low-cost graphic hardware and the texture-based volume rendering to provide visualization tools with high degree of interactivity. All the software was developed using OpenGL and Silicon Graphics Inc. Volumizer, tested on a Pentium mobile CPU on a PC notebook with 64M graphic memory. We render the individual modalities separately, and performing real-time per-voxel fusion. We designed a novel "alpha-spike" transfer function to interactively identify structure of interest from volume rendering of PET/CT. This works by assigning a non-linear opacity to the voxels, thus, allowing the physician to selectively eliminate or reveal information from the PET/CT volumes. As the PET and CT are rendered independently, manipulations can be applied to individual volumes, for instance, the application of transfer function to CT to reveal the lung boundary while adjusting the fusion ration between the CT and PET to enhance the contrast of a tumour region, with the resultant manipulated data sets fused together in real-time as the adjustments are made. In addition to conventional navigation and manipulation tools, such as scaling, LUT, volume slicing, and others, our strategy permits efficient visualization of PET/CT volume rendering which can potentially aid in interpretation and diagnosis.

Impact of Asynchronous Training on Radiology Learning Curve among Emergency Medicine Residents and Clerkship Students

PubMed Central

Pourmand, Ali; Woodward, Christina; Shokoohi, Hamid; King, Jordan B; Taheri, M Reza; King, Jackson; Lawrence, Christopher

2018-01-01

Context Web-based learning (WBL) modules are effectively used to improve medical education curriculum; however, they have not been evaluated to improve head computed tomography (CT) scan interpretation in an emergency medicine (EM) setting. Objective To evaluate the effectiveness of a WBL module to aid identification of cranial structures on CT and to improve ability to distinguish between normal and abnormal findings. Design Prospective, before-and-after trial in the Emergency Department of an academic center. Baseline head CT knowledge was assessed via a standardized test containing ten head CT scans, including normal scans and those showing hemorrhagic stroke, trauma, and infection (abscess). All trainees then participated in a WBL intervention. Three weeks later, they were given the same ten CT scans to evaluate in a standardized posttest. Main Outcome Measures Improvement in test scores. Results A total of 131 EM clerkship students and 32 EM residents were enrolled. Pretest scores correlated with stage of training, with students and first-year residents demonstrating the lowest scores. Overall, there was a significant improvement in percentage of correctly classified CT images after the training intervention from a mean pretest score of 32% ± 12% to posttest score of 67% ± 13% (mean improvement = 35% ± 13%, p < 0.001). Among subsets by training level, all subgroups except first-year residents demonstrated a statistically significant increase in scores after the training. Conclusion Incorporating asynchronous WBL modules into EM clerkship and residency curriculum provides early radiographic exposure in their clinical training and can enhance diagnostic head CT scan interpretation. PMID:29272248

Navigation-aided visualization of lumbosacral nerves for anterior sacroiliac plate fixation: a case report.

PubMed

Takao, Masaki; Nishii, Takashi; Sakai, Takashi; Sugano, Nobuhiko

2014-06-01

Anterior sacroiliac joint plate fixation for unstable pelvic ring fractures avoids soft tissue problems in the buttocks; however, the lumbosacral nerves lie in close proximity to the sacroiliac joint and may be injured during the procedure. A 49 year-old woman with a type C pelvic ring fracture was treated with an anterior sacroiliac plate using a computed tomography (CT)-three-dimensional (3D)-fluoroscopy matching navigation system, which visualized the lumbosacral nerves as well as the iliac and sacral bones. We used a flat panel detector 3D C-arm, which made it possible to superimpose our preoperative CT-based plan on the intra-operative 3D-fluoroscopic images. No postoperative complications were noted. Intra-operative lumbosacral nerve visualization using computer navigation was useful to recognize the 'at-risk' area for nerve injury during anterior sacroiliac plate fixation. Copyright © 2013 John Wiley & Sons, Ltd.

Toward computer-aided emphysema quantification on ultralow-dose CT: reproducibility of ventrodorsal gravity effect measurement and correction

NASA Astrophysics Data System (ADS)

Wiemker, Rafael; Opfer, Roland; Bülow, Thomas; Rogalla, Patrik; Steinberg, Amnon; Dharaiya, Ekta; Subramanyan, Krishna

2007-03-01

Computer aided quantification of emphysema in high resolution CT data is based on identifying low attenuation areas below clinically determined Hounsfield thresholds. However, the emphysema quantification is prone to error since a gravity effect can influence the mean attenuation of healthy lung parenchyma up to +/- 50 HU between ventral and dorsal lung areas. Comparing ultra-low-dose (7 mAs) and standard-dose (70 mAs) CT scans of each patient we show that measurement of the ventrodorsal gravity effect is patient specific but reproducible. It can be measured and corrected in an unsupervised way using robust fitting of a linear function.

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.

Cone Beam CT vs. Fan Beam CT: A Comparison of Image Quality and Dose Delivered Between Two Differing CT Imaging Modalities.

PubMed

Lechuga, Lawrence; Weidlich, Georg A

2016-09-12

A comparison of image quality and dose delivered between two differing computed tomography (CT) imaging modalities-fan beam and cone beam-was performed. A literature review of quantitative analyses for various image quality aspects such as uniformity, signal-to-noise ratio, artifact presence, spatial resolution, modulation transfer function (MTF), and low contrast resolution was generated. With these aspects quantified, cone beam computed tomography (CBCT) shows a superior spatial resolution to that of fan beam, while fan beam shows a greater ability to produce clear and anatomically correct images with better soft tissue differentiation. The results indicate that fan beam CT produces superior images to that of on-board imaging (OBI) cone beam CT systems, while providing a considerably less dose to the patient.

Cone Beam CT vs. Fan Beam CT: A Comparison of Image Quality and Dose Delivered Between Two Differing CT Imaging Modalities

PubMed Central

Weidlich, Georg A.

2016-01-01

A comparison of image quality and dose delivered between two differing computed tomography (CT) imaging modalities—fan beam and cone beam—was performed. A literature review of quantitative analyses for various image quality aspects such as uniformity, signal-to-noise ratio, artifact presence, spatial resolution, modulation transfer function (MTF), and low contrast resolution was generated. With these aspects quantified, cone beam computed tomography (CBCT) shows a superior spatial resolution to that of fan beam, while fan beam shows a greater ability to produce clear and anatomically correct images with better soft tissue differentiation. The results indicate that fan beam CT produces superior images to that of on-board imaging (OBI) cone beam CT systems, while providing a considerably less dose to the patient. PMID:27752404

The impact of the CartoSound® image directly acquired from the left atrium for integration in atrial fibrillation ablation.

PubMed

Kaseno, Kenichi; Hisazaki, Kaori; Nakamura, Kohki; Ikeda, Etsuko; Hasegawa, Kanae; Aoyama, Daisetsu; Shiomi, Yuichiro; Ikeda, Hiroyuki; Morishita, Tetsuji; Ishida, Kentaro; Amaya, Naoki; Uzui, Hiroyasu; Tada, Hiroshi

2018-04-14

Intracardiac echocardiographic (ICE) imaging might be useful for integrating three-dimensional computed tomographic (CT) images for left atrial (LA) catheter navigation during atrial fibrillation (AF) ablation. However, the optimal CT image integration method using ICE has not been established. This study included 52 AF patients who underwent successful circumferential pulmonary vein isolation (CPVI). In all patients, CT image integration was performed after the CPVI with the following two methods: (1) using ICE images of the LA derived from the right atrium and right ventricular outflow tract (RA-merge) and (2) using ICE images of the LA directly derived from the LA added to the image for the RA-merge (LA-merge). The accuracy of these two methods was assessed by the distances between the integrated CT image and ICE image (ICE-to-CT distance), and between the CT image and actual ablated sites for the CPVI (CT-to-ABL distance). The mean ICE-to-CT distance was comparable between the two methods (RA-merge = 1.6 ± 0.5 mm, LA-merge = 1.7 ± 0.4 mm; p = 0.33). However, the mean CT-to-ABL distance was shorter for the LA-merge (2.1 ± 0.6 mm) than RA-merge (2.5 ± 0.8 mm; p < 0.01). The LA, especially the left-sided PVs and LA roof, was more sharply delineated by direct LA imaging, and whereas the greatest CT-to-ABL distance was observed at the roof portion of the left superior PV (3.7 ± 2.8 mm) after the RA-merge, it improved to 2.6 ± 1.9 mm after the LA-merge (p < 0.01). Additional ICE images of the LA directly acquired from the LA might lead to a greater accuracy of the CT image integration for the CVPI.

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.

Dental flat panel conebeam CT in the evaluation of patients with inflammatory sinonasal disease: Diagnostic efficacy and radiation dose savings.

PubMed

Leiva-Salinas, C; Flors, L; Gras, P; Más-Estellés, F; Lemercier, P; Patrie, J T; Wintermark, M; Martí-Bonmatí, L

2014-01-01

CT is the imaging modality of choice to study the paranasal sinuses; unfortunately, it involves significant radiation dose. Our aim was to assess the diagnostic validity, image quality, and radiation-dose savings of dental conebeam CT in the evaluation of patients with suspected inflammatory disorders of the paranasal sinuses. We prospectively studied 40 patients with suspected inflammatory disorders of the sinuses with dental conebeam CT and standard CT. Two radiologists analyzed the images independently, blinded to clinical information. The image quality of both techniques and the diagnostic validity of dental conebeam CT compared with the reference standard CT were assessed by using 3 different scoring systems. Image noise, signal-to-noise ratio, and contrast-to-noise ratio were calculated for both techniques. The absorbed radiation dose to the lenses and thyroid and parotid glands was measured by using a phantom and dosimeter chips. The effective radiation dose for CT was calculated. All dental conebeam CT scans were judged of diagnostic quality. Compared with CT, the conebeam CT image noise was 37.3% higher (P < .001) and the SNR of the bone was 75% lower (P < .001). The effective dose of our conebeam CT protocol was 23 μSv. Compared with CT, the absorbed radiation dose to the lenses and parotid and thyroid glands with conebeam CT was 4%, 7.8%, and 7.3% of the dose delivered to the same organs by conventional CT (P < .001). Dental conebeam CT is a valid imaging procedure for the evaluation of patients with inflammatory sinonasal disorders. © 2014 by American Journal of Neuroradiology.

Cine Computed Tomography Without Respiratory Surrogate in Planning Stereotactic Radiotherapy for Non-Small-Cell Lung Cancer

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

Riegel, Adam C. B.A.; Chang, Joe Y.; Vedam, Sastry S.

2009-02-01

Purpose: To determine whether cine computed tomography (CT) can serve as an alternative to four-dimensional (4D)-CT by providing tumor motion information and producing equivalent target volumes when used to contour in radiotherapy planning without a respiratory surrogate. Methods and Materials: Cine CT images from a commercial CT scanner were used to form maximum intensity projection and respiratory-averaged CT image sets. These image sets then were used together to define the targets for radiotherapy. Phantoms oscillating under irregular motion were used to assess the differences between contouring using cine CT and 4D-CT. We also retrospectively reviewed the image sets for 26more » patients (27 lesions) at our institution who had undergone stereotactic radiotherapy for Stage I non-small-cell lung cancer. The patients were included if the tumor motion was >1 cm. The lesions were first contoured using maximum intensity projection and respiratory-averaged CT image sets processed from cine CT and then with 4D-CT maximum intensity projection and 10-phase image sets. The mean ratios of the volume magnitude were compared with intraobserver variation, the mean centroid shifts were calculated, and the volume overlap was assessed with the normalized Dice similarity coefficient index. Results: The phantom studies demonstrated that cine CT captured a greater extent of irregular tumor motion than did 4D-CT, producing a larger tumor volume. The patient studies demonstrated that the gross tumor defined using cine CT imaging was similar to, or slightly larger than, that defined using 4D-CT. Conclusion: The results of our study have shown that cine CT is a promising alternative to 4D-CT for stereotactic radiotherapy planning.« less

TU-AB-BRA-10: Prognostic Value of Intra-Radiation Treatment FDG-PET and CT Imaging Features in Locally Advanced Head and Neck Cancer

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

Song, J; Pollom, E; Durkee, B

2015-06-15

Purpose: To predict response to radiation treatment using computational FDG-PET and CT images in locally advanced head and neck cancer (HNC). Methods: 68 patients with State III-IVB HNC treated with chemoradiation were included in this retrospective study. For each patient, we analyzed primary tumor and lymph nodes on PET and CT scans acquired both prior to and during radiation treatment, which led to 8 combinations of image datasets. From each image set, we extracted high-throughput, radiomic features of the following types: statistical, morphological, textural, histogram, and wavelet, resulting in a total of 437 features. We then performed unsupervised redundancy removalmore » and stability test on these features. To avoid over-fitting, we trained a logistic regression model with simultaneous feature selection based on least absolute shrinkage and selection operator (LASSO). To objectively evaluate the prediction ability, we performed 5-fold cross validation (CV) with 50 random repeats of stratified bootstrapping. Feature selection and model training was solely conducted on the training set and independently validated on the holdout test set. Receiver operating characteristic (ROC) curve of the pooled Result and the area under the ROC curve (AUC) was calculated as figure of merit. Results: For predicting local-regional recurrence, our model built on pre-treatment PET of lymph nodes achieved the best performance (AUC=0.762) on 5-fold CV, which compared favorably with node volume and SUVmax (AUC=0.704 and 0.449, p<0.001). Wavelet coefficients turned out to be the most predictive features. Prediction of distant recurrence showed a similar trend, in which pre-treatment PET features of lymph nodes had the highest AUC of 0.705. Conclusion: The radiomics approach identified novel imaging features that are predictive to radiation treatment response. If prospectively validated in larger cohorts, they could aid in risk-adaptive treatment of HNC.« less

Overview of positron emission tomography chemistry: clinical and technical considerations and combination with computed tomography.

PubMed

Koukourakis, G; Maravelis, G; Koukouraki, S; Padelakos, P; Kouloulias, V

2009-01-01

The concept of emission and transmission tomography was introduced by David Kuhl and Roy Edwards in the late 1950s. Their work later led to the design and construction of several tomographic instruments at the University of Pennsylvania. Tomographic imaging techniques were further developed by Michel Ter-Pogossian, Michael E. Phelps and others at the Washington University School of Medicine. Positron emission tomography (PET) is a nuclear medicine imaging technique which produces a 3-dimensional image or map of functional processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide (tracer), which is introduced into the body on a biologically active molecule. Images of tracer concentration in 3-dimensional space within the body are then reconstructed by computer analysis. In modern scanners, this reconstruction is often accomplished with the aid of a CT X-ray scan performed on the patient during the same session, in the same machine. If the biologically active molecule chosen for PET is 18F-fluorodeoxyglucose (FDG), an analogue of glucose, the concentrations of tracer imaged give tissue metabolic activity in terms of regional glucose uptake. Although use of this tracer results in the most common type of PET scan, other tracer molecules are used in PET to image the tissue concentration of many other types of molecules of interest. The main role of this article was to analyse the available types of radiopharmaceuticals used in PET-CT along with the principles of its clinical and technical considerations.

CT image electron density quantification in regions with metal implants: implications for radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Jechel, Christopher Alexander

In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.

Automated Tracking of Quantitative Assessments of Tumor Burden in Clinical Trials1

PubMed Central

Rubin, Daniel L; Willrett, Debra; O'Connor, Martin J; Hage, Cleber; Kurtz, Camille; Moreira, Dilvan A

2014-01-01

There are two key challenges hindering effective use of quantitative assessment of imaging in cancer response assessment: 1) Radiologists usually describe the cancer lesions in imaging studies subjectively and sometimes ambiguously, and 2) it is difficult to repurpose imaging data, because lesion measurements are not recorded in a format that permits machine interpretation and interoperability. We have developed a freely available software platform on the basis of open standards, the electronic Physician Annotation Device (ePAD), to tackle these challenges in two ways. First, ePAD facilitates the radiologist in carrying out cancer lesion measurements as part of routine clinical trial image interpretation workflow. Second, ePAD records all image measurements and annotations in a data format that permits repurposing image data for analyses of alternative imaging biomarkers of treatment response. To determine the impact of ePAD on radiologist efficiency in quantitative assessment of imaging studies, a radiologist evaluated computed tomography (CT) imaging studies from 20 subjects having one baseline and three consecutive follow-up imaging studies with and without ePAD. The radiologist made measurements of target lesions in each imaging study using Response Evaluation Criteria in Solid Tumors 1.1 criteria, initially with the aid of ePAD, and then after a 30-day washout period, the exams were reread without ePAD. The mean total time required to review the images and summarize measurements of target lesions was 15% (P < .039) shorter using ePAD than without using this tool. In addition, it was possible to rapidly reanalyze the images to explore lesion cross-sectional area as an alternative imaging biomarker to linear measure. We conclude that ePAD appears promising to potentially improve reader efficiency for quantitative assessment of CT examinations, and it may enable discovery of future novel image-based biomarkers of cancer treatment response. PMID:24772204

Comparison of 68Ga-DOTANOC PET/CT and contrast-enhanced CT in localisation of tumours in ectopic ACTH syndrome

PubMed Central

Jadhav, Swati S; Lila, Anurag R; Kasaliwal, Rajeev; Khare, Shruti; Yerawar, Chaitanya G; Hira, Priya; Phadke, Uday; Shah, Hina; Lele, Vikram R; Malhotra, Gaurav; Bandgar, Tushar; Shah, Nalini S

2016-01-01

Background Localising ectopic adrenocorticotrophic hormone (ACTH) syndrome (EAS) tumour source is challenging. Somatostatin receptor-based PET imaging has shown promising results, but the data is limited to case reports and small case series. We reviewed here the performance of 68Ga-DOTANOC positron emission tomography (PET)/computed tomography (CT) and contrast-enhanced CT (CECT) in our cohort of 12 consecutive EAS patients. Materials and methods Retrospective data analysis of 12 consecutive patients of EAS presenting to a single tertiary care centre in a period between January 2013 and December 2014 was done. CECT and 68Ga-DOTANOC PET/CT were reported (blinded) by an experienced radiologist and a nuclear medicine physician, respectively. The performance of CECT and 68Ga-DOTANOC PET/CT was compared. Results Tumours could be localised in 11 out of 12 patients at initial presentation (overt cases), whereas in one patient, tumour remained occult. Thirteen lesions were identified in 11 patients as EAS source (true positives). CECT localised 12 out of these 13 lesions (sensitivity 92.3%) and identified five false-positive lesions (positive predictive value (PPV) 70.5%). Compared with false-positive lesions, true-positive lesions had greater mean contrast enhancement at 60s (33.2 vs 5.6 Hounsfield units (HU)). 68Ga-DOTANOC PET/CT was able to identify 9 out of 13 lesions (sensitivity 69.2%) and reported no false-positive lesions (PPV 100%). Conclusion CECT remains the first-line investigation in localisation of EAS. The contrast enhancement pattern on CECT can further aid in characterisation of the lesions. 68Ga-DOTANOC PET/CT can be added to CECT, to enhance positive prediction of the suggestive lesions. PMID:27006371

First-order convex feasibility algorithms for x-ray CT

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob S.; Pan, Xiaochuan

2013-01-01

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution—thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle−Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144°. The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application. PMID:23464295

Neural network and its application to CT imaging

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

Nikravesh, M.; Kovscek, A.R.; Patzek, T.W.

We present an integrated approach to imaging the progress of air displacement by spontaneous imbibition of oil into sandstone. We combine Computerized Tomography (CT) scanning and neural network image processing. The main aspects of our approach are (I) visualization of the distribution of oil and air saturation by CT, (II) interpretation of CT scans using neural networks, and (III) reconstruction of 3-D images of oil saturation from the CT scans with a neural network model. Excellent agreement between the actual images and the neural network predictions is found.

Use of the initial trauma CT scan to aid in diagnosis of open pelvic fractures.

PubMed

Scolaro, John A; Wilson, David J; Routt, Milton Lee Chip; Firoozabadi, Reza

2015-10-01

Open pelvic disruptions represent high-energy injuries. The prompt identification and management of these injuries decreases their associated morbidity and mortality. Computed tomography (CT) scans are routinely obtained in the initial evaluation of patients with pelvic injuries. The purpose of this study is to identify the incidence and source of air densities noted on computed tomography (CT) scans of the abdominal and pelvic region in patients with pelvic fractures and evaluate the use of initial CT imaging as an adjunctive diagnostic tool to identify open injuries. A retrospective review of a prospectively collected database was performed at a single institution. Seven hundred and twenty-two consecutive patients with a pelvic disruption over a two-year period were included. Review of initial injury CT scans was performed using bone and lung viewing algorithms to identify the presence of extra-luminal air. The primary outcome was the presence, location and source of air identified on pre-operative CT scans. Secondary measurements were identification of air by plain radiograph and correlation between identified air densities on CT and clinically diagnosed open pelvic fractures. Ninety-eight patients were identified as having extra-luminal air densities on CT scans. Eighty-one patients were included in the final analysis following application of inclusion and exclusion criteria. Air was noted by the radiologist in forty-five (55.6%) instances. Six patients (7.4%) were clinically diagnosed with an open pelvic ring disruption; in two patients (2.4%) this diagnosis was delayed. In all patients, the CT was able to track air from its origin. In patients with pelvic disruptions, the injury CT should also be evaluated for the presence and source of extra-luminal air. In some patients, this finding may represent an open pelvic ring disruption. A complete physical exam and CT evaluation should be used to decrease the missed or delayed diagnosis of an open pelvic ring injury. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

Combining transrectal ultrasound and CT for image-guided adaptive brachytherapy of cervical cancer: Proof of concept.

PubMed

Nesvacil, Nicole; Schmid, Maximilian P; Pötter, Richard; Kronreif, Gernot; Kirisits, Christian

To investigate the feasibility of a treatment planning workflow for three-dimensional image-guided cervix cancer brachytherapy, combining volumetric transrectal ultrasound (TRUS) for target definition with CT for dose optimization to organs at risk (OARs), for settings with no access to MRI. A workflow for TRUS/CT-based volumetric treatment planning was developed, based on a customized system including ultrasound probe, stepper unit, and software for image volume acquisition. A full TRUS/CT-based workflow was simulated in a clinical case and compared with MR- or CT-only delineation. High-risk clinical target volume was delineated on TRUS, and OARs were delineated on CT. Manually defined tandem/ring applicator positions on TRUS and CT were used as a reference for rigid registration of the image volumes. Treatment plan optimization for TRUS target and CT organ volumes was performed and compared to MRI and CT target contours. TRUS/CT-based contouring, applicator reconstruction, image fusion, and treatment planning were feasible, and the full workflow could be successfully demonstrated. The TRUS/CT plan fulfilled all clinical planning aims. Dose-volume histogram evaluation of the TRUS/CT-optimized plan (high-risk clinical target volume D 90 , OARs D 2cm³ for) on different image modalities showed good agreement between dose values reported for TRUS/CT and MRI-only reference contours and large deviations for CT-only target parameters. A TRUS/CT-based workflow for full three-dimensional image-guided cervix brachytherapy treatment planning seems feasible and may be clinically comparable to MRI-based treatment planning. Further development to solve challenges with applicator definition in the TRUS volume is required before systematic applicability of this workflow. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

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.

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

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

Ali, I; Ahmad, S; Alsbou, N

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embeddedmore » into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.« less

WE-G-207-07: Iterative CT Shading Correction Method with No Prior Information

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

Wu, P; Mao, T; Niu, T

2015-06-15

Purpose: Shading artifacts are caused by scatter contamination, beam hardening effects and other non-ideal imaging condition. Our Purpose is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT imaging (e.g., cone-beam CT, low-kVp CT) without relying on prior information. Methods: Our method applies general knowledge of the relatively uniform CT number distribution in one tissue component. Image segmentation is applied to construct template image where each structure is filled with the same CT number of that specific tissue. By subtracting the ideal template from CT image, the residual from various error sources are generated.more » Since the forward projection is an integration process, the non-continuous low-frequency shading artifacts in the image become continuous and low-frequency signals in the line integral. Residual image is thus forward projected and its line integral is filtered using Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error using standard FDK algorithm and added to the original image to obtain the shading corrected one. Since the segmentation is not accurate on shaded CT image, the proposed scheme is iterated until the variation of residual image is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT angiography scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative algorithm for shading correction in CT imaging. Being different from existing algorithms, our method is only assisted by general anatomical and physical information in CT imaging without relying on prior knowledge. Our method is thus practical and attractive as a general solution to CT shading correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less

Study of Image Quality From CT Scanner Multi-Detector by using Americans College of Radiology (ACR) Phantom

NASA Astrophysics Data System (ADS)

Mulyadin; Dewang, Syamsir; Abdullah, Bualkar; Tahir, Dahlang

2018-03-01

In this study, the image quality of CT scan using phantom American College of Radiology (ACR) was determined. Scanning multidetector CT is used to know the image quality parameters by using a solid phantom containing four modules and primarily from materials that are equivalent to water. Each module is 4 cm in diameter and 20 cm in diameter. There is white alignment marks painted white to reflect the alignment laser and there are also “HEAD”, “FOOT”, and “TOP” marks on the phantom to help align. This test obtains CT images of each module according to the routine inspection protocol of the head. Acceptance of image quality obtained for determination: CT Number Accuracy (CTN), CT Number Uniformity and Noise, Linearity CT Number, Slice Technique, Low Contrast Resolution and High Contrast Resolution represent image quality parameters. In testing CT Number Accuracy (CTN), CT Uniform number and Noise are in the range of tolerable values allowed. In the test, Linearity CT Number obtained correlation value above 0.99 is the relationship between electron density and CT Number. In a low contrast resolution test, the smallest contrast groups are visible. In contrast, the high resolution is seen up to 7 lp/cm. The quality of GE CT Scan is very high, as all the image quality tests obtained are within the tolerance brackets of values permitted by the Nuclear Power Control Agency (BAPETEN). Image quality test is a way to get very important information about the accuracy of snoring result by using phantom ACR.

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.

Imaging the Parasinus Region with a Third-Generation Dual-Source CT and the Effect of Tin Filtration on Image Quality and Radiation Dose.

PubMed

Lell, M M; May, M S; Brand, M; Eller, A; Buder, T; Hofmann, E; Uder, M; Wuest, W

2015-07-01

CT is the imaging technique of choice in the evaluation of midface trauma or inflammatory disease. We performed a systematic evaluation of scan protocols to optimize image quality and radiation exposure on third-generation dual-source CT. CT protocols with different tube voltage (70-150 kV), current (25-300 reference mAs), prefiltration, pitch value, and rotation time were systematically evaluated. All images were reconstructed with iterative reconstruction (Advanced Modeled Iterative Reconstruction, level 2). To individually compare results with otherwise identical factors, we obtained all scans on a frozen human head. Conebeam CT was performed for image quality and dose comparison with multidetector row CT. Delineation of important anatomic structures and incidental pathologic conditions in the cadaver head was evaluated. One hundred kilovolts with tin prefiltration demonstrated the best compromise between dose and image quality. The most dose-effective combination for trauma imaging was Sn100 kV/250 mAs (volume CT dose index, 2.02 mGy), and for preoperative sinus surgery planning, Sn100 kV/150 mAs (volume CT dose index, 1.22 mGy). "Sn" indicates an additional prefiltration of the x-ray beam with a tin filter to constrict the energy spectrum. Exclusion of sinonasal disease was possible with even a lower dose by using Sn100 kV/25 mAs (volume CT dose index, 0.2 mGy). High image quality at very low dose levels can be achieved by using a Sn100-kV protocol with iterative reconstruction. The effective dose is comparable with that of conventional radiography, and the high image quality at even lower radiation exposure favors multidetector row CT over conebeam CT. © 2015 by American Journal of Neuroradiology.

Pseudo CT estimation from MRI using patch-based random forest

NASA Astrophysics Data System (ADS)

Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian

2017-02-01

Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.

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.

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.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2008-09-01

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 CT 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.

Nondestructive Evaluation of Hardwood Logs Using Automated Interpretation of CT Images

Treesearch

Daniel L. Schmoldt; Dongping Zhu; Richard W. Conners

1993-01-01

Computed tomography (CT) imaging is being used to examine the internal structure of hardwood logs. The following steps are used to automatically interpret CT images: (1) preprocessing to remove unwanted portions of the image, e.g., annual ring structure, (2) image-by-image segmentation to produce relatively homogeneous image areas, (3) volume growing to create volumes...

Maxillary sinus marrow hyperplasia in sickle cell anemia.

PubMed

Fernandez, M; Slovis, T L; Whitten-Shurney, W

1995-11-01

Marrow hyperplasia is a sequela of sickle cell anemia (SCA) and may be seen in the skull in children after 5 years of age [1]. The facial bones, except for the mandible and orbits, are usually not involved [1-3]. We report an unusual case of a 28-month-old black boy with SCA who presented with extensive marrow hyperplasia of the maxillary sinuses in addition to severe calvarial and mandibular changes. The imaging characteristics on CT (similar to other sites of marrow hyperplasia) and MR (low signal on both T1 and T2 sequences) should aid in making the correct diagnosis.

Automated extraction method for the center line of spinal canal and its application to the spinal curvature quantification in torso X-ray CT images

NASA Astrophysics Data System (ADS)

Hayashi, Tatsuro; Zhou, Xiangrong; Chen, Huayue; Hara, Takeshi; Miyamoto, Kei; Kobayashi, Tatsunori; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi

2010-03-01

X-ray CT images have been widely used in clinical routine in recent years. CT images scanned by a modern CT scanner can show the details of various organs and tissues. This means various organs and tissues can be simultaneously interpreted on CT images. However, CT image interpretation requires a lot of time and energy. Therefore, support for interpreting CT images based on image-processing techniques is expected. The interpretation of the spinal curvature is important for clinicians because spinal curvature is associated with various spinal disorders. We propose a quantification scheme of the spinal curvature based on the center line of spinal canal on CT images. The proposed scheme consists of four steps: (1) Automated extraction of the skeletal region based on CT number thresholding. (2) Automated extraction of the center line of spinal canal. (3) Generation of the median plane image of spine, which is reformatted based on the spinal canal. (4) Quantification of the spinal curvature. The proposed scheme was applied to 10 cases, and compared with the Cobb angle that is commonly used by clinicians. We found that a high-correlation (for the 95% confidence interval, lumbar lordosis: 0.81-0.99) between values obtained by the proposed (vector) method and Cobb angle. Also, the proposed method can provide the reproducible result (inter- and intra-observer variability: within 2°). These experimental results suggested a possibility that the proposed method was efficient for quantifying the spinal curvature on CT images.

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.

Contemporary carotid imaging: from degree of stenosis to plaque vulnerability.

PubMed

Brinjikji, Waleed; Huston, John; Rabinstein, Alejandro A; Kim, Gyeong-Moon; Lerman, Amir; Lanzino, Giuseppe

2016-01-01

Carotid artery stenosis is a well-established risk factor of ischemic stroke, contributing to up to 10%-20% of strokes or transient ischemic attacks. Many clinical trials over the last 20 years have used measurements of carotid artery stenosis as a means to risk stratify patients. However, with improvements in vascular imaging techniques such as CT angiography and MR angiography, ultrasonography, and PET/CT, it is now possible to risk stratify patients, not just on the degree of carotid artery stenosis but also on how vulnerable the plaque is to rupture, resulting in ischemic stroke. These imaging techniques are ushering in an emerging paradigm shift that allows for risk stratifications based on the presence of imaging features such as intraplaque hemorrhage (IPH), plaque ulceration, plaque neovascularity, fibrous cap thickness, and presence of a lipid-rich necrotic core (LRNC). It is important for the neurosurgeon to be aware of these new imaging techniques that allow for improved patient risk stratification and outcomes. For example, a patient with a low-grade stenosis but an ulcerated plaque may benefit more from a revascularization procedure than a patient with a stable 70% asymptomatic stenosis with a thick fibrous cap. This review summarizes the current state-of-the-art advances in carotid plaque imaging. Currently, MRI is the gold standard in carotid plaque imaging, with its high resolution and high sensitivity for identifying IPH, ulceration, LRNC, and inflammation. However, MRI is limited due to time constraints. CT also allows for high-resolution imaging and can accurately detect ulceration and calcification, but cannot reliably differentiate LRNC from IPH. PET/CT is an effective technique to identify active inflammation within the plaque, but it does not allow for assessment of anatomy, ulceration, IPH, or LRNC. Ultrasonography, with the aid of contrast enhancement, is a cost-effective technique to assess plaque morphology and characteristics, but it is limited in sensitivity and specificity for detecting LRNC, plaque hemorrhage, and ulceration compared with MRI. Also summarized is how these advanced imaging techniques are being used in clinical practice to risk stratify patients with low- and high-grade carotid artery stenosis. For example, identification of IPH on MRI in patients with low-grade carotid artery stenosis is a risk factor for failure of medical therapy, and studies have shown that such patients may fair better with carotid endarterectomy (CEA). MR plaque imaging has also been found to be useful in identifying revascularization candidates who would be better candidates for CEA than carotid artery stenting (CAS), as high intraplaque signal on time of flight imaging is associated with vulnerable plaque and increased rates of adverse events in patients undergoing CAS but not CEA.

In vivo small animal micro-CT using nanoparticle contrast agents

PubMed Central

Ashton, Jeffrey R.; West, Jennifer L.; Badea, Cristian T.

2015-01-01

Computed tomography (CT) is one of the most valuable modalities for in vivo imaging because it is fast, high-resolution, cost-effective, and non-invasive. Moreover, CT is heavily used not only in the clinic (for both diagnostics and treatment planning) but also in preclinical research as micro-CT. Although CT is inherently effective for lung and bone imaging, soft tissue imaging requires the use of contrast agents. For small animal micro-CT, nanoparticle contrast agents are used in order to avoid rapid renal clearance. A variety of nanoparticles have been used for micro-CT imaging, but the majority of research has focused on the use of iodine-containing nanoparticles and gold nanoparticles. Both nanoparticle types can act as highly effective blood pool contrast agents or can be targeted using a wide variety of targeting mechanisms. CT imaging can be further enhanced by adding spectral capabilities to separate multiple co-injected nanoparticles in vivo. Spectral CT, using both energy-integrating and energy-resolving detectors, has been used with multiple contrast agents to enable functional and molecular imaging. This review focuses on new developments for in vivo small animal micro-CT using novel nanoparticle probes applied in preclinical research. PMID:26581654

Image quality of conventional images of dual-layer SPECTRAL CT: A phantom study.

PubMed

van Ommen, Fasco; Bennink, Edwin; Vlassenbroek, Alain; Dankbaar, Jan Willem; Schilham, Arnold M R; Viergever, Max A; de Jong, Hugo W A M

2018-05-10

Spectral CT using a dual layer detector offers the possibility of retrospectively introducing spectral information to conventional CT images. In theory, the dual-layer technology should not come with a dose or image quality penalty for conventional images. In this study, we evaluate the influence of a dual-layer detector (IQon Spectral CT, Philips Healthcare) on the image quality of conventional CT images, by comparing these images with those of a conventional but otherwise technically comparable single-layer CT scanner (Brilliance iCT, Philips Healthcare), by means of phantom experiments. For both CT scanners, conventional CT images were acquired using four adult scanning protocols: (a) body helical, (b) body axial, (c) head helical, and (d) head axial. A CATPHAN 600 phantom was scanned to conduct an assessment of image quality metrics at equivalent (CTDI) dose levels. Noise was characterized by means of noise power spectra (NPS) and standard deviation (SD) of a uniform region, and spatial resolution was evaluated with modulation transfer functions (MTF) of a tungsten wire. In addition, contrast-to-noise ratio (CNR), image uniformity, CT number linearity, slice thickness, slice spacing, and spatial linearity were measured and evaluated. Additional measurements of CNR, resolution and noise were performed in two larger phantoms. The resolution levels at 50%, 10%, and 5% MTF of the iCT and IQon showed small, but significant differences up to 0.25 lp/cm for body scans, and up to 0.2 lp/cm for head scans in favor of the IQon. The iCT and IQon showed perfect CT linearity for body scans, but for head scans both scanners showed an underestimation of the CT numbers of materials with a high opacity. Slice thickness was slightly overestimated for both scanners. Slice spacing was comparable and reconstructed correctly. In addition, spatial linearity was excellent for both scanners, with a maximum error of 0.11 mm. CNR was higher on the IQon compared to the iCT for both normal and larger phantoms with differences up to 0.51. Spatial resolution did not change with phantom size, but noise levels increased significantly. For head scans, IQon had a noise level that was significantly lower than the iCT, on the other hand IQon showed noise levels significantly higher than the iCT for body scans. Still, these differences were well within the specified range of performance of iCT scanners. At equivalent dose levels, this study showed similar quality of conventional images acquired on iCT and IQon for medium-sized phantoms and slightly degraded image quality for (very) large phantoms at lower tube voltages on the IQon. Accordingly, it may be concluded that the introduction of a dual-layer detector neither compromises image quality of conventional images nor increases radiation dose for normal-sized patients, and slightly degrades dose efficiency for large patients at 120 kVp and lower tube voltages. © 2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Development of personalized annuloplasty rings: combination of CT images and CAD-CAM tools.

PubMed

Díaz Lantada, Andrés; Valle-Fernández, Raquel Del; Morgado, Pilar Lafont; Muñoz-García, Julio; Muñoz Sanz, José Luis; Munoz-Guijosa, Juan Manuel; Otero, Javier Echávarri

2010-02-01

Although the use of personalized annuloplasty rings manufactured for each patient according to the size and morphology of their valve complex could be beneficial for the treatment of mitral insufficiency, this possibility has been limited for reasons of time-lines and costs as well as for design and manufacturing difficulties, as has been the case with other personalized implant and prosthetic developments. However, the present quality of medical image capture equipment together with the benefits to be had from computer-aided design and manufacturing technologies (CAD-CAM) and the capabilities furnished by rapid prototyping technologies, present new opportunities for a personalized response to the development of implants and prostheses, the social impact of which could turn out to be highly positive. This paper sets out a personalized development of an annuloplasty ring based on the combined use of information from medical imaging, from CAD-CAM design programs and prototype manufacture using rapid prototyping technologies.

TH-E-202-02: The Use of Hypoxia PET Imaging for Radiotherapy

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

Humm, J.

2016-06-15

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy.more » The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand the basics of using FDG PET/CT for tumor response evaluation. Learn about recent advancement in PET/CT radiomics and non-FDG PET tracers for response assessment. This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

Development of a new technique for pedicle screw and Magerl screw insertion using a 3-dimensional image guide.

PubMed

Kawaguchi, Yoshiharu; Nakano, Masato; Yasuda, Taketoshi; Seki, Shoji; Hori, Takeshi; Kimura, Tomoatsu

2012-11-01

We developed a new technique for cervical pedicle screw and Magerl screw insertion using a 3-dimensional image guide. In posterior cervical spinal fusion surgery, instrumentation with screws is virtually routine. However, malpositioning of screws is not rare. To avoid complications during cervical pedicle screw and Magerl screw insertion, the authors developed a new technique which is a mold shaped to fit the lamina. Cervical pedicle screw fixation and Magerl screw fixation provide good correction of cervical alignment, rigid fixation, and a high fusion rate. However, malpositioning of screws is not a rare occurrence, and thus the insertion of screws has a potential risk of neurovascular injury. It is necessary to determine a safe insertion procedure for these screws. Preoperative computed tomographic (CT) scans of 1-mm slice thickness were obtained of the whole surgical area. The CT data were imported into a computer navigation system. We developed a 3-dimensional full-scale model of the patient's spine using a rapid prototyping technique from the CT data. Molds of the left and right sides at each vertebra were also constructed. One hole (2.0 mm in diameter and 2.0 cm in length) was made in each mold for the insertion of a screw guide. We performed a simulated surgery using the bone model and the mold before operation in all patients. The mold was firmly attached to the surface of the lamina and the guide wire was inserted using the intraoperative image of lateral vertebra. The proper insertion point, direction, and length of the guide were also confirmed both with the model bone and the image intensifier in the operative field. Then, drilling using a cannulated drill and tapping using a cannulated tapping device were carried out. Eleven consecutive patients who underwent posterior spinal fusion surgery using this technique since 2009 are included. The screw positions in the sagittal and axial planes were evaluated by postoperative CT scan to check for malpositioning. The screw insertion was done in the same manner as the simulated surgery. With the aid of this guide the pedicle screws and Magerl screws could be easily inserted even at the level where the pedicle seemed to be very thin and sclerotic on the CT scan. Postoperative CT scan showed that there were no critical breaches of the screws. This method employing the device using a 3-dimensional image guide seems to be easy and safe to use. The technique may improve the safety of pedicle screw and Magerl screw insertion even in difficult cases with narrow sclerotic pedicles.

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

Utility of CT-compatible EEG electrodes in critically ill children.

PubMed

Abend, Nicholas S; Dlugos, Dennis J; Zhu, Xiaowei; Schwartz, Erin S

2015-04-01

Electroencephalographic monitoring is being used with increasing frequency in critically ill children who may require frequent and sometimes urgent brain CT scans. Standard metallic disk EEG electrodes commonly produce substantial imaging artifact, and they must be removed and later reapplied when CT scans are indicated. To determine whether conductive plastic electrodes caused artifact that limited CT interpretation. We describe a retrospective cohort of 13 consecutive critically ill children who underwent 17 CT scans with conductive plastic electrodes during 1 year. CT images were evaluated by a pediatric neuroradiologist for artifact presence, type and severity. All CT scans had excellent quality images without artifact that impaired CT interpretation except for one scan in which improper wire placement resulted in artifact. Conductive plastic electrodes do not cause artifact limiting CT scan interpretation and may be used in critically ill children to permit concurrent electroencephalographic monitoring and CT imaging.

TH-E-BRF-02: 4D-CT Ventilation Image-Based IMRT Plans Are Dosimetrically Comparable to SPECT Ventilation Image-Based Plans

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

Kida, S; University of Tokyo Hospital, Bunkyo, Tokyo; Bal, M

Purpose: An emerging lung ventilation imaging method based on 4D-CT can be used in radiotherapy to selectively avoid irradiating highly-functional lung regions, which may reduce pulmonary toxicity. Efforts to validate 4DCT ventilation imaging have been focused on comparison with other imaging modalities including SPECT and xenon CT. The purpose of this study was to compare 4D-CT ventilation image-based functional IMRT plans with SPECT ventilation image-based plans as reference. Methods: 4D-CT and SPECT ventilation scans were acquired for five thoracic cancer patients in an IRB-approved prospective clinical trial. The ventilation images were created by quantitative analysis of regional volume changes (amore » surrogate for ventilation) using deformable image registration of the 4D-CT images. A pair of 4D-CT ventilation and SPECT ventilation image-based IMRT plans was created for each patient. Regional ventilation information was incorporated into lung dose-volume objectives for IMRT optimization by assigning different weights on a voxel-by-voxel basis. The objectives and constraints of the other structures in the plan were kept identical. The differences in the dose-volume metrics have been evaluated and tested by a paired t-test. SPECT ventilation was used to calculate the lung functional dose-volume metrics (i.e., mean dose, V20 and effective dose) for both 4D-CT ventilation image-based and SPECT ventilation image-based plans. Results: Overall there were no statistically significant differences in any dose-volume metrics between the 4D-CT and SPECT ventilation imagebased plans. For example, the average functional mean lung dose of the 4D-CT plans was 26.1±9.15 (Gy), which was comparable to 25.2±8.60 (Gy) of the SPECT plans (p = 0.89). For other critical organs and PTV, nonsignificant differences were found as well. Conclusion: This study has demonstrated that 4D-CT ventilation image-based functional IMRT plans are dosimetrically comparable to SPECT ventilation image-based plans, providing evidence to use 4D-CT ventilation imaging for clinical applications. Supported in part by Free to Breathe Young Investigator Research Grant and NIH/NCI R01 CA 093626. The authors thank Philips Radiation Oncology Systems for the Pinnacle3 treatment planning systems.« less

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

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.

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

PubMed Central

Jiang, Hao; Zhao, Dehua; Cai, Ying; An, Shuqing

2012-01-01

In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT), the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI) as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal) thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV) of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling) normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3%) and overall (92.0%–93.1%) accuracies. Our results suggest that Method of 0.1% index scaling provides a feasible way to apply CT models directly to images from sensors or time periods that differ from those of the images used to develop the original models.

Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM.

PubMed

Razifar, Pasha; Sandström, Mattias; Schnieder, Harald; Långström, Bengt; Maripuu, Enn; Bengtsson, Ewert; Bergström, Mats

2005-08-25

Positron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone. Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT. Experiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images. The most important finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images. The combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

Instantiation and registration of statistical shape models of the femur and pelvis using 3D ultrasound imaging.

PubMed

Barratt, Dean C; Chan, Carolyn S K; Edwards, Philip J; Penney, Graeme P; Slomczykowski, Mike; Carter, Timothy J; Hawkes, David J

2008-06-01

Statistical shape modelling potentially provides a powerful tool for generating patient-specific, 3D representations of bony anatomy for computer-aided orthopaedic surgery (CAOS) without the need for a preoperative CT scan. Furthermore, freehand 3D ultrasound (US) provides a non-invasive method for digitising bone surfaces in the operating theatre that enables a much greater region to be sampled compared with conventional direct-contact (i.e., pointer-based) digitisation techniques. In this paper, we describe how these approaches can be combined to simultaneously generate and register a patient-specific model of the femur and pelvis to the patient during surgery. In our implementation, a statistical deformation model (SDM) was constructed for the femur and pelvis by performing a principal component analysis on the B-spline control points that parameterise the freeform deformations required to non-rigidly register a training set of CT scans to a carefully segmented template CT scan. The segmented template bone surface, represented by a triangulated surface mesh, is instantiated and registered to a cloud of US-derived surface points using an iterative scheme in which the weights corresponding to the first five principal modes of variation of the SDM are optimised in addition to the rigid-body parameters. The accuracy of the method was evaluated using clinically realistic data obtained on three intact human cadavers (three whole pelves and six femurs). For each bone, a high-resolution CT scan and rigid-body registration transformation, calculated using bone-implanted fiducial markers, served as the gold standard bone geometry and registration transformation, respectively. After aligning the final instantiated model and CT-derived surfaces using the iterative closest point (ICP) algorithm, the average root-mean-square distance between the surfaces was 3.5mm over the whole bone and 3.7mm in the region of surgical interest. The corresponding distances after aligning the surfaces using the marker-based registration transformation were 4.6 and 4.5mm, respectively. We conclude that despite limitations on the regions of bone accessible using US imaging, this technique has potential as a cost-effective and non-invasive method to enable surgical navigation during CAOS procedures, without the additional radiation dose associated with performing a preoperative CT scan or intraoperative fluoroscopic imaging. However, further development is required to investigate errors using error measures relevant to specific surgical procedures.

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

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.

Radionuclide bone scan SPECT-CT: lowering the dose of CT significantly reduces radiation dose without impacting CT image quality

PubMed Central

Gupta, Sandeep Kumar; Trethewey, Scott; Brooker, Bree; Rutherford, Natalie; Diffey, Jenny; Viswanathan, Suresh; Attia, John

2017-01-01

The CT component of SPECT-CT is required for attenuation correction and anatomical localization of the uptake on SPECT but there is no guideline about the optimal CT acquisition parameters. In our department, a standard CT acquisition protocol was changed in 2013 to give lower radiation dose to the patient. In this study, we retrospectively compared the effects on patient dose as well as the CT image quality with current versus older CT protocols. Ninety nine consecutive patients [n=51 Standard dose ‘old’ protocol (SDP); n=48 lower dose ‘new’ protocol (LDP)] with lumbar spine SPECT-CT for bone scan were examined. The main differences between the two protocols were that SDP used 130 kVp tube voltage and reference current-time product of 70 mAs whereas the LDP used 110 kVp and 40 mAs respectively. Various quantitative parameters from the CT images were obtained and the images were also rated blindly by two experienced nuclear medicine physicians for bony definition and noise. The mean calculated dose length product of the LDP group (121.5±39.6 mGy.cm) was significantly lower compared to the SDP group patients (266.9±96.9 mGy.cm; P<0.0001). This translated into a significant reduction in the mean effective dose to 1.8 mSv from 4.0 mSv. The physicians reported better CT image quality for the bony structures in LDP group although for soft tissue structures, the SDP group had better image quality. The optimized new CT acquisition protocol significantly reduced the radiation dose to the patient and in-fact improved CT image quality for the assessment of bony structures. PMID:28533938

Submarine Periscope Depth Course Selection Tactical Decision Aid

DTIC Science & Technology

1997-12-01

are translated to Cartesian coordinates. Co is own ship’s course. 8 X0 = DMho. cos(Co) Yo = DAho . sin(Co) Xc = DMht- cos(Ct) Yc = DMhbt sin(Ct) These...Display Graph. The input parameters of DAho , Ct, and DMiht along with Co as generated by the simulation are used to determine the Cartesian

PET/CT aids the staging of and radiotherapy planning for early-stage extranodal natural killer/T-cell lymphoma, nasal type: A case series

PubMed Central

2011-01-01

Extranodal natural killer/T-cell lymphoma (ENKTL), nasal type, is a rare form of non-Hodgkin lymphoma. Treatment of ENKTL primarily relies on radiation; thus, proper delineation of target volumes is critical. Currently, the ideal modalities for delineation of gross tumor volume for ENKTL are unknown. We describe three consecutive cases of localized ENKTL that presented to the Nova Scotia Cancer Centre in Halifax, Nova Scotia. All patients had a planning CT and MRI as well as a planning FDG-PET/CT in the radiotherapy treatment position, wearing immobilization masks. All patients received radiation alone. In two patients, PET/CT changed not only the stage, but also the target volume requiring treatment. The third patient was unable to tolerate an MRI, but was able to undergo PET/CT, which improved the accuracy of the target volume. PET/CT aided the staging of and radiotherapy planning for our patients and appears to be a promising tool in the treatment of ENKTL. PMID:22208903

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

Johnston, H; UT Southwestern Medical Center, Dallas, TX; Hilts, M

Purpose: To commission a multislice computed tomography (CT) scanner for fast and reliable readout of radiation therapy (RT) dose distributions using CT polymer gel dosimetry (PGD). Methods: Commissioning was performed for a 16-slice CT scanner using images acquired through a 1L cylinder filled with water. Additional images were collected using a single slice machine for comparison purposes. The variability in CT number associated with the anode heel effect was evaluated and used to define a new slice-by-slice background image subtraction technique. Image quality was assessed for the multislice system by comparing image noise and uniformity to that of the singlemore » slice machine. The consistency in CT number across slices acquired simultaneously using the multislice detector array was also evaluated. Finally, the variability in CT number due to increasing x-ray tube load was measured for the multislice scanner and compared to the tube load effects observed on the single slice machine. Results: Slice-by-slice background subtraction effectively removes the variability in CT number across images acquired simultaneously using the multislice scanner and is the recommended background subtraction method when using a multislice CT system. Image quality for the multislice machine was found to be comparable to that of the single slice scanner. Further study showed CT number was consistent across image slices acquired simultaneously using the multislice detector array for each detector configuration of the slice thickness examined. In addition, the multislice system was found to eliminate variations in CT number due to increasing x-ray tube load and reduce scanning time by a factor of 4 when compared to imaging a large volume using a single slice scanner. Conclusion: A multislice CT scanner has been commissioning for CT PGD, allowing images of an entire dose distribution to be acquired in a matter of minutes. Funding support provided by the Natural Sciences and Engineering Research Council of Canada (NSERC)« less

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

CT imaging, then and now: a 30-year review of the economics of computed tomography.

PubMed

Stockburger, Wayne T

2004-01-01

The first computed tomography (CT) scanner in the US was installed in June 1973 at the Mayo Clinic in Rochester, MN. By the end of 1974, 44 similar systems had been installed at medical facilities around the country. Less than 4 years after the introduction of CT imaging in the US, at least 400 CT systems had been installed. The practice of pneumoencephalography was eliminated. The use of nuclear medicine brain scans significantly diminished. At the time, CT imaging was limited to head studies, but with the introduction of contrast agents and full body CT systems the changes in the practice of medicine became even more significant. CT imaging was hailed by the US medical community as the greatest advance in radiology since the discovery of x-rays. But the rapid spread of CT systems, their frequency of use, and the associated increase in healthcare costs combined to draw the attention of decision-makers within the federal and state governments, specifically to establish policies regarding the acquisition and use of diagnostic technologies. Initially, CT imaging was limited to neurological applications, but in the 30 years since its inception, capabilities and applications have been expanded as a result of the advancements in technology and software development. While neurological disorders are still a common reason for CT imaging, many other medical disciplines (oncology, emergency medicine, orthopedics, etc.) have found CT imaging to be the definitive tool for diagnostic information. As such, the clinical demand for CT imaging has steadily increased. Economically, the development of CT imaging has been one of success, even in the face of governmental action to restrict its acquisition and utilization by healthcare facilities. CTimaging has increased the cost of healthcare, but in turn has added unquantifiable value to the practice of medicine in the US.

SU-F-J-114: On-Treatment Imagereconstruction Using Transit Images of Treatment Beams Through Patient and Thosethrough Planning CT Images

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

Lee, H; Cho, S; Cheong, K

Purpose: To reconstruct patient images at the time of radiation delivery using measured transit images of treatment beams through patient and calculated transit images through planning CT images. Methods: We hypothesize that the ratio of the measured transit images to the calculated images may provide changed amounts of the patient image between times of planning CT and treatment. To test, we have devised lung phantoms with a tumor object (3-cm diameter) placed at iso-center (simulating planning CT) and off-center by 1 cm (simulating treatment). CT images of the two phantoms were acquired; the image of the off-centered phantom, unavailable clinically,more » represents the reference on-treatment image in the image quality of planning CT. Cine-transit images through the two phantoms were also acquired in EPID from a non-modulated 6 MV beam when the gantry was rotated 360 degrees; the image through the centered phantom simulates calculated image. While the current study is a feasibility study, in reality our computational EPID model can be applicable in providing accurate transit image from MC simulation. Changed MV HU values were reconstructed from the ratio between two EPID projection data, converted to KV HU values, and added to the planning CT, thereby reconstructing the on-treatment image of the patient limited to the irradiated region of the phantom. Results: The reconstructed image was compared with the reference image. Except for local HU differences>200 as a maximum, excellent agreement was found. The average difference across the entire image was 16.2 HU. Conclusion: We have demonstrated the feasibility of a method of reconstructing on-treatment images of a patient using EPID image and planning CT images. Further studies will include resolving the local HU differences and investigation on the dosimetry impact of the reconstructed image.« less

Comparison Between CT and MR Images as More Favorable Reference Data Sets for Fusion Imaging-Guided Radiofrequency Ablation or Biopsy of Hepatic Lesions: A Prospective Study with Focus on Patient's Respiration.

PubMed

Cha, Dong Ik; Lee, Min Woo; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Kim, Kyunga

2017-10-01

To identify the more accurate reference data sets for fusion imaging-guided radiofrequency ablation or biopsy of hepatic lesions between computed tomography (CT) and magnetic resonance (MR) images. This study was approved by the institutional review board, and written informed consent was received from all patients. Twelve consecutive patients who were referred to assess the feasibility of radiofrequency ablation or biopsy were enrolled. Automatic registration using CT and MR images was performed in each patient. Registration errors during optimal and opposite respiratory phases, time required for image fusion and number of point locks used were compared using the Wilcoxon signed-rank test. The registration errors during optimal respiratory phase were not significantly different between image fusion using CT and MR images as reference data sets (p = 0.969). During opposite respiratory phase, the registration error was smaller with MR images than CT (p = 0.028). The time and the number of points locks needed for complete image fusion were not significantly different between CT and MR images (p = 0.328 and p = 0.317, respectively). MR images would be more suitable as the reference data set for fusion imaging-guided procedures of focal hepatic lesions than CT images.

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

TH-E-202-01: Pitfalls and Remedies in PET/CT Imaging for RT Planning

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

Pan, T.

2016-06-15

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy.more » The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand the basics of using FDG PET/CT for tumor response evaluation. Learn about recent advancement in PET/CT radiomics and non-FDG PET tracers for response assessment. This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

Acceptance test of a commercially available software for automatic image registration of computed tomography (CT), magnetic resonance imaging (MRI) and 99mTc-methoxyisobutylisonitrile (MIBI) single-photon emission computed tomography (SPECT) brain images.

PubMed

Loi, Gianfranco; Dominietto, Marco; Manfredda, Irene; Mones, Eleonora; Carriero, Alessandro; Inglese, Eugenio; Krengli, Marco; Brambilla, Marco

2008-09-01

This note describes a method to characterize the performances of image fusion software (Syntegra) with respect to accuracy and robustness. Computed tomography (CT), magnetic resonance imaging (MRI), and single-photon emission computed tomography (SPECT) studies were acquired from two phantoms and 10 patients. Image registration was performed independently by two couples composed of one radiotherapist and one physicist by means of superposition of anatomic landmarks. Each couple performed jointly and saved the registration. The two solutions were averaged to obtain the gold standard registration. A new set of estimators was defined to identify translation and rotation errors in the coordinate axes, independently from point position in image field of view (FOV). Algorithms evaluated were local correlation (LC) for CT-MRI, normalized mutual information (MI) for CT-MRI, and CT-SPECT registrations. To evaluate accuracy, estimator values were compared to limiting values for the algorithms employed, both in phantoms and in patients. To evaluate robustness, different alignments between images taken from a sample patient were produced and registration errors determined. LC algorithm resulted accurate in CT-MRI registrations in phantoms, but exceeded limiting values in 3 of 10 patients. MI algorithm resulted accurate in CT-MRI and CT-SPECT registrations in phantoms; limiting values were exceeded in one case in CT-MRI and never reached in CT-SPECT registrations. Thus, the evaluation of robustness was restricted to the algorithm of MI both for CT-MRI and CT-SPECT registrations. The algorithm of MI proved to be robust: limiting values were not exceeded with translation perturbations up to 2.5 cm, rotation perturbations up to 10 degrees and roto-translational perturbation up to 3 cm and 5 degrees.

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

MIB-1 Index-Stratified Assessment of Dual-Tracer PET/CT with 68Ga-DOTATATE and 18F-FDG and Multimodality Anatomic Imaging in Metastatic Neuroendocrine Tumors of Unknown Primary in a PRRT Workup Setting.

PubMed

Sampathirao, Nikita; Basu, Sandip

2017-03-01

Our aim was to comparatively assess dual-tracer PET/CT ( 68 Ga-DOTATATE and 18 F-FDG) and multimodality anatomic imaging in studying metastatic neuroendocrine tumors (NETs) of unknown primary (CUP-NETs) scheduled for peptide receptor radionuclide therapy for divergence of tracer uptake on dual-tracer PET/CT, detection of primary, and overall lesion detection vis-a-vis tumor proliferation index (MIB-1/Ki-67). Methods: Fifty-one patients with CUP-NETs (25 men, 26 women; age, 22-74 y), histopathologically proven and thoroughly investigated with conventional imaging modalities (ultrasonography, CT/contrast-enhanced CT, MRI, and endoscopic ultrasound, wherever applicable), were retrospectively analyzed. Patients were primarily referred for deciding on feasibility of peptide receptor radionuclide therapy (except 2 patients), and all had undergone 68 Ga-DOTATATE and 18 F-FDG PET/CT as part of pretreatment workup. The sites of metastases included liver, lung/mediastinum, skeleton, abdominal nodes, and other soft-tissue sites. Patients were divided into 5 groups on the basis of MIB-1/Ki-67 index on a 5-point scale: group I (1%-5%) ( n = 35), group II (6%-10%) ( n = 8), group III (11%-15%) ( n = 4), group IV (16%-20%) ( n = 2), and group V (>20%) ( n = 2). Semiquantitative analysis of tracer uptake was undertaken by SUV max of metastatic lesions and the primary (when detected). The SUV max values were studied over increasing MIB-1/Ki-67 index. The detection sensitivity of 68 Ga-DOTATATE for primary and metastatic lesions was assessed and compared with other imaging modalities including 18 F-FDG PET/CT. Results: Unknown primary was detected on 68 Ga-DOTATATE in 31 of 51 patients, resulting in sensitivity of 60.78% whereas overall lesion detection sensitivity was 96.87%. The overall lesion detection sensitivities (individual groupwise from group I to group V) were 97.75%, 87.5%, 100%, 100%, and 66.67%, respectively. As MIB-1/Ki-67 index increased, 68 Ga-DOTATATE uptake decreased in metastatic and primary lesions (mean SUV max , 43.5 and 22.68 g/dL in group I to 22.54 and 16.83 g/dL in group V, respectively), whereas 18 F-FDG uptake showed a gradual rise (mean SUV max , 3.66 and 2.86 g/dL in group I to 7.53 and 9.58 g/dL in group V, respectively). There was a corresponding decrease in the 68 Ga-DOTATATE-to- 18 F-FDG uptake ratio with increasing MIB-1/Ki-67 index (from 11.89 in group I to 2.99 in group V). Conclusion: In CUP-NETs, the pattern of uptake on dual-tracer PET ( 68 Ga-DOTATATE and 18 F-FDG) correlates well with tumor proliferation index with a few outliers; combined dual-tracer PET/CT with MIB-1/Ki-67 index would aid in better whole-body assessment of tumor biology in CUP-NETs. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

TH-E-202-00: PET for Radiation Therapy

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

NONE

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy.more » The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand the basics of using FDG PET/CT for tumor response evaluation. Learn about recent advancement in PET/CT radiomics and non-FDG PET tracers for response assessment. This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

TH-E-202-03: PET for Tumor Response Evaluation

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

Lu, W.

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy.more » The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand the basics of using FDG PET/CT for tumor response evaluation. Learn about recent advancement in PET/CT radiomics and non-FDG PET tracers for response assessment. This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

TH-CD-202-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY): Evaluation of the Use of Direct Electron Density CT Images in Radiation Therapy

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

Zhao, T; Sun, B; Li, H

Purpose: The current standard for calculation of photon and electron dose requires conversion of Hounsfield Units (HU) to Electron Density (ED) by applying a calibration curve specifically constructed for the corresponding CT tube voltage. This practice limits the use of the CT scanner to a single tube voltage and hinders the freedom in the selection of optimal tube voltage for better image quality. The objective of this study is to report a prototype CT reconstruction algorithm that provides direct ED images from the raw CT data independently of tube voltages used during acquisition. Methods: A tissue substitute phantom was scannedmore » for Stoichiometric CT calibrations at tube voltages of 70kV, 80kV, 100kV, 120kV and 140kV respectively. HU images and direct ED images were acquired sequentially on a thoracic anthropomorphic phantom at the same tube voltages. Electron densities converted from the HU images were compared to ED obtained from the direct ED images. A 7-field treatment plan was made on all HU and ED images. Gamma analysis was performed to demonstrate quantitatively dosimetric change from the two schemes in acquiring ED. Results: The average deviation of EDs obtained from the direct ED images was −1.5%±2.1% from the EDs from HU images with the corresponding CT calibration curves applied. Gamma analysis on dose calculated on the direct ED images and the HU images acquired at the same tube voltage indicated negligible difference with lowest passing rate at 99.9%. Conclusion: Direct ED images require no CT calibration while demonstrate equivalent dosimetry compared to that obtained from standard HU images. The ability of acquiring direct ED images simplifies the current practice at a safer level by eliminating CT calibration and HU conversion from commissioning and treatment planning respectively. Furthermore, it unlocks a wider range of tube voltages in CT scanner for better imaging quality while maintaining similar dosimetric accuracy.« less

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

Multi-modality PET-CT imaging of breast cancer in an animal model using nanoparticle x-ray contrast agent and 18F-FDG

NASA Astrophysics Data System (ADS)

Badea, C. T.; Ghaghada, K.; Espinosa, G.; Strong, L.; Annapragada, A.

2011-03-01

Multi-modality PET-CT imaging is playing an important role in the field of oncology. While PET imaging facilitates functional interrogation of tumor status, the use of CT imaging is primarily limited to anatomical reference. In an attempt to extract comprehensive information about tumor cells and its microenvironment, we used a nanoparticle xray contrast agent to image tumor vasculature and vessel 'leakiness' and 18F-FDG to investigate the metabolic status of tumor cells. In vivo PET/CT studies were performed in mice implanted with 4T1 mammary breast cancer cells.Early-phase micro-CT imaging enabled visualization 3D vascular architecture of the tumors whereas delayedphase micro-CT demonstrated highly permeable vessels as evident by nanoparticle accumulation within the tumor. Both imaging modalities demonstrated the presence of a necrotic core as indicated by a hypo-enhanced region in the center of the tumor. At early time-points, the CT-derived fractional blood volume did not correlate with 18F-FDG uptake. At delayed time-points, the tumor enhancement in 18F-FDG micro-PET images correlated with the delayed signal enhanced due to nanoparticle extravasation seen in CT images. The proposed hybrid imaging approach could be used to better understand tumor angiogenesis and to be the basis for monitoring and evaluating anti-angiogenic and nano-chemotherapies.

Detection of Sentinel Lymph Nodes in Gynecologic Tumours by Planar Scintigraphy and SPECT/CT

PubMed Central

Kraft, Otakar; Havel, Martin

2012-01-01

Objective: Assess the role of planar lymphoscintigraphy and fusion imaging of SPECT/CT in sentinel lymph node (SLN) detection in patients with gynecologic tumours. Material and Methods: Planar scintigraphy and hybrid modality SPECT/CT were performed in 64 consecutive women with gynecologic tumours (mean age 53.6 with range 30-77 years): 36 pts with cervical cancer (Group A), 21 pts with endometrial cancer (Group B), 7 pts with vulvar carcinoma (Group C). Planar and SPECT/CT images were interpreted separately by two nuclear medicine physicians. Efficacy of these two techniques to image SLN were compared. Results: Planar scintigraphy did not image SLN in 7 patients (10.9%), SPECT/CT was negative in 4 patients (6.3%). In 35 (54.7%) patients the number of SLNs captured on SPECT/CT was higher than on planar imaging. Differences in detection of SLN between planar and SPECT/CT imaging in the group of all 64 patients are statistically significant (p<0.05). Three foci of uptake (1.7% from totally visible 177 foci on planar images) in 2 patients interpreted on planar images as hot LNs were found to be false positive non-nodal sites of uptake when further assessed on SPECT/CT. SPECT/CT showed the exact anatomical location of all visualised sentinel nodes. Conclusion: In some patients with gynecologic cancers SPECT/CT improves detection of sentinel lymph nodes. It can image nodes not visible on planar scintigrams, exclude false positive uptake and exactly localise pelvic and paraaortal SLNs. It improves anatomic localization of SLNs. Conflict of interest:None declared. PMID:23486989

Diagnostic role of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for early and atypical bone metastases.

PubMed

Chen, Xiao-Liang; Li, Qian; Cao, Lin; Jiang, Shi-Xi

2014-01-01

The bone metastasis appeared early before the bone imaging for most of the above patients. (99)Tc(m)-MDP ((99)Tc(m) marked methylene diphosphonate) bone imaging could diagnosis the bone metastasis with highly sensitivity, but with lower specificity. The aim of this study is to explore the diagnostic value of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for the early period atypical bone metastases. 15 to 30 mCi (99)Tc(m)-MDP was intravenously injected to the 34 malignant patients diagnosed as doubtful early bone metastases. SPECT, CT and SPECT/CT images were captured and analyzed consequently. For the patients diagnosed as early period atypical bone metastases by SPECT/CT, combining the SPECT/CT and MRI together as the SPECT/MRI integrated image. The obtained SPECT/MRI image was analyzed and compared with the pathogenic results of patients. The results indicated that 34 early period doubtful metastatic focus, including 34 SPECT positive focus, 17 focus without special changes by using CT method, 11 bone metastases focus by using SPECT/CT method, 23 doubtful bone metastases focus, 8 doubtful bone metastases focus, 14 doubtful bone metastases focus and 2 focus without clear image. Totally, SPECT/CT combined with SPECT/MRI method diagnosed 30 bone metastatic focus and 4 doubtfully metastatic focus. In conclusion, (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging shows a higher diagnostic value for the early period bone metastases, which also enhances the diagnostic accuracy rate.

An audit of imaging test utilization for the management of lymphoma in an oncology hospital: implications for resource planning?

PubMed

Schwartz, A; Gospodarowicz, M K; Khalili, K; Pintilie, M; Goddard, S; Keller, A; Tsang, R W

2006-02-01

The purpose of this study was to assist with resource planning by examining the pattern of physician utilization of imaging procedures for lymphoma patients in a dedicated oncology hospital. The proportion of imaging tests ordered for routine follow up with no specific clinical indication was quantified, with specific attention to CT scans. A 3-month audit was performed. The reasons for ordering all imaging procedures (X-rays, CT scans, ultrasound, nuclear scan and MRI) were determined through a retrospective chart review. 411 lymphoma patients had 686 assessments (sets of imaging tests) and 981 procedures (individual imaging tests). Most procedures were CT scans (52%) and chest radiographs (30%). The most common reasons for ordering imaging were assessing response (23%), and investigating new symptoms (19%). Routine follow up constituted 21% of the assessments (142/686), and of these, 82% were chest radiographs (116/142), while 24% (34/142) were CT scans. With analysis restricted to CT scans (296 assessments in 248 patients), the most common reason for ordering CT scans were response evaluation (40%), and suspicion of recurrence and/or new symptom (23%). Follow-up CT scans done with no clinical indication comprised 8% (25/296) of all CT assessments. Staging CT scans were under-represented at 6% of all assessments. Imaging with CT scans for follow up of asymptomatic patients is infrequent. However, scans done for staging new lymphoma patients were unexpectedly low in frequency, due to scans done elsewhere prior to referral. This analysis uncovered utilization patterns, helped resource planning and provided data to reduce unnecessary imaging procedures.

18F-FDG PET/MRI fusion in characterizing pancreatic tumors: comparison to PET/CT.

PubMed

Tatsumi, Mitsuaki; Isohashi, Kayako; Onishi, Hiromitsu; Hori, Masatoshi; Kim, Tonsok; Higuchi, Ichiro; Inoue, Atsuo; Shimosegawa, Eku; Takeda, Yutaka; Hatazawa, Jun

2011-08-01

To demonstrate that positron emission tomography (PET)/magnetic resonance imaging (MRI) fusion was feasible in characterizing pancreatic tumors (PTs), comparing MRI and computed tomography (CT) as mapping images for fusion with PET as well as fused PET/MRI and PET/CT. We retrospectively reviewed 47 sets of (18)F-fluorodeoxyglucose ((18)F -FDG) PET/CT and MRI examinations to evaluate suspected or known pancreatic cancer. To assess the ability of mapping images for fusion with PET, CT (of PET/CT), T1- and T2-weighted (w) MR images (all non-contrast) were graded regarding the visibility of PT (5-point confidence scale). Fused PET/CT, PET/T1-w or T2-w MR images of the upper abdomen were evaluated to determine whether mapping images provided additional diagnostic information to PET alone (3-point scale). The overall quality of PET/CT or PET/MRI sets in diagnosis was also assessed (3-point scale). These PET/MRI-related scores were compared to PET/CT-related scores and the accuracy in characterizing PTs was compared. Forty-three PTs were visualized on CT or MRI, including 30 with abnormal FDG uptake and 13 without. The confidence score for the visibility of PT was significantly higher on T1-w MRI than CT. The scores for additional diagnostic information to PET and overall quality of each image set in diagnosis were significantly higher on the PET/T1-w MRI set than the PET/CT set. The diagnostic accuracy was higher on PET/T1-w or PET/T2-w MRI (93.0 and 90.7%, respectively) than PET/CT (88.4%), but statistical significance was not obtained. PET/MRI fusion, especially PET with T1-w MRI, was demonstrated to be superior to PET/CT in characterizing PTs, offering better mapping and fusion image quality.

Aorta-Lesion-Attenuation-Difference (ALAD) on contrast-enhanced CT: a potential imaging biomarker for differentiating malignant from benign oncocytic neoplasms.

PubMed

Dhyani, Manish; Grajo, Joseph R; Rodriguez, Dayron; Chen, Zhikui; Feldman, Adam; Tambouret, Rosemary; Gervais, Debra A; Arellano, Ronald S; Hahn, Peter F; Samir, Anthony E

2017-06-01

To evaluate whether the Aorta-Lesion-Attenuation-Difference on contrast-enhanced CT can aid in the differentiation of malignant and benign oncocytic renal neoplasms. Two independent cohorts-an initial (biopsy) dataset and a validation (surgical) dataset-with oncocytomas and chromophobe renal cell carcinomas (chRCC) were included in this IRB-approved retrospective study. A region of interest was placed on the renal mass and abdominal aorta on the same CT image slice to calculate an Aorta-Lesion-Attenuation-Difference (ALAD). ROC curves were plotted for different enhancement phases, and diagnostic performance of ALAD for differentiating chRCC from oncocytomas was calculated. Seventy-nine renal masses (56 oncocytomas, 23 chRCC) were analyzed in the initial (biopsy) dataset. Thirty-six renal masses (16 oncocytomas, 20 chRCC) were reviewed in the validation (surgical) cohort. ALAD showed a statistically significant difference between oncocytomas and chromophobes during the nephrographic phase (p < 0.001), early excretory phase (p < 0.001), and excretory phase (p = 0.029). The area under the ROC curve for the nephrographic phase was 1.00 (95% CI: 1.00-1.00) for the biopsy dataset and showed the narrowest confidence interval. At a threshold value of 25.5 HU, sensitivity was 100 (82.2%-100%) and specificity was 81.5 (61.9%-93.7%). When tested on the validation dataset on measurements made by an independent reader, the AUROC was 0.93 (95% CI: 0.84-1.00) with a sensitivity of 100 (80.0%-100%) and a specificity of 87.5 (60.4%-97.8%). Nephrographic phase ALAD has potential to differentiate benign and malignant oncocytic renal neoplasms on contrast-enhanced CT if histologic evaluation on biopsy is indeterminate.

Valuable use of computer-aided surgery in congenital bony aural atresia.

PubMed

Caversaccio, Marco; Romualdez, Joel; Baechler, Richard; Nolte, Lutz-Peter; Kompis, Martin; Häusler, Rudolf

2003-04-01

Congenital aural atresia repair is difficult owing to unpredictable anatomy. Benefits may be gained from computer-aided surgery (CAS), but its exact role has yet to be clearly defined. This is a retrospective study of 18 patients with bony type C (Schuknecht classification) congenital atresia. In the first group (n = 9), repair was performed with CAS while in the second group (n = 9), similar intervention was applied without CAS. Intra- and post-operative clinical and audiological findings were compared. CAS computed tomography (CT) images correlated well with intra-operative findings giving the surgeon more security and reducing operative time by 25 minutes. In our estimation, CAS is valuable for type C congenital aural atresia repair. It serves as an educational tool and as a guide for the experienced surgeon in critical situations where anatomical landmarks are distorted and where access is limited.

Does positron emission tomography/computed tomography aid the diagnosis of prosthetic valve infective endocarditis?

PubMed

Balmforth, Damian; Chacko, Jacob; Uppal, Rakesh

2016-10-01

A best evidence topic was constructed according to a structured protocol. The question addressed was whether (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) aids the diagnosis of prosthetic valve endocarditis (PVE)? A total of 107 publications were found using the reported search, of which 6 represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. The reported outcome of all studies was a final diagnosis of confirmed endocarditis on follow-up. All the six studies were non-randomized, single-centre, observational studies and thus represented level 3 evidence. The diagnostic capability of PET/CT for PVE was compared with that of the modified Duke Criteria and echocardiography, and reported in terms of sensitivity, specificity and positive and negative predictive values. All studies demonstrated an increased sensitivity for the diagnosis of PVE when PET/CT was combined with the modified Duke Criteria on admission. A higher SUVmax on PET was found to be significantly associated with a confirmed diagnosis of endocarditis and an additional diagnostic benefit of PET/CT angiography over conventional PET/non-enhanced CT is reported due to improved anatomical resolution. However, PET/CT was found to be unreliable in the early postoperative period due to its inability to distinguish between infection and residual postoperative inflammatory changes. PET/CT was also found to be poor at diagnosing cases of native valve endocarditis. We conclude that PET/CT aids in the diagnosis of PVE when combined with the modified Duke Criteria on admission by increasing the diagnostic sensitivity. The diagnostic ability of PET/CT can be potentiated by the use of PET/CTA; however, its use may be unreliable in the early postoperative period or in native valve endocarditis. © The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD).

PubMed

Suzuki, Kenji

2009-09-21

Computer-aided diagnosis (CAD) has been an active area of study in medical image analysis. A filter for the enhancement of lesions plays an important role for improving the sensitivity and specificity in CAD schemes. The filter enhances objects similar to a model employed in the filter; e.g. a blob-enhancement filter based on the Hessian matrix enhances sphere-like objects. Actual lesions, however, often differ from a simple model; e.g. a lung nodule is generally modeled as a solid sphere, but there are nodules of various shapes and with internal inhomogeneities such as a nodule with spiculations and ground-glass opacity. Thus, conventional filters often fail to enhance actual lesions. Our purpose in this study was to develop a supervised filter for the enhancement of actual lesions (as opposed to a lesion model) by use of a massive-training artificial neural network (MTANN) in a CAD scheme for detection of lung nodules in CT. The MTANN filter was trained with actual nodules in CT images to enhance actual patterns of nodules. By use of the MTANN filter, the sensitivity and specificity of our CAD scheme were improved substantially. With a database of 69 lung cancers, nodule candidate detection by the MTANN filter achieved a 97% sensitivity with 6.7 false positives (FPs) per section, whereas nodule candidate detection by a difference-image technique achieved a 96% sensitivity with 19.3 FPs per section. Classification-MTANNs were applied for further reduction of the FPs. The classification-MTANNs removed 60% of the FPs with a loss of one true positive; thus, it achieved a 96% sensitivity with 2.7 FPs per section. Overall, with our CAD scheme based on the MTANN filter and classification-MTANNs, an 84% sensitivity with 0.5 FPs per section was achieved.

Correlation between standardized uptake value and apparent diffusion coefficient of neoplastic lesions evaluated with whole-body simultaneous hybrid PET/MRI.

PubMed

Rakheja, Rajan; Chandarana, Hersh; DeMello, Linda; Jackson, Kimberly; Geppert, Christian; Faul, David; Glielmi, Christopher; Friedman, Kent P

2013-11-01

The purpose of this study was to assess the correlation between standardized uptake value (SUV) and apparent diffusion coefficient (ADC) of neoplastic lesions in the use of a simultaneous PET/MRI hybrid system. Twenty-four patients with known primary malignancies underwent FDG PET/CT. They then underwent whole-body PET/MRI. Diffusion-weighted imaging was performed with free breathing and a single-shot spin-echo echo-planar imaging sequence with b values of 0, 350, and 750 s/mm(2). Regions of interest were manually drawn along the contours of neoplastic lesions larger than 1 cm, which were clearly identified on PET and diffusion-weighted images. Maximum SUV (SUVmax) on PET/MRI and PET/CT images, mean SUV (SUVmean), minimum ADC (ADCmin), and mean ADC (ADCmean) were recorded on PET/MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient. Pearson correlation coefficient was used to asses the following relations: SUVmax versus ADCmin on PET/MR and PET/CT images, SUVmean versus ADCmean, and ratio of SUVmax to mean liver SUV (SUV ratio) versus ADCmin. A subanalysis of patients with progressive disease versus partial treatment response was performed with the ratio of SUVmax to ADCmin for the most metabolically active lesion. Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. A significant inverse Pearson correlation coefficient was found between PET/MRI SUVmax and ADCmin (r = -0.21, p = 0.04), between SUVmean and ADCmean (r = -0.18, p = 0.07), and between SUV ratio and ADCmin (r = -0.27, p = 0.01). A similar inverse Pearson correlation coefficient was found between the PET/CT SUVmax and ADCmin. Twenty of 24 patients had previously undergone PET/CT; five patients had a partial treatment response, and six had progressive disease according to Response Evaluation Criteria in Solid Tumors 1.1. The ratio between SUVmax and ADCmin was higher among patients with progressive disease than those with a partial treatment response. Simultaneous PET/MRI is a promising technology for the detection of neoplastic disease. There are inverse correlations between SUVmax and ADCmin and between SUV ratio and ADCmin. Correlation coefficients between SUVmax and ADCmin from PET/MRI were similar to values obtained with SUVmax from the same-day PET/CT. Given that both SUV and ADC are related to malignancy and that the correlation between the two biomarkers is relatively weak, SUV and ADC values may offer complementary information to aid in determination of prognosis and treatment response. The combined tumoral biomarker, ratio between SUVmax and ADCmin, may be useful for assessing progressive disease versus partial treatment response.

Validity of multislice computerized tomography for diagnosis of maxillofacial fractures using an independent workstation.

PubMed

Dos Santos, Denise Takehana; Costa e Silva, Adriana Paula Andrade; Vannier, Michael Walter; Cavalcanti, Marcelo Gusmão Paraiso

2004-12-01

The purpose of this study was to demonstrate the sensitivity and specificity of multislice computerized tomography (CT) for diagnosis of maxillofacial fractures following specific protocols using an independent workstation. The study population consisted of 56 patients with maxillofacial fractures who were submitted to a multislice CT. The original data were transferred to an independent workstation using volumetric imaging software to generate axial images and simultaneous multiplanar (MPR) and 3-dimensional (3D-CT) volume rendering reconstructed images. The images were then processed and interpreted by 2 examiners using the following protocols independently of each other: axial, MPR/axial, 3D-CT images, and the association of axial/MPR/3D images. The clinical/surgical findings were considered the gold standard corroborating the diagnosis of the fractures and their anatomic localization. The statistical analysis was carried out using validity and chi-squared tests. The association of axial/MPR/3D images indicated a higher sensitivity (range 95.8%) and specificity (range 99%) than the other methods regarding the analysis of all regions. CT imaging demonstrated high specificity and sensitivity for maxillofacial fractures. The association of axial/MPR/3D-CT images added important information in relationship to other CT protocols.

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose

PubMed Central

Wenz, Holger; Maros, Máté E.; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O.; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

2015-01-01

Objectives To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. Methods 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Results Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024). Subjective image quality improved with increasing IR levels. Conclusion Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels. PMID:26288186

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

2015-01-01

To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024). Subjective image quality improved with increasing IR levels. Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.

Application of 3-Dimensional Printing in a Case of Osteogenesis Imperfecta for Patient Education, Anatomic Understanding, Preoperative Planning, and Intraoperative Evaluation.

PubMed

Eisenmenger, Laura B; Wiggins, Richard H; Fults, Daniel W; Huo, Eugene J

2017-11-01

The techniques and applications of 3-dimensional (3D) printing have progressed at a fast pace. In the last 10 years, there has been significant progress in applying this technology to medical applications. We present a case of osteogenesis imperfecta in which treatment was aided by prospectively using patient-specific, anatomically accurate 3D prints of the calvaria. The patient-specific, anatomically accurate 3D prints were used in the clinic and in the operating room to augment patient education, improve surgical decision making, and enhance preoperative planning. A 41-year-old woman with osteogenesis imperfecta and an extensive neurosurgical history presented for cranioplasty revision. Computed tomography (CT) data obtained as part of routine preoperative imaging were processed into a 3D model. The 3D patient-specific models were used in the clinic for patient education and in the operating room for preoperative visualization, planning, and intraoperative evaluation of anatomy. The patient reported the 3D models improved her understanding and comfort with the planned surgery when compared with discussing the procedure with the neurosurgeon or viewing the CT images with a neuroradiologist. The neurosurgeon reported an improved understanding of the patient's anatomy and potential cause of patient symptoms as well as improved preoperative planning compared with viewing the CT imaging alone. The neurosurgeon also reported an improvement in the planned surgical approach with a better intraoperative visualization and confirmation of the regions of planned calvarial resection. The use of patient-specific, anatomically accurate 3D prints may improve patient education, surgeon understanding and visualization, preoperative decision making, and intraoperative management. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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.

Imaging Lung Function in Mice Using SPECT/CT and Per-Voxel Analysis

PubMed Central

Jobse, Brian N.; Rhem, Rod G.; McCurry, Cory A. J. R.; Wang, Iris Q.; Labiris, N. Renée

2012-01-01

Chronic lung disease is a major worldwide health concern but better tools are required to understand the underlying pathologies. Ventilation/perfusion (V/Q) single photon emission computed tomography (SPECT) with per-voxel analysis allows for non-invasive measurement of regional lung function. A clinically adapted V/Q methodology was used in healthy mice to investigate V/Q relationships. Twelve week-old mice were imaged to describe normal lung function while 36 week-old mice were imaged to determine how age affects V/Q. Mice were ventilated with Technegas™ and injected with 99mTc-macroaggregated albumin to trace ventilation and perfusion, respectively. For both processes, SPECT and CT images were acquired, co-registered, and quantitatively analyzed. On a per-voxel basis, ventilation and perfusion were moderately correlated (R = 0.58±0.03) in 12 week old animals and a mean log(V/Q) ratio of −0.07±0.01 and standard deviation of 0.36±0.02 were found, defining the extent of V/Q matching. In contrast, 36 week old animals had significantly increased levels of V/Q mismatching throughout the periphery of the lung. Measures of V/Q were consistent across healthy animals and differences were observed with age demonstrating the capability of this technique in quantifying lung function. Per-voxel analysis and the ability to non-invasively assess lung function will aid in the investigation of chronic lung disease models and drug efficacy studies. PMID:22870297

Experimental Evaluation of a Deformable Registration Algorithm for Motion Correction in PET-CT Guided Biopsy.

PubMed

Khare, Rahul; Sala, Guillaume; Kinahan, Paul; Esposito, Giuseppe; Banovac, Filip; Cleary, Kevin; Enquobahrie, Andinet

2013-01-01

Positron emission tomography computed tomography (PET-CT) images are increasingly being used for guidance during percutaneous biopsy. However, due to the physics of image acquisition, PET-CT images are susceptible to problems due to respiratory and cardiac motion, leading to inaccurate tumor localization, shape distortion, and attenuation correction. To address these problems, we present a method for motion correction that relies on respiratory gated CT images aligned using a deformable registration algorithm. In this work, we use two deformable registration algorithms and two optimization approaches for registering the CT images obtained over the respiratory cycle. The two algorithms are the BSpline and the symmetric forces Demons registration. In the first optmization approach, CT images at each time point are registered to a single reference time point. In the second approach, deformation maps are obtained to align each CT time point with its adjacent time point. These deformations are then composed to find the deformation with respect to a reference time point. We evaluate these two algorithms and optimization approaches using respiratory gated CT images obtained from 7 patients. Our results show that overall the BSpline registration algorithm with the reference optimization approach gives the best results.

CT-assisted agile manufacturing

NASA Astrophysics Data System (ADS)

Stanley, James H.; Yancey, Robert N.

1996-11-01

The next century will witness at least two great revolutions in the way goods are produced. First, workers will use the medium of virtual reality in all aspects of marketing, research, development, prototyping, manufacturing, sales and service. Second, market forces will drive manufacturing towards small-lot production and just-in-time delivery. Already, we can discern the merging of these megatrends into what some are calling agile manufacturing. Under this new paradigm, parts and processes will be designed and engineered within the mind of a computer, tooled and manufactured by the offspring of today's rapid prototyping equipment, and evaluated for performance and reliability by advanced nondestructive evaluation (NDE) techniques and sophisticated computational models. Computed tomography (CT) is the premier example of an NDE method suitable for future agile manufacturing activities. It is the only modality that provides convenient access to the full suite of engineering data that users will need to avail themselves of computer- aided design, computer-aided manufacturing, and computer- aided engineering capabilities, as well as newly emerging reverse engineering, rapid prototyping and solid freeform fabrication technologies. As such, CT is assured a central, utilitarian role in future industrial operations. An overview of this exciting future for industrial CT is presented.

TU-AB-207A-03: Image Quality, Dose, and Clinical Applications

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

Dong, F.

Practicing medical physicists are often time charged with the tasks of evaluating and troubleshooting complex image quality issues related to CT scanners. This course will equip them with a solid and practical understanding of common CT imaging chain and its major components with emphasis on acquisition physics and hardware, reconstruction, artifacts, image quality, dose, and advanced clinical applications. The core objective is to explain the effects of these major system components on the image quality. This course will not focus on the rapid-changing advanced technologies given the two-hour time limit, but the fundamental principles discussed in this course may facilitatemore » better understanding of those more complicated technologies. The course will begin with an overview of CT acquisition physics and geometry. X-ray tube and CT detector are important acquisition hardware critical to the overall image quality. Each of these two subsystems consists of several major components. An in-depth description of the function and failure modes of these components will be provided. Examples of artifacts related to these failure modes will be presented: off-focal radiation, tube arcing, heel effect, oil bubble, offset drift effect, cross-talk effect, and bad pixels. The fundamentals of CT image reconstruction will first be discussed on an intuitive level. Approaches that do not require rigorous derivation of mathematical formulations will be presented. This is followed by a detailed derivation of the Fourier slice theorem: the foundation of the FBP algorithm. FBP for parallel-beam, fan-beam, and cone-beam geometries will be discussed. To address the issue of radiation dose related to x-ray CT, recent advances in iterative reconstruction, their advantages, and clinical applications will also be described. Because of the nature of fundamental physics and mathematics, limitations in data acquisition, and non-ideal conditions of major system components, image artifact often arise in the reconstructed images. Because of the limited scope of this course, only major imaging artifacts, their appearance, and possible mitigation and corrections will be discussed. Assessment of the performance of a CT scanner is a complicated subject. Procedures to measure common image quality metrics such as high contrast spatial resolution, low contrast detectability, and slice profile will be described. The reason why these metrics used for FBP may not be sufficient for statistical iterative reconstruction will be explained. Optimizing radiation dose requires comprehension of CT dose metrics. This course will briefly describe various dose metrics, and interaction with acquisition parameters and patient habitus. CT is among the most frequently used imaging tools due to its superior image quality, easy to operate, and a broad range of applications. This course will present several interesting CT applications such as a mobile CT unit on an ambulance for stroke patients, low dose lung cancer screening, and single heartbeat cardiac CT. Learning Objectives: Understand the function and impact of major components of X-ray tube on the image quality. Understand the function and impact of major components of CT detector on the image quality. Be familiar with the basic procedure of CT image reconstruction. Understand the effect of image reconstruction on CT image quality and artifacts. Understand the root causes of common CT image artifacts. Be familiar with image quality metrics especially high and low contrast resolution, noise power spectrum, slice sensitivity profile, etc. Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction. Be familiar with various CT dose metrics and their interaction with acquisition parameters. New development in advanced CT clinical applications. JH: Employee of GE Healthcare. FD: No disclosure.; J. Hsieh, Jiang Hsieh is an employee of GE Healthcare.« less

Three-dimensional imaging modalities in endodontics

PubMed Central

Mao, Teresa

2014-01-01

Recent research in endodontics has highlighted the need for three-dimensional imaging in the clinical arena as well as in research. Three-dimensional imaging using computed tomography (CT) has been used in endodontics over the past decade. Three types of CT scans have been studied in endodontics, namely cone-beam CT, spiral CT, and peripheral quantitative CT. Contemporary endodontics places an emphasis on the use of cone-beam CT for an accurate diagnosis of parameters that cannot be visualized on a two-dimensional image. This review discusses the role of CT in endodontics, pertaining to its importance in the diagnosis of root canal anatomy, detection of peri-radicular lesions, diagnosis of trauma and resorption, presurgical assessment, and evaluation of the treatment outcome. PMID:25279337

Computer aided diagnosis based on medical image processing and artificial intelligence methods

NASA Astrophysics Data System (ADS)

Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

2006-12-01

Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

Radiologic and functional evaluation of electrode dislocation from the scala tympani to the scala vestibuli in patients with cochlear implants.

PubMed

Fischer, N; Pinggera, L; Weichbold, V; Dejaco, D; Schmutzhard, J; Widmann, G

2015-02-01

Localization of the electrode after cochlear implantation seems to have an impact on auditory outcome, and conebeam CT has emerged as a reliable method for visualizing the electrode array position within the cochlea. The aim of this retrospective study was to evaluate the frequency and clinical impact of scalar dislocation of various electrodes and surgical approaches and to evaluate its influence on auditory outcome. This retrospective single-center study analyzed a consecutive series of 63 cochlear implantations with various straight electrodes. The placement of the electrode array was evaluated by using multiplanar reconstructed conebeam CT images. For the auditory outcome, we compared the aided hearing thresholds and the charge units of maximum comfortable loudness level at weeks 6, 12, and 24 after implantation. In 7.9% of the cases, the electrode array showed scalar dislocation. In all cases, the electrode array penetrated the basal membrane within 45° of the electrode insertion. All 3 cases of cochleostomy were dislocated in the first 45° segment. No hearing differences were noted, but the charge units of maximum comfortable loudness level seemed to increase with time in patients with dislocations. The intracochlear dislocation rate of various straight electrodes detected by conebeam CT images is relatively low. Scalar dislocation may not negatively influence the hearing threshold but may require an increase of the necessary stimulus charge and should be reported by the radiologist. © 2015 by American Journal of Neuroradiology.

A micro X-ray computed tomography dataset of South African hermit crabs (Crustacea: Decapoda: Anomura: Paguroidea) containing scans of two rare specimens and three recently described species.

PubMed

Landschoff, Jannes; Du Plessis, Anton; Griffiths, Charles L

2018-04-01

Along with the conventional deposition of physical types at natural history museums, the deposition of 3-dimensional (3D) image data has been proposed for rare and valuable museum specimens, such as irreplaceable type material. Micro computed tomography (μCT) scan data of 5 hermit crab species from South Africa, including rare specimens and type material, depicted main identification characteristics of calcified body parts. However, low-image contrasts, especially in larger (>50 mm total length) specimens, did not allow sufficient 3D reconstructions of weakly calcified and fine characteristics, such as soft tissue of the pleon, mouthparts, gills, and setation. Reconstructions of soft tissue were sometimes possible, depending on individual sample and scanning characteristics. The raw data of seven scans are publicly available for download from the GigaDB repository. Calcified body parts visualized from μCT data can aid taxonomic validation and provide additional, virtual deposition of rare specimens. The use of a nondestructive, nonstaining μCT approach for taxonomy, reconstructions of soft tissue structures, microscopic spines, and setae depend on species characteristics. Constrained to these limitations, the presented dataset can be used for future morphological studies. However, our virtual specimens will be most valuable to taxonomists who can download a digital avatar for 3D examination. Simultaneously, in the event of physical damage to or loss of the original physical specimen, this dataset serves as a vital insurance policy.

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-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

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

Niemkiewicz, J; Palmiotti, A; Miner, M

2014-06-01

Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU valuesmore » were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation treatment planning accuracy.« 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

Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images

PubMed Central

Ebadi, Ashkan; Dalboni da Rocha, Josué L.; Nagaraju, Dushyanth B.; Tovar-Moll, Fernanda; Bramati, Ivanei; Coutinho, Gabriel; Sitaram, Ranganatha; Rashidi, Parisa

2017-01-01

The human brain is a complex network of interacting regions. The gray matter regions of brain are interconnected by white matter tracts, together forming one integrative complex network. In this article, we report our investigation about the potential of applying brain connectivity patterns as an aid in diagnosing Alzheimer's disease and Mild Cognitive Impairment (MCI). We performed pattern analysis of graph theoretical measures derived from Diffusion Tensor Imaging (DTI) data representing structural brain networks of 45 subjects, consisting of 15 patients of Alzheimer's disease (AD), 15 patients of MCI, and 15 healthy subjects (CT). We considered pair-wise class combinations of subjects, defining three separate classification tasks, i.e., AD-CT, AD-MCI, and CT-MCI, and used an ensemble classification module to perform the classification tasks. Our ensemble framework with feature selection shows a promising performance with classification accuracy of 83.3% for AD vs. MCI, 80% for AD vs. CT, and 70% for MCI vs. CT. Moreover, our findings suggest that AD can be related to graph measures abnormalities at Brodmann areas in the sensorimotor cortex and piriform cortex. In this way, node redundancy coefficient and load centrality in the primary motor cortex were recognized as good indicators of AD in contrast to MCI. In general, load centrality, betweenness centrality, and closeness centrality were found to be the most relevant network measures, as they were the top identified features at different nodes. The present study can be regarded as a “proof of concept” about a procedure for the classification of MRI markers between AD dementia, MCI, and normal old individuals, due to the small and not well-defined groups of AD and MCI patients. Future studies with larger samples of subjects and more sophisticated patient exclusion criteria are necessary toward the development of a more precise technique for clinical diagnosis. PMID:28293162

Non-contrast CT at comparable dose to an abdominal radiograph in patients with acute renal colic; impact of iterative reconstruction on image quality and diagnostic performance.

PubMed

McLaughlin, P D; Murphy, K P; Hayes, S A; Carey, K; Sammon, J; Crush, L; O'Neill, F; Normoyle, B; McGarrigle, A M; Barry, J E; Maher, M M

2014-04-01

The aim was to assess the performance of low-dose non-contrast CT of the urinary tract (LD-CT) acquired at radiation exposures close to that of abdominal radiography using adaptive statistical iterative reconstruction (ASiR). Thirty-three patients with clinically suspected renal colic were prospectively included. Conventional dose (CD-CT) and LD-CT data sets were contemporaneously acquired. LD-CT images were reconstructed with 40 %, 70 % and 90 % ASiR. Image quality was subjectively and objectively measured. Images were also clinically interpreted. Mean ED was 0.48 ± 0.07 mSv for LD-CT compared with 4.43 ± 3.14 mSv for CD-CT. Increasing the percentage ASiR resulted in a step-wise reduction in mean objective noise (p < 0.001 for all comparisons). Seventy % ASiR LD-CT images had higher diagnostic acceptability and spatial resolution than 90 % ASiR LD-CT images (p < 0.001). Twenty-seven calculi (diameter = 5.5 ± 1.7 mm), including all ureteric stones, were correctly identified using 70 % ASiR LD-CT with two false positives and 16 false negatives (diameter = 2.3 ± 0.7 mm) equating to a sensitivity and specificity of 72 % and 94 %. Seventy % ASiR LD-CT had a sensitivity and specificity of 87 % and 100 % for detection of calculi >3 mm. Reconstruction of LD-CT images with 70 % ASiR resulted in superior image quality than FBP, 40 % ASIR and 90 % ASIR. LD-CT with ASIR demonstrates high sensitivity and specificity for detection of calculi >3 mm. • Low-dose CT studies for urinary calculus detection were performed with a mean dose of 0.48 ± 0.07 mSv • Low-dose CT with 70 % ASiR detected calculi >3 mm with a sensitivity and specificity of 87 % and 100 % • Reconstruction with 70 % ASiR was superior to filtered back projection, 40 % ASiR and 90 % ASiR images.

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

SU-E-J-86: Lobar Lung Function Quantification by PET Galligas and CT Ventilation Imaging in Lung Cancer Patients

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

Eslick, E; Kipritidis, J; Keall, P

2014-06-01

Purpose: The purpose of this study was to quantify the lobar lung function using the novel PET Galligas ([68Ga]-carbon nanoparticle) ventilation imaging and the investigational CT ventilation imaging in lung cancer patients pre-treatment. Methods: We present results on our first three lung cancer patients (2 male, mean age 78 years) as part of an ongoing ethics approved study. For each patient a PET Galligas ventilation (PET-V) image and a pair of breath hold CT images (end-exhale and end-inhale tidal volumes) were acquired using a Siemens Biograph PET CT. CT-ventilation (CT-V) images were created from the pair of CT images usingmore » deformable image registration (DIR) algorithms and the Hounsfield Unit (HU) ventilation metric. A comparison of ventilation quantification from each modality was done on the lobar level and the voxel level. A Bland-Altman plot was used to assess the difference in mean percentage contribution of each lobe to the total lung function between the two modalities. For each patient, a voxel-wise Spearmans correlation was calculated for the whole lungs between the two modalities. Results: The Bland-Altman plot demonstrated strong agreement between PET-V and CT-V for assessment of lobar function (r=0.99, p<0.001; range mean difference: −5.5 to 3.0). The correlation between PET-V and CT-V at the voxel level was moderate(r=0.60, p<0.001). Conclusion: This preliminary study on the three patients data sets demonstrated strong agreement between PET and CT ventilation imaging for the assessment of pre-treatment lung function at the lobar level. Agreement was only moderate at the level of voxel correlations. These results indicate that CT ventilation imaging has potential for assessing pre-treatment lobar lung function in lung cancer patients.« less

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.

Thoracic staging in lung cancer: prospective comparison of 18F-FDG PET/MR imaging and 18F-FDG PET/CT.

PubMed

Heusch, Philipp; Buchbender, Christian; Köhler, Jens; Nensa, Felix; Gauler, Thomas; Gomez, Benedikt; Reis, Henning; Stamatis, Georgios; Kühl, Hilmar; Hartung, Verena; Heusner, Till A

2014-03-01

Therapeutic decisions in non-small cell lung cancer (NSCLC) patients depend on the tumor stage. PET/CT with (18)F-FDG is widely accepted as the diagnostic standard of care. The purpose of this study was to compare a dedicated pulmonary (18)F-FDG PET/MR imaging protocol with (18)F-FDG PET/CT for primary and locoregional lymph node staging in NSCLC patients using histopathology as the reference. Twenty-two patients (12 men, 10 women; mean age ± SD, 65.1 ± 9.1 y) with histopathologically confirmed NSCLC underwent (18)F-FDG PET/CT, followed by (18)F-FDG PET/MR imaging, including a dedicated pulmonary MR imaging protocol. T and N staging according to the seventh edition of the American Joint Committee on Cancer staging manual was performed by 2 readers in separate sessions for (18)F-FDG PET/CT and PET/MR imaging, respectively. Results from histopathology were used as the standard of reference. The mean and maximum standardized uptake value (SUV(mean) and SUV(max), respectively) and maximum diameter of the primary tumor was measured and compared in (18)F-FDG PET/CT and PET/MR imaging. PET/MR imaging and (18)F-FDG PET/CT agreed on T stages in 16 of 16 of patients (100%). All patients were correctly staged by (18)F-FDG PET/CT and PET/MR (100%), compared with histopathology. There was no statistically significant difference between (18)F-FDG PET/CT and (18)F-FDG PET/MR imaging for lymph node metastases detection (P = 0.48). For definition of thoracic N stages, PET/MR imaging and (18)F-FDG PET/CT were concordant in 20 of 22 patients (91%). PET/MR imaging determined the N stage correctly in 20 of 22 patients (91%). (18)F-FDG PET/CT determined the N stage correctly in 18 of 22 patients (82%). The mean differences for SUV(mean) and SUV(max) of NSCLC in (18)F-FDG PET/MR imaging and (18)F-FDG PET/CT were 0.21 and -5.06. These differences were not statistically significant (P > 0.05). The SUV(mean) and SUV(max) measurements derived from (18)F-FDG PET/CT and (18)F-FDG PET/MR imaging exhibited a high correlation (R = 0.74 and 0.86, respectively; P < 0.0001). Size measurements showed an excellent correlation between (18)F-FDG PET/MR imaging and (18)F-FDG PET/CT (R = 0.99; P < 0.0001). The lower and upper limits of agreement between (18)F-FDG PET/CT and (18)F-FDG PET/MR imaging using Bland-Altman analysis were -2.34 to 3.89 for SUV(mean), -7.42 to 4.40 for SUV(max), and -0.59 to 0.83 for the tumor size, respectively. (18)F-FDG PET/MR imaging using a dedicated pulmonary MR imaging protocol, compared with (18)F-FDG PET/CT, does not provide advantages in thoracic staging in NSCLC patients.

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.

Adjunctive role of preoperative liver magnetic resonance imaging for potentially resectable pancreatic cancer.

PubMed

Kim, Hyoung Woo; Lee, Jong-Chan; Paik, Kyu-Hyun; Kang, Jingu; Kim, Young Hoon; Yoon, Yoo-Seok; Han, Ho-Seong; Kim, Jaihwan; Hwang, Jin-Hyeok

2017-06-01

The adjunctive role of magnetic resonance imaging of the liver before pancreatic ductal adenocarcinoma has been unclear. We evaluated whether the combination of hepatic magnetic resonance imaging with multidetector computed tomography using a pancreatic protocol (pCT) could help surgeons select appropriate candidates and decrease the risk of early recurrence. We retrospectively enrolled 167 patients in whom complete resection was achieved without grossly visible residual tumor; 102 patients underwent pCT alone (CT group) and 65 underwent both hepatic magnetic resonance imaging and pCT (magnetic resonance imaging group). By adding hepatic magnetic resonance imaging during preoperative evaluation, hepatic metastases were newly discovered in 3 of 58 patients (5%) without hepatic lesions on pCT and 17 of 53 patients (32%) with indeterminate hepatic lesions on pCT. Patients with borderline resectability, a tumor size >3 cm, or preoperative carbohydrate antigen 19-9 level >1,000 U/mL had a greater rate of hepatic metastasis on subsequent hepatic magnetic resonance imaging. Among 167 patients in whom R0/R1 resection was achieved, the median overall survival was 18.2 vs 24.7 months (P = .020) and the disease-free survival was 8.5 vs 10.0 months (P = .016) in the CT and magnetic resonance imaging groups, respectively (median follow-up, 18.3 months). Recurrence developed in 82 (80%) and 43 (66%) patients in the CT and magnetic resonance imaging groups, respectively. The cumulative hepatic recurrence rate was greater in the CT group than in the magnetic resonance imaging group (P < .001). Preoperative hepatic magnetic resonance imaging should be considered in patients with potentially resectable pancreatic ductal adenocarcinoma, especially those with high tumor burden. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

Evaluation of treatment response after chemoembolisation (TACE) in hepatocellular carcinoma using real time image fusion of contrast-enhanced ultrasound (CEUS) and computed tomography (CT)--preliminary results.

PubMed

Wobser, Hella; Wiest, Reiner; Salzberger, Bernd; Wohlgemuth, Walter Alexander; Stroszczynski, Christian; Jung, Ernst-Michael

2014-01-01

To evaluate treatment response of hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) with a new real-time imaging fusion technique of contrast-enhanced ultrasound (CEUS) with multi-slice detection computed tomography (CT) in comparison to conventional post-interventional follow-up. 40 patients with HCC (26 male, ages 46-81 years) were evaluated 24 hours after TACE using CEUS with ultrasound volume navigation and image fusion with CT compared to non-enhanced CT and follow-up contrast-enhanced CT after 6-8 weeks. Reduction of tumor vascularization to less than 25% was regarded as "successful" treatment, whereas reduction to levels >25% was considered as "partial" treatment response. Homogenous lipiodol retention was regarded as successful treatment in non-enhanced CT. Post-interventional image fusion of CEUS with CT was feasible in all 40 patients. In 24 patients (24/40), post-interventional image fusion with CEUS revealed residual tumor vascularity, that was confirmed by contrast-enhanced CT 6-8 weeks later in 24/24 patients. In 16 patients (16/40), post-interventional image fusion with CEUS demonstrated successful treatment, but follow-up CT detected residual viable tumor (6/16). Non-enhanced CT did not identify any case of treatment failure. Image fusion with CEUS assessed treatment efficacy with a specificity of 100%, sensitivity of 80% and a positive predictive value of 1 (negative predictive value 0.63). Image fusion of CEUS with CT allows a reliable, highly specific post-interventional evaluation of embolization response with good sensitivity without any further radiation exposure. It can detect residual viable tumor at early state, resulting in a close patient monitoring or re-therapy.

Analysis of deformable image registration accuracy using computational modeling

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

Zhong Hualiang; Kim, Jinkoo; Chetty, Indrin J.

2010-03-15

Computer aided modeling of anatomic deformation, allowing various techniques and protocols in radiation therapy to be systematically verified and studied, has become increasingly attractive. In this study the potential issues in deformable image registration (DIR) were analyzed based on two numerical phantoms: One, a synthesized, low intensity gradient prostate image, and the other a lung patient's CT image data set. Each phantom was modeled with region-specific material parameters with its deformation solved using a finite element method. The resultant displacements were used to construct a benchmark to quantify the displacement errors of the Demons and B-Spline-based registrations. The results showmore » that the accuracy of these registration algorithms depends on the chosen parameters, the selection of which is closely associated with the intensity gradients of the underlying images. For the Demons algorithm, both single resolution (SR) and multiresolution (MR) registrations required approximately 300 iterations to reach an accuracy of 1.4 mm mean error in the lung patient's CT image (and 0.7 mm mean error averaged in the lung only). For the low gradient prostate phantom, these algorithms (both SR and MR) required at least 1600 iterations to reduce their mean errors to 2 mm. For the B-Spline algorithms, best performance (mean errors of 1.9 mm for SR and 1.6 mm for MR, respectively) on the low gradient prostate was achieved using five grid nodes in each direction. Adding more grid nodes resulted in larger errors. For the lung patient's CT data set, the B-Spline registrations required ten grid nodes in each direction for highest accuracy (1.4 mm for SR and 1.5 mm for MR). The numbers of iterations or grid nodes required for optimal registrations depended on the intensity gradients of the underlying images. In summary, the performance of the Demons and B-Spline registrations have been quantitatively evaluated using numerical phantoms. The results show that parameter selection for optimal accuracy is closely related to the intensity gradients of the underlying images. Also, the result that the DIR algorithms produce much lower errors in heterogeneous lung regions relative to homogeneous (low intensity gradient) regions, suggests that feature-based evaluation of deformable image registration accuracy must be viewed cautiously.« less

Patient satisfaction with the consent discussion is not improved by showing patients their computed tomography or angiography images before they undergo vascular surgery.

PubMed

LeBlanc, Dominic; Power, Adam H; DeRose, Guy; Duncan, Audra; Dubois, Luc

2018-05-18

Patient-based decision aids and other multimedia tools have been developed to help enrich the preoperative discussion between surgeon and patient. Use of these tools, however, can be time-consuming and logistically challenging. We investigated whether simply showing patients their images from preoperative computed tomography (CT) or angiography would improve patients' satisfaction with the preoperative discussion. We also examined whether this improved the patient's understanding and trust and whether it contributed to increased preoperative anxiety. Patients undergoing either elective abdominal aortic aneurysm repair or lower limb revascularization were randomly assigned to either standard perioperative discussion or perioperative discussion and review of images (CT image or angiogram). Randomization was concealed and stratified by surgeon. Primary outcome was patient satisfaction with the preoperative discussion as measured by a validated 7-item scale (score, 0-28), with higher scores indicating improved satisfaction. Secondary outcomes included patient understanding, patient anxiety, patient trust, and length of preoperative discussion. Scores were compared using t-test. Overall, 51 patients were randomized, 25 to the intervention arm (discussion and imaging) and 26 to the control arm. Most patients were male (69%), and the average age was 70 years. Forty percent of patients underwent abdominal aortic aneurysm repair, whereas 60% underwent lower limb revascularization. Patient satisfaction with the discussion was generally high, with no added improvement when preoperative images were reviewed (mean score, 24.9 ± 3.02 vs 24.8 ± 2.93; P = .88). Similarly, there was no difference in the patient's anxiety, level of trust, or understanding when the imaging review was compared with standard discussion. There was a trend toward longer preoperative discussions in the group that underwent imaging review (8.18 vs 6.35 minutes; P = .07). Showing patients their CT or angiography images during the preoperative discussion does not improve the patient's satisfaction with the consent discussion. Similarly, there was no effect on the patient's trust, understanding, or anxiety level. Our conclusions are limited by the lack of a standardized measure of patient understanding and not measuring outcomes postoperatively, both of which should be considered in future studies. Copyright © 2018 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

PubMed

Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

2014-01-01

The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

New Abstraction Networks and a New Visualization Tool in Support of Auditing the SNOMED CT Content

PubMed Central

Geller, James; Ochs, Christopher; Perl, Yehoshua; Xu, Junchuan

2012-01-01

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT. PMID:23304293

New abstraction networks and a new visualization tool in support of auditing the SNOMED CT content.

PubMed

Geller, James; Ochs, Christopher; Perl, Yehoshua; Xu, Junchuan

2012-01-01

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED 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).

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

Integrated image presentation of transmission and fluorescent X-ray CT using synchrotron radiation

NASA Astrophysics Data System (ADS)

Zeniya, T.; Takeda, T.; Yu, Q.; Hasegawa, Y.; Hyodo, K.; Yuasa, T.; Hiranaka, Y.; Itai, Y.; Akatsuka, T.

2001-07-01

We have developed a computed tomography (CT) system with synchrotron radiation (SR) to detect fluorescent X-rays and transmitted X-rays simultaneously. Both SR transmission X-ray CT (SR-TXCT) and SR fluorescent X-ray CT (SR-FXCT) can describe cross-sectional images with high spatial and contrast resolutions as compared to conventional CT. TXCT gives morphological information and FXCT gives functional information of organs. So, superposed display system for SR-FXCT and SR-TXCT images has been developed for clinical diagnosis with higher reliability. Preliminary experiment with brain phantom was carried out and the superposition of both images was performed. The superposed SR-CT image gave us both functional and morphological information easily with high reliability, thus demonstrating the usefulness of this system.

Comparison of CT enterography and MR enterography imaging features of active Crohn disease in children and adolescents.

PubMed

Gale, Heather I; Sharatz, Steven M; Taphey, Mayureewan; Bradley, William F; Nimkin, Katherine; Gee, Michael S

2017-09-01

Assessment for active Crohn disease by CT enterography and MR enterography relies on identifying mural and perienteric imaging features. To evaluate the performance of established imaging features of active Crohn disease in children and adolescents on CT and MR enterography compared with histological reference. We included patients ages 18 years and younger who underwent either CT or MR enterography from 2007 to 2014 and had endoscopic biopsy within 28 days of imaging. Two pediatric radiologists blinded to the histological results reviewed imaging studies and scored the bowel for the presence or absence of mural features (wall thickening >3 mm, mural hyperenhancement) and perienteric features (mesenteric hypervascularity, edema, fibrofatty proliferation and lymphadenopathy) of active disease. We performed univariate analysis and multivariate logistic regression to compare imaging features with histological reference. We evaluated 452 bowel segments (135 from CT enterography, 317 from MR enterography) from 84 patients. Mural imaging features had the highest association with active inflammation both for MR enterography (wall thickening had 80% accuracy, 69% sensitivity and 91% specificity; mural hyperenhancement had 78%, 53% and 96%, respectively) and CT enterography (wall thickening had 84% accuracy, 72% sensitivity and 91% specificity; mural hyperenhancement had 76%, 51% and 91%, respectively), with perienteric imaging features performing significantly worse on MR enterography relative to CT enterography (P < 0.001). Mural features are predictors of active inflammation for both CT and MR enterography, while perienteric features can be distinguished better on CT enterography compared with MR enterography. This likely reflects the increased conspicuity of the mesentery on CT enterography and suggests that mural features are the most reliable imaging features of active Crohn disease in children and adolescents.

Integration of prior CT into CBCT reconstruction for improved image quality via reconstruction of difference: first patient studies

NASA Astrophysics Data System (ADS)

Zhang, Hao; Gang, Grace J.; Lee, Junghoon; Wong, John; Stayman, J. Webster

2017-03-01

Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.

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.

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.

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

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.

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

PubMed

Xiang, Lei; Wang, Qian; Nie, Dong; Zhang, Lichi; Jin, Xiyao; Qiao, Yu; Shen, Dinggang

2018-07-01

Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted magnetic resonance (MR) image is of great importance, although the mapping between them is highly complex due to large gaps of appearances of the two modalities. In this work, we aim to tackle this MR-to-CT synthesis task by a novel deep embedding convolutional neural network (DECNN). Specifically, we generate the feature maps from MR images, and then transform these feature maps forward through convolutional layers in the network. We can further compute a tentative CT synthesis from the midway of the flow of feature maps, and then embed this tentative CT synthesis result back to the feature maps. This embedding operation results in better feature maps, which are further transformed forward in DECNN. After repeating this embedding procedure for several times in the network, we can eventually synthesize a final CT image in the end of the DECNN. We have validated our proposed method on both brain and prostate imaging datasets, by also comparing with the state-of-the-art methods. Experimental results suggest that our DECNN (with repeated embedding operations) demonstrates its superior performances, in terms of both the perceptive quality of the synthesized CT image and the run-time cost for synthesizing a CT image. Copyright © 2018. Published by Elsevier B.V.

Enhancing 18F-FDG-PET/CT analysis in lung cancer patients. Is CT-CT image fusion helpful in predicting pleural involvement? A pilot study.

PubMed

Kapfhammer, A; Winkens, T; Lesser, T; Reissig, A; Steinert, M; Freesmeyer, M

2015-01-01

To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/CT for lung cancer staging. Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semi-transparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.

Subjective and objective comparisons of image quality between ultra-high-resolution CT and conventional area detector CT in phantoms and cadaveric human lungs.

PubMed

Yanagawa, Masahiro; Hata, Akinori; Honda, Osamu; Kikuchi, Noriko; Miyata, Tomo; Uranishi, Ayumi; Tsukagoshi, Shinsuke; Tomiyama, Noriyuki

2018-05-29

To compare the image quality of the lungs between ultra-high-resolution CT (U-HRCT) and conventional area detector CT (AD-CT) images. Image data of slit phantoms (0.35, 0.30, and 0.15 mm) and 11 cadaveric human lungs were acquired by both U-HRCT and AD-CT devices. U-HRCT images were obtained with three acquisition modes: normal mode (U-HRCT N : 896 channels, 0.5 mm × 80 rows; 512 matrix), super-high-resolution mode (U-HRCT SHR : 1792 channels, 0.25 mm × 160 rows; 1024 matrix), and volume mode (U-HRCT SHR-VOL : non-helical acquisition with U-HRCT SHR ). AD-CT images were obtained with the same conditions as U-HRCT N . Three independent observers scored normal anatomical structures (vessels and bronchi), abnormal CT findings (faint nodules, solid nodules, ground-glass opacity, consolidation, emphysema, interlobular septal thickening, intralobular reticular opacities, bronchovascular bundle thickening, bronchiectasis, and honeycombing), noise, artifacts, and overall image quality on a 3-point scale (1 = worst, 2 = equal, 3 = best) compared with U-HRCT N . Noise values were calculated quantitatively. U-HRCT could depict a 0.15-mm slit. Both U-HRCT SHR and U-HRCT SHR-VOL significantly improved visualization of normal anatomical structures and abnormal CT findings, except for intralobular reticular opacities and reduced artifacts, compared with AD-CT (p < 0.014). Visually, U-HRCT SHR-VOL has less noise than U-HRCT SHR and AD-CT (p < 0.00001). Quantitative noise values were significantly higher in the following order: U-HRCT SHR (mean, 30.41), U-HRCT SHR-VOL (26.84), AD-CT (16.03), and U-HRCT N (15.14) (p < 0.0001). U-HRCT SHR and U-HRCT SHR-VOL resulted in significantly higher overall image quality than AD-CT and were almost equal to U-HRCT N (p < 0.0001). Both U-HRCT SHR and U-HRCT SHR-VOL can provide higher image quality than AD-CT, while U-HRCT SHR-VOL was less noisy than U-HRCT SHR . • Ultra-high-resolution CT (U-HRCT) can improve spatial resolution. • U-HRCT can reduce streak and dark band artifacts. • U-HRCT can provide higher image quality than conventional area detector CT. • In U-HRCT, the volume mode is less noisy than the super-high-resolution mode. • U-HRCT may provide more detailed information about the lung anatomy and pathology.

Automatic detection of axillary lymphadenopathy on CT scans of untreated chronic lymphocytic leukemia patients

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Hua, Jeremy; Chellappa, Vivek; Petrick, Nicholas; Sahiner, Berkman; Farooqui, Mohammed; Marti, Gerald; Wiestner, Adrian; Summers, Ronald M.

2012-03-01

Patients with chronic lymphocytic leukemia (CLL) have an increased frequency of axillary lymphadenopathy. Pretreatment CT scans can be used to upstage patients at the time of presentation and post-treatment CT scans can reduce the number of complete responses. In the current clinical workflow, the detection and diagnosis of lymph nodes is usually performed manually by examining all slices of CT images, which can be time consuming and highly dependent on the observer's experience. A system for automatic lymph node detection and measurement is desired. We propose a computer aided detection (CAD) system for axillary lymph nodes on CT scans in CLL patients. The lung is first automatically segmented and the patient's body in lung region is extracted to set the search region for lymph nodes. Multi-scale Hessian based blob detection is then applied to detect potential lymph nodes within the search region. Next, the detected potential candidates are segmented by fast level set method. Finally, features are calculated from the segmented candidates and support vector machine (SVM) classification is utilized for false positive reduction. Two blobness features, Frangi's and Li's, are tested and their free-response receiver operating characteristic (FROC) curves are generated to assess system performance. We applied our detection system to 12 patients with 168 axillary lymph nodes measuring greater than 10 mm. All lymph nodes are manually labeled as ground truth. The system achieved sensitivities of 81% and 85% at 2 false positives per patient for Frangi's and Li's blobness, respectively.