Multi Length Scale Imaging of Flocculated Estuarine Sediments; Insights into their Complex 3D Structure

NASA Astrophysics Data System (ADS)

Wheatland, Jonathan; Bushby, Andy; Droppo, Ian; Carr, Simon; Spencer, Kate

2015-04-01

Suspended estuarine sediments form flocs that are compositionally complex, fragile and irregularly shaped. The fate and transport of suspended particulate matter (SPM) is determined by the size, shape, density, porosity and stability of these flocs and prediction of SPM transport requires accurate measurements of these three-dimensional (3D) physical properties. However, the multi-scaled nature of flocs in addition to their fragility makes their characterisation in 3D problematic. Correlative microscopy is a strategy involving the spatial registration of information collected at different scales using several imaging modalities. Previously, conventional optical microscopy (COM) and transmission electron microscopy (TEM) have enabled 2-dimensional (2D) floc characterisation at the gross (> 1 µm) and sub-micron scales respectively. Whilst this has proven insightful there remains a critical spatial and dimensional gap preventing the accurate measurement of geometric properties and an understanding of how structures at different scales are related. Within life sciences volumetric imaging techniques such as 3D micro-computed tomography (3D µCT) and focused ion beam scanning electron microscopy [FIB-SEM (or FIB-tomography)] have been combined to characterise materials at the centimetre to micron scale. Combining these techniques with TEM enables an advanced correlative study, allowing material properties across multiple spatial and dimensional scales to be visualised. The aims of this study are; 1) to formulate an advanced correlative imaging strategy combining 3D µCT, FIB-tomography and TEM; 2) to acquire 3D datasets; 3) to produce a model allowing their co-visualisation; 4) to interpret 3D floc structure. To reduce the chance of structural alterations during analysis samples were first 'fixed' in 2.5% glutaraldehyde/2% formaldehyde before being embedding in Durcupan resin. Intermediate steps were implemented to improve contrast and remove pore water, achieved by the addition of heavy metal stains and washing samples in a series of ethanol solutions and acetone. Gross-scale characterisation involved scanning samples using a Nikon Metrology HM X 225 µCT. For micro-scale analysis a working surface was revealed by microtoming the sample. Ultrathin sections were then collected and analysed using a JEOL 1200 Ex II TEM, and FIB-tomography datasets obtained using an FEI Quanta 3D FIB-SEM. Finally, to locate the surface and relate TEM and FIB-tomography datasets to the original floc, samples were rescanned using the µCT. Image processing was initially conducted in ImageJ. Following this datasets were imported into Amira 5.5 where pixel intensity thresholding allowed particle-matrix boundaries to be defined. Using 'landmarks' datasets were then registered to enable their co-visualisation in 3D models. Analysis of registered datasets reveals the complex non-fractal nature of flocs, whose properties span several of orders of magnitude. Primary particles are organised into discrete 'bundles', the arrangement of which directly influences their gross morphology. This strategy, which allows the co-visualisation of spatially registered multi-scale 3D datasets, provides unique insights into the true nature floc which would other have been impossible.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Reliability of voxel gray values in cone beam computed tomography for preoperative implant planning assessment.

PubMed

Parsa, Azin; Ibrahim, Norliza; Hassan, Bassam; Motroni, Alessandro; van der Stelt, Paul; Wismeijer, Daniel

2012-01-01

To assess the reliability of cone beam computed tomography (CBCT) voxel gray value measurements using Hounsfield units (HU) derived from multislice computed tomography (MSCT) as a clinical reference (gold standard). Ten partially edentulous human mandibular cadavers were scanned by two types of computed tomography (CT) modalities: multislice CT and cone beam CT. On MSCT scans, eight regions of interest (ROI) designating the site for preoperative implant placement were selected in each mandible. The datasets from both CT systems were matched using a three-dimensional (3D) registration algorithm. The mean voxel gray values of the region around the implant sites were compared between MSCT and CBCT. Significant differences between the mean gray values obtained by CBCT and HU by MSCT were found. In all the selected ROIs, CBCT showed higher mean values than MSCT. A strong correlation (R=0.968) between mean voxel gray values of CBCT and mean HU of MSCT was determined. Voxel gray values from CBCT deviate from actual HU units. However, a strong linear correlation exists, which may permit deriving actual HU units from CBCT using linear regression models.

A correlative imaging based methodology for accurate quantitative assessment of bone formation in additive manufactured implants.

PubMed

Geng, Hua; Todd, Naomi M; Devlin-Mullin, Aine; Poologasundarampillai, Gowsihan; Kim, Taek Bo; Madi, Kamel; Cartmell, Sarah; Mitchell, Christopher A; Jones, Julian R; Lee, Peter D

2016-06-01

A correlative imaging methodology was developed to accurately quantify bone formation in the complex lattice structure of additive manufactured implants. Micro computed tomography (μCT) and histomorphometry were combined, integrating the best features from both, while demonstrating the limitations of each imaging modality. This semi-automatic methodology registered each modality using a coarse graining technique to speed the registration of 2D histology sections to high resolution 3D μCT datasets. Once registered, histomorphometric qualitative and quantitative bone descriptors were directly correlated to 3D quantitative bone descriptors, such as bone ingrowth and bone contact. The correlative imaging allowed the significant volumetric shrinkage of histology sections to be quantified for the first time (~15 %). This technique demonstrated the importance of location of the histological section, demonstrating that up to a 30 % offset can be introduced. The results were used to quantitatively demonstrate the effectiveness of 3D printed titanium lattice implants.

X-ray computed tomography datasets for forensic analysis of vertebrate fossils.

PubMed

Rowe, Timothy B; Luo, Zhe-Xi; Ketcham, Richard A; Maisano, Jessica A; Colbert, Matthew W

2016-06-07

We describe X-ray computed tomography (CT) datasets from three specimens recovered from Early Cretaceous lakebeds of China that illustrate the forensic interpretation of CT imagery for paleontology. Fossil vertebrates from thinly bedded sediments often shatter upon discovery and are commonly repaired as amalgamated mosaics grouted to a solid backing slab of rock or plaster. Such methods are prone to inadvertent error and willful forgery, and once required potentially destructive methods to identify mistakes in reconstruction. CT is an efficient, nondestructive alternative that can disclose many clues about how a specimen was handled and repaired. These annotated datasets illustrate the power of CT in documenting specimen integrity and are intended as a reference in applying CT more broadly to evaluating the authenticity of comparable fossils.

X-ray computed tomography datasets for forensic analysis of vertebrate fossils

PubMed Central

Rowe, Timothy B.; Luo, Zhe-Xi; Ketcham, Richard A.; Maisano, Jessica A.; Colbert, Matthew W.

2016-01-01

We describe X-ray computed tomography (CT) datasets from three specimens recovered from Early Cretaceous lakebeds of China that illustrate the forensic interpretation of CT imagery for paleontology. Fossil vertebrates from thinly bedded sediments often shatter upon discovery and are commonly repaired as amalgamated mosaics grouted to a solid backing slab of rock or plaster. Such methods are prone to inadvertent error and willful forgery, and once required potentially destructive methods to identify mistakes in reconstruction. CT is an efficient, nondestructive alternative that can disclose many clues about how a specimen was handled and repaired. These annotated datasets illustrate the power of CT in documenting specimen integrity and are intended as a reference in applying CT more broadly to evaluating the authenticity of comparable fossils. PMID:27272251

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

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

Klawikowski, S; Christian, J; Schott, D

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each dailymore » CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.« less

Visualization of conserved structures by fusing highly variable datasets.

PubMed

Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

2002-01-01

Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual Reality (VR) environment. The accuracy of the fusions was determined qualitatively by comparing the transformed atlas overlaid on the appropriate CT. It was examined for where the transformed structure atlas was incorrectly overlaid (false positive) and where it was incorrectly not overlaid (false negative). According to this method, fusions 1 and 2 were correct roughly 50-75% of the time, while fusions 3 and 4 were correct roughly 75-100%. The CT dataset augmented with transformed dataset was viewed arbitrarily in user-centered perspective stereo taking advantage of features such as scaling, windowing and volumetric region of interest selection. This process of auto-coloring conserved structures in variable datasets is a step toward the goal of a broader, standardized automatic structure visualization method for radiological data. If successful it would permit identification, visualization or deletion of structures in radiological data by semi-automatically applying canonical structure information to the radiological data (not just processing and visualization of the data's intrinsic dynamic range). More sophisticated selection of control points and patterns of warping may allow for more accurate transforms, and thus advances in visualization, simulation, education, diagnostics, and treatment planning.

SU-F-R-33: Can CT and CBCT Be Used Simultaneously for Radiomics Analysis

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

Luo, R; Wang, J; Zhong, H

2016-06-15

Purpose: To investigate whether CBCT and CT can be used in radiomics analysis simultaneously. To establish a batch correction method for radiomics in two similar image modalities. Methods: Four sites including rectum, bladder, femoral head and lung were considered as region of interest (ROI) in this study. For each site, 10 treatment planning CT images were collected. And 10 CBCT images which came from same site of same patient were acquired at first radiotherapy fraction. 253 radiomics features, which were selected by our test-retest study at rectum cancer CT (ICC>0.8), were calculated for both CBCT and CT images in MATLAB.more » Simple scaling (z-score) and nonlinear correction methods were applied to the CBCT radiomics features. The Pearson Correlation Coefficient was calculated to analyze the correlation between radiomics features of CT and CBCT images before and after correction. Cluster analysis of mixed data (for each site, 5 CT and 5 CBCT data are randomly selected) was implemented to validate the feasibility to merge radiomics data from CBCT and CT. The consistency of clustering result and site grouping was verified by a chi-square test for different datasets respectively. Results: For simple scaling, 234 of the 253 features have correlation coefficient ρ>0.8 among which 154 features haveρ>0.9 . For radiomics data after nonlinear correction, 240 of the 253 features have ρ>0.8 among which 220 features have ρ>0.9. Cluster analysis of mixed data shows that data of four sites was almost precisely separated for simple scaling(p=1.29 * 10{sup −7}, χ{sup 2} test) and nonlinear correction (p=5.98 * 10{sup −7}, χ{sup 2} test), which is similar to the cluster result of CT data (p=4.52 * 10{sup −8}, χ{sup 2} test). Conclusion: Radiomics data from CBCT can be merged with those from CT by simple scaling or nonlinear correction for radiomics analysis.« less

An exploration of the properties of the CORE problem list subset and how it facilitates the implementation of SNOMED CT

PubMed Central

Xu, Julia

2015-01-01

Objective Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) is the emergent international health terminology standard for encoding clinical information in electronic health records. The CORE Problem List Subset was created to facilitate the terminology’s implementation. This study evaluates the CORE Subset’s coverage and examines its growth pattern as source datasets are being incorporated. Methods Coverage of frequently used terms and the corresponding usage of the covered terms were assessed by “leave-one-out” analysis of the eight datasets constituting the current CORE Subset. The growth pattern was studied using a retrospective experiment, growing the Subset one dataset at a time and examining the relationship between the size of the starting subset and the coverage of frequently used terms in the incoming dataset. Linear regression was used to model that relationship. Results On average, the CORE Subset covered 80.3% of the frequently used terms of the left-out dataset, and the covered terms accounted for 83.7% of term usage. There was a significant positive correlation between the CORE Subset’s size and the coverage of the frequently used terms in an incoming dataset. This implies that the CORE Subset will grow at a progressively slower pace as it gets bigger. Conclusion The CORE Problem List Subset is a useful resource for the implementation of Systematized Nomenclature of Medicine Clinical Terms in electronic health records. It offers good coverage of frequently used terms, which account for a high proportion of term usage. If future datasets are incorporated into the CORE Subset, it is likely that its size will remain small and manageable. PMID:25725003

Advancements in automated tissue segmentation pipeline for contrast-enhanced CT scans of adult and pediatric patients

NASA Astrophysics Data System (ADS)

Somasundaram, Elanchezhian; Kaufman, Robert; Brady, Samuel

2017-03-01

The development of a random forests machine learning technique is presented for fully-automated neck, chest, abdomen, and pelvis tissue segmentation of CT images using Trainable WEKA (Waikato Environment for Knowledge Analysis) Segmentation (TWS) plugin of FIJI (ImageJ, NIH). The use of a single classifier model to segment six tissue classes (lung, fat, muscle, solid organ, blood/contrast agent, bone) in the CT images is studied. An automated unbiased scheme to sample pixels from the training images and generate a balanced training dataset over the seven classes is also developed. Two independent training datasets are generated from a pool of 4 adult (>55 kg) and 3 pediatric patients (<=55 kg) with 7 manually contoured slices for each patient. Classifier training investigated 28 image filters comprising a total of 272 features. Highly correlated and insignificant features are eliminated using Correlated Feature Subset (CFS) selection with Best First Search (BFS) algorithms in WEKA. The 2 training models (from the 2 training datasets) had 74 and 71 input training features, respectively. The study also investigated the effect of varying the number of trees (25, 50, 100, and 200) in the random forest algorithm. The performance of the 2 classifier models are evaluated on inter-patient intra-slice, intrapatient inter-slice and inter-patient inter-slice test datasets. The Dice similarity coefficients (DSC) and confusion matrices are used to understand the performance of the classifiers across the tissue segments. The effect of number of features in the training input on the performance of the classifiers for tissue classes with less than optimal DSC values is also studied. The average DSC values for the two training models on the inter-patient intra-slice test data are: 0.98, 0.89, 0.87, 0.79, 0.68, and 0.84, for lung, fat, muscle, solid organ, blood/contrast agent, and bone, respectively. The study demonstrated that a robust segmentation accuracy for lung, muscle and fat tissue classes. For solid-organ, blood/contrast and bone, the performance of the segmentation pipeline improved significantly by using the advanced capabilities of WEKA. However, further improvements are needed to reduce the noise in the segmentation.

Mutual-information-based registration for ultrasound and CT datasets

NASA Astrophysics Data System (ADS)

Firle, Evelyn A.; Wesarg, Stefan; Dold, Christian

2004-05-01

In many applications for minimal invasive surgery the acquisition of intra-operative medical images is helpful if not absolutely necessary. Especially for Brachytherapy imaging is critically important to the safe delivery of the therapy. Modern computed tomography (CT) and magnetic resonance (MR) scanners allow minimal invasive procedures to be performed under direct imaging guidance. However, conventional scanners do not have real-time imaging capability and are expensive technologies requiring a special facility. Ultrasound (U/S) is a much cheaper and one of the most flexible imaging modalities. It can be moved to the application room as required and the physician sees what is happening as it occurs. Nevertheless it may be easier to interpret these 3D intra-operative U/S images if they are used in combination with less noisier preoperative data such as CT. The purpose of our current investigation is to develop a registration tool for automatically combining pre-operative CT volumes with intra-operatively acquired 3D U/S datasets. The applied alignment procedure is based on the information theoretic approach of maximizing the mutual information of two arbitrary datasets from different modalities. Since the CT datasets include a much bigger field of view we introduced a bounding box to narrow down the region of interest within the CT dataset. We conducted a phantom experiment using a CIRS Model 53 U/S Prostate Training Phantom to evaluate the feasibility and accuracy of the proposed method.

Comparison of image registration based measures of regional lung ventilation from dynamic spiral CT with Xe-CT

PubMed Central

Ding, Kai; Cao, Kunlin; Fuld, Matthew K.; Du, Kaifang; Christensen, Gary E.; Hoffman, Eric A.; Reinhardt, Joseph M.

2012-01-01

Purpose: Regional lung volume change as a function of lung inflation serves as an index of parenchymal and airway status as well as an index of regional ventilation and can be used to detect pathologic changes over time. In this paper, the authors propose a new regional measure of lung mechanics—the specific air volume change by corrected Jacobian. The authors compare this new measure, along with two existing registration based measures of lung ventilation, to a regional ventilation measurement derived from xenon-CT (Xe-CT) imaging. Methods: 4DCT and Xe-CT datasets from four adult sheep are used in this study. Nonlinear, 3D image registration is applied to register an image acquired near end inspiration to an image acquired near end expiration. Approximately 200 annotated anatomical points are used as landmarks to evaluate registration accuracy. Three different registration based measures of regional lung mechanics are derived and compared: the specific air volume change calculated from the Jacobian (SAJ); the specific air volume change calculated by the corrected Jacobian (SACJ); and the specific air volume change by intensity change (SAI). The authors show that the commonly used SAI measure can be derived from the direct SAJ measure by using the air-tissue mixture model and assuming there is no tissue volume change between the end inspiration and end expiration datasets. All three ventilation measures are evaluated by comparing to Xe-CT estimates of regional ventilation. Results: After registration, the mean registration error is on the order of 1 mm. For cubical regions of interest (ROIs) in cubes with size 20 mm × 20 mm × 20 mm, the SAJ and SACJ measures show significantly higher correlation (linear regression, average r2 = 0.75 and r2 = 0.82) with the Xe-CT based measure of specific ventilation (sV) than the SAI measure. For ROIs in slabs along the ventral-dorsal vertical direction with size of 150 mm × 8 mm × 40 mm, the SAJ, SACJ, and SAI all show high correlation (linear regression, average r2 = 0.88, r2 = 0.92, and r2 = 0.87) with the Xe-CT based sV without significant differences when comparing between the three methods. The authors demonstrate a linear relationship between the difference of specific air volume change and difference of tissue volume in all four animals (linear regression, average r2 = 0.86). Conclusions: Given a deformation field by an image registration algorithm, significant differences between the SAJ, SACJ, and SAI measures were found at a regional level compared to the Xe-CT sV in four sheep that were studied. The SACJ introduced here, provides better correlations with Xe-CT based sV than the SAJ and SAI measures, thus providing an improved surrogate for regional ventilation. PMID:22894434

SU-F-BRF-10: Deformable MRI to CT Validation Employing Same Day Planning MRI for Surrogate Analysis

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

Padgett, K; Stoyanova, R; Johnson, P

Purpose: To compare rigid and deformable registrations of the prostate in the multi-modality setting (diagnostic-MRI to planning-CT) by utilizing a planning-MRI as a surrogate. The surrogate allows for the direct quantitative analysis which can be difficult in the multi-modality domain where intensity mapping differs. Methods: For ten subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day in which the planning CT was collected (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets.more » The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. The deformed MRI was then rigidly aligned to the planning MRI which was used as the surrogate for the planning-CT. Agreement between the two MRI datasets was scored using intensity based metrics including Pearson correlation and normalized mutual information, NMI. A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb and combined areas. A similar method was used to assess a rigid registration between the diagnostic-MRI and planning-CT. Results: Utilizing the NMI, the deformable registrations were superior to the rigid registrations in 9 of 10 cases demonstrating a 15.94% improvement (p-value < 0.001) within the combined area. The Pearson correlation showed similar results with the deformable registration superior in the same number of cases and demonstrating a 6.97% improvement (p-value <0.011). Conclusion: Validating deformable multi-modality registrations using spatial intensity based metrics is difficult due to the inherent differences in intensity mapping. This population provides an ideal testing ground for MRI to CT deformable registrations by obviating the need for multi-modality comparisons which are inherently more challenging. Deformable registrations generated in this work significantly outperformed rigid alignments. Research reported in this abstract was supported by the NIH National Cancer Institute R21CA153826 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer” and Bankhead-Coley Cancer Research Program 10BT-03 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer”.« less

18-Fluorodeoxy-Glucose Positron Emission Tomography- Computed Tomography (18-FDG-PET/CT) for Gross Tumor Volume (GTV) Delineation in Gastric Cancer Radiotherapy

PubMed

Dębiec, Kinga; Wydmański, Jerzy; Gorczewska, Izabela; Leszczyńska, Paulina; Gorczewski, Kamil; Leszczyński, Wojciech; d’Amico, Andrea; Kalemba, Michał

2017-11-26

Purpose: Evaluation of the 18-fluorodeoxy-glucose positron emission tomography-computed tomography (18-FDGPET/ CT) for gross tumor volume (GTV) delineation in gastric cancer patients undergoing radiotherapy. Methods: In this study, 29 gastric cancer patients (17 unresectable and 7 inoperable) were initially enrolled for radical chemoradiotherapy (45Gy/25 fractions + chemotherapy based on 5 fluorouracil) or radiotherapy alone (45Gy/25 fractions) with planning based on the 18-FDG-PET/CT images. Five patients were excluded due to excess blood glucose levels (1), false-negative positron emission tomography (1) and distant metastases revealed by 18-FDG-PET/CT (3). The analysis involved measurement of metabolic tumor volumes (MTVs) performed on PET/CT workstations. Different threshold levels of the standardized uptake value (SUV) and liver uptake were set to obtain MTVs. Secondly, GTVPET values were derived manually using the positron emission tomography (PET) dataset blinded to the computed tomography (CT) data. Subsequently, GTVCT values were delineated using a radiotherapy planning system based on the CT scans blinded to the PET data. The referenced GTVCT values were correlated with the GTVPET and were compared with a conformality index (CI). Results: The mean CI was 0.52 (range, 0.12-0.85). In 13/24 patients (54%), the GTVPET was larger than GTVCT, and in the remainder, GTVPET was smaller. Moreover, the cranio-caudal diameter of GTVPET in 16 cases (64%) was larger than that of GTVCT, smaller in 7 cases (29%), and unchanged in one case. Manual PET delineation (GTVPET) achieved the best correlation with GTVCT (Pearson correlation = 0.76, p <0.0001). Among the analyzed MTVs, a statistically significant correlation with GTVCT was revealed for MTV10%SUVmax (r = 0.63; p = 0.0014), MTVliv (r = 0.60; p = 0.0021), MTVSUV2.5 (r = 0.54; p = 0.0063); MTV20%SUVmax (r = 0.44; p = 0.0344); MTV30%SUVmax (r = 0.44; p = 0.0373). Conclusion: 18-FDG-PET/CT in gastric cancer radiotherapy planning may affect the GTV delineation. https://www.ncbi.nlm.nih.gov/pubmed/management

Regression models to predict hip joint centers in pathological hip population.

PubMed

Mantovani, Giulia; Ng, K C Geoffrey; Lamontagne, Mario

2016-02-01

The purpose was to investigate the validity of Harrington's and Davis's hip joint center (HJC) regression equations on a population affected by a hip deformity, (i.e., femoroacetabular impingement). Sixty-seven participants (21 healthy controls, 46 with a cam-type deformity) underwent pelvic CT imaging. Relevant bony landmarks and geometric HJCs were digitized from the images, and skin thickness was measured for the anterior and posterior superior iliac spines. Non-parametric statistical and Bland-Altman tests analyzed differences between the predicted HJC (from regression equations) and the actual HJC (from CT images). The error from Davis's model (25.0 ± 6.7 mm) was larger than Harrington's (12.3 ± 5.9 mm, p<0.001). There were no differences between groups, thus, studies on femoroacetabular impingement can implement conventional regression models. Measured skin thickness was 9.7 ± 7.0mm and 19.6 ± 10.9 mm for the anterior and posterior bony landmarks, respectively, and correlated with body mass index. Skin thickness estimates can be considered to reduce the systematic error introduced by surface markers. New adult-specific regression equations were developed from the CT dataset, with the hypothesis that they could provide better estimates when tuned to a larger adult-specific dataset. The linear models were validated on external datasets and using leave-one-out cross-validation techniques; Prediction errors were comparable to those of Harrington's model, despite the adult-specific population and the larger sample size, thus, prediction accuracy obtained from these parameters could not be improved. Copyright © 2015 Elsevier B.V. All rights reserved.

Automatic segmentation and co-registration of gated CT angiography datasets: measuring abdominal aortic pulsatility

NASA Astrophysics Data System (ADS)

Wentz, Robert; Manduca, Armando; Fletcher, J. G.; Siddiki, Hassan; Shields, Raymond C.; Vrtiska, Terri; Spencer, Garrett; Primak, Andrew N.; Zhang, Jie; Nielson, Theresa; McCollough, Cynthia; Yu, Lifeng

2007-03-01

Purpose: To develop robust, novel segmentation and co-registration software to analyze temporally overlapping CT angiography datasets, with an aim to permit automated measurement of regional aortic pulsatility in patients with abdominal aortic aneurysms. Methods: We perform retrospective gated CT angiography in patients with abdominal aortic aneurysms. Multiple, temporally overlapping, time-resolved CT angiography datasets are reconstructed over the cardiac cycle, with aortic segmentation performed using a priori anatomic assumptions for the aorta and heart. Visual quality assessment is performed following automatic segmentation with manual editing. Following subsequent centerline generation, centerlines are cross-registered across phases, with internal validation of co-registration performed by examining registration at the regions of greatest diameter change (i.e. when the second derivative is maximal). Results: We have performed gated CT angiography in 60 patients. Automatic seed placement is successful in 79% of datasets, requiring either no editing (70%) or minimal editing (less than 1 minute; 12%). Causes of error include segmentation into adjacent, high-attenuating, nonvascular tissues; small segmentation errors associated with calcified plaque; and segmentation of non-renal, small paralumbar arteries. Internal validation of cross-registration demonstrates appropriate registration in our patient population. In general, we observed that aortic pulsatility can vary along the course of the abdominal aorta. Pulsation can also vary within an aneurysm as well as between aneurysms, but the clinical significance of these findings remain unknown. Conclusions: Visualization of large vessel pulsatility is possible using ECG-gated CT angiography, partial scan reconstruction, automatic segmentation, centerline generation, and coregistration of temporally resolved datasets.

Accuracy and Specific Value of Cardiovascular 3D-Models in Pediatric CT-Angiography.

PubMed

Hammon, Matthias; Rompel, Oliver; Seuss, Hannes; Dittrich, Sven; Uder, Michael; Rüffer, Andrè; Cesnjevar, Robert; Ehret, Nicole; Glöckler, Martin

2017-12-01

Computed tomography (CT)-angiography is routinely performed prior to catheter-based and surgical treatment in congenital heart disease. To date, little is known about the accuracy and advantage of different 3D-reconstructions in CT-data. Exact anatomical information is crucial. We analyzed 35 consecutive CT-angiographies of infants with congenital heart disease. All datasets are reconstructed three-dimensionally using volume rendering technique (VRT) and threshold-based segmentation (stereolithographic model, STL). Additionally, the two-dimensional maximum intensity projection (MIP) reconstructs two-dimensional data. In each dataset and resulting image, measurements of vascular diameters for four different vessels were estimated and compared to the reference standard, measured via multiplanar reformation (MPR). The resulting measurements obtained via the STL-images, MIP-images, and the VRT-images were compared with the reference standard. There was a significant difference (p < 0.05) between measurements. The mean difference was 0.0 for STL-images, -0.1 for MIP-images, and -0.3 for VRT-images. The range of the differences was -0.7 to 1.0 mm for STL-images, -0.6 to 0.5 mm for MIP-images and -1.1 to 0.7 mm for VRT-images. There was an excellent correlation between the STL-, MIP-, VRT-measurements, and the reference standard. Inter-reader reliability was excellent (p < 0.01). STL-models of cardiovascular structures are more accurate than the traditional VRT-models. Additionally, they can be standardized and are reproducible.

Technical note: Correlation of respiratory motion between external patient surface and internal anatomical landmarks

PubMed Central

Fayad, Hadi; Pan, Tinsu; Clément, Jean-François; Visvikis, Dimitris

2011-01-01

Purpose Current respiratory motion monitoring devices used for motion synchronization in medical imaging and radiotherapy provide either 1D respiratory signals over a specific region or 3D information based on few external or internal markers. On the other hand, newer technology may offer the potential to monitor the entire patient external surface in real time. The main objective of this study was to assess the motion correlation between such an external patient surface and internal anatomical landmarks motion. Methods Four dimensional Computed Tomography (4D CT) volumes for ten patients were used in this study. Anatomical landmarks were manually selected in the thoracic region across the 4D CT datasets by two experts. The landmarks included normal structures as well as the tumour location. In addition, a distance map representing the entire external patient surface, which corresponds to surfaces acquired by a Time of Flight (ToF) camera or similar devices, was created by segmenting the skin of all 4D CT volumes using a thresholding algorithm. Finally, the correlation between the internal landmarks and external surface motion was evaluated for different regions (placement and size) throughout a patient’s surface. Results Significant variability was observed in the motion of the different parts of the external patient surface. The larger motion magnitude was consistently measured in the central regions of the abdominal and the thoracic areas for the different patient datasets considered. The highest correlation coefficients were observed between the motion of these external surface areas and internal landmarks such as the diaphragm and mediastinum structures as well as the tumour location landmarks (0.8 ± 0.18 and 0.72 ± 0.12 for the abdominal and the thoracic regions respectively). Worse correlation was observed when one considered landmarks not significantly influenced by respiratory motion such as the apex and the sternum. Discussion and conclusions There were large differences in the motion correlation observed considering different regions of interest placed over a patients’ external surface and internal anatomical landmarks. The positioning of current devices used for respiratory motion synchronization may reduce such correlation by averaging the motion over correlated and poorly correlated external regions. The potential of capturing in real-time the motion of the complete external patient surface as well as choosing the area of the surface that correlates best with the internal motion should allow reducing such variability and associated errors in both respiratory motion synchronization and subsequent motion modeling processes. PMID:21815390

X-ray computed tomography library of shark anatomy and lower jaw surface models.

PubMed

Kamminga, Pepijn; De Bruin, Paul W; Geleijns, Jacob; Brazeau, Martin D

2017-04-11

The cranial diversity of sharks reflects disparate biomechanical adaptations to feeding. In order to be able to investigate and better understand the ecomorphology of extant shark feeding systems, we created a x-ray computed tomography (CT) library of shark cranial anatomy with three-dimensional (3D) lower jaw reconstructions. This is used to examine and quantify lower jaw disparity in extant shark species in a separate study. The library is divided in a dataset comprised of medical CT scans of 122 sharks (Selachimorpha, Chondrichthyes) representing 73 extant species, including digitized morphology of entire shark specimens. This CT dataset and additional data provided by other researchers was used to reconstruct a second dataset containing 3D models of the left lower jaw for 153 individuals representing 94 extant shark species. These datasets form an extensive anatomical record of shark skeletal anatomy, necessary for comparative morphological, biomechanical, ecological and phylogenetic studies.

Traversing and labeling interconnected vascular tree structures from 3D medical images

NASA Astrophysics Data System (ADS)

O'Dell, Walter G.; Govindarajan, Sindhuja Tirumalai; Salgia, Ankit; Hegde, Satyanarayan; Prabhakaran, Sreekala; Finol, Ender A.; White, R. James

2014-03-01

Purpose: Detailed characterization of pulmonary vascular anatomy has important applications for the diagnosis and management of a variety of vascular diseases. Prior efforts have emphasized using vessel segmentation to gather information on the number or branches, number of bifurcations, and branch length and volume, but accurate traversal of the vessel tree to identify and repair erroneous interconnections between adjacent branches and neighboring tree structures has not been carefully considered. In this study, we endeavor to develop and implement a successful approach to distinguishing and characterizing individual vascular trees from among a complex intermingling of trees. Methods: We developed strategies and parameters in which the algorithm identifies and repairs false branch inter-tree and intra-tree connections to traverse complicated vessel trees. A series of two-dimensional (2D) virtual datasets with a variety of interconnections were constructed for development, testing, and validation. To demonstrate the approach, a series of real 3D computed tomography (CT) lung datasets were obtained, including that of an anthropomorphic chest phantom; an adult human chest CT; a pediatric patient chest CT; and a micro-CT of an excised rat lung preparation. Results: Our method was correct in all 2D virtual test datasets. For each real 3D CT dataset, the resulting simulated vessel tree structures faithfully depicted the vessel tree structures that were originally extracted from the corresponding lung CT scans. Conclusion: We have developed a comprehensive strategy for traversing and labeling interconnected vascular trees and successfully implemented its application to pulmonary vessels observed using 3D CT images of the chest.

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

PubMed

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

2018-03-01

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

Are CT Scans a Satisfactory Substitute for the Follow-Up of RSA Migration Studies of Uncemented Cups? A Comparison of RSA Double Examinations and CT Datasets of 46 Total Hip Arthroplasties

PubMed Central

Zeleznik, Michael P.; Nilsson, Kjell G.; Olivecrona, Henrik

2017-01-01

As part of the 14-year follow-up of a prospectively randomized radiostereometry (RSA) study on uncemented cup fixation, two pairs of stereo radiographs and a CT scan of 46 hips were compared. Tantalum beads, inserted during the primary operation, were detected in the CT volume and the stereo radiographs and used to produce datasets of 3D coordinates. The limit of agreement between the combined CT and RSA datasets was calculated in the same way as the precision of the double RSA examination. The precision of RSA corresponding to the 99% confidence interval was 1.36°, 1.36°, and 0.60° for X-, Y-, and Z-rotation and 0.40, 0.17, and 0.37 mm for X-, Y-, and Z-translation. The limit of agreement between CT and RSA was 1.51°, 2.17°, and 1.05° for rotation and 0.59, 0.56, and 0.74 mm for translation. The differences between CT and RSA are close to the described normal 99% confidence interval for precision in RSA: 0.3° to 2° for rotation and 0.15 to 0.6 mm for translation. We conclude that measurements using CT and RSA are comparable and that CT can be used for migration studies for longitudinal evaluations of patients with RSA markers. PMID:28243598

Are CT Scans a Satisfactory Substitute for the Follow-Up of RSA Migration Studies of Uncemented Cups? A Comparison of RSA Double Examinations and CT Datasets of 46 Total Hip Arthroplasties.

PubMed

Otten, Volker; Maguire, Gerald Q; Noz, Marilyn E; Zeleznik, Michael P; Nilsson, Kjell G; Olivecrona, Henrik

2017-01-01

As part of the 14-year follow-up of a prospectively randomized radiostereometry (RSA) study on uncemented cup fixation, two pairs of stereo radiographs and a CT scan of 46 hips were compared. Tantalum beads, inserted during the primary operation, were detected in the CT volume and the stereo radiographs and used to produce datasets of 3D coordinates. The limit of agreement between the combined CT and RSA datasets was calculated in the same way as the precision of the double RSA examination. The precision of RSA corresponding to the 99% confidence interval was 1.36°, 1.36°, and 0.60° for X -, Y -, and Z -rotation and 0.40, 0.17, and 0.37 mm for X -, Y -, and Z -translation. The limit of agreement between CT and RSA was 1.51°, 2.17°, and 1.05° for rotation and 0.59, 0.56, and 0.74 mm for translation. The differences between CT and RSA are close to the described normal 99% confidence interval for precision in RSA: 0.3° to 2° for rotation and 0.15 to 0.6 mm for translation. We conclude that measurements using CT and RSA are comparable and that CT can be used for migration studies for longitudinal evaluations of patients with RSA markers.

Time density curve analysis for C-arm FDCT PBV imaging.

PubMed

Kamran, Mudassar; Byrne, James V

2016-04-01

Parenchymal blood volume (PBV) estimation using C-arm flat detector computed tomography (FDCT) assumes a steady-state contrast concentration in cerebral vasculature for the scan duration. Using time density curve (TDC) analysis, we explored if the steady-state assumption is met for C-arm CT PBV scans, and how consistent the contrast-material dynamics in cerebral vasculature are across patients. Thirty C-arm FDCT datasets of 26 patients with aneurysmal-SAH, acquired as part of a prospective study comparing C-arm CT PBV with MR-PWI, were analysed. TDCs were extracted from the 2D rotational projections. Goodness-of-fit of TDCs to a steady-state horizontal-line-model and the statistical similarity among the individual TDCs were tested. Influence of the differences in TDC characteristics on the agreement of resulting PBV measurements with MR-CBV was calculated. Despite identical scan parameters and contrast-injection-protocol, the individual TDCs were statistically non-identical (p < 0.01). Using Dunn's multiple comparisons test, of the total 435 individual comparisons among the 30 TDCs, 330 comparisons (62%) reached statistical significance for difference. All TDCs deviated significantly (p < 0.01) from the steady-state horizontal-line-model. PBV values of those datasets for which the TDCs showed largest deviations from the steady-state model demonstrated poor agreement and correlation with MR-CBV, compared with the PBV values of those datasets for which the TDCs were closer to steady-state. For clinical C-arm CT PBV examinations, the administered contrast material does not reach the assumed 'ideal steady-state' for the duration of scan. Using a prolonged injection protocol, the degree to which the TDCs approximate the ideal steady-state influences the agreement of resulting PBV measurements with MR-CBV. © The Author(s) 2016.

Time density curve analysis for C-arm FDCT PBV imaging

PubMed Central

Byrne, James V

2016-01-01

Introduction Parenchymal blood volume (PBV) estimation using C-arm flat detector computed tomography (FDCT) assumes a steady-state contrast concentration in cerebral vasculature for the scan duration. Using time density curve (TDC) analysis, we explored if the steady-state assumption is met for C-arm CT PBV scans, and how consistent the contrast-material dynamics in cerebral vasculature are across patients. Methods Thirty C-arm FDCT datasets of 26 patients with aneurysmal-SAH, acquired as part of a prospective study comparing C-arm CT PBV with MR-PWI, were analysed. TDCs were extracted from the 2D rotational projections. Goodness-of-fit of TDCs to a steady-state horizontal-line-model and the statistical similarity among the individual TDCs were tested. Influence of the differences in TDC characteristics on the agreement of resulting PBV measurements with MR-CBV was calculated. Results Despite identical scan parameters and contrast-injection-protocol, the individual TDCs were statistically non-identical (p < 0.01). Using Dunn's multiple comparisons test, of the total 435 individual comparisons among the 30 TDCs, 330 comparisons (62%) reached statistical significance for difference. All TDCs deviated significantly (p < 0.01) from the steady-state horizontal-line-model. PBV values of those datasets for which the TDCs showed largest deviations from the steady-state model demonstrated poor agreement and correlation with MR-CBV, compared with the PBV values of those datasets for which the TDCs were closer to steady-state. Conclusion For clinical C-arm CT PBV examinations, the administered contrast material does not reach the assumed ‘ideal steady-state’ for the duration of scan. Using a prolonged injection protocol, the degree to which the TDCs approximate the ideal steady-state influences the agreement of resulting PBV measurements with MR-CBV. PMID:26769736

A web-based instruction module for interpretation of craniofacial cone beam CT anatomy.

PubMed

Hassan, B A; Jacobs, R; Scarfe, W C; Al-Rawi, W T

2007-09-01

To develop a web-based module for learner instruction in the interpretation and recognition of osseous anatomy on craniofacial cone-beam CT (CBCT) images. Volumetric datasets from three CBCT systems were acquired (i-CAT, NewTom 3G and AccuiTomo FPD) for various subjects using equipment-specific scanning protocols. The datasets were processed using multiple software to provide two-dimensional (2D) multiplanar reformatted (MPR) images (e.g. sagittal, coronal and axial) and three-dimensional (3D) visual representations (e.g. maximum intensity projection, minimum intensity projection, ray sum, surface and volume rendering). Distinct didactic modules which illustrate the principles of CBCT systems, guided navigation of the volumetric dataset, and anatomic correlation of 3D models and 2D MPR graphics were developed using a hybrid combination of web authoring and image analysis techniques. Interactive web multimedia instruction was facilitated by the use of dynamic highlighting and labelling, and rendered video illustrations, supplemented with didactic textual material. HTML coding and Java scripting were heavily implemented for the blending of the educational modules. An interactive, multimedia educational tool for visualizing the morphology and interrelationships of osseous craniofacial anatomy, as depicted on CBCT MPR and 3D images, was designed and implemented. The present design of a web-based instruction module may assist radiologists and clinicians in learning how to recognize and interpret the craniofacial anatomy of CBCT based images more efficiently.

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

Van de Velde, Joris, E-mail: joris.vandevelde@ugent.be; Department of Radiotherapy, Ghent University, Ghent; Audenaert, Emmanuel

Purpose: To develop contouring guidelines for the brachial plexus (BP) using anatomically validated cadaver datasets. Magnetic resonance imaging (MRI) and computed tomography (CT) were used to obtain detailed visualizations of the BP region, with the goal of achieving maximal inclusion of the actual BP in a small contoured volume while also accommodating for anatomic variations. Methods and Materials: CT and MRI were obtained for 8 cadavers positioned for intensity modulated radiation therapy. 3-dimensional reconstructions of soft tissue (from MRI) and bone (from CT) were combined to create 8 separate enhanced CT project files. Dissection of the corresponding cadavers anatomically validatedmore » the reconstructions created. Seven enhanced CT project files were then automatically fitted, separately in different regions, to obtain a single dataset of superimposed BP regions that incorporated anatomic variations. From this dataset, improved BP contouring guidelines were developed. These guidelines were then applied to the 7 original CT project files and also to 1 additional file, left out from the superimposing procedure. The percentage of BP inclusion was compared with the published guidelines. Results: The anatomic validation procedure showed a high level of conformity for the BP regions examined between the 3-dimensional reconstructions generated and the dissected counterparts. Accurate and detailed BP contouring guidelines were developed, which provided corresponding guidance for each level in a clinical dataset. An average margin of 4.7 mm around the anatomically validated BP contour is sufficient to accommodate for anatomic variations. Using the new guidelines, 100% inclusion of the BP was achieved, compared with a mean inclusion of 37.75% when published guidelines were applied. Conclusion: Improved guidelines for BP delineation were developed using combined MRI and CT imaging with validation by anatomic dissection.« less

On the radiobiological impact of metal artifacts in head-and-neck IMRT in terms of tumor control probability (TCP) and normal tissue complication probability (NTCP).

PubMed

Kim, Yusung; Tomé, Wolfgang A

2007-11-01

To investigate the effects of distorted head-and-neck (H&N) intensity-modulated radiation therapy (IMRT) dose distributions (hot and cold spots) on normal tissue complication probability (NTCP) and tumor control probability (TCP) due to dental-metal artifacts. Five patients' IMRT treatment plans have been analyzed, employing five different planning image data-sets: (a) uncorrected (UC); (b) homogeneous uncorrected (HUC); (c) sinogram completion corrected (SCC); (d) minimum-value-corrected (MVC); and (e) streak-artifact-reduction including minimum-value-correction (SAR-MVC), which has been taken as the reference data-set. The effects on NTCP and TCP were evaluated using the Lyman-NTCP model and the Logistic-TCP model, respectively. When compared to the predicted NTCP obtained using the reference data-set, the treatment plan based on the original CT data-set (UC) yielded an increase in NTCP of 3.2 and 2.0% for the spared parotid gland and the spinal cord, respectively. While for the treatment plans based on the MVC CT data-set the NTCP increased by a 1.1% and a 0.1% for the spared parotid glands and the spinal cord, respectively. In addition, the MVC correction method showed a reduction in TCP for target volumes (MVC: delta TCP = -0.6% vs. UC: delta TCP = -1.9%) with respect to that of the reference CT data-set. Our results indicate that the presence of dental-metal-artifacts in H&N planning CT data-sets has an impact on the estimates of TCP and NTCP. In particular dental-metal-artifacts lead to an increase in NTCP for the spared parotid glands and a slight decrease in TCP for target volumes.

Hybrid-fusion SPECT/CT systems in parathyroid adenoma: Technological improvements and added clinical diagnostic value.

PubMed

Wong, K K; Chondrogiannis, S; Bowles, H; Fuster, D; Sánchez, N; Rampin, L; Rubello, D

Nuclear medicine traditionally employs planar and single photon emission computed tomography (SPECT) imaging techniques to depict the biodistribution of radiotracers for the diagnostic investigation of a range of disorders of endocrine gland function. The usefulness of combining functional information with anatomy derived from computed tomography (CT), magnetic resonance imaging (MRI), and high resolution ultrasound (US), has long been appreciated, either using visual side-by-side correlation, or software-based co-registration. The emergence of hybrid SPECT/CT camera technology now allows the simultaneous acquisition of combined multi-modality imaging, with seamless fusion of 3D volume datasets. Thus, it is not surprising that there is growing literature describing the many advantages that contemporary SPECT/CT technology brings to radionuclide investigation of endocrine disorders, showing potential advantages for the pre-operative locating of the parathyroid adenoma using a minimally invasive surgical approach, especially in the presence of ectopic glands and in multiglandular disease. In conclusion, hybrid SPECT/CT imaging has become an essential tool to ensure the most accurate diagnostic in the management of patients with hyperparathyroidism. Copyright © 2016 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Forensic microradiology: micro-computed tomography (Micro-CT) and analysis of patterned injuries inside of bone.

PubMed

Thali, Michael J; Taubenreuther, Ulrike; Karolczak, Marek; Braun, Marcel; Brueschweiler, Walter; Kalender, Willi A; Dirnhofer, Richard

2003-11-01

When a knife is stabbed in bone, it leaves an impression in the bone. The characteristics (shape, size, etc.) may indicate the type of tool used to produce the patterned injury in bone. Until now it has been impossible in forensic sciences to document such damage precisely and non-destructively. Micro-computed tomography (Micro-CT) offers an opportunity to analyze patterned injuries of tool marks made in bone. Using high-resolution Micro-CT and computer software, detailed analysis of three-dimensional (3D) architecture has recently become feasible and allows microstructural 3D bone information to be collected. With adequate viewing software, data from 2D slice of an arbitrary plane can be extracted from 3D datasets. Using such software as a "digital virtual knife," the examiner can interactively section and analyze the 3D sample. Analysis of the bone injury revealed that Micro-CT provides an opportunity to correlate a bone injury to an injury-causing instrument. Even broken knife tips can be graphically and non-destructively assigned to a suspect weapon.

A novel CT acquisition and analysis technique for breathing motion modeling

NASA Astrophysics Data System (ADS)

Low, Daniel A.; White, Benjamin M.; Lee, Percy P.; Thomas, David H.; Gaudio, Sergio; Jani, Shyam S.; Wu, Xiao; Lamb, James M.

2013-06-01

To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques.

Dosimetric impact of different CT datasets for stereotactic treatment planning using 3D conformal radiotherapy or volumetric modulated arc therapy.

PubMed

Oechsner, Markus; Odersky, Leonhard; Berndt, Johannes; Combs, Stephanie Elisabeth; Wilkens, Jan Jakob; Duma, Marciana Nona

2015-12-01

The purpose of this study was to assess the impact on dose to the planning target volume (PTV) and organs at risk (OAR) by using four differently generated CT datasets for dose calculation in stereotactic body radiotherapy (SBRT) of lung and liver tumors. Additionally, dose differences between 3D conformal radiotherapy and volumetric modulated arc therapy (VMAT) plans calculated on these CT datasets were determined. Twenty SBRT patients, ten lung cases and ten liver cases, were retrospectively selected for this study. Treatment plans were optimized on average intensity projection (AIP) CTs using 3D conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT). Afterwards, the plans were copied to the planning CTs (PCT), maximum intensity projection (MIP) and mid-ventilation (MidV) CT datasets and dose was recalculated keeping all beam parameters and monitor units unchanged. Ipsilateral lung and liver volumes and dosimetric parameters for PTV (Dmean, D2, D98, D95), ipsilateral lung and liver (Dmean, V30, V20, V10) were determined and statistically analysed using Wilcoxon test. Significant but small mean differences were found for PTV dose between the CTs (lung SBRT: ≤2.5 %; liver SBRT: ≤1.6 %). MIPs achieved the smallest lung and the largest liver volumes. OAR mean doses in MIP plans were distinctly smaller than in the other CT datasets. Furthermore, overlapping of tumors with the diaphragm results in underestimated ipsilateral lung dose in MIP plans. Best agreement was found between AIP and MidV (lung SBRT). Overall, differences in liver SBRT were smaller than in lung SBRT and VMAT plans achieved slightly smaller differences than 3D-CRT plans. Only small differences were found for PTV parameters between the four CT datasets. Larger differences occurred for the doses to organs at risk (ipsilateral lung, liver) especially for MIP plans. No relevant differences were observed between 3D-CRT or VMAT plans. MIP CTs are not appropriate for OAR dose assessment. PCT, AIP and MidV resulted in similar doses. If a 4DCT is acquired PCT can be omitted using AIP or MidV for treatment planning.

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.

Image quality of mean temporal arterial and mean temporal portal venous phase images calculated from low dose dynamic volume perfusion CT datasets in patients with hepatocellular carcinoma and pancreatic cancer.

PubMed

Wang, X; Henzler, T; Gawlitza, J; Diehl, S; Wilhelm, T; Schoenberg, S O; Jin, Z Y; Xue, H D; Smakic, A

2016-11-01

Dynamic volume perfusion CT (dVPCT) provides valuable information on tissue perfusion in patients with hepatocellular carcinoma (HCC) and pancreatic cancer. However, currently dVPCT is often performed in addition to conventional CT acquisitions due to the limited morphologic image quality of dose optimized dVPCT protocols. The aim of this study was to prospectively compare objective and subjective image quality, lesion detectability and radiation dose between mean temporal arterial (mTA) and mean temporal portal venous (mTPV) images calculated from low dose dynamic volume perfusion CT (dVPCT) datasets with linearly blended 120-kVp arterial and portal venous datasets in patients with HCC and pancreatic cancer. All patients gave written informed consent for this institutional review board-approved HIPAA compliant study. 27 consecutive patients (18 men, 9 women, mean age, 69.1 years±9.4) with histologically proven HCC or suspected pancreatic cancer were prospectively enrolled. The study CT protocol included a dVPCT protocol performed with 70 or 80kVp tube voltage (18 spiral acquisitions, 71.2s total acquisition times) and standard dual-energy (90/150kVpSn) arterial and portal venous acquisition performed 25min after the dVPCT. The mTA and mTPV images were manually reconstructed from the 3 to 5 best visually selected single arterial and 3 to 5 best single portal venous phases dVPCT dataset. The linearly blended 120-kVp images were calculated from dual-energy CT (DECT) raw data. Image noise, SNR, and CNR of the liver, abdominal aorta (AA) and main portal vein (PV) were compared between the mTA/mTPV and the linearly blended 120-kVp dual-energy arterial and portal venous datasets, respectively. Subjective image quality was evaluated by two radiologists regarding subjective image noise, sharpness and overall diagnostic image quality using a 5-point Likert Scale. In addition, liver lesion detectability was performed for each liver segment by the two radiologists using the linearly blended120-kVp arterial and portal venous datasets as the reference standard. Image noise, SNR and CNR values of the mTA and mTPV were significantly higher when compared to the corresponding linearly blended arterial and portal venous 120-kVp datasets (all p<0.001) except for image noise within the PV in the portal venous phases (p=0.136). image quality of mTA and mTPV were rated significantly better when compared to the linearly blended 120-kVp arterial and portal venous datasets. Both readers were able to detect all liver lesions found on the linearly blended 120-kVp arterial and portal venous datasets using the mTA and mTPV datasets. The effective radiation dose of the dVPCT was 27.6mSv for the 80kVp protocol and 14.5mSv for the 70kVp protocol. The mean effective radiation dose for the linearly blended 120-kVp arterial and portal venous CT protocol together of the upper abdomen was 5.60mSv±1.48mSv. Our preliminary data suggest that subjective and objective image quality of mTA and mTPV datasets calculated from low-kVp dVPCT datasets is non-inferior when compared to linearly blended 120-kVp arterial and portal venous acquisitions in patients with HCC and pancreatic cancer. Thus, dVPCT could be used as a stand-alone imaging technique without additionally performed conventional arterial and portal venous CT acquisitions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Comparison of epicardial adipose tissue radiodensity threshold between contrast and non-contrast enhanced computed tomography scans: A cohort study of derivation and validation.

PubMed

Xu, Lingyu; Xu, Yuancheng; Coulden, Richard; Sonnex, Emer; Hrybouski, Stanislau; Paterson, Ian; Butler, Craig

2018-05-11

Epicardial adipose tissue (EAT) volume derived from contrast enhanced (CE) computed tomography (CT) scans is not well validated. We aim to establish a reliable threshold to accurately quantify EAT volume from CE datasets. We analyzed EAT volume on paired non-contrast (NC) and CE datasets from 25 patients to derive appropriate Hounsfield (HU) cutpoints to equalize two EAT volume estimates. The gold standard threshold (-190HU, -30HU) was used to assess EAT volume on NC datasets. For CE datasets, EAT volumes were estimated using three previously reported thresholds: (-190HU, -30HU), (-190HU, -15HU), (-175HU, -15HU) and were analyzed by a semi-automated 3D Fat analysis software. Subsequently, we applied a threshold correction to (-190HU, -30HU) based on mean differences in radiodensity between NC and CE images (ΔEATrd = CE radiodensity - NC radiodensity). We then validated our findings on EAT threshold in 21 additional patients with paired CT datasets. EAT volume from CE datasets using previously published thresholds consistently underestimated EAT volume from NC dataset standard by a magnitude of 8.2%-19.1%. Using our corrected threshold (-190HU, -3HU) in CE datasets yielded statistically identical EAT volume to NC EAT volume in the validation cohort (186.1 ± 80.3 vs. 185.5 ± 80.1 cm 3 , Δ = 0.6 cm 3 , 0.3%, p = 0.374). Estimating EAT volume from contrast enhanced CT scans using a corrected threshold of -190HU, -3HU provided excellent agreement with EAT volume from non-contrast CT scans using a standard threshold of -190HU, -30HU. Copyright © 2018. Published by Elsevier B.V.

Feasibility of simultaneous PET/MR of the carotid artery: first clinical experience and comparison to PET/CT

PubMed Central

Ripa, Rasmus S; Knudsen, Andreas; Hag, Anne Mette F; Lebech, Anne-Mette; Loft, Annika; Keller, Sune H; Hansen, Adam E; von Benzon, Eric; Højgaard, Liselotte; Kjær, Andreas

2013-01-01

The study aimed at comparing PET/MR to PET/CT for imaging the carotid arteries in patients with known increased risk of atherosclerosis. Six HIV-positive men underwent sequential PET/MR and PET/CT of the carotid arteries after injection of 400 MBq of 18F-FDG. PET/MR was performed a median of 131 min after injection. Subsequently,PET/CT was performed. Regions of interest (ROI) were drawn slice by slice to include the carotid arteries and standardized uptake values (SUV) were calculated from both datasets independently. Quantitative comparison of 18F-FDG uptake revealed a high congruence between PET data acquired using the PET/MR system compared to the PET/CT system. The mean difference for SUVmean was -0.18 (p < 0.001) and -0.14 for SUVmax (p < 0.001) indicating a small but significant bias towards lower values using the PET/MR system. The 95% limits of agreement were -0.55 to 0.20 for SUVmean and -0.93 to 0.65 for SUVmax. The image quality of the PET/MR allowed for delineation of the carotid vessel wall. The correlations between 18F-FDG uptake from ROI including both vessel wall and vessel lumen to ROI including only the wall were strong (r = 0.98 for SUVmean and r = 1.00 for SUVmax) indicating that the luminal 18F-FDG content had minimal influence on the values. The study shows for the first time that simultaneous PET/MR of the carotid arteries is feasible in patients with increased risk of atherosclerosis. Quantification of 18F-FDG uptake correlated well between PET/MR and PET/CT despite difference in method of PET attenuation correction, reconstruction algorithm, and detector technology. PMID:23900769

Evaluation of automatic image quality assessment in chest CT - A human cadaver study.

PubMed

Franck, Caro; De Crop, An; De Roo, Bieke; Smeets, Peter; Vergauwen, Merel; Dewaele, Tom; Van Borsel, Mathias; Achten, Eric; Van Hoof, Tom; Bacher, Klaus

2017-04-01

The evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers. Chest CT's of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized. Good correlations were found between IQs and the measured physical-technical image quality: noise (ρ=-1.00), contrast-to-noise (ρ=1.00) and contrast-detail (ρ=0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively. The automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

WE-AB-207B-05: Correlation of Normal Lung Density Changes with Dose After Stereotactic Body Radiotherapy (SBRT) for Early Stage Lung Cancer

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

Wu, Q; Devpura, S; Feghali, K

2016-06-15

Purpose: To investigate correlation of normal lung CT density changes with dose accuracy and outcome after SBRT for patients with early stage lung cancer. Methods: Dose distributions for patients originally planned and treated using a 1-D pencil beam-based (PB-1D) dose algorithm were retrospectively recomputed using algorithms: 3-D pencil beam (PB-3D), and model-based Methods: AAA, Acuros XB (AXB), and Monte Carlo (MC). Prescription dose was 12 Gy × 4 fractions. Planning CT images were rigidly registered to the followup CT datasets at 6–9 months after treatment. Corresponding dose distributions were mapped from the planning to followup CT images. Following the methodmore » of Palma et al .(1–2), Hounsfield Unit (HU) changes in lung density in individual, 5 Gy, dose bins from 5–45 Gy were assessed in the peri-tumor region, defined as a uniform, 3 cm expansion around the ITV(1). Results: There is a 10–15% displacement of the high dose region (40–45 Gy) with the model-based algorithms, relative to the PB method, due to the electron scattering of dose away from the tumor into normal lung tissue (Fig.1). Consequently, the high-dose lung region falls within the 40–45 Gy dose range, causing an increase in HU change in this region, as predicted by model-based algorithms (Fig.2). The patient with the highest HU change (∼110) had mild radiation pneumonitis, and the patient with HU change of ∼80–90 had shortness of breath. No evidence of pneumonitis was observed for the 3 patients with smaller CT density changes (<50 HU). Changes in CT densities, and dose-response correlation, as computed with model-based algorithms, are in excellent agreement with the findings of Palma et al. (1–2). Conclusion: Dose computed with PB (1D or 3D) algorithms was poorly correlated with clinically relevant CT density changes, as opposed to model-based algorithms. A larger cohort of patients is needed to confirm these results. This work was supported in part by a grant from Varian Medical Systems, Palo Alto, CA.« less

Evaluation of the sparse coding super-resolution method for improving image quality of up-sampled images in computed tomography

NASA Astrophysics Data System (ADS)

Ota, Junko; Umehara, Kensuke; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

2017-02-01

As the capability of high-resolution displays grows, high-resolution images are often required in Computed Tomography (CT). However, acquiring high-resolution images takes a higher radiation dose and a longer scanning time. In this study, we applied the Sparse-coding-based Super-Resolution (ScSR) method to generate high-resolution images without increasing the radiation dose. We prepared the over-complete dictionary learned the mapping between low- and highresolution patches and seek a sparse representation of each patch of the low-resolution input. These coefficients were used to generate the high-resolution output. For evaluation, 44 CT cases were used as the test dataset. We up-sampled images up to 2 or 4 times and compared the image quality of the ScSR scheme and bilinear and bicubic interpolations, which are the traditional interpolation schemes. We also compared the image quality of three learning datasets. A total of 45 CT images, 91 non-medical images, and 93 chest radiographs were used for dictionary preparation respectively. The image quality was evaluated by measuring peak signal-to-noise ratio (PSNR) and structure similarity (SSIM). The differences of PSNRs and SSIMs between the ScSR method and interpolation methods were statistically significant. Visual assessment confirmed that the ScSR method generated a high-resolution image with sharpness, whereas conventional interpolation methods generated over-smoothed images. To compare three different training datasets, there were no significance between the CT, the CXR and non-medical datasets. These results suggest that the ScSR provides a robust approach for application of up-sampling CT images and yields substantial high image quality of extended images in CT.

Vessel suppressed chest Computed Tomography for semi-automated volumetric measurements of solid pulmonary nodules.

PubMed

Milanese, Gianluca; Eberhard, Matthias; Martini, Katharina; Vittoria De Martini, Ilaria; Frauenfelder, Thomas

2018-04-01

To evaluate whether vessel-suppressed computed tomography (VSCT) can be reliably used for semi-automated volumetric measurements of solid pulmonary nodules, as compared to standard CT (SCT) MATERIAL AND METHODS: Ninety-three SCT were elaborated by dedicated software (ClearRead CT, Riverain Technologies, Miamisburg, OH, USA), that allows subtracting vessels from lung parenchyma. Semi-automated volumetric measurements of 65 solid nodules were compared between SCT and VSCT. The measurements were repeated by two readers. For each solid nodule, volume measured on SCT by Reader 1 and Reader 2 was averaged and the average volume between readers acted as standard of reference value. Concordance between measurements was assessed using Lin's Concordance Correlation Coefficient (CCC). Limits of agreement (LoA) between readers and CT datasets were evaluated. Standard of reference nodule volume ranged from 13 to 366 mm 3 . The mean overestimation between readers was 3 mm 3 and 2.9 mm 3 on SCT and VSCT, respectively. Semi-automated volumetric measurements on VSCT showed substantial agreement with the standard of reference (Lin's CCC = 0.990 for Reader 1; 0.985 for Reader 2). The upper and lower LoA between readers' measurements were (16.3, -22.4 mm 3 ) and (15.5, -21.4 mm 3 ) for SCT and VSCT, respectively. VSCT datasets are feasible for the measurements of solid nodules, showing an almost perfect concordance between readers and with measurements on SCT. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated seed localization from CT datasets of the prostate.

PubMed

Brinkmann, D H; Kline, R W

1998-09-01

With the increasing utilization of permanent brachytherapy implants for treating carcinoma of the prostate, the importance of accurate post-treatment dose calculation also increases for assessing patient outcome and planning future treatments. An automatic method for seed localization of permanent brachytherapy implants, using CT datasets of the prostate, has been developed and tested on a phantom using an actual patient planned seed distribution. This method was also compared to results with the three-film technique for three patient datasets. The automatic method is as accurate or more accurate than the three film technique for 1 mm, 3 mm, and 5 mm contiguous CT slices, and eliminates the inter- and intra-observer variability of the manual methods. The automated method improves the localization of brachytherapy seeds while reducing the time required for the user to input information, and is demonstrated to be less operator dependent, less time consuming, and potentially more accurate than the three-film technique.

CT acquisition technique and quantitative analysis of the lung parenchyma: variability and corrections

NASA Astrophysics Data System (ADS)

Zheng, Bin; Leader, J. K.; Coxson, Harvey O.; Scuirba, Frank C.; Fuhrman, Carl R.; Balkan, Arzu; Weissfeld, Joel L.; Maitz, Glenn S.; Gur, David

2006-03-01

The fraction of lung voxels below a pixel value "cut-off" has been correlated with pathologic estimates of emphysema. We performed a "standard" quantitative CT (QCT) lung analysis using a -950 HU cut-off to determine the volume fraction of emphysema (below the cut-off) and a "corrected" QCT analysis after removing small group (5 and 10 pixels) of connected pixels ("blobs") below the cut-off. CT examinations two dataset of 15 subjects each with a range of visible emphysema and pulmonary obstruction were acquired at "low-dose and conventional dose reconstructed using a high-spatial frequency kernel at 2.5 mm section thickness for the same subject. The "blob" size (i.e., connected-pixels) removed was inversely related to the computed fraction of emphysema. The slopes of emphysema fraction versus blob size were 0.013, 0.009, and 0.005 for subjects with both no emphysema and no pulmonary obstruction, moderate emphysema and pulmonary obstruction, and severe emphysema and severe pulmonary obstruction, respectively. The slopes of emphysema fraction versus blob size were 0.008 and 0.006 for low-dose and conventional CT examinations, respectively. The small blobs of pixels removed are most likely CT image artifacts and do not represent actual emphysema. The magnitude of the blob correction was appropriately associated with COPD severity. The blob correction appears to be applicable to QCT analysis in low-dose and conventional CT exams.

High-definition computed tomography for coronary artery stent imaging: a phantom study.

PubMed

Yang, Wen Jie; Chen, Ke Min; Pang, Li Fang; Guo, Ying; Li, Jian Ying; Zhang, Huang; Pan, Zi Lai

2012-01-01

To assess the performance of a high-definition CT (HDCT) for imaging small caliber coronary stents (≤ 3 mm) by comparing different scan modes of a conventional 64-row standard-definition CT (SDCT). A cardiac phantom with twelve stents (2.5 mm and 3.0 mm in diameter) was scanned by HDCT and SDCT. The scan modes were retrospective electrocardiography (ECG)-gated helical and prospective ECG-triggered axial with tube voltages of 120 kVp and 100 kVp, respectively. The inner stent diameters (ISD) and the in-stent attenuation value (AV(in-stent)) and the in-vessel extra-stent attenuation value (AV(in-vessel)) were measured by two observers. The artificial lumen narrowing (ALN = [ISD - ISD(measured)]/ISD) and artificial attenuation increase between in-stent and in-vessel (AAI = AV(in-stent) - AV(in-vessel)) were calculated. All data was analyzed by intraclass correlation and ANOVA-test. The correlation coefficient of ISD, AV(in-vessel) and AV(in-stent) between the two observers was good. The ALNs of HDCT were statistically lower than that of SDCT (30 ± 5.7% versus 35 ± 5.4%, p < 0.05). HDCT had statistically lower AAI values than SDCT (15.7 ± 81.4 HU versus 71.4 ± 90.5 HU, p < 0.05). The prospective axial dataset demonstrated smaller ALN than the retrospective helical dataset on both HDCT and SDCT (p < 0.05). Additionally, there were no differences in ALN between the 120 kVp and 100 kVp tube voltages on HDCT (p = 0.05). High-definition CT helps improve measurement accuracy for imaging coronary stents compared to SDCT. HDCT with 100 kVp and the prospective ECG-triggered axial technique, with a lower radiation dose than 120 kVp application, may be advantageous in evaluating coronary stents with smaller calibers (≤ 3 mm).

SU-E-T-333: Dosimetric Impact of Rotational Error On the Target Coverage in IMPT Lung Cancer Plans

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

Rana, S; Zheng, Y

2015-06-15

Purpose: The main purpose of this study was to investigate the impact of rotational (yaw, roll, and pitch) error on the planning target volume (PTV) coverage in lung cancer plans generated by intensity modulated proton therapy (IMPT). Methods: In this retrospective study, computed tomography (CT) dataset of previously treated lung case was used. IMPT plan were generated on the original CT dataset using left-lateral (LL) and posterior-anterior (PA) beams for a total dose of 74 Gy[RBE] with 2 Gy[RBE] per fraction. In order to investigate the dosimetric impact of rotational error, 12 new CT datasets were generated by re-sampling themore » original CT dataset for rotational (roll, yaw, and pitch) angles ranged from −5° to +5°, with an increment of 2.5°. A total of 12 new IMPT plans were generated based on the re-sampled CT datasets using beam parameters identical to the ones in the original IMPT plan. All treatment plans were generated in XiO treatment planning system. The PTV coverage (i.e., dose received by 95% of the PTV volume, D95) in new IMPT plans were then compared with the PTV coverage in the original IMPT plan. Results: Rotational errors caused the reduction in the PTV coverage in all 12 new IMPT plans when compared to the original IMPT lung plan. Specifically, the PTV coverage was reduced by 4.94% to 50.51% for yaw, by 4.04% to 23.74% for roll, and by 5.21% to 46.88% for pitch errors. Conclusion: Unacceptable dosimetric results were observed in new IMPT plans as the PTV coverage was reduced by up to 26.87% and 50.51% for rotational error of 2.5° and 5°, respectively. Further investigation is underway in evaluating the PTV coverage loss in the IMPT lung cancer plans for smaller rotational angle change.« less

Automatic initialization for 3D bone registration

NASA Astrophysics Data System (ADS)

Foroughi, Pezhman; Taylor, Russell H.; Fichtinger, Gabor

2008-03-01

In image-guided bone surgery, sample points collected from the surface of the bone are registered to the preoperative CT model using well-known registration methods such as Iterative Closest Point (ICP). These techniques are generally very sensitive to the initial alignment of the datasets. Poor initialization significantly increases the chances of getting trapped local minima. In order to reduce the risk of local minima, the registration is manually initialized by locating the sample points close to the corresponding points on the CT model. In this paper, we present an automatic initialization method that aligns the sample points collected from the surface of pelvis with CT model of the pelvis. The main idea is to exploit a mean shape of pelvis created from a large number of CT scans as the prior knowledge to guide the initial alignment. The mean shape is constant for all registrations and facilitates the inclusion of application-specific information into the registration process. The CT model is first aligned with the mean shape using the bilateral symmetry of the pelvis and the similarity of multiple projections. The surface points collected using ultrasound are then aligned with the pelvis mean shape. This will, in turn, lead to initial alignment of the sample points with the CT model. The experiments using a dry pelvis and two cadavers show that the method can align the randomly dislocated datasets close enough for successful registration. The standard ICP has been used for final registration of datasets.

Degradation of metallic materials studied by correlative tomography

NASA Astrophysics Data System (ADS)

Burnett, T. L.; Holroyd, N. J. H.; Lewandowski, J. J.; Ogurreck, M.; Rau, C.; Kelley, R.; Pickering, E. J.; Daly, M.; Sherry, A. H.; Pawar, S.; Slater, T. J. A.; Withers, P. J.

2017-07-01

There are a huge array of characterization techniques available today and increasingly powerful computing resources allowing for the effective analysis and modelling of large datasets. However, each experimental and modelling tool only spans limited time and length scales. Correlative tomography can be thought of as the extension of correlative microscopy into three dimensions connecting different techniques, each providing different types of information, or covering different time or length scales. Here the focus is on the linking of time lapse X-ray computed tomography (CT) and serial section electron tomography using the focussed ion beam (FIB)-scanning electron microscope to study the degradation of metals. Correlative tomography can provide new levels of detail by delivering a multiscale 3D picture of key regions of interest. Specifically, the Xe+ Plasma FIB is used as an enabling tool for large-volume high-resolution serial sectioning of materials, and also as a tool for preparation of microscale test samples and samples for nanoscale X-ray CT imaging. The exemplars presented illustrate general aspects relating to correlative workflows, as well as to the time-lapse characterisation of metal microstructures during various failure mechanisms, including ductile fracture of steel and the corrosion of aluminium and magnesium alloys. Correlative tomography is already providing significant insights into materials behaviour, linking together information from different instruments across different scales. Multiscale and multifaceted work flows will become increasingly routine, providing a feed into multiscale materials models as well as illuminating other areas, particularly where hierarchical structures are of interest.

Differences between genders in colorectal morphology on CT colonography using a quantitative approach: a pilot study.

PubMed

Weber, Charles N; Poff, Jason A; Lev-Toaff, Anna S; Levine, Marc S; Zafar, Hanna M

To explore quantitative differences between genders in morphologic colonic metrics and determine metric reproducibility. Quantitative colonic metrics from 20 male and 20 female CTC datasets were evaluated twice by two readers; all exams were performed after incomplete optical colonoscopy. Intra-/inter-reader reliability was measured with intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Women had overall decreased colonic volume, increased tortuosity and compactness and lower sigmoid apex height on CTC compared to men (p<0.0001,all). Quantitative measurements in colonic metrics were highly reproducible (ICC=0.9989 and 0.9970; CCC=0.9945). Quantitative morphologic differences between genders can be reproducibility measured. Copyright © 2017 Elsevier Inc. All rights reserved.

Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression

PubMed Central

Liu, Yu-Ying; Li, Shuang; Li, Fuxin; Song, Le; Rehg, James M.

2016-01-01

The Continuous-Time Hidden Markov Model (CT-HMM) is an attractive approach to modeling disease progression due to its ability to describe noisy observations arriving irregularly in time. However, the lack of an efficient parameter learning algorithm for CT-HMM restricts its use to very small models or requires unrealistic constraints on the state transitions. In this paper, we present the first complete characterization of efficient EM-based learning methods for CT-HMM models. We demonstrate that the learning problem consists of two challenges: the estimation of posterior state probabilities and the computation of end-state conditioned statistics. We solve the first challenge by reformulating the estimation problem in terms of an equivalent discrete time-inhomogeneous hidden Markov model. The second challenge is addressed by adapting three approaches from the continuous time Markov chain literature to the CT-HMM domain. We demonstrate the use of CT-HMMs with more than 100 states to visualize and predict disease progression using a glaucoma dataset and an Alzheimer’s disease dataset. PMID:27019571

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy.

PubMed

Kramer, Gerbrand Maria; Frings, Virginie; Heijtel, Dennis; Smit, E F; Hoekstra, Otto S; Boellaard, Ronald

2017-06-01

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'- 18 F-fluorothymidine ( 18 F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18 F-FLT PET/CT to assess the robustness of these methods. Methods : Ten NSCLC patients underwent dynamic 18 F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V T ) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy ( R 2 ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K 1 values ( R 2 = 0.94; intraclass correlation coefficient, 0.96). Parametric K 1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric 18 F-FLT V T images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K 1 data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic 18 F-FLT PET/CT studies; however, SA can also be used. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

NASA Astrophysics Data System (ADS)

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L.; Beauchemin, Steven S.; Rodrigues, George; Gaede, Stewart

2015-02-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging.

PubMed

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L; Beauchemin, Steven S; Rodrigues, George; Gaede, Stewart

2015-02-21

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2017-04-01

With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

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.

Quantitative computed tomography of lung parenchyma in patients with emphysema: analysis of higher-density lung regions

NASA Astrophysics Data System (ADS)

Lederman, Dror; Leader, Joseph K.; Zheng, Bin; Sciurba, Frank C.; Tan, Jun; Gur, David

2011-03-01

Quantitative computed tomography (CT) has been widely used to detect and evaluate the presence (or absence) of emphysema applying the density masks at specific thresholds, e.g., -910 or -950 Hounsfield Unit (HU). However, it has also been observed that subjects with similar density-mask based emphysema scores could have varying lung function, possibly indicating differences of disease severity. To assess this possible discrepancy, we investigated whether density distribution of "viable" lung parenchyma regions with pixel values > -910 HU correlates with lung function. A dataset of 38 subjects, who underwent both pulmonary function testing and CT examinations in a COPD SCCOR study, was assembled. After the lung regions depicted on CT images were automatically segmented by a computerized scheme, we systematically divided the lung parenchyma into different density groups (bins) and computed a number of statistical features (i.e., mean, standard deviation (STD), skewness of the pixel value distributions) in these density bins. We then analyzed the correlations between each feature and lung function. The correlation between diffusion lung capacity (DLCO) and STD of pixel values in the bin of -910HU <= PV < -750HU was -0.43, as compared with a correlation of -0.49 obtained between the post-bronchodilator ratio (FEV1/FVC) measured by the forced expiratory volume in 1 second (FEV1) dividing the forced vital capacity (FVC) and the STD of pixel values in the bin of -1024HU <= PV < -910HU. The results showed an association between the distribution of pixel values in "viable" lung parenchyma and lung function, which indicates that similar to the conventional density mask method, the pixel value distribution features in "viable" lung parenchyma areas may also provide clinically useful information to improve assessments of lung disease severity as measured by lung functional tests.

SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images

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

Sanders, J; Abadi, E; Meng, B

Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standardmore » deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.« less

Development and comparison of projection and image space 3D nodule insertion techniques

NASA Astrophysics Data System (ADS)

Robins, Marthony; Solomon, Justin; Sahbaee, Pooyan; Samei, Ehsan

2016-04-01

This study aimed to develop and compare two methods of inserting computerized virtual lesions into CT datasets. 24 physical (synthetic) nodules of three sizes and four morphologies were inserted into an anthropomorphic chest phantom (LUNGMAN, KYOTO KAGAKU). The phantom was scanned (Somatom Definition Flash, Siemens Healthcare) with and without nodules present, and images were reconstructed with filtered back projection and iterative reconstruction (SAFIRE) at 0.6 mm slice thickness using a standard thoracic CT protocol at multiple dose settings. Virtual 3D CAD models based on the physical nodules were virtually inserted (accounting for the system MTF) into the nodule-free CT data using two techniques. These techniques include projection-based and image-based insertion. Nodule volumes were estimated using a commercial segmentation tool (iNtuition, TeraRecon, Inc.). Differences were tested using paired t-tests and R2 goodness of fit between the virtually and physically inserted nodules. Both insertion techniques resulted in nodule volumes very similar to the real nodules (<3% difference) and in most cases the differences were not statistically significant. Also, R2 values were all <0.97 for both insertion techniques. These data imply that these techniques can confidently be used as a means of inserting virtual nodules in CT datasets. These techniques can be instrumental in building hybrid CT datasets composed of patient images with virtually inserted nodules.

Automatic 3D liver location and segmentation via convolutional neural network and graph cut.

PubMed

Lu, Fang; Wu, Fa; Hu, Peijun; Peng, Zhiyi; Kong, Dexing

2017-02-01

Segmentation of the liver from abdominal computed tomography (CT) images is an essential step in some computer-assisted clinical interventions, such as surgery planning for living donor liver transplant, radiotherapy and volume measurement. In this work, we develop a deep learning algorithm with graph cut refinement to automatically segment the liver in CT scans. The proposed method consists of two main steps: (i) simultaneously liver detection and probabilistic segmentation using 3D convolutional neural network; (ii) accuracy refinement of the initial segmentation with graph cut and the previously learned probability map. The proposed approach was validated on forty CT volumes taken from two public databases MICCAI-Sliver07 and 3Dircadb1. For the MICCAI-Sliver07 test dataset, the calculated mean ratios of volumetric overlap error (VOE), relative volume difference (RVD), average symmetric surface distance (ASD), root-mean-square symmetric surface distance (RMSD) and maximum symmetric surface distance (MSD) are 5.9, 2.7 %, 0.91, 1.88 and 18.94 mm, respectively. For the 3Dircadb1 dataset, the calculated mean ratios of VOE, RVD, ASD, RMSD and MSD are 9.36, 0.97 %, 1.89, 4.15 and 33.14 mm, respectively. The proposed method is fully automatic without any user interaction. Quantitative results reveal that the proposed approach is efficient and accurate for hepatic volume estimation in a clinical setup. The high correlation between the automatic and manual references shows that the proposed method can be good enough to replace the time-consuming and nonreproducible manual segmentation method.

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.

Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis.

PubMed

Padgett, Kyle R; Stoyanova, Radka; Pirozzi, Sara; Johnson, Perry; Piper, Jon; Dogan, Nesrin; Pollack, Alan

2018-03-01

Validating deformable multimodality image registrations is challenging due to intrinsic differences in signal characteristics and their spatial intensity distributions. Evaluating multimodality registrations using these spatial intensity distributions is also complicated by the fact that these metrics are often employed in the registration optimization process. This work evaluates rigid and deformable image registrations of the prostate in between diagnostic-MRI and radiation treatment planning-CT by utilizing a planning-MRI after fiducial marker placement as a surrogate. The surrogate allows for the direct quantitative analysis that can be difficult in the multimodality domain. For thirteen prostate patients, T2 images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day as the planning-CT (planning-MRI). The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available algorithm which synthesizes a deformable image registration (DIR) algorithm from local rigid registrations. The planning-MRI provided an independent surrogate for the planning-CT for assessing registration accuracy using image similarity metrics, including Pearson correlation and normalized mutual information (NMI). A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb, and combined areas. The planning-MRI provided an excellent surrogate for the planning-CT with residual error in fiducial alignment between the two datasets being submillimeter, 0.78 mm. DIR was superior to the rigid registration in 11 of 13 cases demonstrating a 27.37% improvement in NMI (P < 0.009) within a regional area surrounding the prostate and associated critical organs. Pearson correlations showed similar results, demonstrating a 13.02% improvement (P < 0.013). By utilizing the planning-MRI as a surrogate for the planning-CT, an independent evaluation of registration accuracy is possible. This population provides an ideal testing ground for MRI to CT DIR by obviating the need for multimodality comparisons which are inherently more challenging. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Coronary artery calcification identification and labeling in low-dose chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Liu, Shuang; Miller, Albert; Miller, Jeffrey A.; Markowitz, Steven; Akhund, Ali; Reeves, Anthony P.

2017-03-01

A fully automated computer algorithm has been developed to evaluate coronary artery calcification (CAC) from lowdose CT scans. CAC is identified and evaluated in three main coronary artery groups: Left Main and Left Anterior Descending Artery (LM + LAD) CAC, Left Circumflex Artery (LCX) CAC, and Right Coronary Artery (RCA) CAC. The artery labeling is achieved by segmenting all CAC candidates in the heart region and applying geometric constraints on the candidates using locally pre-identified anatomy regions. This algorithm was evaluated on 1,359 low-dose ungated CT scans, in which each artery CAC content was categorically visually scored by a radiologist into none, mild, moderate and extensive. The Spearman correlation coefficient R was used to assess the agreement between three automated CAC scores (Agatston-weighted, volume, and mass) and categorical visual scores. For Agatston-weighted automated scores, R was 0.87 for total CAC, 0.82 for LM + LAD CAC, 0.66 for LCX CAC and 0.72 for RCA CAC; results using volume and mass scores were similar. CAC detection sensitivities were: 0.87 for total, 0.82 for LM + LAD, 0.65 for LCX and 0.74 for RCA. To assess the impact of image noise, the dataset was further partitioned into three subsets based on heart region noise level (low<=80HU, medium=(80HU, 110HU], high>110HU). The low and medium noise subsets had higher sensitivities and correlations than the high noise subset. These results indicate that location specific heart risk assessment is possible from low-dose chest CT images.

Correlations between contouring similarity metrics and simulated treatment outcome for prostate radiotherapy

NASA Astrophysics Data System (ADS)

Roach, D.; Jameson, M. G.; Dowling, J. A.; Ebert, M. A.; Greer, P. B.; Kennedy, A. M.; Watt, S.; Holloway, L. C.

2018-02-01

Many similarity metrics exist for inter-observer contouring variation studies, however no correlation between metric choice and prostate cancer radiotherapy dosimetry has been explored. These correlations were investigated in this study. Two separate trials were undertaken, the first a thirty-five patient cohort with three observers, the second a five patient dataset with ten observers. Clinical and planning target volumes (CTV and PTV), rectum, and bladder were independently contoured by all observers in each trial. Structures were contoured on T2-weighted MRI and transferred onto CT following rigid registration for treatment planning in the first trial. Structures were contoured directly on CT in the second trial. STAPLE and majority voting volumes were generated as reference gold standard volumes for each structure for the two trials respectively. VMAT treatment plans (78 Gy to PTV) were simulated for observer and gold standard volumes, and dosimetry assessed using multiple radiobiological metrics. Correlations between contouring similarity metrics and dosimetry were calculated using Spearman’s rank correlation coefficient. No correlations were observed between contouring similarity metrics and dosimetry for CTV within either trial. Volume similarity correlated most strongly with radiobiological metrics for PTV in both trials, including TCPPoisson (ρ  =  0.57, 0.65), TCPLogit (ρ  =  0.39, 0.62), and EUD (ρ  =  0.43, 0.61) for each respective trial. Rectum and bladder metric correlations displayed no consistency for the two trials. PTV volume similarity was found to significantly correlate with rectum normal tissue complication probability (ρ  =  0.33, 0.48). Minimal to no correlations with dosimetry were observed for overlap or boundary contouring metrics. Future inter-observer contouring variation studies for prostate cancer should incorporate volume similarity to provide additional insights into dosimetry during analysis.

Retrospective data-driven respiratory gating for PET/CT

NASA Astrophysics Data System (ADS)

Schleyer, Paul J.; O'Doherty, Michael J.; Barrington, Sally F.; Marsden, Paul K.

2009-04-01

Respiratory motion can adversely affect both PET and CT acquisitions. Respiratory gating allows an acquisition to be divided into a series of motion-reduced bins according to the respiratory signal, which is typically hardware acquired. In order that the effects of motion can potentially be corrected for, we have developed a novel, automatic, data-driven gating method which retrospectively derives the respiratory signal from the acquired PET and CT data. PET data are acquired in listmode and analysed in sinogram space, and CT data are acquired in cine mode and analysed in image space. Spectral analysis is used to identify regions within the CT and PET data which are subject to respiratory motion, and the variation of counts within these regions is used to estimate the respiratory signal. Amplitude binning is then used to create motion-reduced PET and CT frames. The method was demonstrated with four patient datasets acquired on a 4-slice PET/CT system. To assess the accuracy of the data-derived respiratory signal, a hardware-based signal was acquired for comparison. Data-driven gating was successfully performed on PET and CT datasets for all four patients. Gated images demonstrated respiratory motion throughout the bin sequences for all PET and CT series, and image analysis and direct comparison of the traces derived from the data-driven method with the hardware-acquired traces indicated accurate recovery of the respiratory signal.

Precision of DVC approaches for strain analysis in bone imaged with μCT at different dimensional levels.

NASA Astrophysics Data System (ADS)

Dall'Ara, Enrico; Peña-Fernández, Marta; Palanca, Marco; Giorgi, Mario; Cristofolini, Luca; Tozzi, Gianluca

2017-11-01

Accurate measurement of local strain in heterogeneous and anisotropic bone tissue is fundamental to understand the pathophysiology of musculoskeletal diseases, to evaluate the effect of interventions from preclinical studies, and to optimize the design and delivery of biomaterials. Digital volume correlation (DVC) can be used to measure the three-dimensional displacement and strain fields from micro-Computed Tomography (µCT) images of loaded specimens. However, this approach is affected by the quality of the input images, by the morphology and density of the tissue under investigation, by the correlation scheme, and by the operational parameters used in the computation. Therefore, for each application the precision of the method should be evaluated. In this paper we present the results collected from datasets analyzed in previous studies as well as new data from a recent experimental campaign for characterizing the relationship between the precision of two different DVC approaches and the spatial resolution of the outputs. Different bone structures scanned with laboratory source µCT or Synchrotron light µCT (SRµCT) were processed in zero-strain tests to evaluate the precision of the DVC methods as a function of the subvolume size that ranged from 8 to 2500 micrometers. The results confirmed that for every microstructure the precision of DVC improves for larger subvolume size, following power laws. However, for the first time large differences in the precision of both local and global DVC approaches have been highlighted when SRµCT or in vivo µCT images were used instead of conventional ex vivo µCT. These findings suggest that in situ mechanical testing protocols applied in SRµCT facilities should be optimized in order to allow DVC analyses of localized strain measurements. Moreover, for in vivo µCT applications DVC analyses should be performed only with relatively course spatial resolution for achieving a reasonable precision of the method. In conclusion, we have extensively shown that the precision of both tested DVC approaches is affected by different bone structures, different input image resolution and different subvolume sizes. Before each specific application DVC users should always apply a similar approach to find the best compromise between precision and spatial resolution of the measurements.

Dynamic four-dimensional computed tomography (4D CT) imaging for re-entry risk assessment in re-do sternotomy - first experience.

PubMed

Narayanan, Harish; Viana, Fabiano F; Smith, Julian A; Roumeliotis, Nicholas K; Troupis, Christopher J; Crossett, Marcus P; Troupis, John M

2015-10-01

Repeat cardiac surgeries are well known to have higher rates of complications, one of the important reasons being injuries associated with re-do sternotomy. Routine imaging with CT can help to minimise this risk by pre-operatively assessing the anatomical relation between the sternum and the underlying cardiovascular structures, but is limited by its inability to determine the presence and severity of functional tethering and adhesions between these structures. However, with the evolution of wide area detector MD CT scanners, it is possible to assess the presence of tethering using the dynamic four-dimensional CT (4D CT) imaging technique. Nineteen patients undergoing re-do cardiac surgery were pre-operatively imaged using dynamic 4D CT during regulated respiration. The datasets were assessed in cine mode for presence of differential motion between sternum and underlying cardiovascular structures which indicates lack of significant tethering. Overall, there was excellent correlation between preoperative imaging and intraoperative findings. The technique enabled our surgeons to meticulously plan the procedures and to avoid re-entry related injuries. Our initial experience shows that dynamic 4D CT is useful in risk stratification prior to re-do sternotomy by determining the presence or absence of tethering between sternum and underlying structures based on assessment of differential motion. Furthermore we determined the technique to be superior to non-dynamic assessment of retrocardiac tethering. Copyright © 2015 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

Analysis and calibration of stage axial vibration for synchrotron radiation nanoscale computed tomography.

PubMed

Fu, Jian; Li, Chen; Liu, Zhenzhong

2015-10-01

Synchrotron radiation nanoscale computed tomography (SR nano-CT) is a powerful analysis tool and can be used to perform chemical identification, mapping, or speciation of carbon and other elements together with X-ray fluorescence and X-ray absorption near edge structure (XANES) imaging. In practical applications, there are often challenges for SR nano-CT due to the misaligned geometry caused by the sample stage axial vibration. It occurs quite frequently because of experimental constraints from the mechanical error of manufacturing and assembly and the thermal expansion during the time-consuming scanning. The axial vibration will lead to the structure overlap among neighboring layers and degrade imaging results by imposing artifacts into the nano-CT images. It becomes worse for samples with complicated axial structure. In this work, we analyze the influence of axial vibration on nano-CT image by partial derivative. Then, an axial vibration calibration method for SR nano-CT is developed and investigated. It is based on the cross correlation of plane integral curves of the sample at different view angles. This work comprises a numerical study of the method and its experimental verification using a dataset measured with the full-field transmission X-ray microscope nano-CT setup at the beamline 4W1A of the Beijing Synchrotron Radiation Facility. The results demonstrate that the presented method can handle the stage axial vibration. It can work for random axial vibration and needs neither calibration phantom nor additional calibration scanning. It will be helpful for the development and application of synchrotron radiation nano-CT systems.

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

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

Consistent evaluation of GOSAT, SCIAMACHY, carbontracker, and MACC through comparisons to TCCON

DOE PAGES

Kulawik, S. S.; Wunch, D.; O'Dell, C.; ...

2015-06-22

Consistent validation of satellite CO 2 estimates is a prerequisite for using multiple satellite CO 2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO 2 data record. We focus on validating model and satellite observation attributes that impact flux estimates and CO 2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry air mole fraction (X CO 2) for GOSAT (ACOS b3.5) and SCIAMACHY (BESD v2.00.08) as wellmore » as the CarbonTracker (CT2013b) simulated CO 2 mole fraction fields and the MACC CO 2 inversion system (v13.1) and compare these to TCCON observations (GGG2014). We find standard deviations of 0.9 ppm, 0.9, 1.7, and 2.1 ppm versus TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single target errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. When satellite data are averaged and interpreted according to error 2 = a 2+ b 2 / n (where n are the number of observations averaged, a are the systematic (correlated) errors, and b are the random (uncorrelated) errors), we find that the correlated error term a = 0.6 ppm and the uncorrelated error term b = 1.7 ppm for GOSAT and a = 1.0 ppm, b = 1.4 ppm for SCIAMACHY regional averages. Biases at individual stations have year-to-year variability of ~ 0.3 ppm, with biases larger than the TCCON predicted bias uncertainty of 0.4 ppm at many stations. Using fitting software, we find that GOSAT underpredicts the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46–53° N. In the Southern Hemisphere (SH), CT2013b underestimates the seasonal cycle amplitude. Biases are calculated for 3-month intervals and indicate the months that contribute to the observed amplitude differences. The seasonal cycle phase indicates whether a dataset or model lags another dataset in time. We calculate this at a subset of stations where there is adequate satellite data, and find that the GOSAT retrieved phase improves substantially over the prior and the SCIAMACHY retrieved phase improves substantially for 2 of 7 sites. The models reproduce the measured seasonal cycle phase well except for at Lauder125 (CT2013b), Darwin (MACC), and Izana (+ 10 days, CT2013b), as for Bremen and Four Corners, which are highly influenced by local effects. We compare the variability within one day between TCCON and models in JJA; there is correlation between 0.2 and 0.8 in the NH, with models showing 10–100 % the variability of TCCON at different stations (except Bremen and Four Corners which have no variability compared to TCCON) and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g. the SH for models and 45–67° N for GOSAT« less

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.

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.

Evaluation of in-vivo measurement errors associated with micro-computed tomography scans by means of the bone surface distance approach.

PubMed

Lu, Yongtao; Boudiffa, Maya; Dall'Ara, Enrico; Bellantuono, Ilaria; Viceconti, Marco

2015-11-01

In vivo micro-computed tomography (µCT) scanning is an important tool for longitudinal monitoring of the bone adaptation process in animal models. However, the errors associated with the usage of in vivo µCT measurements for the evaluation of bone adaptations remain unclear. The aim of this study was to evaluate the measurement errors using the bone surface distance approach. The right tibiae of eight 14-week-old C57BL/6 J female mice were consecutively scanned four times in an in vivo µCT scanner using a nominal isotropic image voxel size (10.4 µm) and the tibiae were repositioned between each scan. The repeated scan image datasets were aligned to the corresponding baseline (first) scan image dataset using rigid registration and a region of interest was selected in the proximal tibia metaphysis for analysis. The bone surface distances between the repeated and the baseline scan datasets were evaluated. It was found that the average (±standard deviation) median and 95th percentile bone surface distances were 3.10 ± 0.76 µm and 9.58 ± 1.70 µm, respectively. This study indicated that there were inevitable errors associated with the in vivo µCT measurements of bone microarchitecture and these errors should be taken into account for a better interpretation of bone adaptations measured with in vivo µCT. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

PubMed Central

Reeves, Anthony P.; Xie, Yiting; Liu, Shuang

2017-01-01

Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset. PMID:28612037

A decision tree model for predicting mediastinal lymph node metastasis in non-small cell lung cancer with F-18 FDG PET/CT.

PubMed

Pak, Kyoungjune; Kim, Keunyoung; Kim, Mi-Hyun; Eom, Jung Seop; Lee, Min Ki; Cho, Jeong Su; Kim, Yun Seong; Kim, Bum Soo; Kim, Seong Jang; Kim, In Joo

2018-01-01

We aimed to develop a decision tree model to improve diagnostic performance of positron emission tomography/computed tomography (PET/CT) to detect metastatic lymph nodes (LN) in non-small cell lung cancer (NSCLC). 115 patients with NSCLC were included in this study. The training dataset included 66 patients. A decision tree model was developed with 9 variables, and validated with 49 patients: short and long diameters of LNs, ratio of short and long diameters, maximum standardized uptake value (SUVmax) of LN, mean hounsfield unit, ratio of LN SUVmax and ascending aorta SUVmax (LN/AA), and ratio of LN SUVmax and superior vena cava SUVmax. A total of 301 LNs of 115 patients were evaluated in this study. Nodular calcification was applied as the initial imaging parameter, and LN SUVmax (≥3.95) was assessed as the second. LN/AA (≥2.92) was required to high LN SUVmax. Sensitivity was 50% for training dataset, and 40% for validation dataset. However, specificity was 99.28% for training dataset, and 96.23% for validation dataset. In conclusion, we have developed a new decision tree model for interpreting mediastinal LNs. All LNs with nodular calcification were benign, and LNs with high LN SUVmax and high LN/AA were metastatic Further studies are needed to incorporate subjective parameters and pathologic evaluations into a decision tree model to improve the test performance of PET/CT.

A reconstruction method for cone-beam differential x-ray phase-contrast computed tomography.

PubMed

Fu, Jian; Velroyen, Astrid; Tan, Renbo; Zhang, Junwei; Chen, Liyuan; Tapfer, Arne; Bech, Martin; Pfeiffer, Franz

2012-09-10

Most existing differential phase-contrast computed tomography (DPC-CT) approaches are based on three kinds of scanning geometries, described by parallel-beam, fan-beam and cone-beam. Due to the potential of compact imaging systems with magnified spatial resolution, cone-beam DPC-CT has attracted significant interest. In this paper, we report a reconstruction method based on a back-projection filtration (BPF) algorithm for cone-beam DPC-CT. Due to the differential nature of phase contrast projections, the algorithm restrains from differentiation of the projection data prior to back-projection, unlike BPF algorithms commonly used for absorption-based CT data. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured with a three-grating interferometer and a micro-focus x-ray tube source. Moreover, the numerical simulation and experimental results demonstrate that the proposed method can deal with several classes of truncated cone-beam datasets. We believe that this feature is of particular interest for future medical cone-beam phase-contrast CT imaging applications.

Hard x-ray micro-tomography of a human head post-mortem as a gold standard to compare x-ray modalities

NASA Astrophysics Data System (ADS)

Dalstra, M.; Schulz, G.; Dagassan-Berndt, D.; Verna, C.; Müller-Gerbl, M.; Müller, B.

2016-10-01

An entire human head obtained at autopsy was micro-CT scanned in a nano/micro-CT scanner in a 6-hour long session. Despite the size of the head, it could still be scanned with a pixel size of 70 μm. The aim of this study was to obtain an optimal quality 3D data-set to be used as baseline control in a larger study comparing the image quality of various cone beam CT systems currently used in dentistry. The image quality of the micro-CT scans was indeed better than the ones of the clinical imaging modalities, both with regard to noise and streak artifacts due to metal dental implants. Bony features in the jaws, like the trabecular architecture and the thin wall of the alveolar bone were clearly visible. Therefore, the 3D micro-CT data-set can be used as the gold standard for linear, angular, and volumetric measurements of anatomical features in and around the oral cavity when comparing clinical imaging modalities.

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

PubMed

Li, Liang; Wang, Bigong; Wang, Ge

2016-01-01

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

Fast skin dose estimation system for interventional radiology

PubMed Central

Takata, Takeshi; Kotoku, Jun’ichi; Maejima, Hideyuki; Kumagai, Shinobu; Arai, Norikazu; Kobayashi, Takenori; Shiraishi, Kenshiro; Yamamoto, Masayoshi; Kondo, Hiroshi; Furui, Shigeru

2018-01-01

Abstract To minimise the radiation dermatitis related to interventional radiology (IR), rapid and accurate dose estimation has been sought for all procedures. We propose a technique for estimating the patient skin dose rapidly and accurately using Monte Carlo (MC) simulation with a graphical processing unit (GPU, GTX 1080; Nvidia Corp.). The skin dose distribution is simulated based on an individual patient’s computed tomography (CT) dataset for fluoroscopic conditions after the CT dataset has been segmented into air, water and bone based on pixel values. The skin is assumed to be one layer at the outer surface of the body. Fluoroscopic conditions are obtained from a log file of a fluoroscopic examination. Estimating the absorbed skin dose distribution requires calibration of the dose simulated by our system. For this purpose, a linear function was used to approximate the relation between the simulated dose and the measured dose using radiophotoluminescence (RPL) glass dosimeters in a water-equivalent phantom. Differences of maximum skin dose between our system and the Particle and Heavy Ion Transport code System (PHITS) were as high as 6.1%. The relative statistical error (2 σ) for the simulated dose obtained using our system was ≤3.5%. Using a GPU, the simulation on the chest CT dataset aiming at the heart was within 3.49 s on average: the GPU is 122 times faster than a CPU (Core i7–7700K; Intel Corp.). Our system (using the GPU, the log file, and the CT dataset) estimated the skin dose more rapidly and more accurately than conventional methods. PMID:29136194

Fast skin dose estimation system for interventional radiology.

PubMed

Takata, Takeshi; Kotoku, Jun'ichi; Maejima, Hideyuki; Kumagai, Shinobu; Arai, Norikazu; Kobayashi, Takenori; Shiraishi, Kenshiro; Yamamoto, Masayoshi; Kondo, Hiroshi; Furui, Shigeru

2018-03-01

To minimise the radiation dermatitis related to interventional radiology (IR), rapid and accurate dose estimation has been sought for all procedures. We propose a technique for estimating the patient skin dose rapidly and accurately using Monte Carlo (MC) simulation with a graphical processing unit (GPU, GTX 1080; Nvidia Corp.). The skin dose distribution is simulated based on an individual patient's computed tomography (CT) dataset for fluoroscopic conditions after the CT dataset has been segmented into air, water and bone based on pixel values. The skin is assumed to be one layer at the outer surface of the body. Fluoroscopic conditions are obtained from a log file of a fluoroscopic examination. Estimating the absorbed skin dose distribution requires calibration of the dose simulated by our system. For this purpose, a linear function was used to approximate the relation between the simulated dose and the measured dose using radiophotoluminescence (RPL) glass dosimeters in a water-equivalent phantom. Differences of maximum skin dose between our system and the Particle and Heavy Ion Transport code System (PHITS) were as high as 6.1%. The relative statistical error (2 σ) for the simulated dose obtained using our system was ≤3.5%. Using a GPU, the simulation on the chest CT dataset aiming at the heart was within 3.49 s on average: the GPU is 122 times faster than a CPU (Core i7-7700K; Intel Corp.). Our system (using the GPU, the log file, and the CT dataset) estimated the skin dose more rapidly and more accurately than conventional methods.

Generation of a suite of 3D computer-generated breast phantoms from a limited set of human subject data

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

Hsu, Christina M. L.; Palmeri, Mark L.; Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina 27710

2013-04-15

Purpose: The authors previously reported on a three-dimensional computer-generated breast phantom, based on empirical human image data, including a realistic finite-element based compression model that was capable of simulating multimodality imaging data. The computerized breast phantoms are a hybrid of two phantom generation techniques, combining empirical breast CT (bCT) data with flexible computer graphics techniques. However, to date, these phantoms have been based on single human subjects. In this paper, the authors report on a new method to generate multiple phantoms, simulating additional subjects from the limited set of original dedicated breast CT data. The authors developed an image morphingmore » technique to construct new phantoms by gradually transitioning between two human subject datasets, with the potential to generate hundreds of additional pseudoindependent phantoms from the limited bCT cases. The authors conducted a preliminary subjective assessment with a limited number of observers (n= 4) to illustrate how realistic the simulated images generated with the pseudoindependent phantoms appeared. Methods: Several mesh-based geometric transformations were developed to generate distorted breast datasets from the original human subject data. Segmented bCT data from two different human subjects were used as the 'base' and 'target' for morphing. Several combinations of transformations were applied to morph between the 'base' and 'target' datasets such as changing the breast shape, rotating the glandular data, and changing the distribution of the glandular tissue. Following the morphing, regions of skin and fat were assigned to the morphed dataset in order to appropriately assign mechanical properties during the compression simulation. The resulting morphed breast was compressed using a finite element algorithm and simulated mammograms were generated using techniques described previously. Sixty-two simulated mammograms, generated from morphing three human subject datasets, were used in a preliminary observer evaluation where four board certified breast radiologists with varying amounts of experience ranked the level of realism (from 1 ='fake' to 10 ='real') of the simulated images. Results: The morphing technique was able to successfully generate new and unique morphed datasets from the original human subject data. The radiologists evaluated the realism of simulated mammograms generated from the morphed and unmorphed human subject datasets and scored the realism with an average ranking of 5.87 {+-} 1.99, confirming that overall the phantom image datasets appeared more 'real' than 'fake.' Moreover, there was not a significant difference (p > 0.1) between the realism of the unmorphed datasets (6.0 {+-} 1.95) compared to the morphed datasets (5.86 {+-} 1.99). Three of the four observers had overall average rankings of 6.89 {+-} 0.89, 6.9 {+-} 1.24, 6.76 {+-} 1.22, whereas the fourth observer ranked them noticeably lower at 2.94 {+-} 0.7. Conclusions: This work presents a technique that can be used to generate a suite of realistic computerized breast phantoms from a limited number of human subjects. This suite of flexible breast phantoms can be used for multimodality imaging research to provide a known truth while concurrently producing realistic simulated imaging data.« less

Prostate Localization on Daily Cone-Beam Computed Tomography Images: Accuracy Assessment of Similarity Metrics

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

Kim, Jinkoo, E-mail: jkim3@hfhs.or; Hammoud, Rabih; Pradhan, Deepak

2010-07-15

Purpose: To evaluate different similarity metrics (SM) using natural calcifications and observation-based measures to determine the most accurate prostate and seminal vesicle localization on daily cone-beam CT (CBCT) images. Methods and Materials: CBCT images of 29 patients were retrospectively analyzed; 14 patients with prostate calcifications (calcification data set) and 15 patients without calcifications (no-calcification data set). Three groups of test registrations were performed. Test 1: 70 CT/CBCT pairs from calcification dataset were registered using 17 SMs (6,580 registrations) and compared using the calcification mismatch error as an endpoint. Test 2: Using the four best SMs from Test 1, 75 CT/CBCTmore » pairs in the no-calcification data set were registered (300 registrations). Accuracy of contour overlays was ranked visually. Test 3: For the best SM from Tests 1 and 2, accuracy was estimated using 356 CT/CBCT registrations. Additionally, target expansion margins were investigated for generating registration regions of interest. Results: Test 1-Incremental sign correlation (ISC), gradient correlation (GC), gradient difference (GD), and normalized cross correlation (NCC) showed the smallest errors ({mu} {+-} {sigma}: 1.6 {+-} 0.9 {approx} 2.9 {+-} 2.1 mm). Test 2-Two of the three reviewers ranked GC higher. Test 3-Using GC, 96% of registrations showed <3-mm error when calcifications were filtered. Errors were left/right: 0.1 {+-} 0.5mm, anterior/posterior: 0.8 {+-} 1.0mm, and superior/inferior: 0.5 {+-} 1.1 mm. The existence of calcifications increased the success rate to 97%. Expansion margins of 4-10 mm were equally successful. Conclusion: Gradient-based SMs were most accurate. Estimated error was found to be <3 mm (1.1 mm SD) in 96% of the registrations. Results suggest that the contour expansion margin should be no less than 4 mm.« less

Automated anatomical labeling of bronchial branches extracted from CT datasets based on machine learning and combination optimization and its application to bronchoscope guidance.

PubMed

Mori, Kensaku; Ota, Shunsuke; Deguchi, Daisuke; Kitasaka, Takayuki; Suenaga, Yasuhito; Iwano, Shingo; Hasegawa, Yosihnori; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi

2009-01-01

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.

Creation of anatomical models from CT data

NASA Astrophysics Data System (ADS)

Alaytsev, Innokentiy K.; Danilova, Tatyana V.; Manturov, Alexey O.; Mareev, Gleb O.; Mareev, Oleg V.

2018-04-01

Computed tomography is a great source of biomedical data because it allows a detailed exploration of complex anatomical structures. Some structures are not visible on CT scans, and some are hard to distinguish due to partial volume effect. CT datasets require preprocessing before using them as anatomical models in a simulation system. The work describes segmentation and data transformation methods for an anatomical model creation from the CT data. The result models may be used for visual and haptic rendering and drilling simulation in a virtual surgery system.

Can DCE-MRI Explain the Heterogeneity in Radiopeptide Uptake Imaged by SPECT in a Pancreatic Neuroendocrine Tumor Model?

PubMed Central

Groen, Harald C.; Niessen, Wiro J.; Bernsen, Monique R.; de Jong, Marion; Veenland, Jifke F.

2013-01-01

Although efficient delivery and distribution of treatment agents over the whole tumor is essential for successful tumor treatment, the distribution of most of these agents cannot be visualized. However, with single-photon emission computed tomography (SPECT), both delivery and uptake of radiolabeled peptides can be visualized in a neuroendocrine tumor model overexpressing somatostatin receptors. A heterogeneous peptide uptake is often observed in these tumors. We hypothesized that peptide distribution in the tumor is spatially related to tumor perfusion, vessel density and permeability, as imaged and quantified by DCE-MRI in a neuroendocrine tumor model. Four subcutaneous CA20948 tumor-bearing Lewis rats were injected with the somatostatin-analog 111In-DTPA-Octreotide (50 MBq). SPECT-CT and MRI scans were acquired and MRI was spatially registered to SPECT-CT. DCE-MRI was analyzed using semi-quantitative and quantitative methods. Correlation between SPECT and DCE-MRI was investigated with 1) Spearman’s rank correlation coefficient; 2) SPECT uptake values grouped into deciles with corresponding median DCE-MRI parametric values and vice versa; and 3) linear regression analysis for median parameter values in combined datasets. In all tumors, areas with low peptide uptake correlated with low perfusion/density/ /permeability for all DCE-MRI-derived parameters. Combining all datasets, highest linear regression was found between peptide uptake and semi-quantitative parameters (R2>0.7). The average correlation coefficient between SPECT and DCE-MRI-derived parameters ranged from 0.52-0.56 (p<0.05) for parameters primarily associated with exchange between blood and extracellular extravascular space. For these parameters a linear relation with peptide uptake was observed. In conclusion, the ‘exchange-related’ DCE-MRI-derived parameters seemed to predict peptide uptake better than the ‘contrast amount- related’ parameters. Consequently, fast and efficient diffusion through the vessel wall into tissue is an important factor for peptide delivery. DCE-MRI helps to elucidate the relation between vascular characteristics, peptide delivery and treatment efficacy, and may form a basis to predict targeting efficiency. PMID:24116203

Automatic categorization of anatomical landmark-local appearances based on diffeomorphic demons and spectral clustering for constructing detector ensembles.

PubMed

Hanaoka, Shouhei; Masutani, Yoshitaka; Nemoto, Mitsutaka; Nomura, Yukihiro; Yoshikawa, Takeharu; Hayashi, Naoto; Ohtomo, Kuni

2012-01-01

A method for categorizing landmark-local appearances extracted from computed tomography (CT) datasets is presented. Anatomical landmarks in the human body inevitably have inter-individual variations that cause difficulty in automatic landmark detection processes. The goal of this study is to categorize subjects (i.e., training datasets) according to local shape variations of such a landmark so that each subgroup has less shape variation and thus the machine learning of each landmark detector is much easier. The similarity between each subject pair is measured based on the non-rigid registration result between them. These similarities are used by the spectral clustering process. After the clustering, all training datasets in each cluster, as well as synthesized intermediate images calculated from all subject-pairs in the cluster, are used to train the corresponding subgroup detector. All of these trained detectors compose a detector ensemble to detect the target landmark. Evaluation with clinical CT datasets showed great improvement in the detection performance.

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.

Normalized gradient fields cross-correlation for automated detection of prostate in magnetic resonance images

NASA Astrophysics Data System (ADS)

Fotin, Sergei V.; Yin, Yin; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter L.

2012-02-01

Fully automated prostate segmentation helps to address several problems in prostate cancer diagnosis and treatment: it can assist in objective evaluation of multiparametric MR imagery, provides a prostate contour for MR-ultrasound (or CT) image fusion for computer-assisted image-guided biopsy or therapy planning, may facilitate reporting and enables direct prostate volume calculation. Among the challenges in automated analysis of MR images of the prostate are the variations of overall image intensities across scanners, the presence of nonuniform multiplicative bias field within scans and differences in acquisition setup. Furthermore, images acquired with the presence of an endorectal coil suffer from localized high-intensity artifacts at the posterior part of the prostate. In this work, a three-dimensional method for fast automated prostate detection based on normalized gradient fields cross-correlation, insensitive to intensity variations and coil-induced artifacts, is presented and evaluated. The components of the method, offline template learning and the localization algorithm, are described in detail. The method was validated on a dataset of 522 T2-weighted MR images acquired at the National Cancer Institute, USA that was split in two halves for development and testing. In addition, second dataset of 29 MR exams from Centre d'Imagerie Médicale Tourville, France were used to test the algorithm. The 95% confidence intervals for the mean Euclidean distance between automatically and manually identified prostate centroids were 4.06 +/- 0.33 mm and 3.10 +/- 0.43 mm for the first and second test datasets respectively. Moreover, the algorithm provided the centroid within the true prostate volume in 100% of images from both datasets. Obtained results demonstrate high utility of the detection method for a fully automated prostate segmentation.

The Cryosphere Model Comparison Tool (CmCt): Ice Sheet Model Validation and Comparison Tool for Greenland and Antarctica

NASA Astrophysics Data System (ADS)

Simon, E.; Nowicki, S.; Neumann, T.; Tyahla, L.; Saba, J. L.; Guerber, J. R.; Bonin, J. A.; DiMarzio, J. P.

2017-12-01

The Cryosphere model Comparison tool (CmCt) is a web based ice sheet model validation tool that is being developed by NASA to facilitate direct comparison between observational data and various ice sheet models. The CmCt allows the user to take advantage of several decades worth of observations from Greenland and Antarctica. Currently, the CmCt can be used to compare ice sheet models provided by the user with remotely sensed satellite data from ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry, GRACE (Gravity Recovery and Climate Experiment) satellite, and radar altimetry (ERS-1, ERS-2, and Envisat). One or more models can be uploaded through the CmCt website and compared with observational data, or compared to each other or other models. The CmCt calculates statistics on the differences between the model and observations, and other quantitative and qualitative metrics, which can be used to evaluate the different model simulations against the observations. The qualitative metrics consist of a range of visual outputs and the quantitative metrics consist of several whole-ice-sheet scalar values that can be used to assign an overall score to a particular simulation. The comparison results from CmCt are useful in quantifying improvements within a specific model (or within a class of models) as a result of differences in model dynamics (e.g., shallow vs. higher-order dynamics approximations), model physics (e.g., representations of ice sheet rheological or basal processes), or model resolution (mesh resolution and/or changes in the spatial resolution of input datasets). The framework and metrics could also be used for use as a model-to-model intercomparison tool, simply by swapping outputs from another model as the observational datasets. Future versions of the tool will include comparisons with other datasets that are of interest to the modeling community, such as ice velocity, ice thickness, and surface mass balance.

On the Discrepancy in Simultaneous Observations of the Structure Parameter of Temperature Using Scintillometers and Unmanned Aircraft

NASA Astrophysics Data System (ADS)

Braam, Miranda; Beyrich, Frank; Bange, Jens; Platis, Andreas; Martin, Sabrina; Maronga, Björn; Moene, Arnold F.

2016-02-01

We elaborate on the preliminary results presented in Beyrich et al. (in Boundary-Layer Meteorol 144:83-112, 2012), who compared the structure parameter of temperature ({CT^2}_{}) obtained with the unmanned meteorological mini aerial vehicle (M2 AV) versus {CT^2}_{} obtained with two large-aperture scintillometers (LASs) for a limited dataset from one single experiment (LITFASS-2009). They found that {CT^2}_{} obtained from the M2 AV data is significantly larger than that obtained from the LAS data. We investigate if similar differences can be found for the flights on the other six days during LITFASS-2009 and LITFASS-2010, and whether these differences can be reduced or explained through a more elaborate processing of both the LAS data and the M2 AV data. This processing includes different corrections and measures to reduce the differences between the spatial and temporal averaging of the datasets. We conclude that the differences reported in Beyrich et al. can be found for other days as well. For the LAS-derived values the additional processing steps that have the largest effect are the saturation correction and the humidity correction. For the M2 AV -derived values the most important step is the application of the scintillometer path-weighting function. Using the true air speed of the M2 AV to convert from a temporal to a spatial structure function rather than the ground speed (as in Beyrich et al.) does not change the mean discrepancy, but it does affect {CT^2}_{} values for individual flights. To investigate whether {CT^2}_{} derived from the M2 AV data depends on the fact that the underlying temperature dataset combines spatial and temporal sampling, we used large-eddy simulation data to analyze {CT^2}_{} from virtual flights with different mean ground speeds. This analysis shows that {CT^2}_{} does only slightly depends on the true air speed when averaged over many flights.

Towards real time 2D to 3D registration for ultrasound-guided endoscopic and laparoscopic procedures.

PubMed

San José Estépar, Raúl; Westin, Carl-Fredrik; Vosburgh, Kirby G

2009-11-01

A method to register endoscopic and laparoscopic ultrasound (US) images in real time with pre-operative computed tomography (CT) data sets has been developed with the goal of improving diagnosis, biopsy guidance, and surgical interventions in the abdomen. The technique, which has the potential to operate in real time, is based on a new phase correlation technique: LEPART, which specifies the location of a plane in the CT data which best corresponds to the US image. Validation of the method was carried out using an US phantom with cyst regions and with retrospective analysis of data sets from animal model experiments. The phantom validation study shows that local translation displacements can be recovered for each US frame with a root mean squared error of 1.56 +/- 0.78 mm in less than 5 sec, using non-optimized algorithm implementations. A new method for multimodality (preoperative CT and intraoperative US endoscopic images) registration to guide endoscopic interventions was developed and found to be efficient using clinically realistic datasets. The algorithm is inherently capable of being implemented in a parallel computing system so that full real time operation appears likely.

CT-based manual segmentation and evaluation of paranasal sinuses.

PubMed

Pirner, S; Tingelhoff, K; Wagner, I; Westphal, R; Rilk, M; Wahl, F M; Bootz, F; Eichhorn, Klaus W G

2009-04-01

Manual segmentation of computed tomography (CT) datasets was performed for robot-assisted endoscope movement during functional endoscopic sinus surgery (FESS). Segmented 3D models are needed for the robots' workspace definition. A total of 50 preselected CT datasets were each segmented in 150-200 coronal slices with 24 landmarks being set. Three different colors for segmentation represent diverse risk areas. Extension and volumetric measurements were performed. Three-dimensional reconstruction was generated after segmentation. Manual segmentation took 8-10 h for each CT dataset. The mean volumes were: right maxillary sinus 17.4 cm(3), left side 17.9 cm(3), right frontal sinus 4.2 cm(3), left side 4.0 cm(3), total frontal sinuses 7.9 cm(3), sphenoid sinus right side 5.3 cm(3), left side 5.5 cm(3), total sphenoid sinus volume 11.2 cm(3). Our manually segmented 3D-models present the patient's individual anatomy with a special focus on structures in danger according to the diverse colored risk areas. For safe robot assistance, the high-accuracy models represent an average of the population for anatomical variations, extension and volumetric measurements. They can be used as a database for automatic model-based segmentation. None of the segmentation methods so far described provide risk segmentation. The robot's maximum distance to the segmented border can be adjusted according to the differently colored areas.

A method for encoding clinical datasets with SNOMED CT.

PubMed

Lee, Dennis H; Lau, Francis Y; Quan, Hue

2010-09-17

Over the past decade there has been a growing body of literature on how the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) can be implemented and used in different clinical settings. Yet, for those charged with incorporating SNOMED CT into their organisation's clinical applications and vocabulary systems, there are few detailed encoding instructions and examples available to show how this can be done and the issues involved. This paper describes a heuristic method that can be used to encode clinical terms in SNOMED CT and an illustration of how it was applied to encode an existing palliative care dataset. The encoding process involves: identifying input data items; cleaning the data items; encoding the cleaned data items; and exporting the encoded terms as output term sets. Four outputs are produced: the SNOMED CT reference set; interface terminology set; SNOMED CT extension set and unencodeable term set. The original palliative care database contained 211 data elements, 145 coded values and 37,248 free text values. We were able to encode ~84% of the terms, another ~8% require further encoding and verification while terms that had a frequency of fewer than five were not encoded (~7%). From the pilot, it would seem our SNOMED CT encoding method has the potential to become a general purpose terminology encoding approach that can be used in different clinical systems.

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

Khoo, Eric L.H., E-mail: eric.khoo@roq.net.au; Schick, Karlissa; Plank, Ashley W.

Purpose: To assess whether an education program on CT and MRI prostate anatomy would reduce inter- and intraobserver prostate contouring variation among experienced radiation oncologists. Methods and Materials: Three patient CT and MRI datasets were selected. Five radiation oncologists contoured the prostate for each patient on CT first, then MRI, and again between 2 and 4 weeks later. Three education sessions were then conducted. The same contouring process was then repeated with the same datasets and oncologists. The observer variation was assessed according to changes in the ratio of the encompassing volume to intersecting volume (volume ratio [VR]), across setsmore » of target volumes. Results: For interobserver variation, there was a 15% reduction in mean VR with CT, from 2.74 to 2.33, and a 40% reduction in mean VR with MRI, from 2.38 to 1.41 after education. A similar trend was found for intraobserver variation, with a mean VR reduction for CT and MRI of 9% (from 1.51 to 1.38) and 16% (from 1.37 to 1.15), respectively. Conclusion: A well-structured education program has reduced both inter- and intraobserver prostate contouring variations. The impact was greater on MRI than on CT. With the ongoing incorporation of new technologies into routine practice, education programs for target contouring should be incorporated as part of the continuing medical education of radiation oncologists.« less

Exploring homogeneity of correlation structures of gene expression datasets within and between etiological disease categories.

PubMed

Jong, Victor L; Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-12-01

The literature shows that classifiers perform differently across datasets and that correlations within datasets affect the performance of classifiers. The question that arises is whether the correlation structure within datasets differ significantly across diseases. In this study, we evaluated the homogeneity of correlation structures within and between datasets of six etiological disease categories; inflammatory, immune, infectious, degenerative, hereditary and acute myeloid leukemia (AML). We also assessed the effect of filtering; detection call and variance filtering on correlation structures. We downloaded microarray datasets from ArrayExpress for experiments meeting predefined criteria and ended up with 12 datasets for non-cancerous diseases and six for AML. The datasets were preprocessed by a common procedure incorporating platform-specific recommendations and the two filtering methods mentioned above. Homogeneity of correlation matrices between and within datasets of etiological diseases was assessed using the Box's M statistic on permuted samples. We found that correlation structures significantly differ between datasets of the same and/or different etiological disease categories and that variance filtering eliminates more uncorrelated probesets than detection call filtering and thus renders the data highly correlated.

Segmentation of the ovine lung in 3D CT Images

NASA Astrophysics Data System (ADS)

Shi, Lijun; Hoffman, Eric A.; Reinhardt, Joseph M.

2004-04-01

Pulmonary CT images can provide detailed information about the regional structure and function of the respiratory system. Prior to any of these analyses, however, the lungs must be identified in the CT data sets. A popular animal model for understanding lung physiology and pathophysiology is the sheep. In this paper we describe a lung segmentation algorithm for CT images of sheep. The algorithm has two main steps. The first step is lung extraction, which identifies the lung region using a technique based on optimal thresholding and connected components analysis. The second step is lung separation, which separates the left lung from the right lung by identifying the central fissure using an anatomy-based method incorporating dynamic programming and a line filter algorithm. The lung segmentation algorithm has been validated by comparing our automatic method to manual analysis for five pulmonary CT datasets. The RMS error between the computer-defined and manually-traced boundary is 0.96 mm. The segmentation requires approximately 10 minutes for a 512x512x400 dataset on a PC workstation (2.40 GHZ CPU, 2.0 GB RAM), while it takes human observer approximately two hours to accomplish the same task.

Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images.

PubMed

Hanaoka, Shouhei; Masutani, Yoshitaka; Nemoto, Mitsutaka; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu; Hayashi, Naoto; Ohtomo, Kuni; Shimizu, Akinobu

2017-03-01

A fully automatic multiatlas-based method for segmentation of the spine and pelvis in a torso CT volume is proposed. A novel landmark-guided diffeomorphic demons algorithm is used to register a given CT image to multiple atlas volumes. This algorithm can utilize both grayscale image information and given landmark coordinate information optimally. The segmentation has four steps. Firstly, 170 bony landmarks are detected in the given volume. Using these landmark positions, an atlas selection procedure is performed to reduce the computational cost of the following registration. Then the chosen atlas volumes are registered to the given CT image. Finally, voxelwise label voting is performed to determine the final segmentation result. The proposed method was evaluated using 50 torso CT datasets as well as the public SpineWeb dataset. As a result, a mean distance error of [Formula: see text] and a mean Dice coefficient of [Formula: see text] were achieved for the whole spine and the pelvic bones, which are competitive with other state-of-the-art methods. From the experimental results, the usefulness of the proposed segmentation method was validated.

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.

Clinical Value of Dual-energy CT in Detection of Pancreatic Adenocarcinoma: Investigation of the Best Pancreatic Tumor Contrast to Noise Ratio.

PubMed

He, Yong-Lan; Zhang, Da-Ming; Xue, Hua-Dan; Jin, Zheng-Yu

2013-01-01

Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNRF) and CNR of the major psoas muscle (CNRM) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNRF (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNRF (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNRF in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNRF of mono-energetic image sets vs. CNRF of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.

Correlations between symptoms, nasal endoscopy, and in-office computed tomography in post-surgical chronic rhinosinusitis patients.

PubMed

Ryan, William R; Ramachandra, Tara; Hwang, Peter H

2011-03-01

To determine correlations between symptoms, nasal endoscopy findings, and computed tomography (CT) scan findings in post-surgical chronic rhinosinusitis (CRS) patients. Cross-sectional. A total of 51 CRS patients who had undergone endoscopic sinus surgery (ESS) completed symptom questionnaires, underwent endoscopy, and received an in-office sinus CT scan during one clinic visit. For metrics, we used the Sinonasal Outcomes Test-20 (SNOT-20) questionnaire, visual analog symptom scale (VAS), Lund-Kennedy endoscopy scoring scale, and Lund-MacKay (LM) CT scoring scale. We determined Pearson correlation coefficients, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) between scores for symptoms, endoscopy, and CT. The SNOT-20 score and most VAS symptoms had poor correlation coefficients with both endoscopy and CT scores (0.03-0.24). Nasal drainage of pus, nasal congestion, and impaired sense of smell had moderate correlation coefficients with endoscopy and CT (0.24-0.42). Endoscopy had a strong correlation coefficient with CT (0.76). Drainage, edema, and polyps had strong correlation coefficients with CT (0.80, 0.69, and 0.49, respectively). Endoscopy had a PPV of 92.5% and NPV of 45.5% for detecting an abnormal sinus CT (LM score ≥1). In post-ESS CRS patients, most symptoms do not correlate well with either endoscopy or CT findings. Endoscopy and CT scores correlate well. Abnormal endoscopy findings have the ability to confidently rule in the presence of CT opacification, thus validating the importance of endoscopy in clinical decision making. However, a normal endoscopy cannot assure a normal CT. Thus, symptoms, endoscopy, and CT are complementary in the evaluation of the post-ESS CRS patient. Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc., Rhinological, and Otological Society, Inc.

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.

Estimation of genetic parameters for reproductive traits in alpacas.

PubMed

Cruz, A; Cervantes, I; Burgos, A; Morante, R; Gutiérrez, J P

2015-12-01

One of the main deficiencies affecting animal breeding programs in Peruvian alpacas is the low reproductive performance leading to low number of animals available to select from, decreasing strongly the selection intensity. Some reproductive traits could be improved by artificial selection, but very few information about genetic parameters exists for these traits in this specie. The aim of this study was to estimate genetic parameters for six reproductive traits in alpacas both in Suri (SU) and Huacaya (HU) ecotypes, as well as their genetic relationship with fiber and morphological traits. Dataset belonging to Pacomarca experimental farm collected between 2000 and 2014 was used. Number of records for age at first service (AFS), age at first calving (AFC), copulation time (CT), pregnancy diagnosis (PD), gestation length (GL), and calving interval (CI) were, respectively, 1704, 854, 19,770, 5874, 4290 and 934. Pedigree consisted of 7742 animals. Regarding reproductive traits, model of analysis included additive and residual random effects for all traits, and also permanent environmental effect for CT, PD, GL and CI traits, with color and year of recording as fixed effects for all the reproductive traits and also age at mating and sex of calf for GL trait. Estimated heritabilities, respectively for HU and SU were 0.19 and 0.09 for AFS, 0.45 and 0.59 for AFC, 0.04 and 0.05 for CT, 0.07 and 0.05 for PD, 0.12 and 0.20 for GL, and 0.14 and 0.09 for CI. Genetic correlations between them ranged from -0.96 to 0.70. No important genetic correlations were found between reproductive traits and fiber or morphological traits in HU. However, some moderate favorable genetic correlations were found between reproductive and either fiber and morphological traits in SU. According to estimated genetic correlations, some reproductive traits might be included as additional selection criteria in HU. Copyright © 2015 Elsevier B.V. All rights reserved.

Temporal subtraction contrast-enhanced dedicated breast CT

NASA Astrophysics Data System (ADS)

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-09-01

The development of a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, intensity difference adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using normalized cross correlation (NCC), symmetric uncertainty coefficient, normalized mutual information (NMI), mean square error (MSE) and target registration error (TRE). The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE (0-16%), NCC (0-6%), NMI (0-13%) and TRE (0-34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake.

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

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.

SPET/CT image co-registration in the abdomen with a simple and cost-effective tool.

PubMed

Förster, Gregor J; Laumann, Christina; Nickel, Otmar; Kann, Peter; Rieker, Olaf; Bartenstein, Peter

2003-01-01

Fusion of morphology and function has been shown to improve diagnostic accuracy in many clinical circumstances. Taking this into account, a number of instruments combining computed tomography (CT) with positron emission tomography (PET) or single-photon emission tomography (SPET) are appearing on the market. The aim of this study was to evaluate a simple and cost-effective approach to generate fusion images of similar quality. For the evaluation of the proposed approach, patients with neuroendocrine abdominal tumours with liver metastases were chosen, since the exact superimposition in the abdomen is more difficult than in other regions. Five hours following the injection of 110 MBq (111)In-DTPA-octreotide, patients were fixed in a vacuum cushion (MED-TEC, Vac-Loc) and investigated with helical CT in a mid-inspiration position ( n=14). Directly following the CT, a SPET study (SPET1) of the abdominal region was performed without changing the position of the patient. A second SPET study (SPET2), 24 h p.i., was acquired after repositioning the patient in his or her individually moulded vacuum cushion. A total of nine markers suitable for imaging with CT and SPET were fixed on the cushion. Datasets were fused by means of internal landmarks (e.g. metastases or margin of abdominal organs) or by the external markers. Image fusion using external markers was fast and easy to handle compared with the use of internal landmarks. Using this technique, all lesions detectable by SPET ( n=28) appeared exactly superpositioned on the respective CT morphology by visual inspection. Image fusion of CT/SPET1 and CT/SPET2 showed a mean deviation of the external markers that in the former case was smaller than the voxel size of 4.67 mm: 4.17+/-0.61 (CT/SPET1; +/-SD) and 5.52+/-1.56 mm (CT/SPET2), respectively. Using internal landmarks, the mean deviation of the chosen landmarks was 6.47+/-1.37 and 7.78+/-1.21 mm. Vector subtraction of corresponding anatomical points of the CT and the re-sampled SPET volume datasets resulted in a similar accuracy. Vector subtraction of the metastases showed a significantly less accurate superimposition when internal landmarks were used ( P<0.001). The vacuum cushion did not affect the image quality of CT and SPET. The proposed technique is a simple and cost-effective way to generate abdominal datasets suitable for image fusion. External markers positioned on the cushion allow for a rapid and robust overlay even if no readily identifiable internal landmarks are present. This technique is, in principle, also suitable for CT/PET fusion as well as for fusions of MRI data with PET or SPET.

Technical note: RabbitCT--an open platform for benchmarking 3D cone-beam reconstruction algorithms.

PubMed

Rohkohl, C; Keck, B; Hofmann, H G; Hornegger, J

2009-09-01

Fast 3D cone beam reconstruction is mandatory for many clinical workflows. For that reason, researchers and industry work hard on hardware-optimized 3D reconstruction. Backprojection is a major component of many reconstruction algorithms that require a projection of each voxel onto the projection data, including data interpolation, before updating the voxel value. This step is the bottleneck of most reconstruction algorithms and the focus of optimization in recent publications. A crucial limitation, however, of these publications is that the presented results are not comparable to each other. This is mainly due to variations in data acquisitions, preprocessing, and chosen geometries and the lack of a common publicly available test dataset. The authors provide such a standardized dataset that allows for substantial comparison of hardware accelerated backprojection methods. They developed an open platform RabbitCT (www.rabbitCT.com) for worldwide comparison in backprojection performance and ranking on different architectures using a specific high resolution C-arm CT dataset of a rabbit. This includes a sophisticated benchmark interface, a prototype implementation in C++, and image quality measures. At the time of writing, six backprojection implementations are already listed on the website. Optimizations include multithreading using Intel threading building blocks and OpenMP, vectorization using SSE, and computation on the GPU using CUDA 2.0. There is a need for objectively comparing backprojection implementations for reconstruction algorithms. RabbitCT aims to provide a solution to this problem by offering an open platform with fair chances for all participants. The authors are looking forward to a growing community and await feedback regarding future evaluations of novel software- and hardware-based acceleration schemes.

Validation of geometric measurements of the left atrium and pulmonary veins for analysis of reverse structural remodeling following ablation therapy

NASA Astrophysics Data System (ADS)

Rettmann, M. E.; Holmes, D. R., III; Gunawan, M. S.; Ge, X.; Karwoski, R. A.; Breen, J. F.; Packer, D. L.; Robb, R. A.

2012-03-01

Geometric analysis of the left atrium and pulmonary veins is important for studying reverse structural remodeling following cardiac ablation therapy. It has been shown that the left atrium decreases in volume and the pulmonary vein ostia decrease in diameter following ablation therapy. Most analysis techniques, however, require laborious manual tracing of image cross-sections. Pulmonary vein diameters are typically measured at the junction between the left atrium and pulmonary veins, called the pulmonary vein ostia, with manually drawn lines on volume renderings or on image cross-sections. In this work, we describe a technique for making semi-automatic measurements of the left atrium and pulmonary vein ostial diameters from high resolution CT scans and multi-phase datasets. The left atrium and pulmonary veins are segmented from a CT volume using a 3D volume approach and cut planes are interactively positioned to separate the pulmonary veins from the body of the left atrium. The cut plane is also used to compute the pulmonary vein ostial diameter. Validation experiments are presented which demonstrate the ability to repeatedly measure left atrial volume and pulmonary vein diameters from high resolution CT scans, as well as the feasibility of this approach for analyzing dynamic, multi-phase datasets. In the high resolution CT scans the left atrial volume measurements show high repeatability with approximately 4% intra-rater repeatability and 8% inter-rater repeatability. Intra- and inter-rater repeatability for pulmonary vein diameter measurements range from approximately 2 to 4 mm. For the multi-phase CT datasets, differences in left atrial volumes between a standard slice-by-slice approach and the proposed 3D volume approach are small, with percent differences on the order of 3% to 6%.

Dose accumulation of multiple high dose rate prostate brachytherapy treatments in two commercially available image registration systems.

PubMed

Poder, Joel; Yuen, Johnson; Howie, Andrew; Bece, Andrej; Bucci, Joseph

2017-11-01

The purpose of this study was to assess whether deformable image registration (DIR) is required for dose accumulation of multiple high dose rate prostate brachytherapy (HDRPBT) plans treated with the same catheter pattern on two different CT datasets. DIR was applied to 20 HDRPBT patients' planning CT images who received two treatment fractions on sequential days, on two different CT datasets, with the same implant. Quality of DIR in Velocity and MIM image registration systems was assessed by calculating the Dice Similarity Coefficient (DSC) and mean distance to agreement (MDA) for the prostate, urethra and rectum contours. Accumulated doses from each system were then calculated using the same DIR technique and dose volume histogram (DVH) parameters compared to manual addition with no DIR. The average DSC was found to be 0.83 (Velocity) and 0.84 (MIM), 0.80 (Velocity) and 0.80 (MIM), 0.80 (Velocity) and 0.81 (MIM), for the prostate, rectum and urethra contours, respectively. The average difference in calculated DVH parameters between the two systems using dose accumulation was less than 1%, and there was no statistically significant difference found between deformably accumulated doses in the two systems versus manual DVH addition with no DIR. Contour propagation using DIR in velocity and MIM was shown to be at least equivalent to inter-observer contouring variability on CT. The results also indicate that dose accumulation through manual addition of DVH parameters may be sufficient for HDRPBT treatments treated with the same catheter pattern on two different CT datasets. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

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

Pollard, J; Prajapati, S; Gao, S

Purpose: To evaluate correlation between the reproducibility of tumor position under feedback guided voluntary deep inspiration breath hold gating at simulation and at treatment. Methods: All patients treated with breath hold (BH) have 3-6 BH CTs taken at simulation (sim). In addition, if the relationship between the tumor and nearby bony anatomy on treatment BH CT(or CBCT) is found to be greater than 5 mm different at treatment than it was at sim, a repeat BH CT is taken before treatment. We retrospectively analyzed the sim CTs for 19 patients who received BH SBRT lung treatments and had repeat BHmore » CT on treatment. We evaluated the reproducibility of the tumor position during the simulation CTs and compared this to the reproducibility of the tumor position on the repeat treatment CT with our in-house CT alignment software (CT-Assisted Targeting for Radiotherapy). Results: Comparing the tumor position for multiple simulation BH CTs, we calculated: maximum difference (max) = 0.69cm; average difference (x) = 0.28cm; standard deviation (σ) = 0.18cm. Comparing the repeat BH CBCTs on treatment days we calculated: max = 0.44cm; x = 0.16cm; σ = 0.22cm. We also found that for 95% of our BH cases, the absolute variation in tumor position within the same imaging day was within 5mm of the range at the time of simulation and treatment. We found that 75% of the BH cases had less residual tumor motion on treatment days than at simulation. Conclusion: This suggests that a GTV contour based upon the residual tumor motion in multiple BH datasets plus 2 mm margin should be sufficient to cover the full range of residual tumor motion on treatment days.« less

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

PubMed

Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

2017-08-01

Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

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

Thomas, S; Yuen, C; Huang, V

Purpose: In this abstract we implement and validate a 4D VMAT Acuros XB dose calculation using Gafchromic film. Special attention is paid to the physical material assignment in the CT dataset and to reported dose to water and dose to medium. Methods: A QUASAR phantom with a 3 cm sinusoidal tumor motion and 5 second period was scanned using 4D computed tomography. A CT was also obtained of the static QUASAR phantom with the tumor at the central position. A VMAT plan was created on the average CT dataset and was delivered on a Varian TrueBeam linear accelerator. The trajectorymore » log file from this treatment was acquired and used to create 10 VMAT subplans (one for each portion of the breathing cycle). Motion for each subplan was simulated by moving the beam isocentre in the superior/inferior direction in the Treatment Planning System on the static CT scan. The 10 plans were calculated (both dose to medium and dose to water) and summed for 1) the original HU values from the static CT scan and 2) the correct physical material assignment in the CT dataset. To acquire a breathing phase synchronized film measurements the trajectory log was used to create a VMAT delivery plan which includes dynamic couch motion using the Developer Mode. Three different treatment start phases were investigated (mid inhalation, full inhalation and full exhalation). Results: For each scenario the coronal dose distributions were measured using Gafchromic film and compared to the corresponding calculation with Film QA Pro Software using a Gamma test with a 3%/3mm distance to agreement criteria. Good agreement was found between calculation and measurement. No statistically significant difference in agreement was found between calculations to original HU values vs calculations to over-written (material-assigned) HU values. Conclusion: The investigated 4D dose calculation method agrees well with measurement.« less

SU-F-J-57: Effectiveness of Daily CT-Based Three-Dimensional Image Guided and Adaptive Proton Therapy

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

Moriya, S; National Cancer Center, Kashiwa, Chiba; Tachibana, H

Purpose: Daily CT-based three-dimensional image-guided and adaptive (CTIGRT-ART) proton therapy system was designed and developed. We also evaluated the effectiveness of the CTIGRT-ART. Methods: Retrospective analysis was performed in three lung cancer patients: Proton treatment planning was performed using CT image datasets acquired by Toshiba Aquilion ONE. Planning target volume and surrounding organs were contoured by a well-trained radiation oncologist. Dose distribution was optimized using 180-deg. and 270-deg. two fields in passive scattering proton therapy. Well commissioned Simplified Monte Carlo algorithm was used as dose calculation engine. Daily consecutive CT image datasets was acquired by an in-room CT (Toshiba Aquilionmore » LB). In our in-house program, two image registrations for bone and tumor were performed to shift the isocenter using treatment CT image dataset. Subsequently, dose recalculation was performed after the shift of the isocenter. When the dose distribution after the tumor registration exhibits change of dosimetric parameter of CTV D90% compared to the initial plan, an additional process of was performed that the range shifter thickness was optimized. Dose distribution with CTV D90% for the bone registration, the tumor registration only and adaptive plan with the tumor registration was compared to the initial plan. Results: In the bone registration, tumor dose coverage was decreased by 16% on average (Maximum: 56%). The tumor registration shows better coverage than the bone registration, however the coverage was also decreased by 9% (Maximum: 22%) The adaptive plan shows similar dose coverage of the tumor (Average: 2%, Maximum: 7%). Conclusion: There is a high possibility that only image registration for bone and tumor may reduce tumor coverage. Thus, our proposed methodology of image guidance and adaptive planning using the range adaptation after tumor registration would be effective for proton therapy. This research is partially supported by Japan Agency for Medical Research and Development (AMED).« less

Large scale validation of the M5L lung CAD on heterogeneous CT datasets.

PubMed

Torres, E Lopez; Fiorina, E; Pennazio, F; Peroni, C; Saletta, M; Camarlinghi, N; Fantacci, M E; Cerello, P

2015-04-01

M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number of features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.

Classification of orbital morphology for decompression surgery in Graves' orbitopathy: two-dimensional versus three-dimensional orbital parameters.

PubMed

Borumandi, Farzad; Hammer, Beat; Noser, Hansrudi; Kamer, Lukas

2013-05-01

Three-dimensional (3D) CT reconstruction of the bony orbit for accurate measurement and classification of the complex orbital morphology may not be suitable for daily practice. We present an easily measurable two-dimensional (2D) reference dataset of the bony orbit for study of individual orbital morphology prior to decompression surgery in Graves' orbitopathy. CT images of 70 European adults (140 orbits) with unaffected orbits were included. On axial views, the following orbital dimensions were assessed: orbital length (OL), globe length (GL), GL/OL ratio and cone angle. Postprocessed CT data were required to measure the corresponding 3D orbital parameters. The 2D and 3D orbital parameters were correlated. The 2D orbital parameters were significantly correlated to the corresponding 3D parameters (significant at the 0.01 level). The average GL was 25 mm (SD±1.0), the average OL was 42 mm (SD±2.0) and the average GL/OL ratio was 0.6 (SD±0.03). The posterior cone angle was, on average, 50.2° (SD±4.1). Three orbital sizes were classified: short (OL≤40 mm), medium (OL>40 to <45 mm) and large (OL≥45 mm). We present easily measurable reference data for the orbit that can be used for preoperative study and classification of individual orbital morphology. A short and shallow orbit may require a different decompression technique than a large and deep orbit. Prospective clinical trials are needed to demonstrate how individual orbital morphology affects the outcome of decompression surgery.

Sarcoidosis: correlation of pulmonary parenchymal pattern at CT with results of pulmonary function tests

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

Bergin, C.J.; Bell, D.Y.; Coblentz, C.L.

1989-06-01

The appearances of the lungs on radiographs and computed tomographic (CT) scans were correlated with degree of uptake on gallium scans and results of pulmonary function tests (PFTs) in 27 patients with sarcoidosis. CT scans were evaluated both qualitatively and quantitatively. Patients were divided into five categories on the basis of the pattern of abnormality at CT: 1 = normal (n = 4); 2 = segmental air-space disease (n = 4); 3 = spherical (alveolar) masslike opacities (n = 4); 4 = multiple, discrete, small nodules (n = 6); and 5 = distortion of parenchymal structures (fibrotic end-stage sarcoidosis) (nmore » = 9). The percentage of the volume judged to be abnormal (CT grade) was correlated with PFT results for each CT and radiographic category. CT grades were also correlated with gallium scanning results and percentage of lymphocytes recovered from bronchoalveolar lavage (BAL). Patients in CT categories 1 and 2 had normal lung function, those in category 3 had mild functional impairment, and those in categories 4 and 5 showed moderate to severe dysfunction. The overall CT grade correlated well with PFT results expressed as a percentage of the predicted value. In five patients, CT scans showed extensive parenchymal disease not seen on radiographs. CT grades did not correlate with the results of gallium scanning or BAL lymphocytes. The authors conclude that patterns of parenchymal sarcoidosis seen at CT correlate with the PFT results and can be used to indicate respiratory impairment.« less

Dual energy CT: How to best blend both energies in one fused image?

NASA Astrophysics Data System (ADS)

Eusemann, Christian; Holmes, David R., III; Schmidt, Bernhard; Flohr, Thomas G.; Robb, Richard; McCollough, Cynthia; Hough, David M.; Huprich, James E.; Wittmer, Michael; Siddiki, Hasan; Fletcher, Joel G.

2008-03-01

In x-ray based imaging, attenuation depends on the type of tissue scanned and the average energy level of the x-ray beam, which can be adjusted via the x-ray tube potential. Conventional computed tomography (CT) imaging uses a single kV value, usually 120kV. Dual energy CT uses two different tube potentials (e.g. 80kV & 140kV) to obtain two image datasets with different attenuation characteristics. This difference in attenuation levels allows for classification of the composition of the tissues. In addition, the different energies significantly influence the contrast resolution and noise characteristics of the two image datasets. 80kV images provide greater contrast resolution than 140kV, but are limited because of increased noise. While dual-energy CT may provide useful clinical information, the question arises as to how to best realize and visualize this benefit. In conventional single energy CT, patient image data is presented to the physicians using well understood organ specific window and level settings. Instead of viewing two data series (one for each tube potential), the images are most often fused into a single image dataset using a linear mixing of the data with a 70% 140kV and a 30% 80kV mixing ratio, as available on one commercial systems. This ratio provides a reasonable representation of the anatomy/pathology, however due to the linear nature of the blending, the advantages of each dataset (contrast or sharpness) is partially offset by its drawbacks (blurring or noise). This project evaluated a variety of organ specific linear and non-linear mixing algorithms to optimize the blending of the low and high kV information for display in a way that combines the benefits (contrast and sharpness) of both energies in a single image. A blinded review analysis by subspecialty abdominal radiologists found that, unique, tunable, non-linear mixing algorithms that we developed outperformed linear, fixed mixing for a variety of different organs and pathologies of interest.

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method

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

Li, L; Tan, S; Lu, W

Purpose: PET images are usually blurred due to the finite spatial resolution, while CT images suffer from low contrast. Segment a tumor from either a single PET or CT image is thus challenging. To make full use of the complementary information between PET and CT, we propose a novel variational method for simultaneous PET image restoration and PET/CT images co-segmentation. Methods: The proposed model was constructed based on the Γ-convergence approximation of Mumford-Shah (MS) segmentation model for PET/CT co-segmentation. Moreover, a PET de-blur process was integrated into the MS model to improve the segmentation accuracy. An interaction edge constraint termmore » over the two modalities were specially designed to share the complementary information. The energy functional was iteratively optimized using an alternate minimization (AM) algorithm. The performance of the proposed method was validated on ten lung cancer cases and five esophageal cancer cases. The ground truth were manually delineated by an experienced radiation oncologist using the complementary visual features of PET and CT. The segmentation accuracy was evaluated by Dice similarity index (DSI) and volume error (VE). Results: The proposed method achieved an expected restoration result for PET image and satisfactory segmentation results for both PET and CT images. For lung cancer dataset, the average DSI (0.72) increased by 0.17 and 0.40 than single PET and CT segmentation. For esophageal cancer dataset, the average DSI (0.85) increased by 0.07 and 0.43 than single PET and CT segmentation. Conclusion: The proposed method took full advantage of the complementary information from PET and CT images. This work was supported in part by the National Cancer Institute Grants R01CA172638. Shan Tan and Laquan Li were supported in part by the National Natural Science Foundation of China, under Grant Nos. 60971112 and 61375018.« less

Measurement of time delay for a prospectively gated CT simulator.

PubMed

Goharian, M; Khan, R F H

2010-04-01

For the management of mobile tumors, respiratory gating is the ideal option, both during imaging and during therapy. The major advantage of respiratory gating during imaging is that it is possible to create a single artifact-free CT data-set during a selected phase of the patient's breathing cycle. The purpose of the present work is to present a simple technique to measure the time delay during acquisition of a prospectively gated CT. The time delay of a Philips Brilliance BigBore (Philips Medical Systems, Madison, WI) scanner attached to a Varian Real-Time Position Management (RPM) system (Varian Medical Systems, Palo Alto, CA) was measured. Two methods were used to measure the CT time delay: using a motion phantom and using a recorded data file from the RPM system. In the first technique, a rotating wheel phantom was altered by placing two plastic balls on its axis and rim, respectively. For a desired gate, the relative positions of the balls were measured from the acquired CT data and converted into corresponding phases. Phase difference was calculated between the measured phases and the desired phases. Using period of motion, the phase difference was converted into time delay. The Varian RPM system provides an external breathing signal; it also records transistor-transistor logic (TTL) 'X-Ray ON' status signal from the CT scanner in a text file. The TTL 'X-Ray ON' indicates the start of CT image acquisition. Thus, knowledge of the start time of CT acquisition, combined with the real-time phase and amplitude data from the external respiratory signal, provides time-stamping of all images in an axial CT scan. The TTL signal with time-stamp was used to calculate when (during the breathing cycle) a slice was recorded. Using the two approaches, the time delay between the prospective gating signal and CT simulator has been determined to be 367 +/- 40 ms. The delay requires corrections both at image acquisition and while setting gates for the treatment delivery; otherwise the simulation and treatment may not be correlated with the patient's breathing.

Automated segmentation of cardiac visceral fat in low-dose non-contrast chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Liang, Mingzhu; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2015-03-01

Cardiac visceral fat was segmented from low-dose non-contrast chest CT images using a fully automated method. Cardiac visceral fat is defined as the fatty tissues surrounding the heart region, enclosed by the lungs and posterior to the sternum. It is measured by constraining the heart region with an Anatomy Label Map that contains robust segmentations of the lungs and other major organs and estimating the fatty tissue within this region. The algorithm was evaluated on 124 low-dose and 223 standard-dose non-contrast chest CT scans from two public datasets. Based on visual inspection, 343 cases had good cardiac visceral fat segmentation. For quantitative evaluation, manual markings of cardiac visceral fat regions were made in 3 image slices for 45 low-dose scans and the Dice similarity coefficient (DSC) was computed. The automated algorithm achieved an average DSC of 0.93. Cardiac visceral fat volume (CVFV), heart region volume (HRV) and their ratio were computed for each case. The correlation between cardiac visceral fat measurement and coronary artery and aortic calcification was also evaluated. Results indicated the automated algorithm for measuring cardiac visceral fat volume may be an alternative method to the traditional manual assessment of thoracic region fat content in the assessment of cardiovascular disease risk.

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

Technical Note: FreeCT_ICD: An Open Source Implementation of a Model-Based Iterative Reconstruction Method using Coordinate Descent Optimization for CT Imaging Investigations.

PubMed

Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael

2018-06-01

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Generation of synthetic CT using multi-scale and dual-contrast patches for brain MRI-only external beam radiotherapy.

PubMed

Aouadi, Souha; Vasic, Ana; Paloor, Satheesh; Torfeh, Tarraf; McGarry, Maeve; Petric, Primoz; Riyas, Mohamed; Hammoud, Rabih; Al-Hammadi, Noora

2017-10-01

To create a synthetic CT (sCT) from conventional brain MRI using a patch-based method for MRI-only radiotherapy planning and verification. Conventional T1 and T2-weighted MRI and CT datasets from 13 patients who underwent brain radiotherapy were included in a retrospective study whereas 6 patients were tested prospectively. A new contribution to the Non-local Means Patch-Based Method (NMPBM) framework was done with the use of novel multi-scale and dual-contrast patches. Furthermore, the training dataset was improved by pre-selecting the closest database patients to the target patient for computation time/accuracy balance. sCT and derived DRRs were assessed visually and quantitatively. VMAT planning was performed on CT and sCT for hypothetical PTVs in homogeneous and heterogeneous regions. Dosimetric analysis was done by comparing Dose Volume Histogram (DVH) parameters of PTVs and organs at risk (OARs). Positional accuracy of MRI-only image-guided radiation therapy based on CBCT or kV images was evaluated. The retrospective (respectively prospective) evaluation of the proposed Multi-scale and Dual-contrast Patch-Based Method (MDPBM) gave a mean absolute error MAE=99.69±11.07HU (98.95±8.35HU), and a Dice in bones DI bone =83±0.03 (0.82±0.03). Good agreement with conventional planning techniques was obtained; the highest percentage of DVH metric deviations was 0.43% (0.53%) for PTVs and 0.59% (0.75%) for OARs. The accuracy of sCT/CBCT or DRR sCT /kV images registration parameters was <2mm and <2°. Improvements with MDPBM, compared to NMPBM, were significant. We presented a novel method for sCT generation from T1 and T2-weighted MRI potentially suitable for MRI-only external beam radiotherapy in brain sites. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Evaluation of bone formation in calcium phosphate scaffolds with μCT-method validation using SEM.

PubMed

Lewin, S; Barba, A; Persson, C; Franch, J; Ginebra, M-P; Öhman-Mägi, C

2017-10-05

There is a plethora of calcium phosphate (CaP) scaffolds used as synthetic substitutes to bone grafts. The scaffold performance is often evaluated from the quantity of bone formed within or in direct contact with the scaffold. Micro-computed tomography (μCT) allows three-dimensional evaluation of bone formation inside scaffolds. However, the almost identical x-ray attenuation of CaP and bone obtrude the separation of these phases in μCT images. Commonly, segmentation of bone in μCT images is based on gray scale intensity, with manually determined global thresholds. However, image analysis methods, and methods for manual thresholding in particular, lack standardization and may consequently suffer from subjectivity. The aim of the present study was to provide a methodological framework for addressing these issues. Bone formation in two types of CaP scaffold architectures (foamed and robocast), obtained from a larger animal study (a 12 week canine animal model) was evaluated by μCT. In addition, cross-sectional scanning electron microscopy (SEM) images were acquired as references to determine thresholds and to validate the result. μCT datasets were registered to the corresponding SEM reference. Global thresholds were then determined by quantitatively correlating the different area fractions in the μCT image, towards the area fractions in the corresponding SEM image. For comparison, area fractions were also quantified using global thresholds determined manually by two different approaches. In the validation the manually determined thresholds resulted in large average errors in area fraction (up to 17%), whereas for the evaluation using SEM references, the errors were estimated to be less than 3%. Furthermore, it was found that basing the thresholds on one single SEM reference gave lower errors than determining them manually. This study provides an objective, robust and less error prone method to determine global thresholds for the evaluation of bone formation in CaP scaffolds.

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

Spatial Distortion in MRI-Guided Stereotactic Procedures: Evaluation in 1.5-, 3- and 7-Tesla MRI Scanners.

PubMed

Neumann, Jan-Oliver; Giese, Henrik; Biller, Armin; Nagel, Armin M; Kiening, Karl

2015-01-01

Magnetic resonance imaging (MRI) is replacing computed tomography (CT) as the main imaging modality for stereotactic transformations. MRI is prone to spatial distortion artifacts, which can lead to inaccuracy in stereotactic procedures. Modern MRI systems provide distortion correction algorithms that may ameliorate this problem. This study investigates the different options of distortion correction using standard 1.5-, 3- and 7-tesla MRI scanners. A phantom was mounted on a stereotactic frame. One CT scan and three MRI scans were performed. At all three field strengths, two 3-dimensional sequences, volumetric interpolated breath-hold examination (VIBE) and magnetization-prepared rapid acquisition with gradient echo, were acquired, and automatic distortion correction was performed. Global stereotactic transformation of all 13 datasets was performed and two stereotactic planning workflows (MRI only vs. CT/MR image fusion) were subsequently analysed. Distortion correction on the 1.5- and 3-tesla scanners caused a considerable reduction in positional error. The effect was more pronounced when using the VIBE sequences. By using co-registration (CT/MR image fusion), even a lower positional error could be obtained. In ultra-high-field (7 T) MR imaging, distortion correction introduced even higher errors. However, the accuracy of non-corrected 7-tesla sequences was comparable to CT/MR image fusion 3-tesla imaging. MRI distortion correction algorithms can reduce positional errors by up to 60%. For stereotactic applications of utmost precision, we recommend a co-registration to an additional CT dataset. © 2015 S. Karger AG, Basel.

Pre-operative segmentation of neck CT datasets for the planning of neck dissections

NASA Astrophysics Data System (ADS)

Cordes, Jeanette; Dornheim, Jana; Preim, Bernhard; Hertel, Ilka; Strauss, Gero

2006-03-01

For the pre-operative segmentation of CT neck datasets, we developed the software assistant NeckVision. The relevant anatomical structures for neck dissection planning can be segmented and the resulting patient-specific 3D-models are visualized afterwards in another software system for intervention planning. As a first step, we examined the appropriateness of elementary segmentation techniques based on gray values and contour information to extract the structures in the neck region from CT data. Region growing, interactive watershed transformation and live-wire are employed for segmentation of different target structures. It is also examined, which of the segmentation tasks can be automated. Based on this analysis, the software assistant NeckVision was developed to optimally support the workflow of image analysis for clinicians. The usability of NeckVision was tested within a first evaluation with four otorhinolaryngologists from the university hospital of Leipzig, four computer scientists from the university of Magdeburg and two laymen in both fields.

Structural and functional correlates of motor imagery BCI performance: Insights from the patterns of fronto-parietal attention network.

PubMed

Zhang, Tao; Liu, Tiejun; Li, Fali; Li, Mengchen; Liu, Dongbo; Zhang, Rui; He, Hui; Li, Peiyang; Gong, Jinnan; Luo, Cheng; Yao, Dezhong; Xu, Peng

2016-07-01

Motor imagery (MI)-based brain-computer interfaces (BCIs) have been widely used for rehabilitation of motor abilities and prosthesis control for patients with motor impairments. However, MI-BCI performance exhibits a wide variability across subjects, and the underlying neural mechanism remains unclear. Several studies have demonstrated that both the fronto-parietal attention network (FPAN) and MI are involved in high-level cognitive processes that are crucial for the control of BCIs. Therefore, we hypothesized that the FPAN may play an important role in MI-BCI performance. In our study, we recorded multi-modal datasets consisting of MI electroencephalography (EEG) signals, T1-weighted structural and resting-state functional MRI data for each subject. MI-BCI performance was evaluated using the common spatial pattern to extract the MI features from EEG signals. One cortical structural feature (cortical thickness (CT)) and two measurements (degree centrality (DC) and eigenvector centrality (EC)) of node centrality were derived from the structural and functional MRI data, respectively. Based on the information extracted from the EEG and MRI, a correlation analysis was used to elucidate the relationships between the FPAN and MI-BCI performance. Our results show that the DC of the right ventral intraparietal sulcus, the EC and CT of the left inferior parietal lobe, and the CT of the right dorsolateral prefrontal cortex were significantly associated with MI-BCI performance. Moreover, the receiver operating characteristic analysis and machine learning classification revealed that the EC and CT of the left IPL could effectively predict the low-aptitude BCI users from the high-aptitude BCI users with 83.3% accuracy. Those findings consistently reveal that the individuals who have efficient FPAN would perform better on MI-BCI. Our findings may deepen the understanding of individual variability in MI-BCI performance, and also may provide a new biomarker to predict individual MI-BCI performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts

PubMed Central

Genders, Tessa S S; Steyerberg, Ewout W; Nieman, Koen; Galema, Tjebbe W; Mollet, Nico R; de Feyter, Pim J; Krestin, Gabriel P; Alkadhi, Hatem; Leschka, Sebastian; Desbiolles, Lotus; Meijs, Matthijs F L; Cramer, Maarten J; Knuuti, Juhani; Kajander, Sami; Bogaert, Jan; Goetschalckx, Kaatje; Cademartiri, Filippo; Maffei, Erica; Martini, Chiara; Seitun, Sara; Aldrovandi, Annachiara; Wildermuth, Simon; Stinn, Björn; Fornaro, Jürgen; Feuchtner, Gudrun; De Zordo, Tobias; Auer, Thomas; Plank, Fabian; Friedrich, Guy; Pugliese, Francesca; Petersen, Steffen E; Davies, L Ceri; Schoepf, U Joseph; Rowe, Garrett W; van Mieghem, Carlos A G; van Driessche, Luc; Sinitsyn, Valentin; Gopalan, Deepa; Nikolaou, Konstantin; Bamberg, Fabian; Cury, Ricardo C; Battle, Juan; Maurovich-Horvat, Pál; Bartykowszki, Andrea; Merkely, Bela; Becker, Dávid; Hadamitzky, Martin; Hausleiter, Jörg; Dewey, Marc; Zimmermann, Elke; Laule, Michael

2012-01-01

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations. Design Retrospective pooled analysis of individual patient data. Setting 18 hospitals in Europe and the United States. Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory. Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates. PMID:22692650

Acquisition of thin coronal sectional dataset of cadaveric liver.

PubMed

Lou, Li; Liu, Shu Wei; Zhao, Zhen Mei; Tang, Yu Chun; Lin, Xiang Tao

2014-04-01

To obtain the thin coronal sectional anatomic dataset of the liver by using digital freezing milling technique. The upper abdomen of one Chinese adult cadaver was selected as the specimen. After CT and MRI examinations verification of absent liver lesions, the specimen was embedded with gelatin in stand erect position and frozen under profound hypothermia, and the specimen was then serially sectioned from anterior to posterior layer by layer with digital milling machine in the freezing chamber. The sequential images were captured by means of a digital camera and the dataset was imported to imaging workstation. The thin serial section of the liver added up to 699 layers with each layer being 0.2 mm in thickness. The shape, location, structure, intrahepatic vessels and adjacent structures of the liver was displayed clearly on each layer of the coronal sectional slice. CT and MR images through the body were obtained at 1.0 and 3.0 mm intervals, respectively. The methodology reported here is an adaptation of the milling methods previously described, which is a new data acquisition method for sectional anatomy. The thin coronal sectional anatomic dataset of the liver obtained by this technique is of high precision and good quality.

Computer-assisted virtual autopsy using surgical navigation techniques.

PubMed

Ebert, Lars Christian; Ruder, Thomas D; Martinez, Rosa Maria; Flach, Patricia M; Schweitzer, Wolf; Thali, Michael J; Ampanozi, Garyfalia

2015-01-01

OBJECTIVE; Virtual autopsy methods, such as postmortem CT and MRI, are increasingly being used in forensic medicine. Forensic investigators with little to no training in diagnostic radiology and medical laypeople such as state's attorneys often find it difficult to understand the anatomic orientation of axial postmortem CT images. We present a computer-assisted system that permits postmortem CT datasets to be quickly and intuitively resliced in real time at the body to narrow the gap between radiologic imaging and autopsy. Our system is a potentially valuable tool for planning autopsies, showing findings to medical laypeople, and teaching CT anatomy, thus further closing the gap between radiology and forensic pathology.

Focal fluorine-18 fluorodeoxyglucose-avid lesions without computed tomography correlate at whole-body positron emission tomography-computed tomography in oncology patients: how often are they malignant?

PubMed

Kumar, Rahi; Hawkins, Randall A; Yeh, Benjamin M; Wang, Zhen Jane

2011-09-01

To retrospectively evaluate the rate of malignancy of focal fluorine-18 fluorodeoxyglucose (18F-FDG)-avid lesions without computed tomography (CT) correlate at whole-body positron emission tomography (PET)-CT in oncology patients, because better defining these abnormalities could potentially lead to improved patient management algorithms that rely on PET-CT for detection, staging, and treatment monitoring of malignancies. We performed a computer search of all PET-CT studies performed at our institution from 2006 to 2009, and identified 87 studies with findings of focal 18F-FDG-avid lesions without correlate at CT. The rate of malignancy of such lesions was determined by reviewing findings at follow-up imaging or by clinical or histopathological follow-up. Rates of malignancy were categorized and compared by lesion location and by the type of primary malignancy. The most common locations for focal 18F-FDG-avid lesions without CT correlate were: lymph node location (without visible lymph nodes; 27/87), bone (21/87), soft tissue (17/87), liver (9/87), and gastrointestinal tract (8/87). Forty-one percent (36/87) of the focal FDG-avid lesions without CT correlate were malignant (either metastatic disease or a second malignancy) at follow-up (mean follow-up: 5 months, range: 1-25 months). Focal FDG-avid lesions in lymph node location and in bone without CT correlate had higher rates of malignancy (56%, 15/27 and 52%, 11/21, respectively) than lesions in all other locations (26%, 10/39, P=0.028). In 15 of 87 cases, the only significant finding at PET-CT was an FDG-avid lesion without CT correlate. Of those, 53% (8/15) was positive for malignancy. There were no significant differences in the rates of malignancy for the focal FDG-avid lesions without CT correlate when stratified by the type of primary malignancy in this series. Focal FDG avid lesions without CT correlate were malignant in 41% of cases in our series of oncology patients. Lesions in lymph node location and in bones had the highest rates of malignancy. Knowledge of the patterns and risk of malignancy of focal FDG-avid lesions without CT correlate in oncology patients may facilitate the management of oncology patients with such lesions on PET-CT, and could lead to an improved interpretation of PET-CT scans by imaging specialists.

Correlation between average tissue depth data and quantitative accuracy of forensic craniofacial reconstructions measured by geometric surface comparison method.

PubMed

Lee, Won-Joon; Wilkinson, Caroline M; Hwang, Hyeon-Shik; Lee, Sang-Mi

2015-05-01

Accuracy is the most important factor supporting the reliability of forensic facial reconstruction (FFR) comparing to the corresponding actual face. A number of methods have been employed to evaluate objective accuracy of FFR. Recently, it has been attempted that the degree of resemblance between computer-generated FFR and actual face is measured by geometric surface comparison method. In this study, three FFRs were produced employing live adult Korean subjects and three-dimensional computerized modeling software. The deviations of the facial surfaces between the FFR and the head scan CT of the corresponding subject were analyzed in reverse modeling software. The results were compared with those from a previous study which applied the same methodology as this study except average facial soft tissue depth dataset. Three FFRs of this study that applied updated dataset demonstrated lesser deviation errors between the facial surfaces of the FFR and corresponding subject than those from the previous study. The results proposed that appropriate average tissue depth data are important to increase quantitative accuracy of FFR. © 2015 American Academy of Forensic Sciences.

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

Temporal subtraction contrast-enhanced dedicated breast CT

PubMed Central

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-01-01

Purpose To develop a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. Methods An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, Intensity Difference Adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using Normalized Cross Correlation (NCC), Symmetric Uncertainty Coefficient (SUC), Normalized Mutual Information (NMI), Mean Square Error (MSE) and Target Registration Error (TRE). Results The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE(0–16%), NCC (0–6%), NMI (0–13%) and TRE (0–34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Conclusion Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake. PMID:27494376

SU-E-J-120: Comparing 4D CT Computed Ventilation to Lung Function Measured with Hyperpolarized Xenon-129 MRI

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

Neal, B; Chen, Q

2015-06-15

Purpose: To correlate ventilation parameters computed from 4D CT to ventilation, profusion, and gas exchange measured with hyperpolarized Xenon-129 MRI for a set of lung cancer patients. Methods: Hyperpolarized Xe-129 MRI lung scans were acquired for lung cancer patients, before and after radiation therapy, measuring ventilation, perfusion, and gas exchange. In the standard clinical workflow, these patients also received 4D CT scans before treatment. Ventilation was computed from 4D CT using deformable image registration (DIR). All phases of the 4D CT scan were registered using a B-spline deformable registration. Ventilation at the voxel level was then computed for each phasemore » based on a Jacobian volume expansion metric, yielding phase sorted ventilation images. Ventilation based upon 4D CT and Xe-129 MRI were co-registered, allowing qualitative visual comparison and qualitative comparison via the Pearson correlation coefficient. Results: Analysis shows a weak correlation between hyperpolarized Xe-129 MRI and 4D CT DIR ventilation, with a Pearson correlation coefficient of 0.17 to 0.22. Further work will refine the DIR parameters to optimize the correlation. The weak correlation could be due to the limitations of 4D CT, registration algorithms, or the Xe-129 MRI imaging. Continued development will refine parameters to optimize correlation. Conclusion: Current analysis yields a minimal correlation between 4D CT DIR and Xe-129 MRI ventilation. Funding provided by the 2014 George Amorino Pilot Grant in Radiation Oncology at the University of Virginia.« less

MO-C-17A-10: Comparison of Dose Deformable Accumulation by Using Parallel and Serial Approaches

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

Gao, Z; Li, M; Wong, J

Purpose: The uncertainty of dose accumulation over multiple CT datasets with deformable fusion may have significant impact on clinical decisions. In this study, we investigate the difference of two dose summation approaches involving deformable fusion. Methods: Five patients, four external beam and one brachytherapy(BT), were chosen for the study. The BT patient was treated with CT-based HDR. The CT image sets acquired in the imageguidance process (8-11 CTs/patient) were used to determine the dose delivered to the four external beam patients. (prostate, pelvis, lung and head and neck). For the HDR patient (cervix), five CT image sets and the correspondingmore » BT plans were used. In total 44 CT datasets and RT dose/plans were imported into the image fusion software MiM (6.0.4) for analysis.For each of the five clinical cases, the dose from each fraction was accumulated into the primary CT dataset by using both Parallel and Serial approaches. The dose-volume histogram (DVH) for CTV and selected organs-at-risks (OAR) were generated. The D95(CTV), OAR(mean) and OAR(max) for the four external beam cases the D90(CTV), and the max dose to bladder and rectum for the BT case were compared. Results: For the four external beam patients, the difference in D95(CTV) were <1.2% PD between the parallel and the serial approaches. The differences of the OAR(mean) and the OAR(max ) range from 0 to 3.7% and <1% PD respectively. For the HDR patient, the dose difference for D90 is 11% PD while that of the max dose to bladder and rectum were 11.5% and 23.3% respectively. Conclusion: For external beam treatments, the parallel and serial approaches have <5% difference probably because tumor volume and OAR have less changes from fraction to fraction. For the brachytherapy case, >10% dose difference between the two approaches was observed as significant volume changes of tumor and OAR were observed among treatment fractions.« less

Promote quantitative ischemia imaging via myocardial perfusion CT iterative reconstruction with tensor total generalized variation regularization

NASA Astrophysics Data System (ADS)

Gu, Chengwei; Zeng, Dong; Lin, Jiahui; Li, Sui; He, Ji; Zhang, Hao; Bian, Zhaoying; Niu, Shanzhou; Zhang, Zhang; Huang, Jing; Chen, Bo; Zhao, Dazhe; Chen, Wufan; Ma, Jianhua

2018-06-01

Myocardial perfusion computed tomography (MPCT) imaging is commonly used to detect myocardial ischemia quantitatively. A limitation in MPCT is that an additional radiation dose is required compared to unenhanced CT due to its repeated dynamic data acquisition. Meanwhile, noise and streak artifacts in low-dose cases are the main factors that degrade the accuracy of quantifying myocardial ischemia and hamper the diagnostic utility of the filtered backprojection reconstructed MPCT images. Moreover, it is noted that the MPCT images are composed of a series of 2/3D images, which can be naturally regarded as a 3/4-order tensor, and the MPCT images are globally correlated along time and are sparse across space. To obtain higher fidelity ischemia from low-dose MPCT acquisitions quantitatively, we propose a robust statistical iterative MPCT image reconstruction algorithm by incorporating tensor total generalized variation (TTGV) regularization into a penalized weighted least-squares framework. Specifically, the TTGV regularization fuses the spatial correlation of the myocardial structure and the temporal continuation of the contrast agent intake during the perfusion. Then, an efficient iterative strategy is developed for the objective function optimization. Comprehensive evaluations have been conducted on a digital XCAT phantom and a preclinical porcine dataset regarding the accuracy of the reconstructed MPCT images, the quantitative differentiation of ischemia and the algorithm’s robustness and efficiency.

Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.

PubMed

Wu, Panpan; Xia, Kewen; Yu, Hengyong

2016-11-01

Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An algebraic iterative reconstruction technique for differential X-ray phase-contrast computed tomography.

PubMed

Fu, Jian; Schleede, Simone; Tan, Renbo; Chen, Liyuan; Bech, Martin; Achterhold, Klaus; Gifford, Martin; Loewen, Rod; Ruth, Ronald; Pfeiffer, Franz

2013-09-01

Iterative reconstruction has a wide spectrum of proven advantages in the field of conventional X-ray absorption-based computed tomography (CT). In this paper, we report on an algebraic iterative reconstruction technique for grating-based differential phase-contrast CT (DPC-CT). Due to the differential nature of DPC-CT projections, a differential operator and a smoothing operator are added to the iterative reconstruction, compared to the one commonly used for absorption-based CT data. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured at a two-grating interferometer setup. Since the algorithm is easy to implement and allows for the extension to various regularization possibilities, we expect a significant impact of the method for improving future medical and industrial DPC-CT applications. Copyright © 2012. Published by Elsevier GmbH.

Segmentation and Visual Analysis of Whole-Body Mouse Skeleton microSPECT

PubMed Central

Khmelinskii, Artem; Groen, Harald C.; Baiker, Martin; de Jong, Marion; Lelieveldt, Boudewijn P. F.

2012-01-01

Whole-body SPECT small animal imaging is used to study cancer, and plays an important role in the development of new drugs. Comparing and exploring whole-body datasets can be a difficult and time-consuming task due to the inherent heterogeneity of the data (high volume/throughput, multi-modality, postural and positioning variability). The goal of this study was to provide a method to align and compare side-by-side multiple whole-body skeleton SPECT datasets in a common reference, thus eliminating acquisition variability that exists between the subjects in cross-sectional and multi-modal studies. Six whole-body SPECT/CT datasets of BALB/c mice injected with bone targeting tracers 99mTc-methylene diphosphonate (99mTc-MDP) and 99mTc-hydroxymethane diphosphonate (99mTc-HDP) were used to evaluate the proposed method. An articulated version of the MOBY whole-body mouse atlas was used as a common reference. Its individual bones were registered one-by-one to the skeleton extracted from the acquired SPECT data following an anatomical hierarchical tree. Sequential registration was used while constraining the local degrees of freedom (DoFs) of each bone in accordance to the type of joint and its range of motion. The Articulated Planar Reformation (APR) algorithm was applied to the segmented data for side-by-side change visualization and comparison of data. To quantitatively evaluate the proposed algorithm, bone segmentations of extracted skeletons from the correspondent CT datasets were used. Euclidean point to surface distances between each dataset and the MOBY atlas were calculated. The obtained results indicate that after registration, the mean Euclidean distance decreased from 11.5±12.1 to 2.6±2.1 voxels. The proposed approach yielded satisfactory segmentation results with minimal user intervention. It proved to be robust for “incomplete” data (large chunks of skeleton missing) and for an intuitive exploration and comparison of multi-modal SPECT/CT cross-sectional mouse data. PMID:23152834

SU-G-IeP2-03: Comparison of Dose Calculation On MAR (metal Artifact Reduction) and Non-MAR Datasets for Pelvic Patients with Hip Prosthesis and Head and Neck Patients with Dental Filling

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

Huang, V; Kohli, K

Purpose: Metal artifact reduction (MAR) software in computed tomography (CT) was previously evaluated with phantoms demonstrating the algorithm is capable of reducing metal artifacts without affecting the overall image quality. The goal of this study is to determine the dosimetric impact when calculating with CT datasets reconstructed with and without MAR software. Methods: Twelve head and neck cancer patients with dental fillings and four pelvic cancer patients with hip prosthesis were scanned with a GE Optima RT 580 CT scanner. Images were reconstructed with and without the MAR software. 6MV IMRT and VMAT plans were calculated with AAA on themore » MAR dataset until all constraints met our clinic’s guidelines. Contours from the MAR dataset were copied to the non-MAR dataset. Next, dose calculation on the non-MAR dataset was performed using the same field arrangements and fluence as the MAR plan. Conformality index, D99% and V100% to PTV were compared between MAR and non-MAR plans. Results: Differences between MAR and non-MAR plans were evaluated. For head and neck plans, the largest variations in conformality index, D99% and V100% were −3.8%, −0.9% and −2.1% respectively whereas for pelvic plans, the biggest discrepancies were −32.7%, −0.4% and -33.5% respectively. The dosimetric impact from hip prosthesis is greater because it produces more artifacts compared to dental fillings. Coverage to PTV can increase or decrease depending on the artifacts since dark streaks reduce the HU whereas bright streaks increase the HU. In the majority of the cases, PTV dose in the non-MAR plans is higher than MAR plans. Conclusion: With the presence of metals, MAR algorithm can allow more accurate delineation of targets and OARs. Dose difference between MAR and non-MAR plans depends on the proximity of the organ to the high density material, the streaking artifacts and the beam arrangements of the plan.« less

Comparison of onboard low-field magnetic resonance imaging versus onboard computed tomography for anatomy visualization in radiotherapy.

PubMed

Noel, Camille E; Parikh, Parag J; Spencer, Christopher R; Green, Olga L; Hu, Yanle; Mutic, Sasa; Olsen, Jeffrey R

2015-01-01

Onboard magnetic resonance imaging (OB-MRI) for daily localization and adaptive radiotherapy has been under development by several groups. However, no clinical studies have evaluated whether OB-MRI improves visualization of the target and organs at risk (OARs) compared to standard onboard computed tomography (OB-CT). This study compared visualization of patient anatomy on images acquired on the MRI-(60)Co ViewRay system to those acquired with OB-CT. Fourteen patients enrolled on a protocol approved by the Institutional Review Board (IRB) and undergoing image-guided radiotherapy for cancer in the thorax (n = 2), pelvis (n = 6), abdomen (n = 3) or head and neck (n = 3) were imaged with OB-MRI and OB-CT. For each of the 14 patients, the OB-MRI and OB-CT datasets were displayed side-by-side and independently reviewed by three radiation oncologists. Each physician was asked to evaluate which dataset offered better visualization of the target and OARs. A quantitative contouring study was performed on two abdominal patients to assess if OB-MRI could offer improved inter-observer segmentation agreement for adaptive planning. In total 221 OARs and 10 targets were compared for visualization on OB-MRI and OB-CT by each of the three physicians. The majority of physicians (two or more) evaluated visualization on MRI as better for 71% of structures, worse for 10% of structures, and equivalent for 14% of structures. 5% of structures were not visible on either. Physicians agreed unanimously for 74% and in majority for > 99% of structures. Targets were better visualized on MRI in 4/10 cases, and never on OB-CT. Low-field MR provides better anatomic visualization of many radiotherapy targets and most OARs as compared to OB-CT. Further studies with OB-MRI should be pursued.

An application of cascaded 3D fully convolutional networks for medical image segmentation.

PubMed

Roth, Holger R; Oda, Hirohisa; Zhou, Xiangrong; Shimizu, Natsuki; Yang, Ying; Hayashi, Yuichiro; Oda, Masahiro; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-06-01

Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures (ranging from the large organs to thin vessels) can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models. To this end, we propose a two-stage, coarse-to-fine approach that will first use a 3D FCN to roughly define a candidate region, which will then be used as input to a second 3D FCN. This reduces the number of voxels the second FCN has to classify to ∼10% and allows it to focus on more detailed segmentation of the organs and vessels. We utilize training and validation sets consisting of 331 clinical CT images and test our models on a completely unseen data collection acquired at a different hospital that includes 150 CT scans, targeting three anatomical organs (liver, spleen, and pancreas). In challenging organs such as the pancreas, our cascaded approach improves the mean Dice score from 68.5 to 82.2%, achieving the highest reported average score on this dataset. We compare with a 2D FCN method on a separate dataset of 240 CT scans with 18 classes and achieve a significantly higher performance in small organs and vessels. Furthermore, we explore fine-tuning our models to different datasets. Our experiments illustrate the promise and robustness of current 3D FCN based semantic segmentation of medical images, achieving state-of-the-art results. 1 . Copyright © 2018 Elsevier Ltd. All rights reserved.

Inter-algorithm lesion volumetry comparison of real and 3D simulated lung lesions in CT

NASA Astrophysics Data System (ADS)

Robins, Marthony; Solomon, Justin; Hoye, Jocelyn; Smith, Taylor; Ebner, Lukas; Samei, Ehsan

2017-03-01

The purpose of this study was to establish volumetric exchangeability between real and computational lung lesions in CT. We compared the overall relative volume estimation performance of segmentation tools when used to measure real lesions in actual patient CT images and computational lesions virtually inserted into the same patient images (i.e., hybrid datasets). Pathologically confirmed malignancies from 30 thoracic patient cases from Reference Image Database to Evaluate Therapy Response (RIDER) were modeled and used as the basis for the comparison. Lesions included isolated nodules as well as those attached to the pleura or other lung structures. Patient images were acquired using a 16 detector row or 64 detector row CT scanner (Lightspeed 16 or VCT; GE Healthcare). Scans were acquired using standard chest protocols during a single breath-hold. Virtual 3D lesion models based on real lesions were developed in Duke Lesion Tool (Duke University), and inserted using a validated image-domain insertion program. Nodule volumes were estimated using multiple commercial segmentation tools (iNtuition, TeraRecon, Inc., Syngo.via, Siemens Healthcare, and IntelliSpace, Philips Healthcare). Consensus based volume comparison showed consistent trends in volume measurement between real and virtual lesions across all software. The average percent bias (+/- standard error) shows -9.2+/-3.2% for real lesions versus -6.7+/-1.2% for virtual lesions with tool A, 3.9+/-2.5% and 5.0+/-0.9% for tool B, and 5.3+/-2.3% and 1.8+/-0.8% for tool C, respectively. Virtual lesion volumes were statistically similar to those of real lesions (< 4% difference) with p >.05 in most cases. Results suggest that hybrid datasets had similar inter-algorithm variability compared to real datasets.

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

PubMed

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

2018-02-01

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

Impact of gastric filling on radiation dose delivered to gastroesophageal junction tumors.

PubMed

Bouchard, Myriam; McAleer, Mary Frances; Starkschall, George

2010-05-01

This study examined the impact of gastric filling variation on target coverage of gastroesophageal junction (GEJ) tumors in three-dimensional conformal radiation therapy (3DCRT), intensity-modulated radiation therapy (IMRT), or IMRT with simultaneous integrated boost (IMRT-SIB) plans. Eight patients previously receiving radiation therapy for esophageal cancer had computed tomography (CT) datasets acquired with full stomach (FS) and empty stomach (ES). We generated treatment plans for 3DCRT, IMRT, or IMRT-SIB for each patient on the ES-CT and on the FS-CT datasets. The 3DCRT and IMRT plans were planned to 50.4 Gy to the clinical target volume (CTV), and the same for IMRT-SIB plus 63.0 Gy to the gross tumor volume (GTV). Target coverage was evaluated using dose-volume histogram data for patient treatments simulated with ES-CT sets, assuming treatment on an FS for the entire course, and vice versa. FS volumes were a mean of 3.3 (range, 1.7-7.5) times greater than ES volumes. The volume of the GTV receiving >or=50.4 Gy (V(50.4Gy)) was 100% in all situations. The planning GTV V(63Gy) became suboptimal when gastric filling varied, regardless of whether simulation was done on the ES-CT or the FS-CT set. Stomach filling has a negligible impact on prescribed dose delivered to the GEJ GTV, using either 3DCRT or IMRT planning. Thus, local relapses are not likely to be related to variations in gastric filling. Dose escalation for GEJ tumors with IMRT-SIB may require gastric filling monitoring.

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

PubMed

Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

2018-06-01

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Time-Adjusted Internal Target Volume: A Novel Approach Focusing on Heterogeneity of Tumor Motion Based on 4-Dimensional Computed Tomography Imaging for Radiation Therapy Planning of Lung Cancer

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

Nishibuchi, Ikuno; Department of Radiation Oncology, Hiroshima Prefectural Hospital, Hiroshima; Kimura, Tomoki, E-mail: tkkimura@hiroshima-u.ac.jp

2014-08-01

Purpose: To consider nonuniform tumor motion within the internal target volume (ITV) by defining time-adjusted ITV (TTV), a volume designed to include heterogeneity of tumor existence on the basis of 4-dimensional computed tomography (4D-CT). Methods and Materials: We evaluated 30 lung cancer patients. Breath-hold CT (BH-CT) and free-breathing 4D-CT scans were acquired for each patient. The tumors were manually delineated using a lung CT window setting (window, 1600 HU; level, −300 HU). Tumor in BH-CT images was defined as gross tumor volume (GTV), and the sum of tumors in 4D-CT images was defined as ITV-4D. The TTV images were generatedmore » from the 4D-CT datasets, and the tumor existence probability within ITV-4D was calculated. We calculated the TTV{sub 80} value, which is the percentage of the volume with a tumor existence probability that exceeded 80% on ITV-4D. Several factors that affected the TTV{sub 80} value, such as the ITV-4D/GTV ratio or tumor centroid deviation, were evaluated. Results: Time-adjusted ITV images were acquired for all patients, and tumor respiratory motion heterogeneity was visualized. The median (range) ITV-4D/GTV ratio and median tumor centroid deviation were 1.6 (1.0-4.1) and 6.3 mm (0.1-30.3 mm), respectively. The median TTV{sub 80} value was 43.3% (2.9-98.7%). Strong correlations were observed between the TTV{sub 80} value and the ITV-4D/GTV ratio (R=−0.71) and tumor centroid deviation (R=−0.72). The TTV images revealed the tumor motion pattern features within ITV. Conclusions: The TTV images reflected nonuniform tumor motion, and they revealed the tumor motion pattern features, suggesting that the TTV concept may facilitate various aspects of radiation therapy planning of lung cancer while incorporating respiratory motion in the future.« less

Adrenocortical tumours: high CT attenuation value correlates with eosinophilia but does not discriminate lipid-poor adenomas from malignancy.

PubMed

Pennanen, Mirkka; Raade, Merja; Louhimo, Johanna; Sane, Timo; Heiskanen, Ilkka; Arola, Johanna; Haglund, Caj

2013-12-01

Characterisation of adrenal tumours is an important clinical problem. Unenhanced CT is the primary imaging modality to assess the nature of these lesions. To study the correlation between unenhanced CT attenuation value and the specific histopathology, as well as the proportion of lipid-poor eosinophilic cells in adrenocortical tumours. We studied retrospectively primary adrenocortical tumours that had been operated on at Helsinki University Central Hospital between 2002 and 2008. Of 171 tumours, 79 had appropriate preoperative CT scans and were included in the study. We evaluated the unenhanced CT attenuation values (Hounsfield units, HU) of these tumours and determined their histopathological diagnosis by the Weiss scoring system. We also assessed the proportion of lipid-poor eosinophilic cells for each tumour. Unenhanced CT attenuation value (HU) in adrenocortical tumours correlated well with the proportion of lipid-poor eosinophilic cells (rs=0.750, p<0.001). HU and Weiss score also had a correlation (rs=0.582, p<0.001). Unenhanced CT attenuation value correlates well with the percentage of lipid-poor eosinophilic cells, but unenhanced CT attenuation value fails to differentiate between benign lipid-poor adenomas and malignant adrenocortical tumours. All adrenocortical tumours with unenhanced CT attenuation value ≤10 HU are histologically benign lipid-rich tumours.

Reproducibility of abdominal fat assessment by ultrasound and computed tomography

PubMed Central

Mauad, Fernando Marum; Chagas-Neto, Francisco Abaeté; Benedeti, Augusto César Garcia Saab; Nogueira-Barbosa, Marcello Henrique; Muglia, Valdair Francisco; Carneiro, Antonio Adilton Oliveira; Muller, Enrico Mattana; Elias Junior, Jorge

2017-01-01

Objective: To test the accuracy and reproducibility of ultrasound and computed tomography (CT) for the quantification of abdominal fat in correlation with the anthropometric, clinical, and biochemical assessments. Materials and Methods: Using ultrasound and CT, we determined the thickness of subcutaneous and intra-abdominal fat in 101 subjects-of whom 39 (38.6%) were men and 62 (61.4%) were women-with a mean age of 66.3 years (60-80 years). The ultrasound data were correlated with the anthropometric, clinical, and biochemical parameters, as well as with the areas measured by abdominal CT. Results: Intra-abdominal thickness was the variable for which the correlation with the areas of abdominal fat was strongest (i.e., the correlation coefficient was highest). We also tested the reproducibility of ultrasound and CT for the assessment of abdominal fat and found that CT measurements of abdominal fat showed greater reproducibility, having higher intraobserver and interobserver reliability than had the ultrasound measurements. There was a significant correlation between ultrasound and CT, with a correlation coefficient of 0.71. Conclusion: In the assessment of abdominal fat, the intraobserver and interobserver reliability were greater for CT than for ultrasound, although both methods showed high accuracy and good reproducibility. PMID:28670024

Reproducibility of abdominal fat assessment by ultrasound and computed tomography.

PubMed

Mauad, Fernando Marum; Chagas-Neto, Francisco Abaeté; Benedeti, Augusto César Garcia Saab; Nogueira-Barbosa, Marcello Henrique; Muglia, Valdair Francisco; Carneiro, Antonio Adilton Oliveira; Muller, Enrico Mattana; Elias Junior, Jorge

2017-01-01

To test the accuracy and reproducibility of ultrasound and computed tomography (CT) for the quantification of abdominal fat in correlation with the anthropometric, clinical, and biochemical assessments. Using ultrasound and CT, we determined the thickness of subcutaneous and intra-abdominal fat in 101 subjects-of whom 39 (38.6%) were men and 62 (61.4%) were women-with a mean age of 66.3 years (60-80 years). The ultrasound data were correlated with the anthropometric, clinical, and biochemical parameters, as well as with the areas measured by abdominal CT. Intra-abdominal thickness was the variable for which the correlation with the areas of abdominal fat was strongest (i.e., the correlation coefficient was highest). We also tested the reproducibility of ultrasound and CT for the assessment of abdominal fat and found that CT measurements of abdominal fat showed greater reproducibility, having higher intraobserver and interobserver reliability than had the ultrasound measurements. There was a significant correlation between ultrasound and CT, with a correlation coefficient of 0.71. In the assessment of abdominal fat, the intraobserver and interobserver reliability were greater for CT than for ultrasound, although both methods showed high accuracy and good reproducibility.

Automated assessment of aortic and main pulmonary arterial diameters using model-based blood vessel segmentation for predicting chronic thromboembolic pulmonary hypertension in low-dose CT lung screening

NASA Astrophysics Data System (ADS)

Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Sugiura, Toshihiko; Tanabe, Nobuhiro; Kusumoto, Masahiko; Eguchi, Kenji; Kaneko, Masahiro

2018-02-01

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 lowdose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening.

In-line phase contrast micro-CT reconstruction for biomedical specimens.

PubMed

Fu, Jian; Tan, Renbo

2014-01-01

X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.

Energy-Discriminative Performance of a Spectral Micro-CT System

PubMed Central

He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge

2013-01-01

Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864

3D Printing of CT Dataset: Validation of an Open Source and Consumer-Available Workflow.

PubMed

Bortolotto, Chandra; Eshja, Esmeralda; Peroni, Caterina; Orlandi, Matteo A; Bizzotto, Nicola; Poggi, Paolo

2016-02-01

The broad availability of cheap three-dimensional (3D) printing equipment has raised the need for a thorough analysis on its effects on clinical accuracy. Our aim is to determine whether the accuracy of 3D printing process is affected by the use of a low-budget workflow based on open source software and consumer's commercially available 3D printers. A group of test objects was scanned with a 64-slice computed tomography (CT) in order to build their 3D copies. CT datasets were elaborated using a software chain based on three free and open source software. Objects were printed out with a commercially available 3D printer. Both the 3D copies and the test objects were measured using a digital professional caliper. Overall, the objects' mean absolute difference between test objects and 3D copies is 0.23 mm and the mean relative difference amounts to 0.55 %. Our results demonstrate that the accuracy of 3D printing process remains high despite the use of a low-budget workflow.

Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation

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

Landry, Guillaume, E-mail: g.landry@lmu.de; Nijhuis, Reinoud; Thieke, Christian

2015-03-15

Purpose: Intensity modulated proton therapy (IMPT) of head and neck (H and N) cancer patients may be improved by plan adaptation. The decision to adapt the treatment plan based on a dose recalculation on the current anatomy requires a diagnostic quality computed tomography (CT) scan of the patient. As gantry-mounted cone beam CT (CBCT) scanners are currently being offered by vendors, they may offer daily or weekly updates of patient anatomy. CBCT image quality may not be sufficient for accurate proton dose calculation and it is likely necessary to perform CBCT CT number correction. In this work, the authors investigatedmore » deformable image registration (DIR) of the planning CT (pCT) to the CBCT to generate a virtual CT (vCT) to be used for proton dose recalculation. Methods: Datasets of six H and N cancer patients undergoing photon intensity modulated radiation therapy were used in this study to validate the vCT approach. Each dataset contained a CBCT acquired within 3 days of a replanning CT (rpCT), in addition to a pCT. The pCT and rpCT were delineated by a physician. A Morphons algorithm was employed in this work to perform DIR of the pCT to CBCT following a rigid registration of the two images. The contours from the pCT were deformed using the vector field resulting from DIR to yield a contoured vCT. The DIR accuracy was evaluated with a scale invariant feature transform (SIFT) algorithm comparing automatically identified matching features between vCT and CBCT. The rpCT was used as reference for evaluation of the vCT. The vCT and rpCT CT numbers were converted to stopping power ratio and the water equivalent thickness (WET) was calculated. IMPT dose distributions from treatment plans optimized on the pCT were recalculated with a Monte Carlo algorithm on the rpCT and vCT for comparison in terms of gamma index, dose volume histogram (DVH) statistics as well as proton range. The DIR generated contours on the vCT were compared to physician-drawn contours on the rpCT. Results: The DIR accuracy was better than 1.4 mm according to the SIFT evaluation. The mean WET differences between vCT (pCT) and rpCT were below 1 mm (2.6 mm). The amount of voxels passing 3%/3 mm gamma criteria were above 95% for the vCT vs rpCT. When using the rpCT contour set to derive DVH statistics from dose distributions calculated on the rpCT and vCT the differences, expressed in terms of 30 fractions of 2 Gy, were within [−4, 2 Gy] for parotid glands (D{sub mean}), spinal cord (D{sub 2%}), brainstem (D{sub 2%}), and CTV (D{sub 95%}). When using DIR generated contours for the vCT, those differences ranged within [−8, 11 Gy]. Conclusions: In this work, the authors generated CBCT based stopping power distributions using DIR of the pCT to a CBCT scan. DIR accuracy was below 1.4 mm as evaluated by the SIFT algorithm. Dose distributions calculated on the vCT agreed well to those calculated on the rpCT when using gamma index evaluation as well as DVH statistics based on the same contours. The use of DIR generated contours introduced variability in DVH statistics.« less

Shape-intensity prior level set combining probabilistic atlas and probability map constrains for automatic liver segmentation from abdominal CT images.

PubMed

Wang, Jinke; Cheng, Yuanzhi; Guo, Changyong; Wang, Yadong; Tamura, Shinichi

2016-05-01

Propose a fully automatic 3D segmentation framework to segment liver on challenging cases that contain the low contrast of adjacent organs and the presence of pathologies from abdominal CT images. First, all of the atlases are weighted in the selected training datasets by calculating the similarities between the atlases and the test image to dynamically generate a subject-specific probabilistic atlas for the test image. The most likely liver region of the test image is further determined based on the generated atlas. A rough segmentation is obtained by a maximum a posteriori classification of probability map, and the final liver segmentation is produced by a shape-intensity prior level set in the most likely liver region. Our method is evaluated and demonstrated on 25 test CT datasets from our partner site, and its results are compared with two state-of-the-art liver segmentation methods. Moreover, our performance results on 10 MICCAI test datasets are submitted to the organizers for comparison with the other automatic algorithms. Using the 25 test CT datasets, average symmetric surface distance is [Formula: see text] mm (range 0.62-2.12 mm), root mean square symmetric surface distance error is [Formula: see text] mm (range 0.97-3.01 mm), and maximum symmetric surface distance error is [Formula: see text] mm (range 12.73-26.67 mm) by our method. Our method on 10 MICCAI test data sets ranks 10th in all the 47 automatic algorithms on the site as of July 2015. Quantitative results, as well as qualitative comparisons of segmentations, indicate that our method is a promising tool to improve the efficiency of both techniques. The applicability of the proposed method to some challenging clinical problems and the segmentation of the liver are demonstrated with good results on both quantitative and qualitative experimentations. This study suggests that the proposed framework can be good enough to replace the time-consuming and tedious slice-by-slice manual segmentation approach.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Can computed tomography volumetry of the renal cortex replace MAG3-scintigraphy in all patients for determining split renal function?

PubMed

Houbois, Christian; Haneder, Stefan; Merkt, Martin; Morelli, John N; Schmidt, Matthias; Hellmich, Martin; Mueller, Roman-Ulrich; Wahba, Roger; Maintz, David; Puesken, Michael

2018-06-01

The current gold standard for determination of split renal function (SRF) is Tc-99m-mercapto-acetyltriglycin (MAG3) scintigraphy. Initial studies comparing MAG3-scintigraphy and CT-based renal cortex volumetry (RCV) for calculation of SRF have shown similar results in highly selected patient collectives with normal renal function (i.e. living kidney donors). This study aims to compare MAG3-scintigraphy and CT-RCV within a large unselected patient collective including patients with impaired renal function. For this assessment, 279 datasets (131 men, 148 women; mean age: 54.2 ± 12.9 years, range: 24-84 years) of patients who underwent MAG3-scintigraphy and contrast-enhanced abdominal CT within two weeks were retrospectively analyzed. Two independent readers assessed the CT-RCV in all CT datasets using a semi-automated volumetry tool. The MAG3-scintigraphy and CT-RCV methods were compared, stratified for the eGFR. Statistical analysis included descriptive statistics as well as inter- observer agreement. The absolute mean difference between the percentage contribution of the left and the right kidneys in total MAG3-clearance was 8.6%. Independent of eGFR, an overall sufficient agreement between both methods was established in all patients. A relatively small, tolerable systemic error resulted in an underestimation (max. 2%) of the left renal contribution to overall RCV. The results demonstrate that CT-RCV is a potential clinical replacement for MAG3-scintigraphy for calculation of SRF: CT-RCV demonstrates clinically tolerable differences with MAG3-scintigraphy, independent of patient eGFR. The relative complexity of the RCV method utilized is a potential limitation and may have contributed to the acceptable but only fair to moderate level of intra-reader reliability. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Correlation between the Open-Circuit Voltage and Charge Transfer State Energy in Organic Photovoltaic Cells.

PubMed

Zou, Yunlong; Holmes, Russell J

2015-08-26

In order to further improve the performance of organic photovoltaic cells (OPVs), it is essential to better understand the factors that limit the open-circuit voltage (VOC). Previous work has sought to correlate the value of VOC in donor-acceptor (D-A) OPVs to the interface energy level offset (EDA). In this work, measurements of electroluminescence are used to extract the charge transfer (CT) state energy for multiple small molecule D-A pairings. The CT state as measured from electroluminescence is found to show better correlation to the maximum VOC than EDA. The difference between EDA and the CT state energy is attributed to the Coulombic binding energy of the CT state. This correlation is demonstrated explicitly by inserting an insulating spacer layer between the donor and acceptor materials, reducing the binding energy of the CT state and increasing the measured VOC. These results demonstrate a direct correlation between maximum VOC and CT state energy.

Correlation of iodine uptake and perfusion parameters between dual-energy CT imaging and first-pass dual-input perfusion CT in lung cancer.

PubMed

Chen, Xiaoliang; Xu, Yanyan; Duan, Jianghui; Li, Chuandong; Sun, Hongliang; Wang, Wu

2017-07-01

To investigate the potential relationship between perfusion parameters from first-pass dual-input perfusion computed tomography (DI-PCT) and iodine uptake levels estimated from dual-energy CT (DE-CT).The pre-experimental part of this study included a dynamic DE-CT protocol in 15 patients to evaluate peak arterial enhancement of lung cancer based on time-attenuation curves, and the scan time of DE-CT was determined. In the prospective part of the study, 28 lung cancer patients underwent whole-volume perfusion CT and single-source DE-CT using 320-row CT. Pulmonary flow (PF, mL/min/100 mL), aortic flow (AF, mL/min/100 mL), and a perfusion index (PI = PF/[PF + AF]) were automatically generated by in-house commercial software using the dual-input maximum slope method for DI-PCT. For the dual-energy CT data, iodine uptake was estimated by the difference (λ) and the slope (λHU). λ was defined as the difference of CT values between 40 and 70 KeV monochromatic images in lung lesions. λHU was calculated by the following equation: λHU = |λ/(70 - 40)|. The DI-PCT and DE-CT parameters were analyzed by Pearson/Spearman correlation analysis, respectively.All subjects were pathologically proved as lung cancer patients (including 16 squamous cell carcinoma, 8 adenocarcinoma, and 4 small cell lung cancer) by surgery or CT-guided biopsy. Interobserver reproducibility in DI-PCT (PF, AF, PI) and DE-CT (λ, λHU) were relatively good to excellent (intraclass correlation coefficient [ICC]Inter = 0.8726-0.9255, ICCInter = 0.8179-0.8842; ICCInter = 0.8881-0.9177, ICCInter = 0.9820-0.9970, ICCInter = 0.9780-0.9971, respectively). Correlation coefficient between λ and AF, and PF were as follows: 0.589 (P < .01) and 0.383 (P < .05). Correlation coefficient between λHU and AF, and PF were as follows: 0.564 (P < .01) and 0.388 (P < .05).Both the single-source DE-CT and dual-input CT perfusion analysis method can be applied to assess blood supply of lung cancer patients. Preliminary results demonstrated that the iodine uptake relevant parameters derived from DE-CT significantly correlated with perfusion parameters derived from DI-PCT.

Clinical utility of computed tomographic lung volumes in patients with chronic obstructive pulmonary disease.

PubMed

Lee, Jae Seung; Lee, Sang-Min; Seo, Joon Beom; Lee, Sei Won; Huh, Jin Won; Oh, Yeon-Mok; Lee, Sang-Do

2014-01-01

Published data concerning the utility of computed tomography (CT)-based lung volumes are limited to correlation with lung function. The aim of this study was to evaluate the clinical utility of the CT expiratory-to-inspiratory lung volume ratio (CT Vratio) by assessing the relationship with clinically relevant outcomes. A total of 75 stable chronic obstructive pulmonary disease (COPD) patients having pulmonary function testing and volumetric CT at full inspiration and expiration were retrospectively evaluated. Inspiratory and expiratory CT lung volumes were measured using in-house software. Correlation of the CT Vratio with patient-centered outcomes, including the modified Medical Research Council (MMRC) dyspnea score, the 6-min walk distance (6MWD), the St. George's Respiratory Questionnaire (SGRQ) score, and multidimensional COPD severity indices, such as the BMI, airflow obstruction, dyspnea, and exercise capacity index (BODE) and age, dyspnea, and airflow obstruction (ADO), were analyzed. The CT Vratio correlated significantly with BMI (r = -0.528, p < 0.001). The CT Vratio was also significantly associated with MMRC dyspnea (r = 0.387, p = 0.001), 6MWD (r = -0.459, p < 0.001), and SGRQ (r = 0.369, p = 0.001) scores. Finally, the CT Vratio had significant correlations with the BODE and ADO multidimensional COPD severity indices (r = 0.605, p < 0.001; r = 0.411, p < 0.001). The CT Vratio had significant correlations with patient-centered outcomes and multidimensional COPD severity indices. © 2013 S. Karger AG, Basel.

TU-C-12A-11: Comparisons Between Cu-ATSM PET and DCE-CT Kinetic Parameters in Canine Sinonasal Tumors

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

La Fontaine, M; Bradshaw, T; Kubicek, L

2014-06-15

Purpose: Regions of poor perfusion within tumors may be associated with higher hypoxic levels. This study aimed to test this hypothesis by comparing measurements of hypoxia from Cu-ATSM PET to vasculature kinetic parameters from DCE-CT kinetic analysis. Methods: Ten canine patients with sinonasal tumors received one Cu-ATSM PET/CT scan and three DCE-CT scans prior to treatment. Cu-ATSM PET/CT and DCE-CT scans were registered and resampled to matching voxel dimensions. Kinetic analysis was performed on DCE-CT scans and for each patient, the resulting kinetic parameter values from the three DCE-CT scans were averaged together. Cu-ATSM SUVs were spatially correlated (r{sub spatial})more » on a voxel-to-voxel basis against the following DCE-CT kinetic parameters: transit time (t{sub 1}), blood flow (F), vasculature fraction (v{sub 1}), and permeability (PS). In addition, whole-tumor comparisons were performed by correlating (r{sub ROI}) the mean Cu-ATSM SUV (SUV{sub mean}) with median kinetic parameter values. Results: The spatial correlations (r{sub spatial}) were poor and ranged from -0.04 to 0.21 for all kinetic parameters. These low spatial correlations may be due to high variability in the DCE-CT kinetic parameter voxel values between scans. In our hypothesis, t{sub 1} was expected to have a positive correlation, while F was expected to have a negative correlation to hypoxia. However, in wholetumor analysis the opposite was found for both t{sub 1} (r{sub ROI} = -0.25) and F (r{sub ROI} = 0.56). PS and v{sub 1} may depict angiogenic responses to hypoxia and found positive correlations to Cu-ATSM SUV for PS (r{sub ROI} = 0.41), and v{sub 1} (r{sub ROI} = 0.57). Conclusion: Low spatial correlations were found between Cu-ATSM uptake and DCE-CT vasculature parameters, implying that poor perfusion is not associated with higher hypoxic regions. Across patients, the most hypoxic tumors tended to have higher blood flow values, which is contrary to our initial hypothesis. Funding: R01 CA136927.« less

Secure corridor for infraacetabular screws in acetabular fracture fixation-a 3-D radiomorphometric analysis of 124 pelvic CT datasets.

PubMed

Arlt, Stephan; Noser, Hansrudi; Wienke, Andreas; Radetzki, Florian; Hofmann, Gunther Olaf; Mendel, Thomas

2018-05-21

Acetabular fracture surgery is directed toward anatomical reduction and stable fixation to allow for the early functional rehabilitation of an injured hip joint. Recent biomechanical investigations have shown the superiority of using an additional screw in the infraacetabular (IA) region, thereby transfixing the separated columns to strengthen the construct by closing the periacetabular fixation frame. However, the inter-individual existence and variance concerning secure IA screw corridors are poorly understood. This computer-aided 3-D radiomorphometric study examined 124 CT Digital Imaging and Communications in Medicine (DICOM) datasets of intact human pelves (248 acetabula) to visualize the spatial IA corridors as the sum of all intraosseous screw positions. DICOM files were pre-processed using the Amira® 4.2 visualization software. Final corridor computation was accomplished using a custom-made software algorithm. The volumetric measurement data of each corridor were calculated for further statistical analyses. Correlations between the volumetric values and the biometric data were investigated. Furthermore, the influence of hip dysplasia on the IA corridor configuration was analyzed. The IA corridors consistently showed a double-cone shape with the isthmus located at the acetabular fovea. In 97% of male and 91% of female acetabula, a corridor for a 3.5-mm screw could be found. The number of IA corridors was significantly lower in females for screw diameters ≥ 4.5 mm. The mean 3.5-mm screw corridor volume was 16 cm 3 in males and 9.2 cm 3 in female pelves. Corridor volumes were significantly positively correlated with body height and weight and with the diameter of Köhler's teardrop on standard AP pelvic X-rays. No correlation was observed between hip dysplasia and the IA corridor extent. IA corridors are consistently smaller in females. However, 3.5-mm small fragment screws may still be used as the standard implant because sex-specific differences are significant only with screw diameters ≥ 4.5 mm. Congenital hip dysplasia does not affect secure IA screw insertion. The described method allows 3-D shape analyses with highly reliable results. The visualization of secure IA corridors may support the spatial awareness of surgeons. Volumetric data allow the reliable assessment of individual IA corridors using standard AP X-ray views, which aids preoperative planning.

A dataset describing brooding in three species of South African brittle stars, comprising seven high-resolution, micro X-ray computed tomography scans.

PubMed

Landschoff, Jannes; Du Plessis, Anton; Griffiths, Charles L

2015-01-01

Brooding brittle stars have a special mode of reproduction whereby they retain their eggs and juveniles inside respiratory body sacs called bursae. In the past, studying this phenomenon required disturbance of the sample by dissecting the adult. This caused irreversible damage and made the sample unsuitable for future studies. Micro X-ray computed tomography (μCT) is a promising technique, not only to visualise juveniles inside the bursae, but also to keep the sample intact and make the dataset of the scan available for future reference. Seven μCT scans of five freshly fixed (70 % ethanol) individuals, representing three differently sized brittle star species, provided adequate image quality to determine the numbers, sizes and postures of internally brooded young, as well as anatomy and morphology of adults. No staining agents were necessary to achieve high-resolution, high-contrast images, which permitted visualisations of both calcified and soft tissue. The raw data (projection and reconstruction images) are publicly available for download from GigaDB. Brittle stars of all sizes are suitable candidates for μCT imaging. This explicitly adds a new technique to the suite of tools available for studying the development of internally brooded young. The purpose of applying the technique was to visualise juveniles inside the adult, but because of the universally good quality of the dataset, the images can also be used for anatomical or comparative morphology-related studies of adult structures.

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.

Diagnostic value of contrast-enhanced CT combined with 18-FDG PET in patients selected for cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (HIPEC).

PubMed

Sommariva, Antonio; Evangelista, Laura; Pintacuda, Giovanna; Cervino, Anna Rita; Ramondo, Gaetano; Rossi, Carlo Riccardo

2018-05-01

Aim of the study is to assess the reliability and correlation with surgical peritoneal cancer index (PCI) of combined PET/CT and ceCT scans (PET/ceCT) performed in a session in patients with peritoneal carcinomatosis candidates for cytoreductive surgery (CS) and hyperthermic intraperitoneal chemotherapy (HIPEC). We retrospectively analyzed data collected from 27 patients with different types of peritoneal carcinomatosis candidates to CS + HIPEC who underwent FDG PET/ceCT in a single session. Two nuclear medicine physicians and two radiologists independently and blindly evaluated PET/CT and ceCT imaging, respectively. In the case of discordance, the consensus was reached by a discussion between the specialists. Moreover, the combined images were evaluated by all the specialists in consensus. The PCIs obtained from surgical look, PET/CT, ceCT, and PET/ceCT were compared with each other. The coefficients of correlation (r) were calculated. The study was conducted after approval of local ethics committee. Surgical PCI was available in 21 patients. The coefficient of correlation between PCI of PET/CT and surgery was 0.528, while it resulted higher between PET/ceCT and surgery (r = 0.878), very similar to ceCT and surgery (r = 0.876). The r coefficient between surgical PCI and PET/CT was higher in patients with a non-mucinous cancer (n = 12) than the counterpart (0.601 vs. 0.303) and the addition of ceCT significantly increases the correlation (r = 0.863), which is anyway similar to ceCT alone (r = 0.856). PET/ceCT as single examination is more accurate than PET/CT but not than ceCT alone for the definition of PCI in a selected group of patients candidates to CS + HIPEC.

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

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

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

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

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

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

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

2013-12-15

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

Quantitative CT Evaluation of Small Pulmonary Vessels in Patients with Acute Pulmonary Embolism.

PubMed

Matsuoka, Shin; Kotoku, Akiyuki; Yamashiro, Tsuneo; Matsushita, Shoichiro; Fujikawa, Atsuko; Yagihashi, Kunihiro; Nakajima, Yasuo

2018-05-01

The objective of this study was to investigate the correlation between the computed tomography (CT) cross-sectional area (CSA) of small pulmonary vessels and the CT obstruction index in patients with acute pulmonary embolism (PE) and the correlation between the changes in these measurements after anticoagulant therapy. Fifty-two patients with acute PE were selected for this study. We measured the CSA less than 5 mm 2 on coronal reconstructed images to obtain the percentage of the CSA (%CSA < 5). CT angiographic index was obtained based on the Qanadli method for the evaluation of the degree of pulmonary arterial obstruction. Spearman rank correlation analysis was used to evaluate the relationship between the initial and the follow-up values and changes in the %CSA < 5 and the CT obstruction index. There was no significant correlation between the %CSA < 5 and CT obstruction index on both initial (ρ = -0.03, P = 0.84) and follow-up (ρ = -0.03, P = 0.82) assessments. In contrast, there was a significant negative correlation between the changes in %CSA < 5 and the CT obstruction index (ρ = -0.59, P < 0.0001). Although the absolute %CSA < 5 and CT obstruction index were not significantly correlated, the changes in the values of the two parameters had a significant correlation. Changes in %CSA < 5, which can be obtained easily, can be used as biomarker of therapeutic response in patients with acute PE. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Correlation of intra-tumor 18F-FDG uptake heterogeneity indices with perfusion CT derived parameters in colorectal cancer.

PubMed

Tixier, Florent; Groves, Ashley M; Goh, Vicky; Hatt, Mathieu; Ingrand, Pierre; Le Rest, Catherine Cheze; Visvikis, Dimitris

2014-01-01

Thirty patients with proven colorectal cancer prospectively underwent integrated 18F-FDG PET/DCE-CT to assess the metabolic-flow phenotype. Both CT blood flow parametric maps and PET images were analyzed. Correlations between PET heterogeneity and perfusion CT were assessed by Spearman's rank correlation analysis. Blood flow visualization provided by DCE-CT images was significantly correlated with 18F-FDG PET metabolically active tumor volume as well as with uptake heterogeneity for patients with stage III/IV tumors (|ρ|:0.66 to 0.78; p-value<0.02). The positive correlation found with tumor blood flow indicates that intra-tumor heterogeneity of 18F-FDG PET accumulation reflects to some extent tracer distribution and consequently indicates that 18F-FDG PET intra-tumor heterogeneity may be associated with physiological processes such as tumor vascularization.

Development of a protocol to quantify local bone adaptation over space and time: Quantification of reproducibility.

PubMed

Lu, Yongtao; Boudiffa, Maya; Dall'Ara, Enrico; Bellantuono, Ilaria; Viceconti, Marco

2016-07-05

In vivo micro-computed tomography (µCT) scanning of small rodents is a powerful method for longitudinal monitoring of bone adaptation. However, the life-time bone growth in small rodents makes it a challenge to quantify local bone adaptation. Therefore, the aim of this study was to develop a protocol, which can take into account large bone growth, to quantify local bone adaptations over space and time. The entire right tibiae of eight 14-week-old C57BL/6J female mice were consecutively scanned four times in an in vivo µCT scanner using a nominal isotropic image voxel size of 10.4µm. The repeated scan image datasets were aligned to the corresponding baseline (first) scan image dataset using rigid registration. 80% of tibia length (starting from the endpoint of the proximal growth plate) was selected as the volume of interest and partitioned into 40 regions along the tibial long axis (10 divisions) and in the cross-section (4 sectors). The bone mineral content (BMC) was used to quantify bone adaptation and was calculated in each region. All local BMCs have precision errors (PE%CV) of less than 3.5% (24 out of 40 regions have PE%CV of less than 2%), least significant changes (LSCs) of less than 3.8%, and 38 out of 40 regions have intraclass correlation coefficients (ICCs) of over 0.8. The proposed protocol allows to quantify local bone adaptations over an entire tibia in longitudinal studies, with a high reproducibility, an essential requirement to reduce the number of animals to achieve the necessary statistical power. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Bone quality evaluation at dental implant site using multislice CT, micro-CT, and cone beam CT.

PubMed

Parsa, Azin; Ibrahim, Norliza; Hassan, Bassam; van der Stelt, Paul; Wismeijer, Daniel

2015-01-01

The first purpose of this study was to analyze the correlation between bone volume fraction (BV/TV) and calibrated radiographic bone density Hounsfield units (HU) in human jaws, derived from micro-CT and multislice computed tomography (MSCT), respectively. The second aim was to assess the accuracy of cone beam computed tomography (CBCT) in evaluating trabecular bone density and microstructure using MSCT and micro-CT, respectively, as reference gold standards. Twenty partially edentulous human mandibular cadavers were scanned by three types of CT modalities: MSCT (Philips, Best, the Netherlands), CBCT (3D Accuitomo 170, J Morita, Kyoto, Japan), and micro-CT (SkyScan 1173, Kontich, Belgium). Image analysis was performed using Amira (v4.1, Visage Imaging Inc., Carlsbad, CA, USA), 3Diagnosis (v5.3.1, 3diemme, Cantu, Italy), Geomagic (studio(®) 2012, Morrisville, NC, USA), and CTAn (v1.11, SkyScan). MSCT, CBCT, and micro-CT scans of each mandible were matched to select the exact region of interest (ROI). MSCT HU, micro-CT BV/TV, and CBCT gray value and bone volume fraction of each ROI were derived. Statistical analysis was performed to assess the correlations between corresponding measurement parameters. Strong correlations were observed between CBCT and MSCT density (r = 0.89) and between CBCT and micro-CT BV/TV measurements (r = 0.82). Excellent correlation was observed between MSCT HU and micro-CT BV/TV (r = 0.91). However, significant differences were found between all comparisons pairs (P < 0.001) except for mean measurement between CBCT BV/TV and micro-CT BV/TV (P = 0.147). An excellent correlation exists between bone volume fraction and bone density as assessed on micro-CT and MSCT, respectively. This suggests that bone density measurements could be used to estimate bone microstructural parameters. A strong correlation also was found between CBCT gray values and BV/TV and their gold standards, suggesting the potential of this modality in bone quality assessment at implant site. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

EFFECT ON PERFUSION VALUES OF SAMPLING INTERVAL OF CT PERFUSION ACQUISITIONS IN NEUROENDOCRINE LIVER METASTASES AND NORMAL LIVER

PubMed Central

Ng, Chaan S.; Hobbs, Brian P.; Wei, Wei; Anderson, Ella F.; Herron, Delise H.; Yao, James C.; Chandler, Adam G.

2014-01-01

Objective To assess the effects of sampling interval (SI) of CT perfusion acquisitions on CT perfusion values in normal liver and liver metastases from neuroendocrine tumors. Methods CT perfusion in 16 patients with neuroendocrine liver metastases were analyzed by distributed parameter modeling to yield tissue blood flow, blood volume, mean transit time, permeability, and hepatic arterial fraction, for tumor and normal liver. CT perfusion values for the reference sampling interval of 0.5s (SI0.5) were compared with those of SI datasets of 1s, 2s, 3s and 4s, using mixed-effects model analyses. Results Increases in SI beyond 1s were associated with significant and increasing departures of CT perfusion parameters from reference values at SI0.5 (p≤0.0009). CT perfusion values deviated from reference with increasing uncertainty with increasing SIs. Findings for normal liver were concordant. Conclusion Increasing SIs beyond 1s yield significantly different CT perfusion parameter values compared to reference values at SI0.5. PMID:25626401

Computed Tomography Scanning and Geophysical Measurements of Core from the Coldstream 1MH Well

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

Crandall, Dustin M.; Brown, Sarah; Moore, Johnathan E.

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) Morgantown, West Virginia site were used to characterize core of the Marcellus Shale from a vertical well, the Coldstream 1MH Well in Clearfield County, PA. The core is comprised primarily of the Marcellus Shale from a depth of 7,002 to 7,176 ft. The primary impetus of this work is a collaboration between West Virginia University (WVU) and NETL to characterize core from multiple wells to better understand the structure and variation of the Marcellus and Utica shale formations. As part of thismore » effort, bulk scans of core were obtained from the Coldstream 1MH well, provided by the Energy Corporation of America (now Greylock Energy). This report, and the associated scans, provide detailed datasets not typically available from unconventional shales for analysis. The resultant datasets are presented in this report, and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/coldstream-1mh-well. All equipment and techniques used were non-destructive, enabling future examinations to be performed on these cores. None of the equipment used was suitable for direct visualization of the shale pore space, although fractures and discontinuities were detectable with the methods tested. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with x-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis as well as fractured zones. En echelon fractures were observed at 7,100 ft and were CT scanned using NETL’s industrial CT scanner at higher resolution. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provides both a macro and micro description of the core that is relevant for many subsurface energy-related examinations that have traditionally been performed at NETL.« less

Correlations to predict frictional pressure loss of hydraulic-fracturing slurry in coiled tubing

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

Shah, S.; Zhoi, Y.X.; Bailey, M.

2009-08-15

Compared with conventional-tubing fracturing, coiled-tubing (CT) fracturing has several advantages. CT fracturing has become an effective stimulation technique for multizone oil and gas wells. It is also an attractive production-enhancement method for multiseam coalbed-methane wells, and wells with bypassed zones. The excessive frictional pressure loss through CT has been a concern in fracturing. The small diameter of the string limits the cross-sectional area open to flow. Furthermore, the tubing curvature causes secondary flow and results in extra flow resistance. This increased frictional pressure loss results in high surface pumping pressure. The maximum possible pump rate and sand concentration, therefore, havemore » to be reduced. To design a CT fracturing job properly, it is essential to predict the frictional pressure loss through the tubing accurately. This paper presents correlations for the prediction of frictional pressure loss of fracturing slurries in straight tubing and CT. They are developed on the basis of full-scale slurry-flow tests with 11/2-in. CT and slurries prepared with 35 lbm/1,000 gal of guar gel. The extensive experiments were conducted at the full-scale CT-flow test facility. The proposed correlations have been verified with the experimental data and actual field CT-fracturing data. Case studies of wells recently fractured are provided to demonstrate the application of the correlations. The correlations will be useful to the CT engineers in their hydraulics design calculations.« less

Prevalence and Correlates of Chlamydia trachomatis and Neisseria gonorrhoeae by Anatomic Site Among Urban Thai Men Who Have Sex With Men.

PubMed

Tongtoyai, Jaray; Todd, Catherine S; Chonwattana, Wannee; Pattanasin, Sarika; Chaikummao, Supaporn; Varangrat, Anchalee; Lokpichart, Somchai; Holtz, Timothy H; van Griensven, Frits; Curlin, Marcel E

2015-08-01

Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infection are prevalent among men who have sex with men (MSM) and may infect multiple anatomic sites. We measured site-specific prevalence and correlates of CT and NG infection among Bangkok MSM Cohort Study participants. In April 2006 to November 2010, 1744 men enrolled in the Bangkok MSM Cohort Study. Participants provided historical information and underwent physical examination. Rectal, urethral, and pharyngeal CT and NG screening were performed by nucleic acid amplification and/or culture. Logistic regression was used to identify correlates of site-specific CT, NG, and coinfection. Among 1743 participants, 19.2% were infected with CT and/or NG. CT, NG, and CT-NG coinfection were detected in 11.6%, 4.6%, and 2.9%, of participants, respectively. Rectal, urethral, and pharyngeal CT infections were detected in 9.5%, 4.5%, and 3.6% of cases. N. gonorrhoeae was present at these sites in 6.1%, 1.8%, and 0.5% of cases. Most infections were asymptomatic (CT: 95.3%, NG: 83.2%). Rectal CT and NG infections were mutually associated (CT: adjusted odds ratio [AOR], 5.4; 95% confidence interval [CI], 3.4-8.7; NG: AOR, 2.4; 95% CI, 1.1-5.2) and independently associated with HIV infection (CT: AOR, 1.6, 95% CI, 1.0-2.4; NG: AOR, 2.0, 95% CI, 1.3-3.1). Numerous behavioral correlates of infection were observed. CT and NG infections are highly prevalent among MSM in Bangkok, most frequently affect the rectum, and are most often asymptomatic. Routine screening of asymptomatic MSM for CT and NG infection should include rectal sampling and focus on men with HIV and a history of other sexually transmitted infections.

Lung fissure detection in CT images using global minimal paths

NASA Astrophysics Data System (ADS)

Appia, Vikram; Patil, Uday; Das, Bipul

2010-03-01

Pulmonary fissures separate human lungs into five distinct regions called lobes. Detection of fissure is essential for localization of the lobar distribution of lung diseases, surgical planning and follow-up. Treatment planning also requires calculation of the lobe volume. This volume estimation mandates accurate segmentation of the fissures. Presence of other structures (like vessels) near the fissure, along with its high variational probability in terms of position, shape etc. makes the lobe segmentation a challenging task. Also, false incomplete fissures and occurrence of diseases add to the complications of fissure detection. In this paper, we propose a semi-automated fissure segmentation algorithm using a minimal path approach on CT images. An energy function is defined such that the path integral over the fissure is the global minimum. Based on a few user defined points on a single slice of the CT image, the proposed algorithm minimizes a 2D energy function on the sagital slice computed using (a) intensity (b) distance of the vasculature, (c) curvature in 2D, (d) continuity in 3D. The fissure is the infimum energy path between a representative point on the fissure and nearest lung boundary point in this energy domain. The algorithm has been tested on 10 CT volume datasets acquired from GE scanners at multiple clinical sites. The datasets span through different pathological conditions and varying imaging artifacts.

Turbulence structure of the near-surface boundary layer in complex terrain

NASA Astrophysics Data System (ADS)

Sfyri, Eleni; Rotach, Mathias Walter; Stiperski, Ivana; Bosveld, Fred; Lehner, Manuela; Obleitner, Friedrich

2017-04-01

Monin-Obukhov Similarity Theory (MOST) is evaluated in two cases: truly complex terrain (CT) and horizontally inhomogeneous and flat (HIF) terrain. CT data are derived from 5 measurement sites, which differ in terms of slope, orientation and surface roughness at the Inn Valley of Austria (i-Box) and HIF data come from one measurement site at the Cabauw experimental site (Netherlands). The applicability of the surface-layer, 'ideal' similarity relations is examined for both data-sets and the non-dimensional variances of temperature and humidity as a function of stability (z/L, where L is the Obukhov length) are compared for each type of terrain. Large deviations from the reference curves in case of temperature are observed in both CT and HIF, leading to the conclusion that these deviations are not due to the complex terrain but due to inappropriate near-neutral description of the reference curves. It is found here that the non-dimensional temperature variance exhibits a -1 slope in the near-neutral region, for both CT and HIF datasets. In addition, the constant-fluxes hypothesis of the MOST is evaluated at one i-Box site. It is found that only about 1% of the data show constant momentum, sensible and latent heat fluxes with height. Therefore, local scaling instead of surface layer scaling is being used in this study.

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.

SU-C-BRA-04: Use of Esophageal Wall Thickness in Evaluation of the Response to Chemoradiation Therapy for Esophageal Cancer

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

Wang, J; Kligerman, S; Lu, W

2015-06-15

Purpose: To quantitatively evaluate the esophageal cancer response to chemoradiation therapy (CRT) by measuring the esophageal wall thickness in CT. Method: Two datasets were used in this study. The first dataset is composed of CT scans of 15 esophageal cancer patients and 15 normal controls. The second dataset is composed of 20 esophageal cancer patients who underwent PET/CT scans before (Pre-CRT) and after CRT (Post-CRT). We first segmented the esophagus using a multi-atlas-based algorithm. The esophageal wall thickness was then computed, on each slice, as the equivalent circle radius of the segmented esophagus excluding the lumen. To evaluate the changesmore » of wall thickness, we computed the standard deviation (SD), coefficient of variation (COV, SD/Mean), and flatness [(Max–Min)/Mean] of wall thickness along the entire esophagus. Results: For the first dataset, the mean wall thickness of cancer patients and normal controls were 6.35 mm and 6.03 mm, respectively. The mean SD, COV, and flatness of the wall thickness were 2.59, 0.21, and 1.27 for the cancer patients and 1.99, 0.16, and 1.13 for normal controls. Statistically significant differences (p < 0.05) were identified in SD and flatness. For the second dataset, the mean wall thickness of pre-CRT and post-CRT patients was 7.13 mm and 6.84 mm, respectively. The mean SD, COV, and flatness were 1.81, 0.26, and 1.06 for pre-CRT and 1.69, 0.26, and 1.06 for post-CRT. Statistically significant difference was not identified for these measurements. Current results are based on the entire esophagus. We believe significant differences between pre- and post-CRT scans could be obtained, if we conduct the measurements at tumor sites. Conclusion: Results show thicker wall thickness in pre-CRT scans and differences in wall thickness changes between normal and abnormal esophagus. This demonstrated the potential of esophageal wall thickness as a marker in the tumor CRT response evaluation. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Multi-Mounted X-Ray Computed Tomography.

PubMed

Fu, Jian; Liu, Zhenzhong; Wang, Jingzheng

2016-01-01

Most existing X-ray computed tomography (CT) techniques work in single-mounted mode and need to scan the inspected objects one by one. It is time-consuming and not acceptable for the inspection in a large scale. In this paper, we report a multi-mounted CT method and its first engineering implementation. It consists of a multi-mounted scanning geometry and the corresponding algebraic iterative reconstruction algorithm. This approach permits the CT rotation scanning of multiple objects simultaneously without the increase of penetration thickness and the signal crosstalk. Compared with the conventional single-mounted methods, it has the potential to improve the imaging efficiency and suppress the artifacts from the beam hardening and the scatter. This work comprises a numerical study of the method and its experimental verification using a dataset measured with a developed multi-mounted X-ray CT prototype system. We believe that this technique is of particular interest for pushing the engineering applications of X-ray CT.

Consumers' Use of UMLS Concepts on Social Media: Diabetes-Related Textual Data Analysis in Blog and Social Q&A Sites.

PubMed

Park, Min Sook; He, Zhe; Chen, Zhiwei; Oh, Sanghee; Bian, Jiang

2016-11-24

The widely known terminology gap between health professionals and health consumers hinders effective information seeking for consumers. The aim of this study was to better understand consumers' usage of medical concepts by evaluating the coverage of concepts and semantic types of the Unified Medical Language System (UMLS) on diabetes-related postings in 2 types of social media: blogs and social question and answer (Q&A). We collected 2 types of social media data: (1) a total of 3711 blogs tagged with "diabetes" on Tumblr posted between February and October 2015; and (2) a total of 58,422 questions and associated answers posted between 2009 and 2014 in the diabetes category of Yahoo! Answers. We analyzed the datasets using a widely adopted biomedical text processing framework Apache cTAKES and its extension YTEX. First, we applied the named entity recognition (NER) method implemented in YTEX to identify UMLS concepts in the datasets. We then analyzed the coverage and the popularity of concepts in the UMLS source vocabularies across the 2 datasets (ie, blogs and social Q&A). Further, we conducted a concept-level comparative coverage analysis between SNOMED Clinical Terms (SNOMED CT) and Open-Access Collaborative Consumer Health Vocabulary (OAC CHV)-the top 2 UMLS source vocabularies that have the most coverage on our datasets. We also analyzed the UMLS semantic types that were frequently observed in our datasets. We identified 2415 UMLS concepts from blog postings, 6452 UMLS concepts from social Q&A questions, and 10,378 UMLS concepts from the answers. The medical concepts identified in the blogs can be covered by 56 source vocabularies in the UMLS, while those in questions and answers can be covered by 58 source vocabularies. SNOMED CT was the dominant vocabulary in terms of coverage across all the datasets, ranging from 84.9% to 95.9%. It was followed by OAC CHV (between 73.5% and 80.0%) and Metathesaurus Names (MTH) (between 55.7% and 73.5%). All of the social media datasets shared frequent semantic types such as "Amino Acid, Peptide, or Protein," "Body Part, Organ, or Organ Component," and "Disease or Syndrome." Although the 3 social media datasets vary greatly in size, they exhibited similar conceptual coverage among UMLS source vocabularies and the identified concepts showed similar semantic type distributions. As such, concepts that are both frequently used by consumers and also found in professional vocabularies such as SNOMED CT can be suggested to OAC CHV to improve its coverage. ©Min Sook Park, Zhe He, Zhiwei Chen, Sanghee Oh, Jiang Bian. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 24.11.2016.

Consumers’ Use of UMLS Concepts on Social Media: Diabetes-Related Textual Data Analysis in Blog and Social Q&A Sites

PubMed Central

Chen, Zhiwei; Oh, Sanghee; Bian, Jiang

2016-01-01

Background The widely known terminology gap between health professionals and health consumers hinders effective information seeking for consumers. Objective The aim of this study was to better understand consumers’ usage of medical concepts by evaluating the coverage of concepts and semantic types of the Unified Medical Language System (UMLS) on diabetes-related postings in 2 types of social media: blogs and social question and answer (Q&A). Methods We collected 2 types of social media data: (1) a total of 3711 blogs tagged with “diabetes” on Tumblr posted between February and October 2015; and (2) a total of 58,422 questions and associated answers posted between 2009 and 2014 in the diabetes category of Yahoo! Answers. We analyzed the datasets using a widely adopted biomedical text processing framework Apache cTAKES and its extension YTEX. First, we applied the named entity recognition (NER) method implemented in YTEX to identify UMLS concepts in the datasets. We then analyzed the coverage and the popularity of concepts in the UMLS source vocabularies across the 2 datasets (ie, blogs and social Q&A). Further, we conducted a concept-level comparative coverage analysis between SNOMED Clinical Terms (SNOMED CT) and Open-Access Collaborative Consumer Health Vocabulary (OAC CHV)—the top 2 UMLS source vocabularies that have the most coverage on our datasets. We also analyzed the UMLS semantic types that were frequently observed in our datasets. Results We identified 2415 UMLS concepts from blog postings, 6452 UMLS concepts from social Q&A questions, and 10,378 UMLS concepts from the answers. The medical concepts identified in the blogs can be covered by 56 source vocabularies in the UMLS, while those in questions and answers can be covered by 58 source vocabularies. SNOMED CT was the dominant vocabulary in terms of coverage across all the datasets, ranging from 84.9% to 95.9%. It was followed by OAC CHV (between 73.5% and 80.0%) and Metathesaurus Names (MTH) (between 55.7% and 73.5%). All of the social media datasets shared frequent semantic types such as “Amino Acid, Peptide, or Protein,” “Body Part, Organ, or Organ Component,” and “Disease or Syndrome.” Conclusions Although the 3 social media datasets vary greatly in size, they exhibited similar conceptual coverage among UMLS source vocabularies and the identified concepts showed similar semantic type distributions. As such, concepts that are both frequently used by consumers and also found in professional vocabularies such as SNOMED CT can be suggested to OAC CHV to improve its coverage. PMID:27884812

Can technical characteristics predict clinical performance in PET/CT imaging? A correlation study for thyroid cancer diagnosis

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Menychtas, Dimitrios; Georgakopoulos, Alexandros; Pianou, Nikoletta; Metaxas, Marinos; Chatziioannou, Sofia

2013-03-01

The purpose of this study was to determine whether image characteristics could be used to predict the outcome of ROC studies in PET/CT imaging. Patients suspected for recurrent thyroid cancer underwent a standard whole body (WB) examination and an additional high-resolution head-and-neck (HN) F18-FDG PET/CT scan. The value of the latter was determined with an ROC study, the results of which showed that the WB+HN combination was better than WB alone for thyroid cancer detection and diagnosis. Following the ROC experiment, the WB and HN images of confirmed benign or malignant thyroid disease were analyzed and first and second order textural features were determined. Features included minimum, mean, and maximum intensity, as well as contrast in regions of interest encircling the thyroid lesions. Lesion size and standard uptake values (SUV) were also determined. Bivariate analysis was applied to determine relationships between WB and HN features and between observer ROC responses and the various feature values. The two sets showed significant associations in the values of SUV, contrast, and lesion size. They were completely different when the intensities were considered; no relationship was found between the WB minimum, maximum, and mean ROI values and their HN counterparts. SUV and contrast were the strongest predictors of ROC performance on PET/CT examinations of thyroid cancer. The high resolution HN images seem to enhance these relationships but without a single dramatic effect as was projected from the ROC results. A combination of features from both WB and HN datasets may possibly be a more robust predictor of ROC performance.

Relative location prediction in CT scan images using convolutional neural networks.

PubMed

Guo, Jiajia; Du, Hongwei; Zhu, Jianyue; Yan, Ting; Qiu, Bensheng

2018-07-01

Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and speed of these methods cannot meet the requirement of medical scenario. In this paper, we propose a regression model based on one-dimensional convolutional neural networks (CNN) to determine the relative location of a CT scan image both quickly and precisely. In contrast to other common CNN models that use a two-dimensional image as an input, the input of this CNN model is a feature vector extracted by a shape context algorithm with spatial correlation. Normalization via z-score is first applied as a pre-processing step. Then, in order to prevent overfitting and improve model's performance, 20% of the elements of the feature vectors are randomly set to zero. This CNN model consists primarily of three one-dimensional convolutional layers, three dropout layers and two fully-connected layers with appropriate loss functions. A public dataset is employed to validate the performance of the proposed model using a 5-fold cross validation. Experimental results demonstrate an excellent performance of the proposed model when compared with contemporary techniques, achieving a median absolute error of 1.04 cm and mean absolute error of 1.69 cm. The time taken for each relative location prediction is approximately 2 ms. Results indicate that the proposed CNN method can contribute to a quick and accurate relative location prediction in CT scan images, which can improve efficiency of the medical picture archiving and communication system in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

CtBP2 overexpression promotes tumor cell proliferation and invasion in gastric cancer and is associated with poor prognosis.

PubMed

Dai, Faxiang; Xuan, Yi; Jin, Jie-Jie; Yu, Shengjia; Long, Zi-Wen; Cai, Hong; Liu, Xiao-Wen; Zhou, Ye; Wang, Ya-Nong; Chen, Zhong; Huang, Hua

2017-04-25

C-terminal binding protein-2 (CtBP2), a transcriptional corepressor, has been reported to correlate with tumorigenesis and progression and predict a poor prognosis in several human cancers. However, few studies on CtBP2 in gastric cancer (GC) have been performed. In this research, we evaluated the correlations between CtBP2 expression and the clinicopathological characteristics, as well as prognosis of GC patients. The effects of silencing CtBP2 expression on GC cells biology activity were also assessed. The results showed that CtBP2 was overexpressed in GC tissues and closely correlated with poor differentiation, advanced tumor stage and poor prognosis in GC patients. CtBP2 induced epithelial-to-mesenchymal transition (EMT) and repressed PTEN to increase proliferation rate, migration, and invasion in GC cells. Silencing CtBP2 inhibited GC growth in nude mice model. In conclusion, CtBP2 is overexpressed in GC and may accelerate GC tumorigenesis and metastasis, which could represent an independent prognostic marker and promising therapeutic target for GC.

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

Real-time compression of raw computed tomography data: technology, architecture, and benefits

NASA Astrophysics Data System (ADS)

Wegener, Albert; Chandra, Naveen; Ling, Yi; Senzig, Robert; Herfkens, Robert

2009-02-01

Compression of computed tomography (CT) projection samples reduces slip ring and disk drive costs. A lowcomplexity, CT-optimized compression algorithm called Prism CTTM achieves at least 1.59:1 and up to 2.75:1 lossless compression on twenty-six CT projection data sets. We compare the lossless compression performance of Prism CT to alternative lossless coders, including Lempel-Ziv, Golomb-Rice, and Huffman coders using representative CT data sets. Prism CT provides the best mean lossless compression ratio of 1.95:1 on the representative data set. Prism CT compression can be integrated into existing slip rings using a single FPGA. Prism CT decompression operates at 100 Msamp/sec using one core of a dual-core Xeon CPU. We describe a methodology to evaluate the effects of lossy compression on image quality to achieve even higher compression ratios. We conclude that lossless compression of raw CT signals provides significant cost savings and performance improvements for slip rings and disk drive subsystems in all CT machines. Lossy compression should be considered in future CT data acquisition subsystems because it provides even more system benefits above lossless compression while achieving transparent diagnostic image quality. This result is demonstrated on a limited dataset using appropriately selected compression ratios and an experienced radiologist.

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

NASA Astrophysics Data System (ADS)

Roth, Holger; Oda, Masahiro; Shimizu, Natsuki; Oda, Hirohisa; Hayashi, Yuichiro; Kitasaka, Takayuki; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-03-01

Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this work, we describe a custom-build 3D fully convolutional network (FCN) that can process a 3D image including the whole pancreas and produce an automatic segmentation. We investigate two variations of the 3D FCN architecture; one with concatenation and one with summation skip connections to the decoder part of the network. We evaluate our methods on a dataset from a clinical trial with gastric cancer patients, including 147 contrast enhanced abdominal CT scans acquired in the portal venous phase. Using the summation architecture, we achieve an average Dice score of 89.7 +/- 3.8 (range [79.8, 94.8])% in testing, achieving the new state-of-the-art performance in pancreas segmentation on this dataset.

SU-F-T-609: Impact of Dosimetric Variation for Prescription Dose Using Analytical Anisotropic Algorithm (AAA) in Lung SBRT

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

Kawai, D; Takahashi, R; Kamima, T

Purpose: Actual irradiated prescription dose to patients cannot be verified. Thus, independent dose verification and second treatment planning system are used as the secondary check. AAA dose calculation engine has contributed to lung SBRT. We conducted a multi-institutional study to assess variation of prescription dose for lung SBRT when using AAA in reference to using Acuros XB and Clarkson algorithm. Methods: Six institutes in Japan participated in this study. All SBRT treatments were planed using AAA in Eclipse and Adaptive Convolve (AC) in Pinnacle3. All of the institutes used a same independent dose verification software program (Simple MU Analysis: SMU,more » Triangle Product, Ishikawa, Japan), which implemented a Clarkson-based dose calculation algorithm using CT image dataset. A retrospective analysis for lung SBRT plans (73 patients) was performed to compute the confidence limit (CL, Average±2SD) in dose between the AAA and the SMU. In one of the institutes, a additional analysis was conducted to evaluate the variations between the AAA and the Acuros XB (AXB). Results: The CL for SMU shows larger systematic and random errors of 8.7±9.9 % for AAA than the errors of 5.7±4.2 % for AC. The variations of AAA correlated with the mean CT values in the voxels of PTV (a correlation coefficient : −0.7) . The comparison of AXB vs. AAA shows smaller systematic and random errors of −0.7±1.7%. The correlation between dose variations for AXB and the mean CT values in PTV was weak (0.4). However, there were several plans with more than 2% deviation of AAPM TG114 (Maximum: −3.3 %). Conclusion: In comparison for AC, prescription dose calculated by AAA may be more variable in lung SBRT patient. Even AXB comparison shows unexpected variation. Care should be taken for the use of AAA in lung SBRT. This research is partially supported by Japan Agency for Medical Research and Development (AMED)« less

Evaluation of the preimplantation worksheet in determining Calypso eligibility for men prescribed postprostatectomy radiotherapy with electromagnetic transponder guidance.

PubMed

Hamilton, Daniel George; Jones, Kingsley; So, Kevin

2017-01-01

This study aimed to assess the design and performance of the preimplant suitability worksheet in determining Calypso eligibility for prostate cancer patients prescribed postprostatectomy radiotherapy with electromagnetic transponder guidance. The medical records and radiotherapy planning datasets of 75 patients prospectively recruited between June 2015 and September 2016 to a Phase 2 trial evaluating electromagnetic transponder-guided postprostatectomy radiotherapy were retrospectively examined. Correlation and differences between computed tomography (CT)-defined greater trochanter and prostatic fossa landmarks were evaluated. Receiver operating characteristic curves were also generated to assess the expected and observed accuracy of the worksheet in determining Calypso eligibility. Strong correlation was demonstrated between anterior surface to planning CT-defined greater trochanter and prostate bed center distances (r = 0.95, p <0.001), with a mean difference between measurements of 1.1 cm (95% confidence interval [CI]: 0.9 to 1.3). A similar correlation coefficient was found for surface to greater trochanter location and posterior beacon location (r = 0.92, p <0.001) but with a reduced mean difference of 0.4 cm (95% CI: 0.1 to 0.6). Performance of the worksheet as assessed by planning CT data demonstrated excellent accuracy as a test to determine eligibility (area under the curve: 0.97; 95% CI: 0.92 to 1.00); however, this was not replicated using the same data captured clinically (area under the curve 0.83; 95% CI: 0.68 to 0.98). Although the greater trochanter is a good surrogate for the prostate bed center, it is better associated with the posterior beacon location. As a result, the worksheet will underestimate the truly eligible population if performed accurately and according to manufacturer guidelines. Theoretically, the worksheet could be improved if a cut off of 20 cm is used and the greater trochanter is accurately identified; however, the latter appears to be difficult to achieve in practice. Copyright © 2017 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Pancreatic mucinous cystic neoplasm size using CT volumetry, spherical and ellipsoid formulas: validation study.

PubMed

Chalian, Hamid; Seyal, Adeel Rahim; Rezai, Pedram; Töre, Hüseyin Gürkan; Miller, Frank H; Bentrem, David J; Yaghmai, Vahid

2014-01-10

The accuracy for determining pancreatic cyst volume with commonly used spherical and ellipsoid methods is unknown. The role of CT volumetry in volumetric assessment of pancreatic cysts needs to be explored. To compare volumes of the pancreatic cysts by CT volumetry, spherical and ellipsoid methods and determine their accuracy by correlating with actual volume as determined by EUS-guided aspiration. Setting This is a retrospective analysis performed at a tertiary care center. Patients Seventy-eight pathologically proven pancreatic cysts evaluated with CT and endoscopic ultrasound (EUS) were included. Design The volume of fourteen cysts that had been fully aspirated by EUS was compared to CT volumetry and the routinely used methods (ellipsoid and spherical volume). Two independent observers measured all cysts using commercially available software to evaluate inter-observer reproducibility for CT volumetry. The volume of pancreatic cysts as determined by various methods was compared using repeated measures analysis of variance. Bland-Altman plot and intraclass correlation coefficient were used to determine mean difference and correlation between observers and methods. The error was calculated as the percentage of the difference between the CT estimated volumes and the aspirated volume divided by the aspirated one. CT volumetry was comparable to aspirated volume (P=0.396) with very high intraclass correlation (r=0.891, P<0.001) and small mean difference (0.22 mL) and error (8.1%). Mean difference with aspirated volume and error were larger for ellipsoid (0.89 mL, 30.4%; P=0.024) and spherical (1.73 mL, 55.5%; P=0.004) volumes than CT volumetry. There was excellent inter-observer correlation in volumetry of the entire cohort (r=0.997, P<0.001). CT volumetry is accurate and reproducible. Ellipsoid and spherical volume overestimate the true volume of pancreatic cysts.

X-ray computed tomography using curvelet sparse regularization.

PubMed

Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias

2015-04-01

Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.

Population of 224 realistic human subject-based computational breast phantoms

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

Erickson, David W.; Wells, Jered R., E-mail: jered.wells@duke.edu; Sturgeon, Gregory M.

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was thenmore » applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.« less

Population of 224 realistic human subject-based computational breast phantoms

PubMed Central

Erickson, David W.; Wells, Jered R.; Sturgeon, Gregory M.; Dobbins, James T.; Segars, W. Paul; Lo, Joseph Y.

2016-01-01

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns. PMID:26745896

Hypercalcitoninemia in infancy.

PubMed

Cannarozzi, D B; Canale, D D; Donabedian, R K

1976-02-02

Immunoreactive calcitonin (iCT) was measured in 19 infants with neonatal hypocalcemia. The infants had a variety of neonatal diseases and stresses. iCT levels were generally elevated to two to 20 times the adult values. Poor correlation existed between the infant age and the level of iCT or between iCT alone and the serum calcium. However, there was significant correlation between the serum calcium and the ratio of the iCT to infant age from conception, suggesting that both infant age and iCT levels in combination may be related to hypocalcemia. Also, it appears that a variety of neonatal stresses may be associated with increased sensitivity to the hypocalcemic effect of iCT, as well as increased levels of iCT.

Time efficient 124I-PET volumetry in benign thyroid disorders by automatic isocontour procedures: mathematic adjustment using manual contoured measurements in low-dose CT.

PubMed

Freesmeyer, Martin; Kühnel, Christian; Westphal, Julian G

2015-01-01

Benign thyroid diseases are widely common in western societies. However, the volumetry of the thyroid gland, especially when enlarged or abnormally formed, proves to be a challenge in clinical routine. The aim of this study was to develop a simple and rapid threshold-based isocontour extraction method for thyroid volumetry from (124)I-PET/CT data in patients scheduled for radioactive iodine therapy. PET/CT data from 45 patients were analysed 30 h after 1 MBq (124)I administration. Anatomical reference volume was calculated using manually contoured data from low-dose CT images of the neck (MC). In addition, we applied an automatic isocontour extraction method (IC0.2/1.0), with two different threshold values (0.2 and 1.0 kBq/ml), for volumetry of the PET data-set. IC0.2/1.0 shape data that showed significant variation from MC data were excluded. Subsequently, a mathematical correlation using a model of linear regression with multiple variables and step-wise elimination (mIC0.2/1.0), between IC0.2/1.0 and MC, was established. Data from 41 patients (IC0.2), and 32 patients (IC1.0) were analysed. The mathematically calculated volume, mIC, showed a median deviation from the reference (MC), of ±9 % (1-54 %) for mIC0.2 and of ±8.2 % (1-50 %) for mIC1.0 CONCLUSION: Contour extraction with both, mIC1.0 and mIC0.2 gave rapid and reliable results. However, mIC0.2 can be applied to significantly more patients (>90 %) and is, therefore, deemed to be more suitable for clinical routine, keeping in mind the potential advantages of using (124)I-PET/CT for the preparation of patients scheduled for radioactive iodine therapy.

Interactive visualization and analysis of multimodal datasets for surgical applications.

PubMed

Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

2012-12-01

Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

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

Li, Dengwang; Wang, Qinfen; Li, H

Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contourmore » structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity differences between primary and lymphoma tumor by multi-scale image texture analysis. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)« less

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

PubMed

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

2018-05-08

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

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.

Quantifying the tibiofemoral joint space using x-ray tomosynthesis.

PubMed

Kalinosky, Benjamin; Sabol, John M; Piacsek, Kelly; Heckel, Beth; Gilat Schmidt, Taly

2011-12-01

Digital x-ray tomosynthesis (DTS) has the potential to provide 3D information about the knee joint in a load-bearing posture, which may improve diagnosis and monitoring of knee osteoarthritis compared with projection radiography, the current standard of care. Manually quantifying and visualizing the joint space width (JSW) from 3D tomosynthesis datasets may be challenging. This work developed a semiautomated algorithm for quantifying the 3D tibiofemoral JSW from reconstructed DTS images. The algorithm was validated through anthropomorphic phantom experiments and applied to three clinical datasets. A user-selected volume of interest within the reconstructed DTS volume was enhanced with 1D multiscale gradient kernels. The edge-enhanced volumes were divided by polarity into tibial and femoral edge maps and combined across kernel scales. A 2D connected components algorithm was performed to determine candidate tibial and femoral edges. A 2D joint space width map (JSW) was constructed to represent the 3D tibiofemoral joint space. To quantify the algorithm accuracy, an adjustable knee phantom was constructed, and eleven posterior-anterior (PA) and lateral DTS scans were acquired with the medial minimum JSW of the phantom set to 0-5 mm in 0.5 mm increments (VolumeRad™, GE Healthcare, Chalfont St. Giles, United Kingdom). The accuracy of the algorithm was quantified by comparing the minimum JSW in a region of interest in the medial compartment of the JSW map to the measured phantom setting for each trial. In addition, the algorithm was applied to DTS scans of a static knee phantom and the JSW map compared to values estimated from a manually segmented computed tomography (CT) dataset. The algorithm was also applied to three clinical DTS datasets of osteoarthritic patients. The algorithm segmented the JSW and generated a JSW map for all phantom and clinical datasets. For the adjustable phantom, the estimated minimum JSW values were plotted against the measured values for all trials. A linear fit estimated a slope of 0.887 (R² = 0.962) and a mean error across all trials of 0.34 mm for the PA phantom data. The estimated minimum JSW values for the lateral adjustable phantom acquisitions were found to have low correlation to the measured values (R² = 0.377), with a mean error of 2.13 mm. The error in the lateral adjustable-phantom datasets appeared to be caused by artifacts due to unrealistic features in the phantom bones. JSW maps generated by DTS and CT varied by a mean of 0.6 mm and 0.8 mm across the knee joint, for PA and lateral scans. The tibial and femoral edges were successfully segmented and JSW maps determined for PA and lateral clinical DTS datasets. A semiautomated method is presented for quantifying the 3D joint space in a 2D JSW map using tomosynthesis images. The proposed algorithm quantified the JSW across the knee joint to sub-millimeter accuracy for PA tomosynthesis acquisitions. Overall, the results suggest that x-ray tomosynthesis may be beneficial for diagnosing and monitoring disease progression or treatment of osteoarthritis by providing quantitative images of JSW in the load-bearing knee.

SU-E-J-242: Volume-Dependence of Quantitative Imaging Features From CT and CE-CT Images of NSCLC

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

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

Purpose: To determine whether tumor volume plays a significant role in the values obtained for texture features when they are extracted from computed tomography (CT) images of non-small cell lung cancer (NSCLC). We also sought to identify whether features can be reliably measured at all volumes or if a minimum volume threshold should be recommended. Methods: Eleven features were measured on 40 CT and 32 contrast-enhanced CT (CECT) patient images for this study. Features were selected for their prognostic/diagnostic value in previous publications. Direct correlations between these textures and volume were evaluated using the Spearman correlation coefficient. Any texture thatmore » the Wilcoxon rank-sum test was used to compare the variation above and below a volume cutoff. Four different volume thresholds (5, 10, 15, and 20 cm{sup 3}) were tested. Results: Four textures were found to be significantly correlated with volume in both the CT and CE-CT images. These were busyness, coarseness, gray-level nonuniformity, and run-length nonuniformity with correlation coefficients of 0.92, −0.96, 0.94, and 0.98 for the CT images and 0.95, −0.97, 0.98, and 0.98 for the CE-CT images. After volume normalization, the correlation coefficients decreased substantially. For the data obtained from the CT images, the results of the Wilcoxon rank-sum test were significant when volume thresholds of 5–15 cm3 were used. No volume threshold was shown to be significant for the CE-CT data. Conclusion: Equations for four features that have been used in several published studies were found to be volume-dependent. Future studies should consider implementing normalization factors or removing these features entirely to prevent this potential source of redundancy or bias. This work was supported in part by National Cancer Institute grant R03CA178495-01. Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« 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.

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

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

Kipritidis, J; Woodruff, H; Counter, W

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

Development and validation of an automated and marker-free CT-based spatial analysis method (CTSA) for assessment of femoral hip implant migration: In vitro accuracy and precision comparable to that of radiostereometric analysis (RSA).

PubMed

Scheerlinck, Thierry; Polfliet, Mathias; Deklerck, Rudi; Van Gompel, Gert; Buls, Nico; Vandemeulebroucke, Jef

2016-01-01

We developed a marker-free automated CT-based spatial analysis (CTSA) method to detect stem-bone migration in consecutive CT datasets and assessed the accuracy and precision in vitro. Our aim was to demonstrate that in vitro accuracy and precision of CTSA is comparable to that of radiostereometric analysis (RSA). Stem and bone were segmented in 2 CT datasets and both were registered pairwise. The resulting rigid transformations were compared and transferred to an anatomically sound coordinate system, taking the stem as reference. This resulted in 3 translation parameters and 3 rotation parameters describing the relative amount of stem-bone displacement, and it allowed calculation of the point of maximal stem migration. Accuracy was evaluated in 39 comparisons by imposing known stem migration on a stem-bone model. Precision was estimated in 20 comparisons based on a zero-migration model, and in 5 patients without stem loosening. Limits of the 95% tolerance intervals (TIs) for accuracy did not exceed 0.28 mm for translations and 0.20° for rotations (largest standard deviation of the signed error (SD(SE)): 0.081 mm and 0.057°). In vitro, limits of the 95% TI for precision in a clinically relevant setting (8 comparisons) were below 0.09 mm and 0.14° (largest SD(SE): 0.012 mm and 0.020°). In patients, the precision was lower, but acceptable, and dependent on CT scan resolution. CTSA allows detection of stem-bone migration with an accuracy and precision comparable to that of RSA. It could be valuable for evaluation of subtle stem loosening in clinical practice.

Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations.

PubMed

Noël, Peter B; Engels, Stephan; Köhler, Thomas; Muenzel, Daniela; Franz, Daniela; Rasper, Michael; Rummeny, Ernst J; Dobritz, Martin; Fingerle, Alexander A

2018-01-01

Background The explosive growth of computer tomography (CT) has led to a growing public health concern about patient and population radiation dose. A recently introduced technique for dose reduction, which can be combined with tube-current modulation, over-beam reduction, and organ-specific dose reduction, is iterative reconstruction (IR). Purpose To evaluate the quality, at different radiation dose levels, of three reconstruction algorithms for diagnostics of patients with proven liver metastases under tumor follow-up. Material and Methods A total of 40 thorax-abdomen-pelvis CT examinations acquired from 20 patients in a tumor follow-up were included. All patients were imaged using the standard-dose and a specific low-dose CT protocol. Reconstructed slices were generated by using three different reconstruction algorithms: a classical filtered back projection (FBP); a first-generation iterative noise-reduction algorithm (iDose4); and a next generation model-based IR algorithm (IMR). Results The overall detection of liver lesions tended to be higher with the IMR algorithm than with FBP or iDose4. The IMR dataset at standard dose yielded the highest overall detectability, while the low-dose FBP dataset showed the lowest detectability. For the low-dose protocols, a significantly improved detectability of the liver lesion can be reported compared to FBP or iDose 4 ( P = 0.01). The radiation dose decreased by an approximate factor of 5 between the standard-dose and the low-dose protocol. Conclusion The latest generation of IR algorithms significantly improved the diagnostic image quality and provided virtually noise-free images for ultra-low-dose CT imaging.

Agile convolutional neural network for pulmonary nodule classification using CT images.

PubMed

Zhao, Xinzhuo; Liu, Liyao; Qi, Shouliang; Teng, Yueyang; Li, Jianhua; Qian, Wei

2018-04-01

To distinguish benign from malignant pulmonary nodules using CT images is critical for their precise diagnosis and treatment. A new Agile convolutional neural network (CNN) framework is proposed to conquer the challenges of a small-scale medical image database and the small size of the nodules, and it improves the performance of pulmonary nodule classification using CT images. A hybrid CNN of LeNet and AlexNet is constructed through combining the layer settings of LeNet and the parameter settings of AlexNet. A dataset with 743 CT image nodule samples is built up based on the 1018 CT scans of LIDC to train and evaluate the Agile CNN model. Through adjusting the parameters of the kernel size, learning rate, and other factors, the effect of these parameters on the performance of the CNN model is investigated, and an optimized setting of the CNN is obtained finally. After finely optimizing the settings of the CNN, the estimation accuracy and the area under the curve can reach 0.822 and 0.877, respectively. The accuracy of the CNN is significantly dependent on the kernel size, learning rate, training batch size, dropout, and weight initializations. The best performance is achieved when the kernel size is set to [Formula: see text], the learning rate is 0.005, the batch size is 32, and dropout and Gaussian initialization are used. This competitive performance demonstrates that our proposed CNN framework and the optimization strategy of the CNN parameters are suitable for pulmonary nodule classification characterized by small medical datasets and small targets. The classification model might help diagnose and treat pulmonary nodules effectively.

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.

Automatic multi-label annotation of abdominal CT images using CBIR

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2017-03-01

We present a technique to annotate multiple organs shown in 2-D abdominal/pelvic CT images using CBIR. This annotation task is motivated by our research interests in visual question-answering (VQA). We aim to apply results from this effort in Open-iSM, a multimodal biomedical search engine developed by the National Library of Medicine (NLM). Understanding visual content of biomedical images is a necessary step for VQA. Though sufficient annotational information about an image may be available in related textual metadata, not all may be useful as descriptive tags, particularly for anatomy on the image. In this paper, we develop and evaluate a multi-label image annotation method using CBIR. We evaluate our method on two 2-D CT image datasets we generated from 3-D volumetric data obtained from a multi-organ segmentation challenge hosted in MICCAI 2015. Shape and spatial layout information is used to encode visual characteristics of the anatomy. We adapt a weighted voting scheme to assign multiple labels to the query image by combining the labels of the images identified as similar by the method. Key parameters that may affect the annotation performance, such as the number of images used in the label voting and the threshold for excluding labels that have low weights, are studied. The method proposes a coarse-to-fine retrieval strategy which integrates the classification with the nearest-neighbor search. Results from our evaluation (using the MICCAI CT image datasets as well as figures from Open-i) are presented.

Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks.

PubMed

Liu, Xiaoming; Guo, Shuxu; Yang, Bingtao; Ma, Shuzhi; Zhang, Huimao; Li, Jing; Sun, Changjian; Jin, Lanyi; Li, Xueyan; Yang, Qi; Fu, Yu

2018-04-20

Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help physicians distinguish diseases, an automatic organ segmentation framework is presented. The framework utilized convolution neural networks (CNN) to classify pixels. To reduce the redundant inputs, the simple linear iterative clustering (SLIC) of super-pixels and the support vector machine (SVM) classifier are introduced. To establish the perfect boundary of organs in one-pixel-level, the pixels need to be classified step-by-step. First, the SLIC is used to cut an image into grids and extract respective digital signatures. Next, the signature is classified by the SVM, and the rough edges are acquired. Finally, a precise boundary is obtained by the CNN, which is based on patches around each pixel-point. The framework is applied to abdominal CT scans of livers and high-resolution computed tomography (HRCT) scans of lungs. The experimental CT scans are derived from two public datasets (Sliver 07 and a Chinese local dataset). Experimental results show that the proposed method can precisely and efficiently detect the organs. This method consumes 38 s/slice for liver segmentation. The Dice coefficient of the liver segmentation results reaches to 97.43%. For lung segmentation, the Dice coefficient is 97.93%. This finding demonstrates that the proposed framework is a favorable method for lung segmentation of HRCT scans.

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.

The impact of computed tomography slice thickness on the assessment of stereotactic, 3D conformal and intensity-modulated radiotherapy of brain tumors.

PubMed

Caivano, R; Fiorentino, A; Pedicini, P; Califano, G; Fusco, V

2014-05-01

To evaluate radiotherapy treatment planning accuracy by varying computed tomography (CT) slice thickness and tumor size. CT datasets from patients with primary brain disease and metastatic brain disease were selected. Tumor volumes ranging from about 2.5 to 100 cc and CT scan at different slice thicknesses (1, 2, 4, 6 and 10 mm) were used to perform treatment planning (1-, 2-, 4-, 6- and 10-CT, respectively). For any slice thickness, a conformity index (CI) referring to 100, 98, 95 and 90 % isodoses and tumor size was computed. All the CI and volumes obtained were compared to evaluate the impact of CT slice thickness on treatment plans. The smallest volumes reduce significantly if defined on 1-CT with respect to 4- and 6-CT, while the CT slice thickness does not affect target definition for the largest volumes. The mean CI for all the considered isodoses and CT slice thickness shows no statistical differences when 1-CT is compared to 2-CT. Comparing the mean CI of 1- with 4-CT and 1- with 6-CT, statistical differences appear only for the smallest volumes with respect to 100, 98 and 95 % isodoses-the CI for 90 % isodose being not statistically significant for all the considered PTVs. The accuracy of radiotherapy tumor volume definition depends on CT slice thickness. To achieve a better tumor definition and dose coverage, 1- and 2-CT would be suitable for small targets, while 4- and 6-CT are suitable for the other volumes.

Dynamic CT imaging of volumetric changes in pulmonary nodules correlates with physical measurements of stiffness.

PubMed

Lartey, Frederick M; Rafat, Marjan; Negahdar, Mohammadreza; Malkovskiy, Andrey V; Dong, Xinzhe; Sun, Xiaoli; Li, Mei; Doyle, Timothy; Rajadas, Jayakumar; Graves, Edward E; Loo, Billy W; Maxim, Peter G

2017-02-01

A major challenge in CT screening for lung cancer is limited specificity when distinguishing between malignant and non-malignant pulmonary nodules (PN). Malignant nodules have different mechanical properties and tissue characteristics ('stiffness') from non-malignant nodules. This study seeks to improve CT specificity by demonstrating in rats that measurements of volumetric ratios in PNs with varying composition can be determined by respiratory-gated dynamic CT imaging and that these ratios correlate with direct physical measurements of PN stiffness. Respiratory-gated MicroCT images acquired at extreme tidal volumes of 9 rats with PNs from talc, matrigel and A549 human lung carcinoma were analyzed and their volumetric ratios (δ) derived. PN stiffness was determined by measuring the Young's modulus using atomic force microscopy (AFM) for each nodule excised immediately after MicroCT imaging. There was significant correlation (p=0.0002) between PN volumetric ratios determined by respiratory-gated CT imaging and the physical stiffness of the PNs determined from AFM measurements. We demonstrated proof of concept that PN volume changes measured non-invasively correlate with direct physical measurements of stiffness. These results may translate clinically into a means of improving the specificity of CT screening for lung cancer and/or improving individual prognostic assessments based on lung tumor stiffness. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study.

PubMed

Kalpathy-Cramer, Jayashree; Zhao, Binsheng; Goldgof, Dmitry; Gu, Yuhua; Wang, Xingwei; Yang, Hao; Tan, Yongqiang; Gillies, Robert; Napel, Sandy

2016-08-01

Tumor volume estimation, as well as accurate and reproducible borders segmentation in medical images, are important in the diagnosis, staging, and assessment of response to cancer therapy. The goal of this study was to demonstrate the feasibility of a multi-institutional effort to assess the repeatability and reproducibility of nodule borders and volume estimate bias of computerized segmentation algorithms in CT images of lung cancer, and to provide results from such a study. The dataset used for this evaluation consisted of 52 tumors in 41 CT volumes (40 patient datasets and 1 dataset containing scans of 12 phantom nodules of known volume) from five collections available in The Cancer Imaging Archive. Three academic institutions developing lung nodule segmentation algorithms submitted results for three repeat runs for each of the nodules. We compared the performance of lung nodule segmentation algorithms by assessing several measurements of spatial overlap and volume measurement. Nodule sizes varied from 29 μl to 66 ml and demonstrated a diversity of shapes. Agreement in spatial overlap of segmentations was significantly higher for multiple runs of the same algorithm than between segmentations generated by different algorithms (p < 0.05) and was significantly higher on the phantom dataset compared to the other datasets (p < 0.05). Algorithms differed significantly in the bias of the measured volumes of the phantom nodules (p < 0.05) underscoring the need for assessing performance on clinical data in addition to phantoms. Algorithms that most accurately estimated nodule volumes were not the most repeatable, emphasizing the need to evaluate both their accuracy and precision. There were considerable differences between algorithms, especially in a subset of heterogeneous nodules, underscoring the recommendation that the same software be used at all time points in longitudinal studies.

CT-derived indices of canine osteosarcoma-affected antebrachial strength.

PubMed

Garcia, Tanya C; Steffey, Michele A; Zwingenberger, Allison L; Daniel, Leticia; Stover, Susan M

2017-05-01

To improve the prediction of fractures in dogs with bone tumors of the distal radius by identifying computed tomography (CT) indices that correlate with antebrachial bone strength and fracture location. Prospective experimental study. Dogs with antebrachial osteosarcoma (n = 10), and normal cadaver bones (n=9). Antebrachia were imaged with quantitative CT prior to biomechanical testing to failure. CT indices of structural properties were compared to yield force and maximum force using Pearson correlation tests. Straight beam failure (Fs), axial rigidity, curved beam failure (Fc), and craniocaudal bending moment of inertia (MOICrCd) CT indices most highly correlated (0.77 > R > 0.57) with yield and maximum forces when iOSA-affected and control bones were included in the analysis. Considering only OSA-affected bones, Fs, Fc, and axial rigidity correlated highly (0.85 > R > 0.80) with maximum force. In affected bones, the location of minimum axial rigidity and maximum MOICrCd correlated highly (R > 0.85) with the actual fracture location. CT-derived axial rigidity, Fs, and MOICrCd have strong linear relationships with yield and maximum force. These indices should be further evaluated prospectively in OSA-affected dogs that do, and do not, experience pathologic fracture. © 2017 The American College of Veterinary Surgeons.

Three-dimensional evaluation of human jaw bone microarchitecture: correlation between the microarchitectural parameters of cone beam computed tomography and micro-computer tomography.

PubMed

Kim, Jo-Eun; Yi, Won-Jin; Heo, Min-Suk; Lee, Sam-Sun; Choi, Soon-Chul; Huh, Kyung-Hoe

2015-12-01

To evaluate the potential feasibility of cone beam computed tomography (CBCT) in the assessment of trabecular bone microarchitecture. Sixty-eight specimens from four pairs of human jaw were scanned using both micro-computed tomography (micro-CT) of 19.37-μm voxel size and CBCT of 100-μm voxel size. The correlation of 3-dimensional parameters between CBCT and micro-CT was evaluated. All parameters, except bone-specific surface and trabecular thickness, showed linear correlations between the 2 imaging modalities (P < .05). Among the parameters, bone volume, percent bone volume, trabecular separation, and degree of anisotropy (DA) of CBCT images showed strong correlations with those of micro-CT images. DA showed the strongest correlation (r = 0.693). Most microarchitectural parameters from CBCT were correlated with those from micro-CT. Some microarchitectural parameters, especially DA, could be used as strong predictors of bone quality in the human jaw. Copyright © 2015 Elsevier Inc. All rights reserved.

SU-E-J-33: Cardiac Movement in Deep Inspiration Breath-Hold for Left-Breast Cancer Radiotherapy

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

Kim, M; Lee, S; Suh, T

Purpose: The present study was designed to investigate the displacement of heart using Deep Inspiration Breath Hold (DIBH) CT data compared to free-breathing (FB) CT data and radiation exposure to heart. Methods: Treatment planning was performed on the computed tomography (CT) datasets of 20 patients who had received lumpectomy treatments. Heart, lung and both breasts were outlined. The prescribed dose was 50 Gy divided into 28 fractions. The dose distributions in all the plans were required to fulfill the International Commission on Radiation Units and Measurement specifications that include 100% coverage of the CTV with ≥ 95% of the prescribedmore » dose and that the volume inside the CTV receiving > 107% of the prescribed dose should be minimized. Displacement of heart was measured by calculating the distance between center of heart and left breast. For the evaluation of radiation dose to heart, minimum, maximum and mean dose to heart were calculated. Results: The maximum and minimum left-right (LR) displacements of heart were 8.9 mm and 3 mm, respectively. The heart moved > 4 mm in the LR direction in 17 of the 20 patients. The distances between the heart and left breast ranged from 8.02–17.68 mm (mean, 12.23 mm) and 7.85–12.98 mm (mean, 8.97 mm) with DIBH CT and FB CT, respectively. The maximum doses to the heart were 3115 cGy and 4652 cGy for the DIBH and FB CT dataset, respectively. Conclusion: The present study has demonstrated that the DIBH technique could help to reduce the risk of radiation dose-induced cardiac toxicity by using movement of cardiac; away from radiation field. The DIBH technique could be used in an actual treatment room for a few minutes and could effectively reduce the cardiac dose when used with a sub-device or image acquisition standard to maintain consistent respiratory motion.« less

Plain film measurement error in acute displaced midshaft clavicle fractures

PubMed Central

Archer, Lori Anne; Hunt, Stephen; Squire, Daniel; Moores, Carl; Stone, Craig; O’Dea, Frank; Furey, Andrew

2016-01-01

Background Clavicle fractures are common and optimal treatment remains controversial. Recent literature suggests operative fixation of acute displaced mid-shaft clavicle fractures (DMCFs) shortened more than 2 cm improves outcomes. We aimed to identify correlation between plain film and computed tomography (CT) measurement of displacement and the inter- and intraobserver reliability of repeated radiographic measurements. Methods We obtained radiographs and CT scans of patients with acute DMCFs. Three orthopedic staff and 3 residents measured radiographic displacement at time zero and 2 weeks later. The CT measurements identified absolute shortening in 3 dimensions (by subtracting the length of the fractured from the intact clavicle). We then compared shortening measured on radiographs and shortening measured in 3 dimensions on CT. Interobserver and intraobserver reliability were calculated. Results We reviewed the fractures of 22 patients. Bland–Altman repeatability coefficient calculations indicated that radiograph and CT measurements of shortening could not be correlated owing to an unacceptable amount of measurement error (6 cm). Interobserver reliability for plain radiograph measurements was excellent (Cronbach α = 0.90). Likewise, intraobserver reliabilities for plain radiograph measurements as calculated with paired t tests indicated excellent correlation (p > 0.05 in all but 1 observer [p = 0.04]). Conclusion To establish shortening as an indication for DMCF fixation, reliable measurement tools are required. The low correlation between plain film and CT measurements we observed suggests further research is necessary to establish what imaging modality reliably predicts shortening. Our results indicate weak correlation between radiograph and CT measurement of acute DMCF shortening. PMID:27438054

Separation of left and right lungs using 3D information of sequential CT images and a guided dynamic programming algorithm

PubMed Central

Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin

2011-01-01

Objective this article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on CT examinations. Methods we developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. Results the scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing dataset of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. Conclusions The proposed method is able to robustly and accurately disconnect all connections between left and right lungs and the guided dynamic programming algorithm is able to remove redundant processing. PMID:21412104

Multi-Mounted X-Ray Computed Tomography

PubMed Central

Fu, Jian; Liu, Zhenzhong; Wang, Jingzheng

2016-01-01

Most existing X-ray computed tomography (CT) techniques work in single-mounted mode and need to scan the inspected objects one by one. It is time-consuming and not acceptable for the inspection in a large scale. In this paper, we report a multi-mounted CT method and its first engineering implementation. It consists of a multi-mounted scanning geometry and the corresponding algebraic iterative reconstruction algorithm. This approach permits the CT rotation scanning of multiple objects simultaneously without the increase of penetration thickness and the signal crosstalk. Compared with the conventional single-mounted methods, it has the potential to improve the imaging efficiency and suppress the artifacts from the beam hardening and the scatter. This work comprises a numerical study of the method and its experimental verification using a dataset measured with a developed multi-mounted X-ray CT prototype system. We believe that this technique is of particular interest for pushing the engineering applications of X-ray CT. PMID:27073911

Geometry-constraint-scan imaging for in-line phase contrast micro-CT.

PubMed

Fu, Jian; Yu, Guangyuan; Fan, Dekai

2014-01-01

X-ray phase contrast computed tomography (CT) uses the phase shift that x-rays undergo when passing through matter, rather than their attenuation, as the imaging signal and may provide better image quality in soft-tissue and biomedical materials with low atomic number. Here a geometry-constraint-scan imaging technique for in-line phase contrast micro-CT is reported. It consists of two circular-trajectory scans with x-ray detector at different positions, the phase projection extraction method with the Fresnel free-propagation theory and the filter back-projection reconstruction algorithm. This method removes the contact-detector scan and the pure phase object assumption in classical in-line phase contrast Micro-CT. Consequently it relaxes the experimental conditions and improves the image contrast. This work comprises a numerical study of this technique and its experimental verification using a biomedical composite dataset measured at an x-ray tube source Micro-CT setup. The numerical and experimental results demonstrate the validity of the presented method. It will be of interest for a wide range of in-line phase contrast Micro-CT applications in biology and medicine.

Chest Computed Tomography (CT) Immediately after CT-Guided Transthoracic Needle Aspiration Biopsy as a Predictor of Overt Pneumothorax

PubMed Central

Noh, Tae June; Lee, Chang Hoon; Kang, Young Ae; Kwon, Sung-Youn; Yoon, Ho-Il; Kim, Tae Jung; Lee, Kyung Won; Lee, Jae Ho

2009-01-01

Background/Aims This study examined the correlation between pneumothorax detected by immediate post-transthoracic needle aspiration-biopsy (TTNB) chest computed tomography (CT) and overt pneumothorax detected by chest PA, and investigated factors that might influence the correlation. Methods Adult patients who had undergone CT-guided TTNB for lung lesions from May 2003 to June 2007 at Seoul National University Bundang Hospital were included. Immediate post-TTNB CT and chest PA follow-up at 4 and 16 hours after CT-guided TTNB were performed in 934 patients. Results Pneumothorax detected by immediate chest CT (CT-pneumothorax) was found in 237 (25%) and overt pneumothorax was detected by chest PA follow-up in 92 (38.8%) of the 237 patients. However, overt pneumothorax was found in 18 (2.6%) of the 697 patients without CT-pneumothorax. The width and depth of CT-pneumothorax were predictive risk factors for overt pneumothorax. Conclusions CT-pneumothorax is very sensitive for predicting overt pneumothorax, and the width and depth on CT-pneumothorax are reliable risk factors for predicting overt pneumothorax. PMID:19949733

Patient-specific quantification of image quality: An automated method for measuring spatial resolution in clinical CT images

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

Sanders, Jeremiah, E-mail: jeremiah.sanders@duke.e

Purpose: To develop and validate an automated technique for evaluating the spatial resolution characteristics of clinical computed tomography (CT) images. Methods: Twenty one chest and abdominopelvic clinical CT datasets were examined in this study. An algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge-spread function (ESF) across the patient’s skin. A polygon mesh of the air-skin boundary was created. The faces of the mesh were then used to measure the ESF across the air-skin interface. The ESF was differentiated to obtain the line-spread function (LSF),more » and the LSF was Fourier transformed to obtain the RI. The algorithm’s ability to detect the radial dependence of the RI was investigated. RIs measured with the proposed method were compared with a conventional phantom-based method across two reconstruction algorithms (FBP and iterative) using the spatial frequency at 50% RI, f{sub 50}, as the metric for comparison. Three reconstruction kernels were investigated for each reconstruction algorithm. Finally, an observer study was conducted to determine if observers could visually perceive the differences in the measured blurriness of images reconstructed with a given reconstruction method. Results: RI measurements performed with the proposed technique exhibited the expected dependencies on the image reconstruction. The measured f{sub 50} values increased with harder kernels for both FBP and iterative reconstruction. Furthermore, the proposed algorithm was able to detect the radial dependence of the RI. Patient-specific measurements of the RI were comparable to the phantom-based technique, but the patient data exhibited a large spread in the measured f{sub 50}, indicating that some datasets were blurrier than others even when the projection data were reconstructed with the same reconstruction algorithm and kernel. Results from the observer study substantiated this finding. Conclusions: Clinically informed, patient-specific spatial resolution can be measured from clinical datasets. The method is sufficiently sensitive to reflect changes in spatial resolution due to different reconstruction parameters. The method can be applied to automatically assess the spatial resolution of patient images and quantify dependencies that may not be captured in phantom data.« less

Calculating Effective Elastic Properties of Berea Sandstone Using Segmentation-less Method without Targets

NASA Astrophysics Data System (ADS)

Ikeda, K.; Goldfarb, E. J.; Tisato, N.

2017-12-01

Digital rock physics (DRP) allows performing common laboratory experiments on numerical models to estimate, for example, rock hydraulic permeability. The standard procedure of DRP involves turning a rock sample into a numerical array using X-ray micro computed tomography (micro-CT). Each element of the array bears a value proportional to the X-ray attenuation of the rock at the element (voxel). However, the traditional DRP methodology, which includes segmentation, over-predicts rock moduli by significant amounts (e.g., 100%). Recently, a new methodology - the segmentation-less approach - has been proposed leading to more accurate DRP estimate of elastic moduli. This new method is based on homogenization theory. Typically, segmentation-less approach requires calibration points from known density objects, known as targets. Not all micro-CT datasets have these reference points. Here, we describe how we perform segmentation- and target-less DRP to estimate elastic properties of rocks (i.e., elastic moduli), which are crucial parameters to perform subsurface modeling. We calculate the elastic properties of a Berea sandstone sample that was scanned at a resolution of 40 microns per voxel. We transformed the CT images into density matrices using polynomial fitting curve with four calibration points: the whole rock, the center of quartz grains, the center of iron oxide grains, and the center of air-filled volumes. The first calibration point is obtained by assigning the density of the whole rock to the average of all CT-numbers in the dataset. Then, we locate the center of each phase by finding local extrema point in the dataset. The average CT-numbers of these center points are assigned the density equal to either pristine minerals (quartz and iron oxide) or air. Next, density matrices are transformed to porosity and moduli matrices by means of an effective medium theory. Finally, effective static bulk and shear modulus are numerically calculated by using a Matlab code derived from the elas3D NIST code. The calculated quasi-static P- and S-wave speed overestimates the laboratory result by 37% and 5%, respectively. In fact, our approach predicts wave speeds more accurately than traditional DRP methods. Nevertheless, the presented methodology need to be further investigated and improved.

SPECT/CT tracer uptake is influenced by tunnel orientation and position of the femoral and tibial ACL graft insertion site.

PubMed

Hirschmann, Michael T; Mathis, Dominic; Rasch, Helmut; Amsler, Felix; Friederich, Niklaus F; Arnold, Markus P

2013-02-01

SPECT/CT is a hybrid imaging modality, which combines a 3D scintigraphy (SPECT) and a conventional computerised tomography (CT). SPECT/CT allows accurate anatomical localisation of metabolic tracer activity. It allows the correlation of surgical factors such as tunnel position and orientation with mechanical alignment, clinical outcome and biological factors. The purpose of this study was to investigate whether the SPECT/CT tracer uptake (intensity and distribution) correlates with the stability and laxity of the knee joint and the position and orientation of the tibial and femoral tunnels in patients after anterior cruciate ligament (ACL) reconstruction. A consecutive series of knees (n=66), with symptoms of pain and/or instability after ACL reconstruction were prospectively evaluated using clinical examination and 99mTc-HDP-SPECT/CT. Clinical laxity testing was performed using the Rolimeter (Ormed, Freiburg, Germany) including Lachman testing (0-2 mm, 3-5 mm, 6-10 mm, >10 mm), anterior drawer test (0-2 mm, 3-5 mm, 6-10 mm, >10 mm), pivot shift test (positive versus negative) and patient-based subjective instability (yes versus no). For analysis of SPECT/CT tracer uptake a previously validated SPECT/CT localisation scheme consisting of 17 tibial, nine femoral and four patellar regions on standardised axial, coronal, and sagittal slices was used. The tracer activity on SPECT/CT was localised and recorded using a 3D volumetric and quantitative analysis software. Mean, standard deviation, minimum and maximum of grading for each area of the localisation scheme were recorded. The position and orientation of the tibial and femoral tunnel was assessed using a previously published method on 3D-CT. Correlation of instability, pivot shift as well as clinical laxity testing with 99mTc-HDP-SPECT/CT tracer uptake intensity and distribution showed no significant correlation. 99mTc-HDP-SPECT/CT tracer uptake correlated significantly with the position and orientation of the ACL graft. A more horizontal femoral graft position showed significantly increased tracer uptake within the superior and posterior femoral regions. A more posteriorly-placed femoral insertion site showed significantly more tracer uptake within the femoral and tibial tunnel regions. A more vertical or a less medial tibial tunnel orientation showed significant increased uptake within the tibial and femoral tunnel regions. A more anterior tibial tunnel position showed significantly more tracer uptake in the femoral and tibial tunnel regions as well as the entire tibiofemoral joint. SPECT/CT tracer uptake intensity and distribution showed a significant correlation with the femoral and tibial tunnel position and orientation in patients with symptomatic knees after ACL reconstruction. No correlation was found with stability or clinical laxity. SPECT/CT tracer uptake distribution has the potential to give us important information on joint homeostasis and remodelling after ACL reconstruction. It might help to predict ACL graft failure and improve our surgical ACL reconstruction technique in finding the optimal tunnel and graft position and orientation.

Automated anatomical labeling of bronchial branches using multiple classifiers and its application to bronchoscopy guidance based on fusion of virtual and real bronchoscopy

NASA Astrophysics Data System (ADS)

Ota, Shunsuke; Deguchi, Daisuke; Kitasaka, Takayuki; Mori, Kensaku; Suenaga, Yasuhito; Hasegawa, Yoshinori; Imaizumi, Kazuyoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi

2008-03-01

This paper presents a method for automated anatomical labeling of bronchial branches (ALBB) extracted from 3D CT datasets. The proposed method constructs classifiers that output anatomical names of bronchial branches by employing the machine-learning approach. We also present its application to a bronchoscopy guidance system. Since the bronchus has a complex tree structure, bronchoscopists easily tend to get disoriented and lose the way to a target location. A bronchoscopy guidance system is strongly expected to be developed to assist bronchoscopists. In such guidance system, automated presentation of anatomical names is quite useful information for bronchoscopy. Although several methods for automated ALBB were reported, most of them constructed models taking only variations of branching patterns into account and did not consider those of running directions. Since the running directions of bronchial branches differ greatly in individuals, they could not perform ALBB accurately when running directions of bronchial branches were different from those of models. Our method tries to solve such problems by utilizing the machine-learning approach. Actual procedure consists of three steps: (a) extraction of bronchial tree structures from 3D CT datasets, (b) construction of classifiers using the multi-class AdaBoost technique, and (c) automated classification of bronchial branches by using the constructed classifiers. We applied the proposed method to 51 cases of 3D CT datasets. The constructed classifiers were evaluated by leave-one-out scheme. The experimental results showed that the proposed method could assign correct anatomical names to bronchial branches of 89.1% up to segmental lobe branches. Also, we confirmed that it was quite useful to assist the bronchoscopy by presenting anatomical names of bronchial branches on real bronchoscopic views.

Effect of a Noise-Optimized Second-Generation Monoenergetic Algorithm on Image Noise and Conspicuity of Hypervascular Liver Tumors: An In Vitro and In Vivo Study.

PubMed

Marin, Daniele; Ramirez-Giraldo, Juan Carlos; Gupta, Sonia; Fu, Wanyi; Stinnett, Sandra S; Mileto, Achille; Bellini, Davide; Patel, Bhavik; Samei, Ehsan; Nelson, Rendon C

2016-06-01

The purpose of this study is to investigate whether the reduction in noise using a second-generation monoenergetic algorithm can improve the conspicuity of hypervascular liver tumors on dual-energy CT (DECT) images of the liver. An anthropomorphic liver phantom in three body sizes and iodine-containing inserts simulating hypervascular lesions was imaged with DECT and single-energy CT at various energy levels (80-140 kV). In addition, a retrospective clinical study was performed in 31 patients with 66 hypervascular liver tumors who underwent DECT during the late hepatic arterial phase. Datasets at energy levels ranging from 40 to 80 keV were reconstructed using first- and second-generation monoenergetic algorithms. Noise, tumor-to-liver contrast-to-noise ratio (CNR), and CNR with a noise constraint (CNRNC) set with a maximum noise increase of 50% were calculated and compared among the different reconstructed datasets. The maximum CNR for the second-generation monoenergetic algorithm, which was attained at 40 keV in both phantom and clinical datasets, was statistically significantly higher than the maximum CNR for the first-generation monoenergetic algorithm (p < 0.001) or single-energy CT acquisitions across a wide range of kilovoltage values. With the second-generation monoenergetic algorithm, the optimal CNRNC occurred at 55 keV, corresponding to lower energy levels compared with first-generation algorithm (predominantly at 70 keV). Patient body size did not substantially affect the selection of the optimal energy level to attain maximal CNR and CNRNC using the second-generation monoenergetic algorithm. A noise-optimized second-generation monoenergetic algorithm significantly improves the conspicuity of hypervascular liver tumors.

Evaluation of deformable image registration and a motion model in CT images with limited features.

PubMed

Liu, F; Hu, Y; Zhang, Q; Kincaid, R; Goodman, K A; Mageras, G S

2012-05-07

Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.

Automated Bone Segmentation and Surface Evaluation of a Small Animal Model of Post-Traumatic Osteoarthritis.

PubMed

Ramme, Austin J; Voss, Kevin; Lesporis, Jurinus; Lendhey, Matin S; Coughlin, Thomas R; Strauss, Eric J; Kennedy, Oran D

2017-05-01

MicroCT imaging allows for noninvasive microstructural evaluation of mineralized bone tissue, and is essential in studies of small animal models of bone and joint diseases. Automatic segmentation and evaluation of articular surfaces is challenging. Here, we present a novel method to create knee joint surface models, for the evaluation of PTOA-related joint changes in the rat using an atlas-based diffeomorphic registration to automatically isolate bone from surrounding tissues. As validation, two independent raters manually segment datasets and the resulting segmentations were compared to our novel automatic segmentation process. Data were evaluated using label map volumes, overlap metrics, Euclidean distance mapping, and a time trial. Intraclass correlation coefficients were calculated to compare methods, and were greater than 0.90. Total overlap, union overlap, and mean overlap were calculated to compare the automatic and manual methods and ranged from 0.85 to 0.99. A Euclidean distance comparison was also performed and showed no measurable difference between manual and automatic segmentations. Furthermore, our new method was 18 times faster than manual segmentation. Overall, this study describes a reliable, accurate, and automatic segmentation method for mineralized knee structures from microCT images, and will allow for efficient assessment of bony changes in small animal models of PTOA.

Airways, vasculature, and interstitial tissue: anatomically informed computational modeling of human lungs for virtual clinical trials

NASA Astrophysics Data System (ADS)

Abadi, Ehsan; Sturgeon, Gregory M.; Agasthya, Greeshma; Harrawood, Brian; Hoeschen, Christoph; Kapadia, Anuj; Segars, W. P.; Samei, Ehsan

2017-03-01

This study aimed to model virtual human lung phantoms including both non-parenchymal and parenchymal structures. Initial branches of the non-parenchymal structures (airways, arteries, and veins) were segmented from anatomical data in each lobe separately. A volume-filling branching algorithm was utilized to grow the higher generations of the airways and vessels to the level of terminal branches. The diameters of the airways and vessels were estimated using established relationships between flow rates and diameters. The parenchyma was modeled based on secondary pulmonary lobule units. Polyhedral shapes with variable sizes were modeled, and the borders were assigned to interlobular septa. A heterogeneous background was added inside these units using a non-parametric texture synthesis algorithm which was informed by a high-resolution CT lung specimen dataset. A voxelized based CT simulator was developed to create synthetic helical CT images of the phantom with different pitch values. Results showed the progressive degradation in depiction of lung details with increased pitch. Overall, the enhanced lung models combined with the XCAT phantoms prove to provide a powerful toolset to perform virtual clinical trials in the context of thoracic imaging. Such trials, not practical using clinical datasets or simplistic phantoms, can quantitatively evaluate and optimize advanced imaging techniques towards patient-based care.

Local ROI Reconstruction via Generalized FBP and BPF Algorithms along More Flexible Curves.

PubMed

Yu, Hengyong; Ye, Yangbo; Zhao, Shiying; Wang, Ge

2006-01-01

We study the local region-of-interest (ROI) reconstruction problem, also referred to as the local CT problem. Our scheme includes two steps: (a) the local truncated normal-dose projections are extended to global dataset by combining a few global low-dose projections; (b) the ROI are reconstructed by either the generalized filtered backprojection (FBP) or backprojection-filtration (BPF) algorithms. The simulation results show that both the FBP and BPF algorithms can reconstruct satisfactory results with image quality in the ROI comparable to that of the corresponding global CT reconstruction.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A collection of non-human primate computed tomography scans housed in MorphoSource, a repository for 3D data

PubMed Central

Copes, Lynn E.; Lucas, Lynn M.; Thostenson, James O.; Hoekstra, Hopi E.; Boyer, Doug M.

2016-01-01

A dataset of high-resolution microCT scans of primate skulls (crania and mandibles) and certain postcranial elements was collected to address questions about primate skull morphology. The sample consists of 489 scans taken from 431 specimens, representing 59 species of most Primate families. These data have transformative reuse potential as such datasets are necessary for conducting high power research into primate evolution, but require significant time and funding to collect. Similar datasets were previously only available to select research groups across the world. The physical specimens are vouchered at Harvard’s Museum of Comparative Zoology. The data collection took place at the Center for Nanoscale Systems at Harvard. The dataset is archived on MorphoSource.org. Though this is the largest high fidelity comparative dataset yet available, its provisioning on a web archive that allows unlimited researcher contributions promises a future with vastly increased digital collections available at researchers’ finger tips. PMID:26836025

One-stop shop assessment for atrial septal defect closure using 256-slice coronary CT angiography.

PubMed

Yamasaki, Yuzo; Nagao, Michinobu; Kawanami, Satoshi; Kamitani, Takeshi; Sagiyama, Koji; Yamanouchi, Torahiko; Sakamoto, Ichiro; Yamamura, Kenichiro; Yabuuchi, Hidetake; Honda, Hiroshi

2017-02-01

To investigate the feasibility and accuracy of measurement of the pulmonary to systemic blood flow ratio (Qp/Qs) and defect and rim sizes in secundum atrial septal defects (ASDs) using 256-slice CT, compared to the reference transoesophageal echocardiography (TEE) and right heart catheterization (RHC) measurements. Twenty-three consecutive adult patients with secundum ASDs who underwent retrospective ECG-gated coronary CT angiography (CCTA), TEE and RHC were enrolled in this study. Right ventricular (RV) and left ventricular (LV) stroke volumes (SV) were calculated by biventricular volumetry of CCTA. Qp/Qs-CT was defined as RVSV/LVSV. The sizes of the defect and rim were measured by multi-planar reconstruction CT images. Correlations between Qp/Qs-CT and Qp/Qs-RHC and between the defect diameter obtained by CT and TEE were analyzed by Pearson's coefficient analysis. Rim sizes by CT and TEE were compared by paired t-test. Qp/Qs-CT was significantly correlated with Qp/Qs-RHC (r = 0.83, p < 0.0001), and the defect diameter by CT was significantly correlated with that by TEE (r = 0.95, p < 0.0001). There was no significant difference between CT and TEE in measurements of rim size. 256-slice CCTA allows measuring Qp/Qs and size of defects and rims in patients with secundum ASDs, accomplishing pretreatment evaluation non-invasively and comprehensively. • Quantification of left-to-right shunting can be performed reliably and accurately by CT. • The sizes of defects and rims can be measured accurately using 256-slice CT. • 256-slice CT permits pretreatment evaluation of ASD non-invasively and comprehensively.

Improved correlation between CT emphysema quantification and pulmonary function test by density correction of volumetric CT data based on air and aortic density.

PubMed

Kim, Song Soo; Seo, Joon Beom; Kim, Namkug; Chae, Eun Jin; Lee, Young Kyung; Oh, Yeon Mok; Lee, Sang Do

2014-01-01

To determine the improvement of emphysema quantification with density correction and to determine the optimal site to use for air density correction on volumetric computed tomography (CT). Seventy-eight CT scans of COPD patients (GOLD II-IV, smoking history 39.2±25.3 pack-years) were obtained from several single-vendor 16-MDCT scanners. After density measurement of aorta, tracheal- and external air, volumetric CT density correction was conducted (two reference values: air, -1,000 HU/blood, +50 HU). Using in-house software, emphysema index (EI) and mean lung density (MLD) were calculated. Differences in air densities, MLD and EI prior to and after density correction were evaluated (paired t-test). Correlation between those parameters and FEV1 and FEV1/FVC were compared (age- and sex adjusted partial correlation analysis). Measured densities (HU) of tracheal- and external air differed significantly (-990 ± 14, -1016 ± 9, P<0.001). MLD and EI on original CT data, after density correction using tracheal- and external air also differed significantly (MLD: -874.9 ± 27.6 vs. -882.3 ± 24.9 vs. -860.5 ± 26.6; EI: 16.8 ± 13.4 vs. 21.1 ± 14.5 vs. 9.7 ± 10.5, respectively, P<0.001). The correlation coefficients between CT quantification indices and FEV1, and FEV1/FVC increased after density correction. The tracheal air correction showed better results than the external air correction. Density correction of volumetric CT data can improve correlations of emphysema quantification and PFT. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Automated Radiology-Pathology Module Correlation Using a Novel Report Matching Algorithm by Organ System.

PubMed

Dane, Bari; Doshi, Ankur; Gfytopoulos, Soterios; Bhattacharji, Priya; Recht, Michael; Moore, William

2018-05-01

Radiology-pathology correlation is time-consuming and is not feasible in most clinical settings, with the notable exception of breast imaging. The purpose of this study was to determine if an automated radiology-pathology report pairing system could accurately match radiology and pathology reports, thus creating a feedback loop allowing for more frequent and timely radiology-pathology correlation. An experienced radiologist created a matching matrix of radiology and pathology reports. These matching rules were then exported to a novel comprehensive radiology-pathology module. All distinct radiology-pathology pairings at our institution from January 1, 2016 to July 1, 2016 were included (n = 8999). The appropriateness of each radiology-pathology report pairing was scored as either "correlative" or "non-correlative." Pathology reports relating to anatomy imaged in the specific imaging study were deemed correlative, whereas pathology reports describing anatomy not imaged with the particular study were denoted non-correlative. Overall, there was 88.3% correlation (accuracy) of the radiology and pathology reports (n = 8999). Subset analysis demonstrated that computed tomography (CT) abdomen/pelvis, CT head/neck/face, CT chest, musculoskeletal CT (excluding spine), mammography, magnetic resonance imaging (MRI) abdomen/pelvis, MRI brain, musculoskeletal MRI (excluding spine), breast MRI, positron emission tomography (PET), breast ultrasound, and head/neck ultrasound all demonstrated greater than 91% correlation. When further stratified by imaging modality, CT, MRI, mammography, and PET demonstrated excellent correlation (greater than 96.3%). Ultrasound and non-PET nuclear medicine studies demonstrated poorer correlation (80%). There is excellent correlation of radiology imaging reports and appropriate pathology reports when matched by organ system. Rapid, appropriate radiology-pathology report pairings provide an excellent opportunity to close feedback loop to the interpreting radiologist. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Diffraction-Enhanced Computed Tomographic Imaging of Growing Piglet Joints by Using a Synchrotron Light Source

PubMed Central

Rhoades, Glendon W; Belev, George S; Chapman, L Dean; Wiebe, Sheldon P; Cooper, David M; Wong, Adelaine TF; Rosenberg, Alan M

2015-01-01

The objective of this project was to develop and test a new technology for imaging growing joints by means of diffraction-enhanced imaging (DEI) combined with CT and using a synchrotron radiation source. DEI–CT images of an explanted 4-wk-old piglet stifle joint were acquired by using a 40-keV beam. The series of scanned slices was later ‘stitched’ together, forming a 3D dataset. High-resolution DEI-CT images demonstrated fine detail within all joint structures and tissues. Striking detail of vasculature traversing between bone and cartilage, a characteristic of growing but not mature joints, was demonstrated. This report documents for the first time that DEI combined with CT and a synchrotron radiation source can generate more detailed images of intact, growing joints than can currently available conventional imaging modalities. PMID:26310464

Deep learning for biomarker regression: application to osteoporosis and emphysema on chest CT scans

NASA Astrophysics Data System (ADS)

González, Germán.; Washko, George R.; San José Estépar, Raúl

2018-03-01

Introduction: Biomarker computation using deep-learning often relies on a two-step process, where the deep learning algorithm segments the region of interest and then the biomarker is measured. We propose an alternative paradigm, where the biomarker is estimated directly using a regression network. We showcase this image-tobiomarker paradigm using two biomarkers: the estimation of bone mineral density (BMD) and the estimation of lung percentage of emphysema from CT scans. Materials and methods: We use a large database of 9,925 CT scans to train, validate and test the network for which reference standard BMD and percentage emphysema have been already computed. First, the 3D dataset is reduced to a set of canonical 2D slices where the organ of interest is visible (either spine for BMD or lungs for emphysema). This data reduction is performed using an automatic object detector. Second, The regression neural network is composed of three convolutional layers, followed by a fully connected and an output layer. The network is optimized using a momentum optimizer with an exponential decay rate, using the root mean squared error as cost function. Results: The Pearson correlation coefficients obtained against the reference standards are r = 0.940 (p < 0.00001) and r = 0.976 (p < 0.00001) for BMD and percentage emphysema respectively. Conclusions: The deep-learning regression architecture can learn biomarkers from images directly, without indicating the structures of interest. This approach simplifies the development of biomarker extraction algorithms. The proposed data reduction based on object detectors conveys enough information to compute the biomarkers of interest.

Automation process for morphometric analysis of volumetric CT data from pulmonary vasculature in rats.

PubMed

Shingrani, Rahul; Krenz, Gary; Molthen, Robert

2010-01-01

With advances in medical imaging scanners, it has become commonplace to generate large multidimensional datasets. These datasets require tools for a rapid, thorough analysis. To address this need, we have developed an automated algorithm for morphometric analysis incorporating A Visualization Workshop computational and image processing libraries for three-dimensional segmentation, vascular tree generation and structural hierarchical ordering with a two-stage numeric optimization procedure for estimating vessel diameters. We combine this new technique with our mathematical models of pulmonary vascular morphology to quantify structural and functional attributes of lung arterial trees. Our physiological studies require repeated measurements of vascular structure to determine differences in vessel biomechanical properties between animal models of pulmonary disease. Automation provides many advantages including significantly improved speed and minimized operator interaction and biasing. The results are validated by comparison with previously published rat pulmonary arterial micro-CT data analysis techniques, in which vessels were manually mapped and measured using intense operator intervention. Published by Elsevier Ireland Ltd.

Proton Range Uncertainty Due to Bone Cement Injected Into the Vertebra in Radiation Therapy Planning

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

Lim, Young Kyung; Hwang, Ui-Jung; Shin, Dongho, E-mail: dongho@ncc.re.kr

2011-10-01

We wanted to evaluate the influence of bone cement on the proton range and to derive a conversion factor predicting the range shift by correcting distorted computed tomography (CT) data as a reference to determine whether the correction is needed. Two CT datasets were obtained with and without a bone cement disk placed in a water phantom. Treatment planning was performed on a set of uncorrected CT images with the bone cement disk, and the verification plan was applied to the same set of CT images with an effective CT number for the bone cement disk. The effective CT numbermore » was determined by measuring the actual proton range with the bone cement disk. The effects of CT number, thicknesses, and position of bone cement on the proton range were evaluated in the treatment planning system (TPS) to draw a conversion factor predicting the range shift by correcting the CT number of bone cement. The effective CT number of bone cement was 260 Hounsfield units (HU). The calculated proton range for native CT data was significantly shorter than the measured proton range. However, the calculated range for the corrected CT data with the effective CT number coincided exactly with the measured range. The conversion factor was 209.6 [HU . cm/mm] for bone cement and predicted the range shift by approximately correcting the CT number. We found that the heterogeneity of bone cement could cause incorrect proton ranges in treatment plans using CT images. With an effective CT number of bone cement derived from the proton range and relative stopping power, a more actual proton range could be calculated in the TPS. The conversion factor could predict the necessity for CT data correction with sufficient accuracy.« less

Role of Combined 68Ga-DOTATOC and 18F-FDG Positron Emission Tomography/Computed Tomography in the Diagnostic Workup of Pancreas Neuroendocrine Tumors: Implications for Managing Surgical Decisions.

PubMed

Cingarlini, Sara; Ortolani, Silvia; Salgarello, Matteo; Butturini, Giovanni; Malpaga, Anna; Malfatti, Veronica; DʼOnofrio, Mirko; Davì, Maria Vittoria; Vallerio, Paola; Ruzzenente, Andrea; Capelli, Paola; Citton, Elia; Grego, Elisabetta; Trentin, Chiara; De Robertis, Riccardo; Scarpa, Aldo; Bassi, Claudio; Tortora, Giampaolo

2017-01-01

Ga-DOTATOC (Ga) positron emission tomography (PET)/computed tomography (CT) is recommended in the workup of pancreas neuroendocrine tumors (PanNETs); evidence suggests that F-FDG (F) PET/CT can also provide prognostic information. Aims of this study were to assess the role of combined Ga- and F-PET/CT in the evaluation of grade (G) 1-2 PanNETs and to test the correlation between F-PET/CT positivity and tumor grade. Preoperative Ga- and F-PET/CT of 35 patients with surgically resected G1-2 PanNETs were evaluated. For grading, the 2010 World Health Organization Classification was used; an ancillary analysis with Ki67 cutoffs at 5% to 20% was conducted. Correlation between F-PET/CT positivity (SUVmax > 3.5) and grade was assessed. Of 35 PanNETs, 28.6% and 71.4% were G1 and G2 as per World Health Organization. Ga-PET/CT showed high sensitivity (94.3%) in detecting G1-2 PanNETs. F-PET/CT was positive in 20% and 76% G1 and G2 tumors (P = 0.002). F-PET/CT identified G2 PanNETs with high positive predictive value (PPV, 90.5%). F-PET/CT correlated with tumor grade also in the ancillary analysis (P = 0.009). The high sensitivity of Ga-PET/CT in NET detection is known. The high PPV of F-PET/CT in the identification of G2 forms suggests its potential role in PanNETs prognostication and risk stratification.

4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines.

PubMed

Min, Yugang; Neylon, John; Shah, Amish; Meeks, Sanford; Lee, Percy; Kupelian, Patrick; Santhanam, Anand P

2014-09-01

The accuracy of 4D-CT registration is limited by inconsistent Hounsfield unit (HU) values in the 4D-CT data from one respiratory phase to another and lower image contrast for lung substructures. This paper presents an optical flow and thin-plate spline (TPS)-based 4D-CT registration method to account for these limitations. The use of unified HU values on multiple anatomy levels (e.g., the lung contour, blood vessels, and parenchyma) accounts for registration errors by inconsistent landmark HU value. While 3D multi-resolution optical flow analysis registers each anatomical level, TPS is employed for propagating the results from one anatomical level to another ultimately leading to the 4D-CT registration. 4D-CT registration was validated using target registration error (TRE), inverse consistency error (ICE) metrics, and a statistical image comparison using Gamma criteria of 1 % intensity difference in 2 mm(3) window range. Validation results showed that the proposed method was able to register CT lung datasets with TRE and ICE values <3 mm. In addition, the average number of voxel that failed the Gamma criteria was <3 %, which supports the clinical applicability of the propose registration mechanism. The proposed 4D-CT registration computes the volumetric lung deformations within clinically viable accuracy.

Genetic parameters of infectious bovine keratoconjunctivitis and its relationship with weight and parasite infestations in Australian tropical Bos taurus cattle.

PubMed

Ali, Abdirahman A; O'Neill, Christopher J; Thomson, Peter C; Kadarmideen, Haja N

2012-07-27

Infectious bovine keratoconjunctivitis (IBK) or 'pinkeye' is an economically important ocular disease that significantly impacts animal performance. Genetic parameters for IBK infection and its genetic and phenotypic correlations with cattle tick counts, number of helminth (unspecified species) eggs per gram of faeces and growth traits in Australian tropically adapted Bos taurus cattle were estimated. Animals were clinically examined for the presence of IBK infection before and after weaning when the calves were 3 to 6 months and 15 to 18 months old, respectively and were also recorded for tick counts, helminth eggs counts as an indicator of intestinal parasites and live weights at several ages including 18 months. Negative genetic correlations were estimated between IBK incidence and weight traits for animals in pre-weaning and post-weaning datasets. Genetic correlations among weight measurements were positive, with moderate to high values. Genetic correlations of IBK incidence with tick counts were positive for the pre-weaning and negative for the post-weaning datasets but negative with helminth eggs counts for the pre-weaning dataset and slightly positive for the post-weaning dataset. Genetic correlations between tick and helminth eggs counts were moderate and positive for both datasets. Phenotypic correlations of IBK incidence with helminth eggs per gram of faeces were moderate and positive for both datasets, but were close to zero for both datasets with tick counts. Our results suggest that genetic selection against IBK incidence in tropical cattle is feasible and that calves genetically prone to acquire IBK infection could also be genetically prone to have a slower growth. The positive genetic correlations among weight traits and between tick and helminth eggs counts suggest that they are controlled by common genes (with pleiotropic effects). Genetic correlations between IBK incidence and tick and helminth egg counts were moderate and opposite between pre-weaning and post-weaning datasets, suggesting that the environmental and (or) maternal effects differ between these two growth phases. This preliminary study provides estimated genetic parameters for IBK incidence, which could be used to design selection and breeding programs for tropical adaptation in beef cattle.

Genetic parameters of infectious bovine keratoconjunctivitis and its relationship with weight and parasite infestations in Australian tropical Bos taurus cattle

PubMed Central

2012-01-01

Background Infectious bovine keratoconjunctivitis (IBK) or ‘pinkeye’ is an economically important ocular disease that significantly impacts animal performance. Genetic parameters for IBK infection and its genetic and phenotypic correlations with cattle tick counts, number of helminth (unspecified species) eggs per gram of faeces and growth traits in Australian tropically adapted Bos taurus cattle were estimated. Methods Animals were clinically examined for the presence of IBK infection before and after weaning when the calves were 3 to 6 months and 15 to 18 months old, respectively and were also recorded for tick counts, helminth eggs counts as an indicator of intestinal parasites and live weights at several ages including 18 months. Results Negative genetic correlations were estimated between IBK incidence and weight traits for animals in pre-weaning and post-weaning datasets. Genetic correlations among weight measurements were positive, with moderate to high values. Genetic correlations of IBK incidence with tick counts were positive for the pre-weaning and negative for the post-weaning datasets but negative with helminth eggs counts for the pre-weaning dataset and slightly positive for the post-weaning dataset. Genetic correlations between tick and helminth eggs counts were moderate and positive for both datasets. Phenotypic correlations of IBK incidence with helminth eggs per gram of faeces were moderate and positive for both datasets, but were close to zero for both datasets with tick counts. Conclusions Our results suggest that genetic selection against IBK incidence in tropical cattle is feasible and that calves genetically prone to acquire IBK infection could also be genetically prone to have a slower growth. The positive genetic correlations among weight traits and between tick and helminth eggs counts suggest that they are controlled by common genes (with pleiotropic effects). Genetic correlations between IBK incidence and tick and helminth egg counts were moderate and opposite between pre-weaning and post-weaning datasets, suggesting that the environmental and (or) maternal effects differ between these two growth phases. This preliminary study provides estimated genetic parameters for IBK incidence, which could be used to design selection and breeding programs for tropical adaptation in beef cattle. PMID:22839739

In vivo quantification of mouse autoimmune arthritis by PET/CT

PubMed Central

Kundu-Raychaudhuri, Smriti; Mitra, Anupam; Datta-Mitra, Ananya; Chaudhari, Abhijit J.; Raychaudhuri, Siba P.

2014-01-01

Aim To quantify the progression and severity of mouse collagen-induced arthritis (CIA) using an in vivo imaging tool, 18F-fluorodeoxyglucose (18F-FDG) PET/CT, and validate it against gold standard ‘histopathological’ evaluation. Method The PET radiotracer 18F-FDG, a marker for glucose metabolism, was injected in mice at different stages during the development of CIA and the radiotracer distribution was imaged using a PET scanner. A sequential CT scan provided correlated anatomy. Radiotracer concentration was derived from PET/CT images for individual limb joints and on a per-limb basis at different stages of the disease. The imaging outcomes were subjected to correlation analysis with concurrently-measured clinical and histological score. Results Clinical and histological score, and hence disease severity, showed a strong linear correlation (R2=0.71, p=0.001, and R2=0.87, p<0.001, respectively) with radiotracer concentration measured from PET/CT during the progression of CIA. Conclusions The strong positive correlation of the 18F-FDG PET/CT findings with the histopathological evaluation at different stages of the disease suggest the potential of this imaging tool for the non-invasive assessment of progression and severity in mouse autoimmune arthritis. Thus, 18F-FDG PET/CT can be considered as a non invasive tool in preclinical studies for development of novel therapies of inflammatory arthritis. PMID:24965561

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets

PubMed Central

2012-01-01

Background ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles. Results We develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately. Conclusions iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB. PMID:23194258

SU-F-207-06: CT-Based Assessment of Tumor Volume in Malignant Pleural Mesothelioma

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

Qayyum, F; Armato, S; Straus, C

Purpose: To determine the potential utility of computed tomography (CT) scans in the assessment of physical tumor bulk in malignant pleural mesothelioma patients. Methods: Twenty-eight patients with malignant pleural mesothelioma were used for this study. A CT scan was acquired for each patient prior to surgical resection of the tumor (median time between scan and surgery: 27 days). After surgery, the ex-vivo tumor volume was measured by a pathologist using a water displacement method. Separately, a radiologist identified and outlined the tumor boundary on each CT section that demonstrated tumor. These outlines then were analyzed to determine the total volumemore » of disease present, the number of sections with outlines, and the mean volume of disease per outlined section. Subsets of the initial patient cohort were defined based on these parameters, i.e. cases with at least 30 sections of disease with a mean disease volume of at least 3mL per section. For each subset, the R- squared correlation between CT-based tumor volume and physical ex-vivo tumor volume was calculated. Results: The full cohort of 28 patients yielded a modest correlation between CT-based tumor volume and the ex-vivo tumor volume with an R-squared value of 0.66. In general, as the mean tumor volume per section increased, the correlation of CT-based volume with the physical tumor volume improved substantially. For example, when cases with at least 40 CT sections presenting a mean of at least 2mL of disease per section were evaluated (n=20) the R-squared correlation increased to 0.79. Conclusion: While image-based volumetry for mesothelioma may not generally capture physical tumor volume as accurately as one might expect, there exists a set of conditions in which CT-based volume is highly correlated with the physical tumor volume. SGA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology.« less

Evidence that the association of childhood trauma with psychosis and related psychopathology is not explained by gene-environment correlation: A monozygotic twin differences approach.

PubMed

Lecei, Aleksandra; Decoster, Jeroen; De Hert, Marc; Derom, Catherine; Jacobs, Nele; Menne-Lothmann, Claudia; van Os, Jim; Thiery, Evert; Rutten, Bart P F; Wichers, Marieke; van Winkel, Ruud

2018-05-21

Converging evidence supports childhood trauma as possible causal risk for psychosis and related psychopathology. However, studies have shown that baseline psychotic symptoms may actually increase risk for subsequent victimization, suggesting that exposure to CT is not random but may result from pre-existing vulnerability. Therefore, studies testing whether the association between CT and psychopathology persists when accounting for gene-environment correlation are much needed. A monozygotic (MZ) twin differences approach was used to examine whether differences in CT exposure among MZ twin pairs would be associated with MZ differences in symptoms. As MZ twins are genetically identical, within-pair correlations between CT exposure and psychopathology rule out the possibility that the association is solely attributable to gene-environment correlation. 266 monozygotic twins (133 pairs) from a larger general population study were available for analysis. CT was associated with symptoms of psychosis (B = 0.62; SE = 0.08, p < .001) and overall psychopathology (B = 43.13; SE = 6.27; p < .001). There were measurable differences within pairs in CT exposure and symptoms, allowing for meaningful within-pair differences. Within-pair differences in CT exposure were associated with within-pair differences in symptoms of psychosis (B = 0.35; SE = 0.16; p = .024), as well as with overall psychopathology (B = 29.22; SE = 12.24; p = .018), anxiety (B = 0.65; SE = 0.21; p = .002) and depression (B = 0.37; SE = 0.18; p = .043). While it is not unlikely that pre-existing vulnerability may increase the risk for traumatic exposures, such gene-environment correlation does not explain away the association between CT and psychopathology. The present findings thus suggest that at least part of the association between CT and psychopathology may be causal. Copyright © 2018. Published by Elsevier B.V.

Determination of single-kidney glomerular filtration rate (GFR) with CT urography versus renal dynamic imaging Gates method.

PubMed

You, Shan; Ma, XianWu; Zhang, ChangZhu; Li, Qiang; Shi, WenWei; Zhang, Jing; Yuan, XiaoDong

2018-03-01

To present a single-kidney CT-GFR measurement and compare it with the renal dynamic imaging Gates-GFR. Thirty-six patients with hydronephrosis referred for CT urography and 99mTc-DTPA renal dynamic imaging were prospectively included. Informed consent was obtained from all patients. The CT urography protocol included non-contrast, nephrographic, and excretory phase imaging. The total CT-GFR was calculated by dividing the CT number increments of the total urinary system between the nephrographic and excretory phase by the products of iodine concentration in the aorta and the elapsed time, then multiplied by (1- Haematocrit). The total CT-GFR was then split into single-kidney CT-GFR by a left and right kidney proportionality factor. The results were compared with single-kidney Gates-GFR by using paired t-test, correlation analysis, and Bland-Altman plots. Paired difference between single-kidney CT-GFR (45.02 ± 13.91) and single-kidney Gates-GFR (51.21 ± 14.76) was 6.19 ± 5.63 ml/min, p<0.001, demonstrating 12.1% systematic underestimation with ±11.03 ml/min (±21.5%) measurement deviation. A good correlation was revealed between both measurements (r=0.87, p<0.001). The proposed single-kidney CT-GFR correlates and agrees well with the reference standard despite a systematic underestimation, therefore it could be a one-stop-shop for evaluating urinary tract morphology and split renal function. • A new CT method can assess split renal function • Only using images from CT urography and the value of haematocrit • A one-stop-shop CT technique without additional radiation dose.

Co-registered perfusion SPECT/CT: utility for prediction of improved postoperative outcome in lung volume reduction surgery candidates.

PubMed

Takenaka, Daisuke; Ohno, Yoshiharu; Koyama, Hisanobu; Nogami, Munenobu; Onishi, Yumiko; Matsumoto, Keiko; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Sugimura, Kazuro

2010-06-01

To directly compare the capabilities of perfusion scan, SPECT, co-registered SPECT/CT, and quantitatively and qualitatively assessed MDCT (i.e. quantitative CT and qualitative CT) for predicting postoperative clinical outcome for lung volume reduction surgery (LVRS) candidates. Twenty-five consecutive candidates (19 men and six women, age range: 42-72 years) for LVRS underwent preoperative CT and perfusion scan with SPECT. Clinical outcome of LVRS for all subjects was also assessed by determining the difference between pre- and postoperative forced expiratory volume in 1s (FEV(1)) and 6-min walking distance (6MWD). All SPECT examinations were performed on a SPECT scanner, and co-registered to thin-section CT by using commercially available software. On planar imaging, SPECT and SPECT/CT, upper versus lower zone or lobe ratios (U/Ls) were calculated from regional uptakes between upper and lower lung fields in the operated lung. On quantitatively assessed CT, U/L for all subjects was assessed from regional functional lung volumes. On qualitatively assessed CT, planar imaging, SPECT and co-registered SPECT/CT, U/Ls were assessed with a 4-point visual scoring system. To compare capabilities of predicting clinical outcome, each U/L was statistically correlated with the corresponding clinical outcome. Significantly fair or moderate correlations were observed between quantitatively and qualitatively assessed U/Ls obtained with all four methods and clinical outcomes (-0.60

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging.

PubMed

Lauzier, Pascal Theriault; Tang, Jie; Speidel, Michael A; Chen, Guang-Hong

2012-07-01

To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

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

Lauzier, Pascal Theriault; Tang Jie; Speidel, Michael A.

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise andmore » streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.« less

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

PubMed Central

Lauzier, Pascal Thériault; Tang, Jie; Speidel, Michael A.; Chen, Guang-Hong

2012-01-01

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI. PMID:22830741

Correlative CT and anatomic study of the sciatic nerve

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

Pech, P.; Haughton, V.

1985-05-01

Sciatica can be caused by numerous processes affecting the sciatic nerve or its components within the pelvis including tumors, infectious diseases, aneurysms, fractures, and endometriosis. The CT diagnosis of these causes of sciatica has not been emphasized. This study identified the course and appearance of the normal sciatic nerve in the pelvis by correlating CT and anatomic slices in cadavers. For purposes of discussion, the sciatic nerve complex is conveniently divided into three parts: presacral, muscular, and ischial. Each part is illustrated here by two cryosections with corresponding CT images.

Evaluation of CT Perfusion Biomarkers of Tumor Hypoxia

PubMed Central

Qi, Qi; Yeung, Timothy Pok Chi; Lee, Ting-Yim; Bauman, Glenn; Crukley, Cathie; Morrison, Laura; Hoffman, Lisa; Yartsev, Slav

2016-01-01

Background Tumor hypoxia is associated with treatment resistance to cancer therapies. Hypoxia can be investigated by immunohistopathologic methods but such procedure is invasive. A non-invasive method to interrogate tumor hypoxia is an attractive option as such method can provide information before, during, and after treatment for personalized therapies. Our study evaluated the correlations between computed tomography (CT) perfusion parameters and immunohistopathologic measurement of tumor hypoxia. Methods Wistar rats, 18 controls and 19 treated with stereotactic radiosurgery (SRS), implanted with the C6 glioma tumor were imaged using CT perfusion on average every five days to monitor tumor growth. A final CT perfusion scan and the brain were obtained on average 14 days (8–22 days) after tumor implantation. Tumor hypoxia was detected immunohistopathologically with pimonidazole. The tumor, necrotic, and pimonidazole-positive areas on histology samples were measured. Percent necrotic area and percent hypoxic areas were calculated. Tumor volume (TV), blood flow (BF), blood volume (BV), and permeability-surface area product (PS) were obtained from the CT perfusion studies. Correlations between CT perfusion parameters and histological parameters were assessed by Spearman’s ρ correlation. A Bonferroni-corrected P value < 0.05 was considered significant. Results BF and BV showed significant correlations with percent hypoxic area ρ = -0.88, P < 0.001 and ρ = -0.81, P < 0.001, respectively, for control animals and ρ = -0.7, P < 0.001 and ρ = -0.6, P = 0.003, respectively, for all animals, while TV and BV were correlated (ρ = -0.64, P = 0.01 and ρ = -0.43, P = 0.043, respectively) with percent necrotic area. PS was not correlated with either percent necrotic or percent hypoxic areas. Conclusions Percent hypoxic area provided significant correlations with BF and BV, suggesting that CT perfusion parameters are potential non-invasive imaging biomarkers of tumor hypoxia. PMID:27078858

A new functional method to choose the target lobe for lung volume reduction in emphysema - comparison with the conventional densitometric method.

PubMed

Hetzel, Juergen; Boeckeler, Michael; Horger, Marius; Ehab, Ahmed; Kloth, Christopher; Wagner, Robert; Freitag, Lutz; Slebos, Dirk-Jan; Lewis, Richard Alexander; Haentschel, Maik

2017-01-01

Lung volume reduction (LVR) improves breathing mechanics by reducing hyperinflation. Lobar selection usually focuses on choosing the most destroyed emphysematous lobes as seen on an inspiratory CT scan. However, it has never been shown to what extent these densitometric CT parameters predict the least deflation of an individual lobe during expiration. The addition of expiratory CT analysis allows measurement of the extent of lobar air trapping and could therefore provide additional functional information for choice of potential treatment targets. To determine lobar vital capacity/lobar total capacity (LVC/LTC) as a functional parameter for lobar air trapping using on an inspiratory and expiratory CT scan. To compare lobar selection by LVC/LTC with the established morphological CT density parameters. 36 patients referred for endoscopic LVR were studied. LVC/LTC, defined as delta volume over maximum volume of a lobe, was calculated using inspiratory and expiratory CT scans. The CT morphological parameters of mean lung density (MLD), low attenuation volume (LAV), and 15th percentile of Hounsfield units (15%P) were determined on an inspiratory CT scan for each lobe. We compared and correlated LVC/LTC with MLD, LAV, and 15%P. There was a weak correlation between the functional parameter LVC/LTC and all inspiratory densitometric parameters. Target lobe selection using lowest lobar deflation (lowest LVC/LTC) correlated with target lobe selection based on lowest MLD in 18 patients (50.0%), with the highest LAV in 13 patients (36.1%), and with the lowest 15%P in 12 patients (33.3%). CT-based measurement of deflation (LVC/LTC) as a functional parameter correlates weakly with all densitometric CT parameters on a lobar level. Therefore, morphological criteria based on inspiratory CT densitometry partially reflect the deflation of particular lung lobes, and may be of limited value as a sole predictor for target lobe selection in LVR.

Measurement of myocardial extracellular volume fraction by using equilibrium contrast-enhanced CT: validation against histologic findings.

PubMed

Bandula, Steve; White, Steven K; Flett, Andrew S; Lawrence, David; Pugliese, Francesca; Ashworth, Michael T; Punwani, Shonit; Taylor, Stuart A; Moon, James C

2013-11-01

To develop and validate equilibrium contrast material-enhanced computed tomography (CT) to measure myocardial extracellular volume (ECV) fraction by using a histologic reference standard and to compare equilibrium CT with equilibrium contrast-enhanced magnetic resonance (MR) imaging. A local ethics committee approved the study, and all subjects gave fully informed written consent. An equilibrium CT protocol was developed using iohexol at 300 mg of iodine per milliliter (bolus of 1 mg per kilogram of body weight administered at a rate of 3 mL/sec, followed immediately by an infusion of 1.88 mL/kg per hour with CT imaging before and at 25 minutes after injection of bolus of contrast agent) and ECV within the myocardial septum measured using both equilibrium CT and equilibrium MR imaging in patients with severe aortic stenosis. Biopsy samples of the myocardial septum collected during valve replacement surgery were used for histologic quantification of extracellular fibrosis with picrosirius red staining. Equilibrium CT- and equilibrium MR imaging-derived ECV measurements were compared with histologically quantified fibrosis by using Pearson correlation. Agreement between equilibrium CT and equilibrium MR imaging was assessed by using Bland-Altman comparison. Twenty-three patients (16 male, seven female; mean age, 70.8 years; standard deviation, 8.3) were recruited. The mean percentage of histologic fibrosis was 18% (intersubject range, 5%-40%). There was a significant correlation between both equilibrium CT- and equilibrium MR imaging-derived ECV and percentage of histologic fibrosis (r = 0.71 [P < .001] and r = 0.84 [P < .0001], respectively). Equilibrium CT-derived ECV was significantly correlated to equilibrium MR imaging-derived ECV (r = 0.73). ECV measured by using equilibrium CT in patients with aortic stenosis correlates with histologic quantification of myocardial fibrosis and with ECV derived by using equilibrium MR imaging. RSNA, 2013

A semiautomatic segmentation method for prostate in CT images using local texture classification and statistical shape modeling.

PubMed

Shahedi, Maysam; Halicek, Martin; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei

2018-06-01

Prostate segmentation in computed tomography (CT) images is useful for treatment planning and procedure guidance such as external beam radiotherapy and brachytherapy. However, because of the low, soft tissue contrast of CT images, manual segmentation of the prostate is a time-consuming task with high interobserver variation. In this study, we proposed a semiautomated, three-dimensional (3D) segmentation for prostate CT images using shape and texture analysis and we evaluated the method against manual reference segmentations. The prostate gland usually has a globular shape with a smoothly curved surface, and its shape could be accurately modeled or reconstructed having a limited number of well-distributed surface points. In a training dataset, using the prostate gland centroid point as the origin of a coordination system, we defined an intersubject correspondence between the prostate surface points based on the spherical coordinates. We applied this correspondence to generate a point distribution model for prostate shape using principal component analysis and to study the local texture difference between prostate and nonprostate tissue close to the different prostate surface subregions. We used the learned shape and texture characteristics of the prostate in CT images and then combined them with user inputs to segment a new image. We trained our segmentation algorithm using 23 CT images and tested the algorithm on two sets of 10 nonbrachytherapy and 37 postlow dose rate brachytherapy CT images. We used a set of error metrics to evaluate the segmentation results using two experts' manual reference segmentations. For both nonbrachytherapy and post-brachytherapy image sets, the average measured Dice similarity coefficient (DSC) was 88% and the average mean absolute distance (MAD) was 1.9 mm. The average measured differences between the two experts on both datasets were 92% (DSC) and 1.1 mm (MAD). The proposed, semiautomatic segmentation algorithm showed a fast, robust, and accurate performance for 3D prostate segmentation of CT images, specifically when no previous, intrapatient information, that is, previously segmented images, was available. The accuracy of the algorithm is comparable to the best performance results reported in the literature and approaches the interexpert variability observed in manual segmentation. © 2018 American Association of Physicists in Medicine.

A Simplified Whole-Organ CT Perfusion Technique with Biphasic Acquisition: Preliminary Investigation of Accuracy and Protocol Feasibility in Kidneys.

PubMed

Yuan, XiaoDong; Zhang, Jing; Quan, ChangBin; Tian, Yuan; Li, Hong; Ao, GuoKun

2016-04-01

To determine the feasibility and accuracy of a protocol for calculating whole-organ renal perfusion (renal blood flow [RBF]) and regional perfusion on the basis of biphasic computed tomography (CT), with concurrent dynamic contrast material-enhanced (DCE) CT perfusion serving as the reference standard. This prospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Biphasic CT of the kidneys, including precontrast and arterial phase imaging, was integrated with a first-pass dynamic volume CT protocol and performed and analyzed in 23 patients suspected of having renal artery stenosis. The perfusion value derived from biphasic CT was calculated as CT number enhancement divided by the area under the arterial input function and compared with the DCE CT perfusion data by using the paired t test, correlation analysis, and Bland-Altman plots. Correlation analysis was made between the RBF and the extent of renal artery stenosis. All postprocessing was independently performed by two observers and then averaged as the final result. Mean ± standard deviation biphasic and DCE CT perfusion data for RBF were 425.62 mL/min ± 124.74 and 419.81 mL/min ± 121.13, respectively (P = .53), and for regional perfusion they were 271.15 mL/min per 100 mL ± 82.21 and 266.33 mL/min per 100 mL ± 74.40, respectively (P = .31). Good correlation and agreement were shown between biphasic and DCE CT perfusion for RBF (r = 0.93; ±10% variation from mean perfusion data [P < .001]) and for regional perfusion (r = 0.90; ±13% variation from mean perfusion data [P < .001]). The extent of renal artery stenosis was negatively correlated with RBF with biphasic CT perfusion (r = -0.81, P = .012). Biphasic CT perfusion is clinically feasible and provides perfusion data comparable to DCE CT perfusion data at both global and regional levels in the kidney. Online supplemental material is available for this article.

Micro-CTvlab: A web based virtual gallery of biological specimens using X-ray microtomography (micro-CT).

PubMed

Keklikoglou, Kleoniki; Faulwetter, Sarah; Chatzinikolaou, Eva; Michalakis, Nikitas; Filiopoulou, Irene; Minadakis, Nikos; Panteri, Emmanouela; Perantinos, George; Gougousis, Alexandros; Arvanitidis, Christos

2016-01-01

During recent years, X-ray microtomography (micro-CT) has seen an increasing use in biological research areas, such as functional morphology, taxonomy, evolutionary biology and developmental research. Micro-CT is a technology which uses X-rays to create sub-micron resolution images of external and internal features of specimens. These images can then be rendered in a three-dimensional space and used for qualitative and quantitative 3D analyses. However, the online exploration and dissemination of micro-CT datasets are rarely made available to the public due to their large size and a lack of dedicated online platforms for the interactive manipulation of 3D data. Here, the development of a virtual micro-CT laboratory (Micro-CT vlab ) is described, which can be used by everyone who is interested in digitisation methods and biological collections and aims at making the micro-CT data exploration of natural history specimens freely available over the internet. The Micro-CT vlab offers to the user virtual image galleries of various taxa which can be displayed and downloaded through a web application. With a few clicks, accurate, detailed and three-dimensional models of species can be studied and virtually dissected without destroying the actual specimen. The data and functions of the Micro-CT vlab can be accessed either on a normal computer or through a dedicated version for mobile devices.

Is It Better to Enter a Volume CT Dose Index Value before or after Scan Range Adjustment for Radiation Dose Optimization of Pediatric Cardiothoracic CT with Tube Current Modulation?

PubMed Central

2018-01-01

Objective To determine whether the body size-adapted volume computed tomography (CT) dose index (CTDvol) in pediatric cardiothoracic CT with tube current modulation is better to be entered before or after scan range adjustment for radiation dose optimization. Materials and Methods In 83 patients, cardiothoracic CT with tube current modulation was performed with the body size-adapted CTDIvol entered after (group 1, n = 42) or before (group 2, n = 41) scan range adjustment. Patient-related, radiation dose, and image quality parameters were compared and correlated between the two groups. Results The CTDIvol after the CT scan in group 1 was significantly higher than that in group 2 (1.7 ± 0.1 mGy vs. 1.4 ± 0.3 mGy; p < 0.0001). Image noise (4.6 ± 0.5 Hounsfield units [HU] vs. 4.5 ± 0.7 HU) and image quality (1.5 ± 0.6 vs. 1.5 ± 0.6) showed no significant differences between the two (p > 0.05). In both groups, all patient-related parameters, except body density, showed positive correlations (r = 0.49–0.94; p < 0.01) with the CTDIvol before and after the CT scan. The CTDIvol after CT scan showed modest positive correlation (r = 0.49; p ≤ 0.001) with image noise in group 1 but no significant correlation (p > 0.05) in group 2. Conclusion In pediatric cardiothoracic CT with tube current modulation, the CTDIvol entered before scan range adjustment provides a significant dose reduction (18%) with comparable image quality compared with that entered after scan range adjustment.

Correlation between presumed sinusitis-induced pain and paranasal sinus computed tomographic findings.

PubMed

Mudgil, Shikha P; Wise, Scott W; Hopper, Kenneth D; Kasales, Claudia J; Mauger, David; Fornadley, John A

2002-02-01

The correlation between facial and/or head pain in patients clinically suspected of having sinusitis and actual localized findings on sinus computed tomographic (CT) imaging are poorly understood. To prospectively evaluate the relationship of paranasal sinus pain symptoms with CT imaging. Two hundred consecutive patients referred by otolaryngologists and internists for CT of the paranasal sinuses participated by completing a questionnaire immediately before undergoing CT. Three radiologists blinded to the patients' responses scored the degree of air/fluid level, mucosal thickening, bony reaction, and mucus retention cysts using a graded scale of severity (0 to 3 points). The osteomeatal complexes and nasolacrimal ducts were also evaluated for patency. Bivariate analysis was performed to evaluate the relationship between patients' localized symptoms and CT findings in the respective sinus. One hundred sixty-three patients (82%) reported having some form of facial pain or headache. The right temple/forehead was the most frequently reported region of maximal pain. On CT imaging the maxillary sinus was the most frequently involved sinus. Bivariate analysis failed to show any relationship between patient symptoms and findings on CT. Patients with a normal CT reported a mean 5.88 sites of facial or head pain versus 5.45 sites for patients with an abnormal CT. Patient-based responses of sinonasal pain symptoms fail to correlate with findings in the respective sinuses. CT should therefore be reserved for delineating the anatomy and degree of sinus disease before surgical intervention.

Validation of a novel technique for creating simulated radiographs using computed tomography datasets.

PubMed

Mendoza, Patricia; d'Anjou, Marc-André; Carmel, Eric N; Fournier, Eric; Mai, Wilfried; Alexander, Kate; Winter, Matthew D; Zwingenberger, Allison L; Thrall, Donald E; Theoret, Christine

2014-01-01

Understanding radiographic anatomy and the effects of varying patient and radiographic tube positioning on image quality can be a challenge for students. The purposes of this study were to develop and validate a novel technique for creating simulated radiographs using computed tomography (CT) datasets. A DICOM viewer (ORS Visual) plug-in was developed with the ability to move and deform cuboidal volumetric CT datasets, and to produce images simulating the effects of tube-patient-detector distance and angulation. Computed tomographic datasets were acquired from two dogs, one cat, and one horse. Simulated radiographs of different body parts (n = 9) were produced using different angles to mimic conventional projections, before actual digital radiographs were obtained using the same projections. These studies (n = 18) were then submitted to 10 board-certified radiologists who were asked to score visualization of anatomical landmarks, depiction of patient positioning, realism of distortion/magnification, and image quality. No significant differences between simulated and actual radiographs were found for anatomic structure visualization and patient positioning in the majority of body parts. For the assessment of radiographic realism, no significant differences were found between simulated and digital radiographs for canine pelvis, equine tarsus, and feline abdomen body parts. Overall, image quality and contrast resolution of simulated radiographs were considered satisfactory. Findings from the current study indicated that radiographs simulated using this new technique are comparable to actual digital radiographs. Further studies are needed to apply this technique in developing interactive tools for teaching radiographic anatomy and the effects of varying patient and tube positioning. © 2013 American College of Veterinary Radiology.

Blood vessel-based liver segmentation through the portal phase of a CT dataset

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo

2013-02-01

Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.

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

Peng, Jialin, E-mail: 2004pjl@163.com; Zhang, Hongbo; Hu, Peijun

Purpose: Efficient and accurate 3D liver segmentations from contrast-enhanced computed tomography (CT) images play an important role in therapeutic strategies for hepatic diseases. However, inhomogeneous appearances, ambiguous boundaries, and large variance in shape often make it a challenging task. The existence of liver abnormalities poses further difficulty. Despite the significant intensity difference, liver tumors should be segmented as part of the liver. This study aims to address these challenges, especially when the target livers contain subregions with distinct appearances. Methods: The authors propose a novel multiregion-appearance based approach with graph cuts to delineate the liver surface. For livers with multiplemore » subregions, a geodesic distance based appearance selection scheme is introduced to utilize proper appearance constraint for each subregion. A special case of the proposed method, which uses only one appearance constraint to segment the liver, is also presented. The segmentation process is modeled with energy functions incorporating both boundary and region information. Rather than a simple fixed combination, an adaptive balancing weight is introduced and learned from training sets. The proposed method only calls initialization inside the liver surface. No additional constraints from user interaction are utilized. Results: The proposed method was validated on 50 3D CT images from three datasets, i.e., Medical Image Computing and Computer Assisted Intervention (MICCAI) training and testing set, and local dataset. On MICCAI testing set, the proposed method achieved a total score of 83.4 ± 3.1, outperforming nonexpert manual segmentation (average score of 75.0). When applying their method to MICCAI training set and local dataset, it yielded a mean Dice similarity coefficient (DSC) of 97.7% ± 0.5% and 97.5% ± 0.4%, respectively. These results demonstrated the accuracy of the method when applied to different computed tomography (CT) datasets. In addition, user operator variability experiments showed its good reproducibility. Conclusions: A multiregion-appearance based method is proposed and evaluated to segment liver. This approach does not require prior model construction and so eliminates the burdens associated with model construction and matching. The proposed method provides comparable results with state-of-the-art methods. Validation results suggest that it may be suitable for the clinical use.« less

(18)F-FDG dynamic PET/CT in patients with multiple myeloma: patterns of tracer uptake and correlation with bone marrow plasma cell infiltration rate.

PubMed

Sachpekidis, Christos; Mai, Elias K; Goldschmidt, Hartmut; Hillengass, Jens; Hose, Dirk; Pan, Leyun; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2015-06-01

The value of F-FDG PET in the diagnostic approach of multiple myeloma (MM) remains incompletely elicited. Little is known about the kinetics of F-FDG in the bone marrow and extramedullary sites in MM. This study aimed to evaluate quantitative data on kinetics and distribution patterns of F-FDG in MM patients with regard to pelvic bone marrow plasma cell infiltration. The study included 40 patients with primary MM. Dynamic PET/CT scanning of the lower lumbar spine and pelvis was performed after the administration of F-FDG. Whole-body PET/CT studies were performed. Sites of focal increased tracer uptake were considered as highly suggestive of myelomatous involvement after taking into account the patient history and CT findings. Bone marrow of the os ilium without pathologic tracer accumulation served as reference. The evaluation of dynamic PET/CT studies was based in addition to the conventional visual (qualitative) assessment, on semiquantitative (SUV) calculations, as well as on absolute quantitative estimations after application of a 2-tissue compartment model and a noncompartmental approach. F-FDG quantitative information and corresponding distribution patterns were correlated with pelvic bone marrow plasma cell infiltration. Fifty-two myelomatous lesions were detected in the pelvis. All parameters in suspected MM lesions ranged in significantly higher levels than in reference tissue (P < 0.01). Correlative analyses revealed that bone marrow plasma cell infiltration rate correlated significantly with SUVaverage, SUVmax, and the parameters K1, influx, and fractal dimension of F-FDG in reference bone marrow (P < 0.01). In addition, whole-body static PET/CT imaging demonstrated 4 patterns of tracer uptake; these are as follows: negative, focal, diffuse, and mixed (focal/diffuse) tracer uptake. Patients with a mixed pattern of radiotracer uptake had the highest mean plasma cell infiltration rate in their bone marrow, whereas those with negative PET/CT scans demonstrated the lowest bone marrow plasma cell infiltration. In total, 265 focal myeloma-indicative F-FDG-avid lesions were detected, 129 of which correlated with low-dose CT osteolytic findings. No significant correlation between the number of focal lesions detected in PET/CT and bone marrow infiltration was detected. The F-FDG kinetic parameters K1, influx, and fractal dimension as well as SUVaverage from reference tissue correlated significantly with bone marrow malignant plasma cell infiltration rate. Patients with negative PET/CT demonstrated the lowest bone marrow infiltration by malignant plasma cells, whereas those with a mixed pattern of tracer uptake had the highest infiltration.

Analysis of computed tomography density of liver before and after amiodarone administration.

PubMed

Matsuda, Masazumi; Otaka, Aoi; Tozawa, Tomoki; Asano, Tomoyuki; Ishiyama, Koichi; Hashimoto, Manabu

2018-05-01

To evaluate CT density of liver changes between before and after amiodarone administration. Twenty-five patients underwent non-enhanced CT including the liver before and after amiodarone administration. We set regions of interest (ROIs) at liver S8, spleen, paraspinal muscle, and calculated average CT density in these ROIs, then compared CT density between liver and other organs. Statistical differences between CT density of liver and various ratios before and after administration were determined, along with correlations between cumulative dose of amiodarone and liver density after administration, density change of liver, and various ratios after administration. Liver density, liver-to-spleen ratio, and liver-to-paraspinal muscle ratio differed significantly between before and after amiodarone administration. No significant correlations were found between cumulative doses of amiodarone and any of liver density after administration, density change of liver, or various ratios after administration. CT density of liver after amiodarone administration was significantly higher than that before administration. No correlations were identified between cumulative dose of amiodarone and either liver density after administration or density change of liver. Amiodarone usage should be checked when radiologists identify high density of the liver on CT.

Ocular biometry by computed tomography in different dog breeds.

PubMed

Chiwitt, Carolin L H; Baines, Stephen J; Mahoney, Paul; Tanner, Andrew; Heinrich, Christine L; Rhodes, Michael; Featherstone, Heidi J

2017-09-01

To (i) correlate B-mode ocular ultrasound (US) and computed tomography (CT) (prospective pilot study), (ii) establish a reliable method to measure the normal canine eye using CT, (iii) establish a reference guide for some dog breeds, (iv) compare eye size between different breeds and breed groups, and (v) investigate the correlation between eye dimensions and body weight, gender, and skull type (retrospective study). B-mode US and CT were performed on ten sheep cadaveric eyes. CT biometry involved 100 adult pure-bred dogs with nonocular and nonorbital disease, representing eleven breeds. Eye length, width, and height were each measured in two of three planes (horizontal, sagittal, and equatorial). B-mode US and CT measurements of sheep cadaveric eyes correlated well (0.70-0.71). The shape of the canine eye was found to be akin to an oblate spheroid (a flattened sphere). A reference guide was established for eleven breeds. Eyes of large breed dogs were significantly larger than those of medium and small breed dogs (P < 0.01), and eyes of medium breed dogs were significantly larger than those of small breed dogs (P < 0.01). Eye size correlated with body weight (0.74-0.82) but not gender or skull type. Computed tomography is a suitable method for biometry of the canine eye, and a reference guide was established for eleven breeds. Eye size correlated with breed size and body weight. Because correlation between B-mode US and CT was shown, the obtained values can be applied in the clinical setting, for example, for the diagnosis of microphthalmos and buphthalmos. © 2016 American College of Veterinary Ophthalmologists.

Monitoring of argatroban and lepirudin anticoagulation in critically ill patients by conventional laboratory parameters and rotational thromboelastometry - a prospectively controlled randomized double-blind clinical trial.

PubMed

Beiderlinden, Martin; Werner, Patrick; Bahlmann, Astrid; Kemper, Johann; Brezina, Tobias; Schäfer, Maximilian; Görlinger, Klaus; Seidel, Holger; Kienbaum, Peter; Treschan, Tanja A

2018-02-09

Argatroban or lepirudin anticoagulation therapy in patients with heparin induced thrombocytopenia (HIT) or HIT suspect is typically monitored using the activated partial thromboplastin time (aPTT). Although aPTT correlates well with plasma levels of argatroban and lepirudin in healthy volunteers, it might not be the method of choice in critically ill patients. However, in-vivo data is lacking for this patient population. Therefore, we studied in vivo whether ROTEM or global clotting times would provide an alternative for monitoring the anticoagulant intensity effects in critically ill patients. This study was part of the double-blind randomized trial "Argatroban versus Lepirudin in critically ill patients (ALicia)", which compared critically ill patients treated with argatroban or lepirudin. Following institutional review board approval and written informed consent, for this sub-study blood of 35 critically ill patients was analysed. Before as well as 12, 24, 48 and 72 h after initiation of argatroban or lepirudin infusion, blood was analysed for aPTT, aPTT ratios, thrombin time (TT), INTEM CT,INTEM CT ratios, EXTEM CT, EXTEM CT ratios and maximum clot firmness (MCF) and correlated with the corresponding plasma concentrations of the direct thrombin inhibitor. To reach a target aPTT of 1.5 to 2 times baseline, median [IQR] plasma concentrations of 0.35 [0.01-1.2] μg/ml argatroban and 0.17 [0.1-0.32] μg/ml lepirudin were required. For both drugs, there was no significant correlation between aPTT and aPTT ratios and plasma concentrations. INTEM CT, INTEM CT ratios, EXTEM CT, EXTEM CT ratios, TT and TT ratios correlated significantly with plasma concentrations of both drugs. Additionally, agreement between argatroban plasma levels and EXTEM CT and EXTEM CT ratios were superior to agreement between argatroban plasma levels and aPTT in the Bland Altman analysis. MCF remained unchanged during therapy with both drugs. In critically ill patients, TT and ROTEM parameters may provide better correlation to argatroban and lepirudin plasma concentrations than aPTT. ClinicalTrials.gov , NCT00798525 , registered on 25 Nov 2008.

Technetium-99m-HMPAO SPECT, CT and MRI in the evaluation of patients with chronic traumatic brain injury: a correlation with neuropsychological performance.

PubMed

Ichise, M; Chung, D G; Wang, P; Wortzman, G; Gray, B G; Franks, W

1994-02-01

The purposes of this study were: (1) to compare 99mTc-hexamethylpropyleneamineoxime (HMPAO) SPECT with CT and MRI in chronic traumatic brain injury (TBI) patients and (2) to correlate both functional and structural neuroimaging measurements of brain damage with neuropsychological (NP) performance. Twenty-nine patients (minor TBI, n = 15 and major TBI, n = 14) and 17 normal controls (NC) underwent HMPAO SPECT, CT, MRI and NP testing. Imaging data were analyzed both visually and quantitatively. Nineteen (66%) patients showed 42 abnormalities on SPECT images, whereas 13 (45%) and 10 (34%) patients showed 29 abnormalities on MRI and 24 abnormalities on CT. SPECT detected relatively more abnormalities than CT or MRI in the minor TBI subgroup. The TBI group showed impairment on 11 tests for memory, attention and executive function. Of these, the anterior-posterior ratio (APR) correlated with six tests, whereas the ventricle-to-brain ratio (VBR), a known structural index of a poor NP outcome, correlated with only two tests. In evaluating chronic TBI patients, HMPAO SPECT, as a complement to CT or MRI, may play a useful role by demonstrating brain dysfunction in morphologically intact brain regions and providing objective evidence for some of the impaired NP performance.

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.

Joint Blind Source Separation by Multi-set Canonical Correlation Analysis

PubMed Central

Li, Yi-Ou; Adalı, Tülay; Wang, Wei; Calhoun, Vince D

2009-01-01

In this work, we introduce a simple and effective scheme to achieve joint blind source separation (BSS) of multiple datasets using multi-set canonical correlation analysis (M-CCA) [1]. We first propose a generative model of joint BSS based on the correlation of latent sources within and between datasets. We specify source separability conditions, and show that, when the conditions are satisfied, the group of corresponding sources from each dataset can be jointly extracted by M-CCA through maximization of correlation among the extracted sources. We compare source separation performance of the M-CCA scheme with other joint BSS methods and demonstrate the superior performance of the M-CCA scheme in achieving joint BSS for a large number of datasets, group of corresponding sources with heterogeneous correlation values, and complex-valued sources with circular and non-circular distributions. We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task. PMID:20221319

[Chronic pancreatitis: which is the role of 320-row CT for the staging?].

PubMed

Stabile Ianora, Amato Antonio; Rubini, Giuseppe; Lorusso, Filomenamila; Ambriola, Angela; Rella, Leonarda; Di Crescenzo, Vincenzo; Moschetta, Marco

2013-01-01

The purpose of this study was to evaluate the diagnostic potential of multi-planar and volumetric reconstructions obtained from isotropic data by using 16-slice computed tomography (CT) in the diagnosis and staging of chronic pancreatitis. In a group of 42 patients CT images were evaluated searching for alterations in morphology and structure of the pancreas, alterations of the Wirsung duct, dilatation of the bile ducts, fluid collections, and vascular involvement of the digestive tract. The disease was then staged in mild, moderate and severe and correlated with the clinical staging. CT allowed the recognition of chronic pancreatitis in all cases. The staging was correct in 25/42 patients, with an accuracy rate of 59.5%. In the staging of moderate and severe forms, CT correlation with clinical and laboratory data was valid, but in mild forms it appeared less significant. Multi-detector CT is accurate in the recognition of moderate, advanced forms of chronic pancreatitis and in the identification of its complications, while it is poorly correlated with the clinical staging in mild forms of the disease.

Comparison of distribution of lung aeration measured with EIT and CT in spontaneously breathing, awake patients1.

PubMed

Radke, Oliver C; Schneider, Thomas; Braune, Anja; Pirracchio, Romain; Fischer, Felix; Koch, Thea

2016-09-28

Both Electrical Impedance Tomography (EIT) and Computed Tomography (CT) allow the estimation of the lung area. We compared two algorithms for the detection of the lung area per quadrant from the EIT images with the lung areas derived from the CT images. 39 outpatients who were scheduled for an elective CT scan of the thorax were included in the study. For each patient we recorded EIT images immediately before the CT scan. The lung area per quadrant was estimated from both CT and EIT data using two different algorithms for the EIT data. Data showed considerable variation during spontaneous breathing of the patients. Overall correlation between EIT and CT was poor (0.58-0.77), the correlation between the two EIT algorithms was better (0.90-0.92). Bland-Altmann analysis revealed absence of bias, but wide limits of agreement. Lung area estimation from CT and EIT differs significantly, most probably because of the fundamental difference in image generation.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

PubMed

Madrigal, Pedro

2017-03-01

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

A coarse-to-fine approach for pericardial effusion localization and segmentation in chest CT scans

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Chellamuthu, Karthik; Lu, Le; Bagheri, Mohammadhadi; Summers, Ronald M.

2018-02-01

Pericardial effusion on CT scans demonstrates very high shape and volume variability and very low contrast to adjacent structures. This inhibits traditional automated segmentation methods from achieving high accuracies. Deep neural networks have been widely used for image segmentation in CT scans. In this work, we present a two-stage method for pericardial effusion localization and segmentation. For the first step, we localize the pericardial area from the entire CT volume, providing a reliable bounding box for the more refined segmentation step. A coarse-scaled holistically-nested convolutional networks (HNN) model is trained on entire CT volume. The resulting HNN per-pixel probability maps are then threshold to produce a bounding box covering the pericardial area. For the second step, a fine-scaled HNN model is trained only on the bounding box region for effusion segmentation to reduce the background distraction. Quantitative evaluation is performed on a dataset of 25 CT scans of patient (1206 images) with pericardial effusion. The segmentation accuracy of our two-stage method, measured by Dice Similarity Coefficient (DSC), is 75.59+/-12.04%, which is significantly better than the segmentation accuracy (62.74+/-15.20%) of only using the coarse-scaled HNN model.

SU-F-R-07: Radiomics of CT Features and Associations and Correlation with Outcomes Following Lung SBRT

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

Schreibmann, E; Iwinski Sutter, A; Whitaker, D

Objective: To investigate the prognostic significance of image gradients and in predicting clinical outcomes in a patients with non-small cell lung cancer treated with stereotactic body radiotherapy (SBRT) on 71 patients with 83 treated lesions. Methods: The records of patients treated with lung SBRT were retrospectively reviewed. When applicable, SBRT target volumes were modified to exclude any overlap with pleura, chestwall, or mediastinum. The ITK software package was utilized to generate quantitative measures of image intensity, inhomogeneity, shape morphology and first and second-order CT textures. Multivariate and univariate models containing CT features were generated to assess associations with clinicopathologic factors.more » Results: On univariate analysis, tumor size (HR 0.54, p=0.045) sumHU (HR 0.31, p=0.044) and short run grey level emphasis STD (HR 0.22, p=0.019) were associated with regional failure-free survival; meanHU (HR 0.30, p=0.035), long run emphasis (HR 0.21, p=0.011) and long run low grey level emphasis (HR 0.14, p=0.005) was associated with distant failure-free survival (DFFS). No features were significant on multivariate modeling however long run low grey level emphasis had a hazard ratio of 0.12 (p=0.061) for DFFS. Adenocarcinoma and squamous cell carcinoma differed with respect to long run emphasis STD (p=0.024), short run low grey level emphasis STD (p<0.001), and long run low grey level emphasis STD (p=0.024). Multivariate modeling of texture features associated with tumor histology was used to estimate histologies of 18 lesions treated without histologic confirmation. Of these, MVA suggested the same histology as a prior metachronous lung malignancy in 3/7 patients. Conclusion: Extracting radiomics features on clinical datasets was feasible with the ITK package with minimal effort to identify pre-treatment quantitative CT features with prognostic factors for distant control after lung SBRT.« less

Local ROI Reconstruction via Generalized FBP and BPF Algorithms along More Flexible Curves

PubMed Central

Ye, Yangbo; Zhao, Shiying; Wang, Ge

2006-01-01

We study the local region-of-interest (ROI) reconstruction problem, also referred to as the local CT problem. Our scheme includes two steps: (a) the local truncated normal-dose projections are extended to global dataset by combining a few global low-dose projections; (b) the ROI are reconstructed by either the generalized filtered backprojection (FBP) or backprojection-filtration (BPF) algorithms. The simulation results show that both the FBP and BPF algorithms can reconstruct satisfactory results with image quality in the ROI comparable to that of the corresponding global CT reconstruction. PMID:23165018

Parallelized seeded region growing using CUDA.

PubMed

Park, Seongjin; Lee, Jeongjin; Lee, Hyunna; Shin, Juneseuk; Seo, Jinwook; Lee, Kyoung Ho; Shin, Yeong-Gil; Kim, Bohyoung

2014-01-01

This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests.

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.

Single cross-sectional area of pectoralis muscle by computed tomography - correlation with bioelectrical impedance based skeletal muscle mass in healthy subjects.

PubMed

Kim, Young Saing; Kim, Eun Young; Kang, Shin Myung; Ahn, Hee Kyung; Kim, Hyung Sik

2017-09-01

Skeletal muscle depletion is an important prognostic factor in patients with chronic obstructive pulmonary disease (COPD); a recent study demonstrated significant correlations between pectoralis muscle area on an axial CT image and COPD-related traits. The purpose of this study was to evaluate the relation between pectoralis muscle areas on CT scans and total body skeletal muscle mass (SMM) in healthy subjects. For 434 subjects that underwent a low-dose chest CT and bioelectrical impedance analysis (BIA) during health screening from January to June of 2014, cross-sectional area of pectoralis muscles were measured in CT scans. Pearson's correlation and multiple linear regression analysis were used to assess the relationship between cross-sectional CT areas of pectoralis muscles and BIA-assessed SMMs. Mean age was 50 ± 10 years (78·8% were male). The mean cross-sectional area of pectoralis muscles was 24·1 cm 2  ± 6·8. A moderate correlation was observed between pectoralis muscle area and BIA-based SMM (r = 0·665, P<0.001). Multivariable analysis showed CT determined pectoralis muscle area was significantly associated with BIA-assessed SMM after adjusting for gender, weight, height and age (β = 0·14 ± 0·02, P<0·001). Cross-sectional area of the pectoralis muscles on single axial CT images shows moderate correlation with total body SMM determined by BIA in healthy subjects. © 2015 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

A navigation system for percutaneous needle interventions based on PET/CT images: design, workflow and error analysis of soft tissue and bone punctures.

PubMed

Oliveira-Santos, Thiago; Klaeser, Bernd; Weitzel, Thilo; Krause, Thomas; Nolte, Lutz-Peter; Peterhans, Matthias; Weber, Stefan

2011-01-01

Percutaneous needle intervention based on PET/CT images is effective, but exposes the patient to unnecessary radiation due to the increased number of CT scans required. Computer assisted intervention can reduce the number of scans, but requires handling, matching and visualization of two different datasets. While one dataset is used for target definition according to metabolism, the other is used for instrument guidance according to anatomical structures. No navigation systems capable of handling such data and performing PET/CT image-based procedures while following clinically approved protocols for oncologic percutaneous interventions are available. The need for such systems is emphasized in scenarios where the target can be located in different types of tissue such as bone and soft tissue. These two tissues require different clinical protocols for puncturing and may therefore give rise to different problems during the navigated intervention. Studies comparing the performance of navigated needle interventions targeting lesions located in these two types of tissue are not often found in the literature. Hence, this paper presents an optical navigation system for percutaneous needle interventions based on PET/CT images. The system provides viewers for guiding the physician to the target with real-time visualization of PET/CT datasets, and is able to handle targets located in both bone and soft tissue. The navigation system and the required clinical workflow were designed taking into consideration clinical protocols and requirements, and the system is thus operable by a single person, even during transition to the sterile phase. Both the system and the workflow were evaluated in an initial set of experiments simulating 41 lesions (23 located in bone tissue and 18 in soft tissue) in swine cadavers. We also measured and decomposed the overall system error into distinct error sources, which allowed for the identification of particularities involved in the process as well as highlighting the differences between bone and soft tissue punctures. An overall average error of 4.23 mm and 3.07 mm for bone and soft tissue punctures, respectively, demonstrated the feasibility of using this system for such interventions. The proposed system workflow was shown to be effective in separating the preparation from the sterile phase, as well as in keeping the system manageable by a single operator. Among the distinct sources of error, the user error based on the system accuracy (defined as the distance from the planned target to the actual needle tip) appeared to be the most significant. Bone punctures showed higher user error, whereas soft tissue punctures showed higher tissue deformation error.

Prospective feasibility analysis of a novel off-line approach for MR-guided radiotherapy.

PubMed

Bostel, Tilman; Pfaffenberger, Asja; Delorme, Stefan; Dreher, Constantin; Echner, Gernot; Haering, Peter; Lang, Clemens; Splinter, Mona; Laun, Frederik; Müller, Marco; Jäkel, Oliver; Debus, Jürgen; Huber, Peter E; Sterzing, Florian; Nicolay, Nils H

2018-05-01

The present work aimed to analyze the feasibility of a shuttle-based MRI-guided radiation therapy (MRgRT) in the treatment of pelvic malignancies. 20 patients with pelvic malignancies were included in this prospective feasibility analysis. Patients underwent daily MRI in treatment position prior to radiotherapy at the German Cancer Research Center. Positional inaccuracies, time and patient compliance were assessed for the application of off-line MRgRT. In 78% of applied radiation fractions, MR imaging for position verification could be performed without problems. Additionally, treatment-related side effects and reduced patient compliance were only responsible for omission of MRI in 9% of radiation fractions. The study workflow took a median time of 61 min (range 47-99 min); duration for radiotherapy alone was 13 min (range 7-26 min). Patient positioning, MR imaging and CT imaging including patient repositioning and the shuttle transfer required median times of 10 min (range 7-14 min), 26 min (range 15-60 min), 5 min (range 3-8 min) and 8 min (range 2-36 min), respectively. To assess feasibility of shuttle-based MRgRT, the reference point coordinates for the x, y and z axis were determined for the MR images and CT obtained prior to the first treatment fraction and correlated with the coordinates of the planning CT. In our dataset, the median positional difference between MR imaging and CT-based imaging based on fiducial matching between MR and CT imaging was equal to or less than 2 mm in all spatial directions. The limited space in the MR scanner influenced patient selection, as the bore of the scanner had to accommodate the immobilization device and the constructed stereotactic frame. Therefore, obese, extremely muscular or very tall patients could not be included in this trial in addition to patients for whom exposure to MRI was generally judged inappropriate. This trial demonstrated for the first time the feasibility and patient compliance of a shuttle-based off-line approach to MRgRT of pelvic malignancies.

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

Li, B; Fujita, A; Buch, K

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIsmore » over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast, subtle texture changes in addition to human observers.« less

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

PubMed

Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

2017-10-18

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

Comparison of radiographic and computed tomographic measurement of pedicle and vertebral body dimensions in Koreans: the ratio of pedicle transverse diameter to vertebral body transverse diameter.

PubMed

Kang, Ki Ser; Song, Kwang-Sup; Lee, Jong Seok; Yang, Jae Jun; Song, In Sup

2011-03-01

This study was designed to investigate the characteristics of pedicle transverse diameters (PD), vertebral body transverse diameters (VBD), especially the ratios of PD/VBD (CT ratio), which has never been discussed, in Koreans using computed tomography (CT) scans and to evaluate the possibility of obtaining more accurate estimations of PD from plain radiographs using the CT ratios in each spine level. The T1-L5 vertebrae of 50 participants were analyzed prospectively with CT scans (CT-VBD and CT-PD), and the T9-L5 vertebrae of the same participants were investigated with plain radiographs (X-VBD and X-PD). The CT ratio had a higher correlation with the CT-PD (r2 = 0.630) from T1 to L5, especially in the lower thoracic and lumbar spine (T9-L5, r2 = 0.737). The correlation of VBDs between the two radiologic tools (r2 = 0.896) was higher than that of the PDs (r2 = 0.665). Based on the data, equations for the estimation of a more accurate PD from plain radiographs were developed as follows: estimated PD = estimated VBD × [1.014 × (X-VBD) + 0.152] × the mean CT ratio at each spinal level. The correlation between the estimated PD and the CT-PD (r2 = 0.852) was improved compared with that (r2 = 0.665) between the X-PD and the CT-PD. In conclusion, the CT ratio showed a very similar changing trends to CT-PD from T1 to L5 regardless of sex and body mass, and the measurement error of PD from only plain radiographs could be minimized using estimated VBD and the mean CT ratio at each spinal level.

CT perfusion imaging of the liver and the spleen in patients with cirrhosis: Is there a correlation between perfusion and portal venous hypertension?

PubMed

Talakić, Emina; Schaffellner, Silvia; Kniepeiss, Daniela; Mueller, Helmut; Stauber, Rudolf; Quehenberger, Franz; Schoellnast, Helmut

2017-10-01

To correlate hepatic and splenic CT perfusion parameters with hepatic venous pressure gradient (HVPG) measurements in patients with cirrhosis. Twenty-one patients with cirrhosis (males, 17; females, 4; mean ± SD age, 57 ± 7 years) underwent hepatic and splenic perfusion CT on a 320-detector row volume scanner as well as invasive measurement of HVPG. Different CT perfusion algorithms (maximum slope analysis and Patlak plot) were used to measure hepatic arterial flow (HAF), portal venous flow (PVF), hepatic perfusion index (HPI), splenic arterial flow (SAF), splenic blood volume (SBV) and splenic clearance (SCL). Hepatic and splenic perfusion parameters were correlated with HVPG, and sensitivity and specificity for detection of severe portal hypertension (≥12 mmHg) were calculated. The Spearman correlation coefficient was -0.53 (p < 0.05) between SAF and HVPG, and -0.68 (p < 0.01) between HVPG and SCL. Using a cut-off value of 125 ml/min/100 ml for SCL, sensitivity for detection of a HVPG of ≥12 mmHg was 94%, and specificity 100%. There was no significant correlation between hepatic perfusion parameters and HVPG. CT perfusion in patients with cirrhosis showed a strong correlation between SCL and HVPG and may be used for detection of severe portal hypertension. • SAF and SCL are statistically significantly correlated with HVPG • SCL showed stronger correlation with HVPG than SAF • 125 ml/min/100 ml SCL-cut-off yielded 94 % sensitivity, 100 % specificity for severe PH • HAF, PVF and HPI showed no statistically significant correlation with HVPG.

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

NASA Astrophysics Data System (ADS)

Wang, Junliang; Yang, Jungang; Zhang, Jie; Wang, Xiaoxi; Zhang, Wenjun Chris

2018-07-01

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.

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.

Estimating Glenoid Width for Instability-Related Bone Loss: A CT Evaluation of an MRI Formula.

PubMed

Giles, Joshua W; Owens, Brett D; Athwal, George S

2015-07-01

Determining the magnitude of glenoid bone loss in cases of shoulder instability is an important step in selecting the optimal reconstructive procedure. Recently, a formula has been proposed that estimates native glenoid width based on magnetic resonance imaging (MRI) measurements of height (1/3 × glenoid height + 15 mm). This technique, however, has not been validated for use with computed tomography (CT), which is often the preferred imaging modality to assess bone deficiencies. The purpose of this project was 2-fold: (1) to determine if the MRI-based formula that predicts glenoid width from height is valid with CT and (2) to determine if a more accurate regression can be resolved for use specifically with CT data. Descriptive laboratory study. Ninety normal shoulder CT scans with preserved osseous anatomy were drawn from an existing database and analyzed. Measurements of glenoid height and width were performed by 2 observers on reconstructed 3-dimensional models. After assessment of reliability, the data were correlated, and regression models were created for male and female shoulders. The accuracy of the MRI-based model's predictions was then compared with that of the CT-based models. Intra- and interrater reliabilities were good to excellent for height and width, with intraclass correlation coefficients of 0.765 to 0.992. The height and width values had a strong correlation of 0.900 (P < .001). Regression analyses for male and female shoulders produced CT-specific formulas: for men, glenoid width = 2/3 × glenoid height + 5 mm; for women, glenoid width = 2/3 × glenoid height + 3 mm. Comparison of predictions from the MRI- and CT-specific formulas demonstrated good agreement (intraclass correlation coefficient = 0.818). The CT-specific formulas produced a root mean squared error of 1.2 mm, whereas application of the MRI-specific formula to CT images resulted in a root mean squared error of 1.5 mm. Use of the MRI-based formula on CT scans to predict glenoid width produced estimates that were nearly as accurate as the CT-specific formulas. The CT-specific formulas, however, are more accurate at predicting native glenoid width when applied to CT data. Imaging-specific (CT and MRI) formulas have been developed to estimate glenoid bone loss in patients with instability. The CT-specific formula can accurately predict native glenoid width, having an error of only 2.2% of average glenoid width. © 2015 The Author(s).

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

Tanabe, S; Utsunomiya, S; Abe, E

Purpose: To assess an accuracy of fiducial maker-based setup using ExacTrac (ExT-based setup) as compared with soft tissue-based setup using Cone-beam CT (CBCT-based setup) for patients with prostate cancer receiving intensity-modulated radiation therapy (IMRT) for the purpose of investigating whether ExT-based setup can be an alternative to CBCT-based setup. Methods: The setup accuracy was analyzed prospectively for 7 prostate cancer patients with implanted three fiducial markers received IMRT. All patients were treated after CBCT-based setup was performed and corresponding shifts were recorded. ExacTrac images were obtained before and after CBCT-based setup. The fiducial marker-based shifts were calculated based on thosemore » two images and recorded on the assumption that the setup correction was carried out by fiducial marker-based auto correction. Mean and standard deviation of absolute differences and the correlation between CBCT and ExT shifts were estimated. Results: A total of 178 image dataset were analyzed. On the differences between CBCT and ExT shifts, 133 (75%) of 178 image dataset resulted in smaller differences than 3 mm in all dimensions. Mean differences in the anterior-posterior (AP), superior-inferior (SI), and left-right (LR) dimensions were 1.8 ± 1.9 mm, 0.7 ± 1.9 mm, and 0.6 ± 0.8 mm, respectively. The percentages of shift agreements within ±3 mm were 76% for AP, 90% for SI, and 100% for LR. The Pearson coefficient of correlation for CBCT and ExT shifts were 0.80 for AP, 0.80 for SI, and 0.65 for LR. Conclusion: This work showed that the accuracy of ExT-based setup was correlated with that of CBCT-based setup, implying that ExT-based setup has a potential ability to be an alternative to CBCT-based setup. The further work is to specify the conditions that ExT-based setup can provide the accuracy comparable to CBCT-based setup.« less

Segmentation-less Digital Rock Physics

NASA Astrophysics Data System (ADS)

Tisato, N.; Ikeda, K.; Goldfarb, E. J.; Spikes, K. T.

2017-12-01

In the last decade, Digital Rock Physics (DRP) has become an avenue to investigate physical and mechanical properties of geomaterials. DRP offers the advantage of simulating laboratory experiments on numerical samples that are obtained from analytical methods. Potentially, DRP could allow sparing part of the time and resources that are allocated to perform complicated laboratory tests. Like classic laboratory tests, the goal of DRP is to estimate accurately physical properties of rocks like hydraulic permeability or elastic moduli. Nevertheless, the physical properties of samples imaged using micro-computed tomography (μCT) are estimated through segmentation of the μCT dataset. Segmentation proves to be a challenging and arbitrary procedure that typically leads to inaccurate estimates of physical properties. Here we present a novel technique to extract physical properties from a μCT dataset without the use of segmentation. We show examples in which we use segmentation-less method to simulate elastic wave propagation and pressure wave diffusion to estimate elastic properties and permeability, respectively. The proposed method takes advantage of effective medium theories and uses the density and the porosity that are measured in the laboratory to constrain the results. We discuss the results and highlight that segmentation-less DRP is more accurate than segmentation based DRP approaches and theoretical modeling for the studied rock. In conclusion, the segmentation-less approach here presented seems to be a promising method to improve accuracy and to ease the overall workflow of DRP.

Poster — Thur Eve — 16: 4DCT simulation with synchronized contrast injection of liver SBRT patients

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

Karotki, A.; Korol, R.; Milot, L.

2014-08-15

Stereotactic body radiation therapy (SBRT) has recently emerged as a valid option for treating liver metastases. SBRT delivers highly conformai dose over a small number of fractions. As such it is particularly sensitive to the accuracy of target volume delineation by the radiation oncologist. However, contouring liver metastases remains challenging for the following reasons. First, the liver usually undergoes significant motion due to respiration. Second, liver metastases are often nearly indistinguishable from the surrounding tissue when using computed tomography (CT) for imaging making it difficult to identify and delineate them. Both problems can be overcome by using four dimensional CTmore » (4DCT) synchronized with intravenous contrast injection. We describe a novel CT simulation process which involves two 4DCT scans. The first scan captures the tumor and immediately surrounding tissue which in turn reduces the 4DCT scan time so that it can be optimally timed with intravenous contrast injection. The second 4DCT scan covers a larger volume and is used as the primary CT dataset for dose calculation, as well as patient setup verification on the treatment unit. The combination of two 4DCT scans, short and long, allows visualization of the liver metastases over all phases of breathing cycle while simultaneously acquiring long enough 4DCT dataset suitable for planning and patient setup verification.« less

Relationships among measurements obtained by use of computed tomography and radiography and scores of cartilage microdamage in hip joints with moderate to severe joint laxity of adult dogs.

PubMed

Lopez, Mandi J; Lewis, Brooke P; Swaab, Megan E; Markel, Mark D

2008-03-01

To evaluate correlations among measurements on radiographic and computed tomography (CT) images with articular cartilage microdamage in lax hip joints of dogs. 12 adult mixed-breed hounds. Pelvic CT and radiography were performed. Hip joints were harvested following euthanasia. Orthopedic Foundation for Animals (OFA) and PennHIP radiograph reports were obtained. Norberg angle (NA) and radiographic percentage femoral head coverage (RPC) were determined. Center-edge angle (CEA), horizontal toit externe angle (HTEA), ventral acetabular sector angle (VASA), dorsal acetabular sector angle (DASA), horizontal acetabular sector angle (HASA), acetabular index (AI), and CT percentage femoral head coverage (CPC) were measured on 2-dimensional CT images. Femoral head-acetabular shelf percentage was measured on sagittal 3-dimensional CT (SCT) and transverse 3-dimensional CT (TCT) images. Light microscopy was used to score joint cartilage. Relationships of OFA confirmation and PennHIP osteoarthritis scores with radiography, CT, and cartilage variables and relationships of cartilage scores with radiography and CT measurements were evaluated with Spearman rank correlations. Pearson correlation was used for relationships of distraction index (DI) with radiography, CT, and cartilage variables. Significant relationships included PennHIP osteoarthritis score with cartilage score, CEA, HTEA, DASA, AI, CPC, and TCT; OFA confirmation score with cartilage score, NA, RPC, CEA, HTEA, DASA, AI, CPC, and TCT; cartilage score with NA, RPC, CEA, HTEA, DASA, HASA, AI, and TCT; and DI with cartilage score, CEA, HTEA, DASA, HASA, AI, and CPC. CT appeared to be a valuable imaging modality for predicting cartilage microdamage in canine hip joints.

Defining the lateral edge of the femoroacetabular articulation: correlation analysis between radiographs and computed tomography.

PubMed

Mittal, Ashish; Bomar, James D; Jeffords, Megan E; Huang, Ming-Tung; Wenger, Dennis R; Upasani, Vidyadhar V

2016-10-01

The purpose of this study was to analyze the variation in measuring the lateral center edge angle of Wiberg (LCEA) using the lateral edge of the sourcil (LCEA-S) compared to the lateral edge of the acetabulum (LCEA-E), and to correlate these measurements with three-dimensional computed tomography (3D-CT)-based analysis of the femoroacetabular articulation. A retrospective analysis was performed on 24 patients (45 hips) treated for hip dysplasia at a single institution. All patients were required to have an anteroposterior (AP) pelvis radiograph and pelvic CT. LCEA-S and LCEA-E measurements were calculated from radiographs. Axial CT images were processed to standardize pelvic orientation and calculate the LCEA at three points (posterior, central, anterior) along the acetabular edge. Correlation analysis was used to evaluate radiographic and CT measures. Eight males and 16 females with an average age of 14.6 years were included. The LCEA-S (16.5° ± 2.0°) was found to be significantly less than the LCEA-E (26.0° ± 2.0°) (p < 0.001). The LCEA-S had the greatest correlation with the central measurement on the 3D-CT (r s = 0.893; p < 0.001). The LCEA-E had the greatest correlation with the anterior measurement on the 3D-CT (r = 0.834; p < 0.001). The LCEA can change significantly depending on the bony landmark used to define the lateral edge of the femoroacetabular articulation. The edge of the sourcil most closely correlates with the central weight-bearing portion of the articular surface on the 3D-CT and should be used to define the LCEA when treating patients with hip dysplasia. Level III, retrospective comparison study.

Applying a radiomics approach to predict prognosis of lung cancer patients

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Yan, Shiju; Wang, Yunzhi; Qian, Wei; Guan, Yubao; Zheng, Bin

2016-03-01

Radiomics is an emerging technology to decode tumor phenotype based on quantitative analysis of image features computed from radiographic images. In this study, we applied Radiomics concept to investigate the association among the CT image features of lung tumors, which are either quantitatively computed or subjectively rated by radiologists, and two genomic biomarkers namely, protein expression of the excision repair cross-complementing 1 (ERCC1) genes and a regulatory subunit of ribonucleotide reductase (RRM1), in predicting disease-free survival (DFS) of lung cancer patients after surgery. An image dataset involving 94 patients was used. Among them, 20 had cancer recurrence within 3 years, while 74 patients remained DFS. After tumor segmentation, 35 image features were computed from CT images. Using the Weka data mining software package, we selected 10 non-redundant image features. Applying a SMOTE algorithm to generate synthetic data to balance case numbers in two DFS ("yes" and "no") groups and a leave-one-case-out training/testing method, we optimized and compared a number of machine learning classifiers using (1) quantitative image (QI) features, (2) subjective rated (SR) features, and (3) genomic biomarkers (GB). Data analyses showed relatively lower correlation among the QI, SR and GB prediction results (with Pearson correlation coefficients < 0.5 including between ERCC1 and RRM1 biomarkers). By using area under ROC curve as an assessment index, the QI, SR and GB based classifiers yielded AUC = 0.89+/-0.04, 0.73+/-0.06 and 0.76+/-0.07, respectively, which showed that all three types of features had prediction power (AUC>0.5). Among them, using QI yielded the highest performance.

Optimal Co-segmentation of Tumor in PET-CT Images with Context Information

PubMed Central

Song, Qi; Bai, Junjie; Han, Dongfeng; Bhatia, Sudershan; Sun, Wenqing; Rockey, William; Bayouth, John E.; Buatti, John M.

2014-01-01

PET-CT images have been widely used in clinical practice for radiotherapy treatment planning of the radiotherapy. Many existing segmentation approaches only work for a single imaging modality, which suffer from the low spatial resolution in PET or low contrast in CT. In this work we propose a novel method for the co-segmentation of the tumor in both PET and CT images, which makes use of advantages from each modality: the functionality information from PET and the anatomical structure information from CT. The approach formulates the segmentation problem as a minimization problem of a Markov Random Field (MRF) model, which encodes the information from both modalities. The optimization is solved using a graph-cut based method. Two sub-graphs are constructed for the segmentation of the PET and the CT images, respectively. To achieve consistent results in two modalities, an adaptive context cost is enforced by adding context arcs between the two subgraphs. An optimal solution can be obtained by solving a single maximum flow problem, which leads to simultaneous segmentation of the tumor volumes in both modalities. The proposed algorithm was validated in robust delineation of lung tumors on 23 PET-CT datasets and two head-and-neck cancer subjects. Both qualitative and quantitative results show significant improvement compared to the graph cut methods solely using PET or CT. PMID:23693127

A generic framework to simulate realistic lung, liver and renal pathologies in CT imaging

NASA Astrophysics Data System (ADS)

Solomon, Justin; Samei, Ehsan

2014-11-01

Realistic three-dimensional (3D) mathematical models of subtle lesions are essential for many computed tomography (CT) studies focused on performance evaluation and optimization. In this paper, we develop a generic mathematical framework that describes the 3D size, shape, contrast, and contrast-profile characteristics of a lesion, as well as a method to create lesion models based on CT data of real lesions. Further, we implemented a technique to insert the lesion models into CT images in order to create hybrid CT datasets. This framework was used to create a library of realistic lesion models and corresponding hybrid CT images. The goodness of fit of the models was assessed using the coefficient of determination (R2) and the visual appearance of the hybrid images was assessed with an observer study using images of both real and simulated lesions and receiver operator characteristic (ROC) analysis. The average R2 of the lesion models was 0.80, implying that the models provide a good fit to real lesion data. The area under the ROC curve was 0.55, implying that the observers could not readily distinguish between real and simulated lesions. Therefore, we conclude that the lesion-modeling framework presented in this paper can be used to create realistic lesion models and hybrid CT images. These models could be instrumental in performance evaluation and optimization of novel CT systems.

A shape prior-based MRF model for 3D masseter muscle segmentation

NASA Astrophysics Data System (ADS)

Majeed, Tahir; Fundana, Ketut; Lüthi, Marcel; Beinemann, Jörg; Cattin, Philippe

2012-02-01

Medical image segmentation is generally an ill-posed problem that can only be solved by incorporating prior knowledge. The ambiguities arise due to the presence of noise, weak edges, imaging artifacts, inhomogeneous interior and adjacent anatomical structures having similar intensity profile as the target structure. In this paper we propose a novel approach to segment the masseter muscle using the graph-cut incorporating additional 3D shape priors in CT datasets, which is robust to noise; artifacts; and shape deformations. The main contribution of this paper is in translating the 3D shape knowledge into both unary and pairwise potentials of the Markov Random Field (MRF). The segmentation task is casted as a Maximum-A-Posteriori (MAP) estimation of the MRF. Graph-cut is then used to obtain the global minimum which results in the segmentation of the masseter muscle. The method is tested on 21 CT datasets of the masseter muscle, which are noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. the very common dental fillings and dental implants. We show that the proposed technique produces clinically acceptable results to the challenging problem of muscle segmentation, and further provide a quantitative and qualitative comparison with other methods. We statistically show that adding additional shape prior into both unary and pairwise potentials can increase the robustness of the proposed method in noisy datasets.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

NASA Astrophysics Data System (ADS)

McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

2017-06-01

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images.

PubMed

McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; Connell, Dylan O'; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

2017-06-07

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

PubMed Central

McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D’Souza, Derek; Thomas, David; Connell, Dylan O’; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

2017-01-01

Abstract Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated. PMID:28195833

Relationship between Hounsfield unit in CT scan and gray scale in CBCT

NASA Astrophysics Data System (ADS)

Kamaruddin, Noorshaida; Rajion, Zainul Ahmad; Yusof, Asilah; Aziz, Mohd Ezane

2016-12-01

Cone-beam computed tomography (CBCT) is an imaging system which has advantages over computed tomography (CT). Recently, CBCT has become widely used for oral and maxillofacial imaging. In CT scan, Hounsfield Unit (HU) is proportional to the degree of x-ray attenuation by the tissue. In CBCT, the degree of x-ray attenuation is shown by gray scale (voxel value). The aim of the present (in vitro) study was to investigate the relationship between gray scale in CBCT and HU in CT scan. In this descriptive study, the anthropomorphic head phantom was scanned with CBCT and CT scanner. Gray scales and HUs were detected on images at the crown of the teeth, trabecular and cortical bone of mandible. The images were analyzed to obtain the gray scale value and HU value. The obtained value then used to investigate the relationship between CBCT gray scales and HUs. For the statistical analysis, t-test, Pearson's correlation and regression analysis were used. The differences between the gray scale of CBCT and HU of CT were statistically not significant, whereas the Pearson's correlation coefficients demonstrated a statistically significant correlation between gray scale of CBCT and HU of CT values. Considering the fact that gray scale in CBCT is important in pre assessment evaluation of bone density before implant treatments, it is recommended because of the lower dose and cost compared to CT scan.

Correlations between quantitative fat–water magnetic resonance imaging and computed tomography in human subcutaneous white adipose tissue

PubMed Central

Gifford, Aliya; Walker, Ronald C.; Towse, Theodore F.; Brian Welch, E.

2015-01-01

Abstract. Beyond estimation of depot volumes, quantitative analysis of adipose tissue properties could improve understanding of how adipose tissue correlates with metabolic risk factors. We investigated whether the fat signal fraction (FSF) derived from quantitative fat–water magnetic resonance imaging (MRI) scans at 3.0 T correlates to CT Hounsfield units (HU) of the same tissue. These measures were acquired in the subcutaneous white adipose tissue (WAT) at the umbilical level of 21 healthy adult subjects. A moderate correlation exists between MRI- and CT-derived WAT values for all subjects, R2=0.54, p<0.0001, with a slope of −2.6, (95% CI [−3.3,−1.8]), indicating that a decrease of 1 HU equals a mean increase of 0.38% FSF. We demonstrate that FSF estimates obtained using quantitative fat–water MRI techniques correlate with CT HU values in subcutaneous WAT, and therefore, MRI-based FSF could be used as an alternative to CT HU for assessing metabolic risk factors. PMID:26702407

Principal component analysis of the CT density histogram to generate parametric response maps of COPD

NASA Astrophysics Data System (ADS)

Zha, N.; Capaldi, D. P. I.; Pike, D.; McCormack, D. G.; Cunningham, I. A.; Parraga, G.

2015-03-01

Pulmonary x-ray computed tomography (CT) may be used to characterize emphysema and airways disease in patients with chronic obstructive pulmonary disease (COPD). One analysis approach - parametric response mapping (PMR) utilizes registered inspiratory and expiratory CT image volumes and CT-density-histogram thresholds, but there is no consensus regarding the threshold values used, or their clinical meaning. Principal-component-analysis (PCA) of the CT density histogram can be exploited to quantify emphysema using data-driven CT-density-histogram thresholds. Thus, the objective of this proof-of-concept demonstration was to develop a PRM approach using PCA-derived thresholds in COPD patients and ex-smokers without airflow limitation. Methods: Fifteen COPD ex-smokers and 5 normal ex-smokers were evaluated. Thoracic CT images were also acquired at full inspiration and full expiration and these images were non-rigidly co-registered. PCA was performed for the CT density histograms, from which the components with the highest eigenvalues greater than one were summed. Since the values of the principal component curve correlate directly with the variability in the sample, the maximum and minimum points on the curve were used as threshold values for the PCA-adjusted PRM technique. Results: A significant correlation was determined between conventional and PCA-adjusted PRM with 3He MRI apparent diffusion coefficient (p<0.001), with CT RA950 (p<0.0001), as well as with 3He MRI ventilation defect percent, a measurement of both small airways disease (p=0.049 and p=0.06, respectively) and emphysema (p=0.02). Conclusions: PRM generated using PCA thresholds of the CT density histogram showed significant correlations with CT and 3He MRI measurements of emphysema, but not airways disease.

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.

Critical thinking, self-esteem, and state anxiety of nursing students.

PubMed

Suliman, Wafika A; Halabi, Jehad

2007-02-01

This study aimed at exploring the existing predominant critical thinking disposition(s) of baccalaureate nursing students and the relationship among their critical thinking (CT), self-esteem (SE), and state anxiety (SA). Cross-sectional correlational design was utilized to achieve the said aim. A voluntary convenient sample consisted of first year (n=105) and fourth year (n=60) nursing students. The California Critical Thinking Disposition Inventory, Rosenberg Self-Esteem Scale, and Spielberger State Anxiety Inventory were used for data collection after their translation to Arabic language and test for validity and reliability. Descriptive and inferential statistics were used to analyze data. Results showed that both groups overall CT was marginal indicating no serious deficiency, their SE was average, and their SA was relatively high; they reported analyticity, open-mindedness, systematicity, inquisitiveness, and truth seeking as predominant critical thinking dispositions with no significant difference between them. However, the two groups were weak with significant difference on CT self-confidence (t=-2.053, df=136.904, p=.042) with beginning students reporting poorer level of CT self-confidence. Significant correlation results showed that critical thinking is positively correlated with SE, negatively correlated with SA, and SE is negatively correlated with SA; however, all correlations were actually quite low.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets.

PubMed

Mainali, Kumar P; Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V; Karig, David; Fagan, William F

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

Registration of human skull computed tomography data to an ultrasound treatment space using a sparse high frequency ultrasound hemispherical array

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

O’Reilly, Meaghan A., E-mail: moreilly@sri.utoront

Purpose: Transcranial focused ultrasound (FUS) shows great promise for a range of therapeutic applications in the brain. Current clinical investigations rely on the use of magnetic resonance imaging (MRI) to monitor treatments and for the registration of preoperative computed tomography (CT)-data to the MR images at the time of treatment to correct the sound aberrations caused by the skull. For some applications, MRI is not an appropriate choice for therapy monitoring and its cost may limit the accessibility of these treatments. An alternative approach, using high frequency ultrasound measurements to localize the skull surface and register CT data to themore » ultrasound treatment space, for the purposes of skull-related phase aberration correction and treatment targeting, has been developed. Methods: A prototype high frequency, hemispherical sparse array was fabricated. Pulse-echo measurements of the surface of five ex vivo human skulls were made, and the CT datasets of each skull were obtained. The acoustic data were used to rigidly register the CT-derived skull surface to the treatment space. The ultrasound-based registrations of the CT datasets were compared to the gold-standard landmark-based registrations. Results: The results show on an average sub-millimeter (0.9 ± 0.2 mm) displacement and subdegree (0.8° ± 0.4°) rotation registration errors. Numerical simulations predict that registration errors on this scale will result in a mean targeting error of 1.0 ± 0.2 mm and reduction in focal pressure of 1.0% ± 0.6% when targeting a midbrain structure (e.g., hippocampus) using a commercially available low-frequency brain prototype device (InSightec, 230 kHz brain system). Conclusions: If combined with ultrasound-based treatment monitoring techniques, this registration method could allow for the development of a low-cost transcranial FUS treatment platform to make this technology more widely available.« less

SU-G-JeP3-12: Use of Cone Beam CT and Deformable Image Registration for Assessing Geometrical and Dosimetric Variations During Lung Radiotherapy

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

Jurkovic, I; Stathakis, S; Markovic, M

Purpose: To assess the value of cone beam CT (CBCT) combined with deformable image registration in estimating the accuracy of the delivered treatment and the suitability of the applied target margins. Methods: Two patients with lung tumor were selected. Using their CT images intensity modulated radiation therapy (IMRT) treatment plans were developed to deliver 66Gy to the 95% of the PTV in 2Gy fractions. Using the Velocity AI software, the planning CT of each patient was registered with the fractional CBCT images that were obtained through the course of the treatment. After a CT to CBCT deformable image registration (DIR),more » the same fractional deformation matrix was used for the deformation of the planned dose distributions, as well as of all the contoured volumes, to each CBCT dataset. The dosimetric differences between the planning target volume (PTV) and various organs at risk (OARs) were recorded and compared. Results: CBCT data such as CTV volume change and PTV coverage was analyzed. There was a moderate relationship between volume changes and contouring method (automatic contouring using the DIR transformation vs. manual contouring on each CBCT) for patient #1 (r = 0.49), and a strong relationship for patient #2 (r = 0.83). The average PTV volume coverage from all the CBCT datasets was 91.2% for patient #1 and 95.6% for patient #2. Conclusion: Daily setup variations, tumor volume motion and lung deformation due to breathing yield differences in the actual delivered dose distributions versus the planned ones. The results presented indicate that these differences are apparent even with the use of daily IGRT. In certain fractions, the margins used seem to be insufficient to ensure acceptable lung tumor coverage. The observed differences notably depend on the tumor volume size and location. A larger cohort of patient is under investigation to verify those findings.« less

Registration of human skull computed tomography data to an ultrasound treatment space using a sparse high frequency ultrasound hemispherical array.

PubMed

O'Reilly, Meaghan A; Jones, Ryan M; Birman, Gabriel; Hynynen, Kullervo

2016-09-01

Transcranial focused ultrasound (FUS) shows great promise for a range of therapeutic applications in the brain. Current clinical investigations rely on the use of magnetic resonance imaging (MRI) to monitor treatments and for the registration of preoperative computed tomography (CT)-data to the MR images at the time of treatment to correct the sound aberrations caused by the skull. For some applications, MRI is not an appropriate choice for therapy monitoring and its cost may limit the accessibility of these treatments. An alternative approach, using high frequency ultrasound measurements to localize the skull surface and register CT data to the ultrasound treatment space, for the purposes of skull-related phase aberration correction and treatment targeting, has been developed. A prototype high frequency, hemispherical sparse array was fabricated. Pulse-echo measurements of the surface of five ex vivo human skulls were made, and the CT datasets of each skull were obtained. The acoustic data were used to rigidly register the CT-derived skull surface to the treatment space. The ultrasound-based registrations of the CT datasets were compared to the gold-standard landmark-based registrations. The results show on an average sub-millimeter (0.9 ± 0.2 mm) displacement and subdegree (0.8° ± 0.4°) rotation registration errors. Numerical simulations predict that registration errors on this scale will result in a mean targeting error of 1.0 ± 0.2 mm and reduction in focal pressure of 1.0% ± 0.6% when targeting a midbrain structure (e.g., hippocampus) using a commercially available low-frequency brain prototype device (InSightec, 230 kHz brain system). If combined with ultrasound-based treatment monitoring techniques, this registration method could allow for the development of a low-cost transcranial FUS treatment platform to make this technology more widely available.

Registration of human skull computed tomography data to an ultrasound treatment space using a sparse high frequency ultrasound hemispherical array

PubMed Central

O’Reilly, Meaghan A.; Jones, Ryan M.; Birman, Gabriel; Hynynen, Kullervo

2016-01-01

Purpose: Transcranial focused ultrasound (FUS) shows great promise for a range of therapeutic applications in the brain. Current clinical investigations rely on the use of magnetic resonance imaging (MRI) to monitor treatments and for the registration of preoperative computed tomography (CT)-data to the MR images at the time of treatment to correct the sound aberrations caused by the skull. For some applications, MRI is not an appropriate choice for therapy monitoring and its cost may limit the accessibility of these treatments. An alternative approach, using high frequency ultrasound measurements to localize the skull surface and register CT data to the ultrasound treatment space, for the purposes of skull-related phase aberration correction and treatment targeting, has been developed. Methods: A prototype high frequency, hemispherical sparse array was fabricated. Pulse-echo measurements of the surface of five ex vivo human skulls were made, and the CT datasets of each skull were obtained. The acoustic data were used to rigidly register the CT-derived skull surface to the treatment space. The ultrasound-based registrations of the CT datasets were compared to the gold-standard landmark-based registrations. Results: The results show on an average sub-millimeter (0.9 ± 0.2 mm) displacement and subdegree (0.8° ± 0.4°) rotation registration errors. Numerical simulations predict that registration errors on this scale will result in a mean targeting error of 1.0 ± 0.2 mm and reduction in focal pressure of 1.0% ± 0.6% when targeting a midbrain structure (e.g., hippocampus) using a commercially available low-frequency brain prototype device (InSightec, 230 kHz brain system). Conclusions: If combined with ultrasound-based treatment monitoring techniques, this registration method could allow for the development of a low-cost transcranial FUS treatment platform to make this technology more widely available. PMID:27587036

Evaluation of methods to produce an image library for automatic patient model localization for dose mapping during fluoroscopically guided procedures

NASA Astrophysics Data System (ADS)

Kilian-Meneghin, Josh; Xiong, Z.; Rudin, S.; Oines, A.; Bednarek, D. R.

2017-03-01

The purpose of this work is to evaluate methods for producing a library of 2D-radiographic images to be correlated to clinical images obtained during a fluoroscopically-guided procedure for automated patient-model localization. The localization algorithm will be used to improve the accuracy of the skin-dose map superimposed on the 3D patient- model of the real-time Dose-Tracking-System (DTS). For the library, 2D images were generated from CT datasets of the SK-150 anthropomorphic phantom using two methods: Schmid's 3D-visualization tool and Plastimatch's digitally-reconstructed-radiograph (DRR) code. Those images, as well as a standard 2D-radiographic image, were correlated to a 2D-fluoroscopic image of a phantom, which represented the clinical-fluoroscopic image, using the Corr2 function in Matlab. The Corr2 function takes two images and outputs the relative correlation between them, which is fed into the localization algorithm. Higher correlation means better alignment of the 3D patient-model with the patient image. In this instance, it was determined that the localization algorithm will succeed when Corr2 returns a correlation of at least 50%. The 3D-visualization tool images returned 55-80% correlation relative to the fluoroscopic-image, which was comparable to the correlation for the radiograph. The DRR images returned 61-90% correlation, again comparable to the radiograph. Both methods prove to be sufficient for the localization algorithm and can be produced quickly; however, the DRR method produces more accurate grey-levels. Using the DRR code, a library at varying angles can be produced for the localization algorithm.

Quantification of interstitial fluid on whole body CT: comparison with whole body autopsy.

PubMed

Lo Gullo, Roberto; Mishra, Shelly; Lira, Diego A; Padole, Atul; Otrakji, Alexi; Khawaja, Ranish Deedar Ali; Pourjabbar, Sarvenaz; Singh, Sarabjeet; Shepard, Jo-Anne O; Digumarthy, Subba R; Kalra, Mannudeep K; Stone, James R

2015-12-01

Interstitial fluid accumulation can occur in pleural, pericardial, and peritoneal spaces, and subcutaneous tissue planes. The purpose of the study was to assess if whole body CT examination in a postmortem setting could help determine the presence and severity of third space fluid accumulation in the body. Our study included 41 human cadavers (mean age 61 years, 25 males and 16 females) who had whole-body postmortem CT prior to autopsy. All bodies were maintained in the morgue in the time interval between death and autopsy. Two radiologists reviewed the whole-body CT examinations independently to grade third space fluid in the pleura, pericardium, peritoneum, and subcutaneous space using a 5-point grading system. Qualitative CT grading for third space fluid was correlated with the amount of fluid found on autopsy and the quantitative CT fluid volume, estimated using a dedicated software program (Volume, Syngo Explorer, Siemens Healthcare). Moderate and severe peripheral edema was seen in 16/41 and 7/41 cadavers respectively. It is not possible to quantify anasarca at autopsy. Correlation between imaging data for third space fluid and the quantity of fluid found during autopsy was 0.83 for pleural effusion, 0.4 for pericardial effusion and 0.9 for ascites. The degree of anasarca was significantly correlated with the severity of ascites (p < 0.0001) but not with pleural or pericardial effusion. There was strong correlation between volumetric estimation and qualitative grading for anasarca (p < 0.0001) and pleural effusion (p < 0.0001). Postmortem CT can help in accurate detection and quantification of third space fluid accumulation. The quantity of ascitic fluid on postmortem CT can predict the extent of anasarca.

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.

PubMed

Humphries, Stephen M; Yagihashi, Kunihiro; Huckleberry, Jason; Rho, Byung-Hak; Schroeder, Joyce D; Strand, Matthew; Schwarz, Marvin I; Flaherty, Kevin R; Kazerooni, Ella A; van Beek, Edwin J R; Lynch, David A

2017-10-01

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ 2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ 2 tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.

Contrast-Enhanced C-arm Computed Tomography Imaging of Myocardial Infarction in the Interventional Suite

PubMed Central

Girard, Erin E; Al-Ahmad, Amin; Rosenberg, Jarrett; Luong, Richard; Moore, Teri; Lauritsch, Günter; Chan, Frandics; Lee, David P.; Fahrig, Rebecca

2014-01-01

Objectives Cardiac C-arm CT uses a standard C-arm fluoroscopy system rotating around the patient to provide CT-like images during interventional procedures without moving the patient to a conventional CT scanner. We hypothesize that C-arm computed tomography (CT) can be used to visualize and quantify the size of perfusion defects and late enhancement resulting from a myocardial infarction (MI) using contrast enhanced techniques similar to previous CT and magnetic resonance imaging studies. Materials and Methods A balloon occlusion followed by reperfusion in a coronary artery was used to study acute and subacute MI in 12 swine. ECG-gated C-arm CT images were acquired the day of infarct creation (n=6) or 4 weeks after infarct creation (n = 6). Images were acquired immediately following contrast injection, then at 1 minute, and every 5 minutes up to 30 minutes with no additional contrast. The volume of the infarct as measured on C-arm CT was compared against pathology. Results The volume of acute MI, visualized as a combined region of hyperenhancement with a hypoenhanced core, correlated well with pathologic staining (concordance correlation = 0.89, p<0.0001, mean difference = 0.67±2.98 cm3). The volume of subacute MI, visualized as a region of hyperenhancement, correlated well with pathologic staining at imaging times 5–15 minutes following contrast injection (concordance correlation = 0.82, p<.001, mean difference = −0.64±1.94 cm3). Conclusions C-arm CT visualization of acute and subacute myocardial infarction is possible in a porcine model but improvement in the imaging technique is important before clinical use. Visualization of MI in the catheterization lab may be possible and could provide 3D images for guidance during interventional procedures. PMID:25635589

The assessment of renal cortex and parenchymal volume using automated CT volumetry for predicting renal function after donor nephrectomy.

PubMed

Mitsui, Yosuke; Sadahira, Takuya; Araki, Motoo; Wada, Koichiro; Tanimoto, Ryuta; Ariyoshi, Yuichi; Kobayashi, Yasuyuki; Watanabe, Masami; Watanabe, Toyohiko; Nasu, Yasutomo

2018-04-01

Contrast-enhanced CT is necessary before donor nephrectomy and is usually combined with a Tc-99m-mercapto-acetyltriglycine (MAG3) scan to check split renal function (SRF). However, all transplant programs do not use MAG3 because of its high cost and exposure to radiation. We examined whether CT volumetry of the kidney can be a new tool for evaluating SRF. Sixty-three patients underwent live donor nephrectomy. Patients without a 1.0 mm slice CT or follow-up for <12 months were excluded leaving 34 patients' data being analyzed. SRF was measured by MAG3. Split renal volume (SRV) was calculated automatically using volume analyzer software. The correlation between SRF and SRV was examined. The association between the donor's postoperative estimated glomerular filtration rate (eGFR) and predicted eGFR calculated by MAG3 or CT volumetry was analyzed at 1, 3, and 12 months post nephrectomy. Strong correlations were observed preoperatively in a Bland-Altman plot between SRF measured by MAG3 and either CT cortex or parenchymal volumetry. In addition, eGFR after donation correlated with SRF measured by MAG3 or CT volumetry. The correlation coefficients (R) for eGFR Mag3 split were 0.755, 0.615, and 0.763 at 1, 3 and 12 months, respectively. The corresponding R values for cortex volume split were 0.679, 0.638, and 0.747. Those for parenchymal volume split were 0.806, 0.592, and 0.764. Measuring kidney by CT volumetry is a cost-effective alternative to MAG3 for evaluating SRF and predicting postoperative donor renal function. Both cortex and parenchymal volumetry were similarly effective.

Patient-specific radiation dose and cancer risk estimation in pediatric chest CT: a study in 30 patients

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2010-04-01

Radiation-dose awareness and optimization in CT can greatly benefit from a dosereporting system that provides radiation dose and cancer risk estimates specific to each patient and each CT examination. Recently, we reported a method for estimating patientspecific dose from pediatric chest CT. The purpose of this study is to extend that effort to patient-specific risk estimation and to a population of pediatric CT patients. Our study included thirty pediatric CT patients (16 males and 14 females; 0-16 years old), for whom full-body computer models were recently created based on the patients' clinical CT data. Using a validated Monte Carlo program, organ dose received by the thirty patients from a chest scan protocol (LightSpeed VCT, 120 kVp, 1.375 pitch, 40-mm collimation, pediatric body scan field-of-view) was simulated and used to estimate patient-specific effective dose. Risks of cancer incidence were calculated for radiosensitive organs using gender-, age-, and tissue-specific risk coefficients and were used to derive patientspecific effective risk. The thirty patients had normalized effective dose of 3.7-10.4 mSv/100 mAs and normalized effective risk of 0.5-5.8 cases/1000 exposed persons/100 mAs. Normalized lung dose and risk of lung cancer correlated strongly with average chest diameter (correlation coefficient: r = -0.98 to -0.99). Normalized effective risk also correlated strongly with average chest diameter (r = -0.97 to -0.98). These strong correlations can be used to estimate patient-specific dose and risk prior to or after an imaging study to potentially guide healthcare providers in justifying CT examinations and to guide individualized protocol design and optimization.

SU-D-206-05: A Critical Look at CBCT-Based Dose Calculation Accuracy as It Is Applied to Adaptive Radiotherapy

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

Bejarano Buele, A; Sperling, N; Parsai, E

2016-06-15

Purpose: Cone-beam CTs (CBCT) obtained from On-Board Imaging Devices (OBI) are increasingly being used for dose calculation purposes in adaptive radiotherapy. Patient and target morphology are monitored and the treatment plan is updated using CBCT. Due to the difference in image acquisition parameters, dose calculated in a CBCT can differ from planned dose. We evaluate the difference between dose calculation in kV CBCT and simulation CT, and the effect of HU-density tables in dose discrepancies Methods: HU values for various materials were obtained using a Catphan 504 phantom for a simulator CT (CTSIM) and two different OBI systems using threemore » imaging protocols: Head, Thorax and Pelvis. HU-density tables were created in the TPS for each OBI image protocol. Treatment plans were made on each Catphan 504 dataset and on the head, thorax and pelvis sections of an anthropomorphic phantom, with and without the respective HU-density table. DVH information was compared among OBI systems and planning CT. Results: Dose calculations carried on the Catphan 504 CBCTs, with and without the respective CT-density table, had a maximum difference of −0.65% from the values on the planning CT. The use of the respective HU-density table decreased the percent differences from planned values by half in most of the protocols. For the anthropomorphic phantom datasets, the use of the correct HU-density table reduced differences by 0.89% on OBI1 and 0.59% on OBI2 for the head, 0.49% on OBI1 for the thorax, and 0.25% on OBI2 for the pelvis. Differences from planned values without HU-density correction ranged from 3.13% (OBI1, thorax) to 0.30% (OBI2, thorax). Conclusion: CT-density tables in the TPS yield acceptable differences when used in partly homogeneous medium. Further corrections are needed when the medium contains pronounced density differences for accurate CBCT calculation. Current difference range (1–3%) can be clinically acceptable.« less

WE-AB-202-08: Feasibility of Single-Inhalation/Single-Energy Xenon CT for High-Resolution Imaging of Regional Lung Ventilation in Humans

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

Pinkham, D; Schueler, E; Diehn, M

Purpose: To demonstrate the efficacy of a novel functional lung imaging method that utilizes single-inhalation, single-energy xenon CT (Xe-CT) lung ventilation scans, and to compare it against the current clinical standard, ventilation single-photon emission CT (V-SPECT). Methods: In an IRB-approved clinical study, 14 patients undergoing thoracic radiotherapy received two successive single inhalation, single energy (80keV) CT images of the entire lung using 100% oxygen and a 70%/30% xenon-oxygen mixture. A subset of ten patients also received concurrent SPECT ventilation scans. Anatomic reproducibility between the two scans was achieved using a custom video biofeedback apparatus. The CT images were registered tomore » each other by deformable registration, and a calculated difference image served as surrogate xenon ventilation map. Both lungs were partitioned into twelve sectors, and a sector-wise correlation was performed between the xenon and V-SPECT scans. A linear regression model was developed with forced expiratory volume (FEV) as a predictor and the coefficient of variation (CoV) as the outcome. Results: The ventilation comparison for five of the patients had either moderate to strong Pearson correlation coefficients (0.47 to 0.69, p<0.05). Of these, four also had moderate to strong Spearman correlation coefficients (0.46 to 0.80, p<0.03). The patients with the strongest correlation had clear regional ventilation deficits. The patient comparisons with the weakest correlations had more homogeneous ventilation distributions, and those patients also had diminished lung function as assessed by spirometry. Analysis of the relationship between CoV and FEV yielded a non-significant trend toward negative correlation (Pearson coefficient −0.60, p<0.15). Conclusion: Significant correlations were found between the Xe-CT and V-SPECT ventilation imagery. The results from this small cohort of patients indicate that single inhalation, single energy Xe-CT has the potential to quantify regional lung ventilation volumetrically with high resolution using widely accessible radiologic equipment. Bill Loo and Peter Maxim are founders of TibaRay, Inc. Bill Loo is also a board member. Bill Loo and Peter Maxim have received research grants from Varian Medical Systems, Inc. and RaySearch Laboratory.« less

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

Lopez Torres, E., E-mail: Ernesto.Lopez.Torres@cern.ch, E-mail: cerello@to.infn.it; Fiorina, E.; Pennazio, F.

Purpose: M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. Methods: M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number ofmore » features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. Results: The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. Conclusions: The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.« less

orbital selective correlation reduce in collapse tetragonal phase of CaFe2(As0.935P0.065)2 and electronic structure reconstruction studied by angel resolved photoemission spectroscopy

NASA Astrophysics Data System (ADS)

Zeng, Lingkun

We performed an angle-resolved photoemission spectroscopy (ARPES) study of the CaFe2(As0.935P0.065)2 in the collapse tetragonal(CT) phase and uncollapse tetragonal(UCT) phase. We find in the CT phase the electronic correlation dramatically reduces respective to UCT phase. Meanwhile, the reduction of correlation in CT phase show an orbital selective effect: correlation in dxy reduces the most, and then dxz/yz, while the one in dz2-r2 almost keeps the same. In CT phase, almost all bands sink downwards to higher binding energy, leading to the hole like bands around Brillouin zone(BZ) center sink below EF compared with UCT phase. However, the electron pocket around Brillouin Zone(BZ) corner(M) in UCT phase, forms a hole pocket around BZ center(Z point) in CT phase. Moreover, the dxy exhibits larger movement down to higher binding energy, resulting in farther away from dyz/xz and closer to dxy.We propose the electron filling ,namely high spin state in UCT phase to low spin state in CT phase(due to competing between crystal structure field and Hund's coupling), other than the Fermi surface nesting might be responsible for the absent of magnetic ordering.

[Effects of different tillage patterns on soil properties, maize yield and water use efficiency in Weibei Highland, China.

PubMed

Liu, Dan; Zhang, Xia; Li, Jun; Wang, Xu-Dong

2018-02-01

An eight-year field experiment of straw returning was conducted on dark loessial soil in Weibei Highland to investigate the effects of tillage patterns on soil aggregate, soil organic carbon (SOC), corn yield and soil water use efficiency (WUE). There were six tillage patterns, including conventional tillage (CT/CT), no-tillage (NT/NT), subsoiling tillage (ST/ST), no-tillage/subsoiling tillage (NT/ST), conventional tillage/no-tillage (CT/NT) and conventional tillage/subsoiling tillage (CT/ST). The results showed that compared with CT/CT, the patterns of NT/NT, ST/ST and the rotational tillage patterns (NT/ST, CT/NT and CT/ST) decreased the mean mass diameter of soil mechanical stable aggregate. The patterns of NT/NT, ST/ST and NT/ST increased the content of soil water-stable aggregate with the particle size >0.25 mm (WR 0.25 ) and their mean mass diameter, especially in the depth of 20-50 cm. These patterns reduced the proportion of aggregate destruction (PAD). Compared with CT/CT, the patterns of NT/ST, CT/NT, NT/NT and ST/ST increased the content of SOC in 0-10 cm soil layer. The content of SOC decreased as the increases of soil depth for all tillage patterns, but the decrease in SOC of three single tillage patterns (ST/ST, NT/NT and CT/CT) was larger than that of three rotational tillage patterns. Compared with CT/CT, the other five tillage patterns increased soil water storage in 0-200 cm soil profile, crop yield and WUE in maize. The yield and WUE in NT/ST pattern were significantly increased by 15.1% and 27.5%, respectively. Both corn yield and WUE were significantly and positively correlated with soil water storage in 0-200 cm soil profile in field during the cropping and fallow periods. Moreover, soil water storage during the cropping period was positively correlated with WR 0.25 , but negatively correlated with PAD in 0-50 cm soil layer. Particularly, maize yield, WUE and soil water storage during the cropping period were closely related to WR 0.25 in 20-50 cm soil layer and PAD. Both WUE and soil water storage during the cropping period was correlated with the SOC content in 0-10 cm soil layer. With respect to the soil properties, crop yield and WUE, the tillage pattern of NT/ST was the best stratety in dark loessial soil for spring maize growth in Weibei Highland.

Correlation of 68Ga Ventilation-Perfusion PET/CT with Pulmonary Function Test Indices for Assessing Lung Function.

PubMed

Le Roux, Pierre-Yves; Siva, Shankar; Steinfort, Daniel P; Callahan, Jason; Eu, Peter; Irving, Lou B; Hicks, Rodney J; Hofman, Michael S

2015-11-01

Pulmonary function tests (PFTs) are routinely used to assess lung function, but they do not provide information about regional pulmonary dysfunction. We aimed to assess correlation of quantitative ventilation-perfusion (V/Q) PET/CT with PFT indices. Thirty patients underwent V/Q PET/CT and PFT. Respiration-gated images were acquired after inhalation of (68)Ga-carbon nanoparticles and administration of (68)Ga-macroaggregated albumin. Functional volumes were calculated by dividing the volume of normal ventilated and perfused (%NVQ), unmatched and matched defects by the total lung volume. These functional volumes were correlated with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and diffusing capacity for carbon monoxide (DLCO). All functional volumes were significantly different in patients with chronic obstructive pulmonary disease (P < 0.05). FEV1/FVC and %NVQ had the highest correlation (r = 0.82). FEV1 was also best correlated with %NVQ (r = 0.64). DLCO was best correlated with the volume of unmatched defects (r = -0.55). Considering %NVQ only, a cutoff value of 90% correctly categorized 28 of 30 patients with or without significant pulmonary function impairment. Our study demonstrates strong correlations between V/Q PET/CT functional volumes and PFT parameters. Because V/Q PET/CT is able to assess regional lung function, these data support the feasibility of its use in radiation therapy and preoperative planning and assessing pulmonary dysfunction in a variety of respiratory diseases. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

The relation between magnetite and silicate fabric in granitoids of the Adamello Batholith

NASA Astrophysics Data System (ADS)

Schöpa, A.; Floess, D.; de Saint Blanquat, M.; Annen, C.; Launeau, P.

2015-02-01

The link between the macroscopic silicate fabric and the magnetite-controlled AMS (anisotropy of magnetic susceptibility) fabric in ferromagnetic rocks was investigated through a comprehensive comparison between different fabric measurement techniques. Sample lithologies include tonalites and granodiorites from the Lago della Vacca Complex, Adamello Batholith, Italy. The datasets used to assess the link between subfabrics and the coherence between methods include: 1) macroscopic silicate fabric measured directly in the field; 2) macroscopic silicate fabric derived from image analysis (IA) of outcrop pictures and sample pictures; 3) shape-preferred orientations (SPO) of mafic silicates, 4) SPO of magnetite, and 5) calculated distribution of magnetite grains from computer-assisted high-resolution X-ray tomography (X-ray CT) images; 6) fabrics derived from the AMS. Macroscopic mineral fabrics measured in the field agree with the IA results and with the SPO of mafic silicates obtained from the X-ray CT imaging. The X-ray CT results show that the SPO of the magnetite grains are consistent with the AMS data whereas the spatial distribution of the magnetite grains is less compatible with the AMS fabric. This implies that the AMS signal is mainly controlled by the shape of the magnetic carrier mineral rather than by the spatial arrangement of the magnetite grains. An exception is the presence of magnetite clusters. Furthermore, the SPO of mafic silicates and the SPO of the magnetite grains are consistent with the AMS data. Another finding of this study is that the magnetic susceptibility correlates linearly with the amount of magnetite in the samples. The coherent results obtained from a variety of methods reinforce the application of both AMS measurements and IA as robust tools to analyse fabrics in granitic intrusions.

Evaluation of Collaterals and Clot Burden Using Time-Resolved C-Arm Conebeam CT Angiography in the Angiography Suite: A Feasibility Study.

PubMed

Yang, P; Niu, K; Wu, Y; Struffert, T; Doerfler, A; Holter, P; Aagaard-Kienitz, B; Strother, C; Chen, G-H

2017-04-01

The assessment of collaterals and clot burden in patients with acute ischemic stroke provides important information about treatment options and clinical outcome. Time-resolved C-arm conebeam CT angiography has the potential to provide accurate and reliable evaluations of collaterals and clot burden in the angiographic suite. Experience with this technique is extremely limited, and feasibility studies are needed to validate this technique. Our purpose was to present such a feasibility study. Ten C-arm conebeam CT perfusion datasets from 10 subjects with acute ischemic stroke acquired before endovascular treatment were retrospectively processed to generate time-resolved conebeam CTA. From time-resolved conebeam CTA, 2 experienced readers evaluated the clot burden and collateral flow in consensus by using previously reported scoring systems and assessed the clinical value of this novel imaging technique independently. Interobserver agreement was analyzed by using the intraclass correlation analysis method. Clot burden and collateral flow can be assessed by using the commonly accepted scoring systems for all eligible cases. Additional clinical information (eg, the quantitative dynamic information of collateral flow) can be obtained from this new imaging technique. Two readers agreed that time-revolved C-arm conebeam CTA is the preferred method for evaluating the clot burden and collateral flow compared with other conventional imaging methods. Comprehensive evaluations of clot burden and collateral flow are feasible by using time-resolved C-arm conebeam CTA data acquired in the angiography suite. This technique further enriches the imaging tools in the angiography suite to enable a "one-stop- shop" imaging workflow for patients with acute ischemic stroke. © 2017 by American Journal of Neuroradiology.

Correlation between differential renal function estimation using CT-based functional renal parenchymal volume and (99m)Tc - DTPA renal scan.

PubMed

Sarma, Debanga; Barua, Sasanka K; Rajeev, T P; Baruah, Saumar J

2012-10-01

Nuclear renal scan is currently the gold standard imaging study to determine differential renal function. We propose helical CT as single modality for both the anatomical and functional evaluation of kidney with impaired function. In the present study renal parenchymal volume is measured and percent total renal volume is used as a surrogate marker for differential renal function. The objective of this study is to correlate between differential renal function estimation using CT-based renal parenchymal volume measurement with differential renal function estimation using (99m)TC - DTPA renal scan. Twenty-one patients with unilateral obstructive uropathy were enrolled in this prospective comparative study. They were subjected to (99m)Tc - DTPA renal scan and 64 slice helical CT scan which estimates the renal volume depending on the reconstruction of arterial phase images followed by volume rendering and percent renal volume was calculated. Percent renal volume was correlated with percent renal function, as determined by nuclear renal scan using Pearson coefficient. RESULTS AND OBSERVATION: A strong correlation is observed between percent renal volume and percent renal function in obstructed units (r = 0.828, P < 0.001) as well as in nonobstructed units (r = 0.827, P < 0.001). There is a strong correlation between percent renal volume determined by CT scan and percent renal function determined by (99m)TC - DTPA renal scan both in obstructed and in normal units. CT-based percent renal volume can be used as a single radiological tests for both functional and anatomical assessment of impaired renal units.

Automated Quantitative Computed Tomography Versus Visual Computed Tomography Scoring in Idiopathic Pulmonary Fibrosis: Validation Against Pulmonary Function.

PubMed

Jacob, Joseph; Bartholmai, Brian J; Rajagopalan, Srinivasan; Kokosi, Maria; Nair, Arjun; Karwoski, Ronald; Raghunath, Sushravya M; Walsh, Simon L F; Wells, Athol U; Hansell, David M

2016-09-01

The aim of the study was to determine whether a novel computed tomography (CT) postprocessing software technique (CALIPER) is superior to visual CT scoring as judged by functional correlations in idiopathic pulmonary fibrosis (IPF). A total of 283 consecutive patients with IPF had CT parenchymal patterns evaluated quantitatively with CALIPER and by visual scoring. These 2 techniques were evaluated against: forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), diffusing capacity for carbon monoxide (DLco), carbon monoxide transfer coefficient (Kco), and a composite physiological index (CPI), with regard to extent of interstitial lung disease (ILD), extent of emphysema, and pulmonary vascular abnormalities. CALIPER-derived estimates of ILD extent demonstrated stronger univariate correlations than visual scores for most pulmonary function tests (PFTs): (FEV1: CALIPER R=0.29, visual R=0.18; FVC: CALIPER R=0.41, visual R=0.27; DLco: CALIPER R=0.31, visual R=0.35; CPI: CALIPER R=0.48, visual R=0.44). Correlations between CT measures of emphysema extent and PFTs were weak and did not differ significantly between CALIPER and visual scoring. Intriguingly, the pulmonary vessel volume provided similar correlations to total ILD extent scored by CALIPER for FVC, DLco, and CPI (FVC: R=0.45; DLco: R=0.34; CPI: R=0.53). CALIPER was superior to visual scoring as validated by functional correlations with PFTs. The pulmonary vessel volume, a novel CALIPER CT parameter with no visual scoring equivalent, has the potential to be a CT feature in the assessment of patients with IPF and requires further exploration.

Brain CT scan indexes in the normal pressure hydrocephalus: predictive value in the outcome of patients and correlation to the clinical symptoms.

PubMed

Chatzidakis, Emmanuel M; Barlas, George; Condilis, Nicolas; Bouramas, Dimos; Anagnostopoulos, Demetrios; Volikas, Zacharias; Simopoulos, Konstantinos

2008-01-01

The aim of this study is to find out the correlation of the ventricular size of the brain, as it is estimated using brain computed tomography (CT) scan indexes in patients with normal pressure hydrocephalus (NPH), to: a) the clinical symptoms, and b) the results of cerebrospinal fluid (CSF) shunting procedures. We looked for any predictive value in the estimation of brain CT scan indexes, in patients as above, in whom a shunt is going to be placed. It is well known that it is very difficult to decide who is going to improve after shunting. We studied 40 cases of patients with the diagnosis "NPH" in whom the ventricular shunts were placed. Every symptom (motor disturbance, deficit of memory, incontinence) was separately evaluated preoperatively. The outcome of shunting was also evaluated and the patients were graded. The following CT scan indexes were estimated from the preoperative CT scans of the brain in every case: the ventricle-brain ratio (VBR), the bi-caudate and bi-frontal ratios, the third ventricle-Sylvian fissure (3V-SF) ratio, and the four largest cortical gyri. The method we have used for statistics is "one way analysis of variance", correlating the CT scan indexes to the symptoms of the patients preoperatively, and the outcome of them postoperatively. The main conclusion is that the size of the lateral ventricles of the brain preoperatively is not correlated to the outcome after CSF shunting surgery, but it is correlated to the symptoms of NPH preoperatively.

Evaluation of a new imaging tool for use with major trauma cases in the emergency department.

PubMed

Crönlein, Moritz; Holzapfel, Konstantin; Beirer, Marc; Postl, Lukas; Kanz, Karl-Georg; Pförringer, Dominik; Huber-Wagner, Stefan; Biberthaler, Peter; Kirchhoff, Chlodwig

2016-11-17

The aim of this study was to evaluate potential benefits of a new diagnostic software prototype (Trauma Viewer, TV) automatically reformatting computed tomography (CT) data on diagnostic speed and quality, compared to CT-image data evaluation using a conventional CT console. Multiple trauma CT data sets were analysed by one expert radiology and one expert traumatology fellow independently twice, once using the TV and once using the secondary conventional CT console placed in the CT control room. Actual analysis time and precision of diagnoses assessment were evaluated. The TV and CT-console results were compared respectively, but also a comparison to the initial multiple trauma CT reports assessed by emergency radiology fellows considered as the gold standard was performed. Finally, design and function of the Trauma Viewer were evaluated in a descriptive manner. CT data sets of 30 multiple trauma patients were enrolled. Mean time needed for analysis of one CT dataset was 2.43 min using the CT console and 3.58 min using the TV respectively. Thus, secondary conventional CT console analysis was on average 1.15 min shorter compared to the TV analysis. Both readers missed a total of 11 diagnoses using the secondary conventional CT console compared to 12 missed diagnoses using the TV. However, none of these overlooked diagnoses resulted in an Abbreviated Injury Scale (AIS) > 2 corresponding to life threatening injuries. Even though it took the two expert fellows a little longer to analyse the CT scans on the prototype TV compared to the CT console, which can be explained by the new user interface of the TV, our preliminary results demonstrate that, after further development, the TV might serve as a new diagnostic feature in the trauma room management. Its high potential to improve time and quality of CT-based diagnoses might help in fast decision making regarding treatment of severely injured patients.

Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring

PubMed Central

Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M. Iqbal Bin

2016-01-01

Segmentation of liver tumors from Computed Tomography (CT) and tumor burden analysis play an important role in the choice of therapeutic strategies for liver diseases and treatment monitoring. In this paper, a new segmentation method for liver tumors from contrast-enhanced CT imaging is proposed. As manual segmentation of tumors for liver treatment planning is both labor intensive and time-consuming, a highly accurate automatic tumor segmentation is desired. The proposed framework is fully automatic requiring no user interaction. The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. The accuracy of the proposed method was validated using a clinical liver dataset containing one of the highest numbers of tumors utilized for liver tumor segmentation containing 127 tumors in total with further validation of the results by a consultant radiologist. The proposed method was able to achieve one of the highest accuracies reported in the literature for liver tumor segmentation compared to other segmentation methods with a mean overlap error of 22.78 % and dice similarity coefficient of 0.75 in 3Dircadb dataset and a mean overlap error of 15.61 % and dice similarity coefficient of 0.81 in MIDAS dataset. The proposed method was able to outperform most other tumor segmentation methods reported in the literature while representing an overlap error improvement of 6 % compared to one of the best performing automatic methods in the literature. The proposed framework was able to provide consistently accurate results considering the number of tumors and the variations in tumor contrast enhancements and tumor appearances while the tumor burden was estimated with a mean error of 0.84 % in 3Dircadb dataset. PMID:27540353

Role of the Charge-Transfer State in Reduced Langevin Recombination in Organic Solar Cells: A Theoretical Study

PubMed Central

2015-01-01

Reduced Langevin recombination has been observed in organic solar cells (OSCs) for many years, but its origin is still unclear. A recent work by Burke et al. (Adv. Energy Mater.2015, 5, 1500123-1) was inspired by this reduced Langevin recombination, and they proposed an equilibrium model of charge-transfer (CT) states that correlates the open-circuit voltage of OSCs with experimentally available device parameters. In this work, we extend Burke et al.’s CT model further and for the first time directly correlate the reduced Langevin recombination with the energetic and dynamic behavior of the CT state. Recombination through CT states leads in a straightforward manner to a decrease in the Langevin reduction factor with increasing temperature, without explicit consideration of the temperature dependence of the mobility. To verify the correlation between the CT states and reduced Langevin recombination, we incorporated this CT model and the reduced Langevin model into drift-diffusion simulations of a bilayer OSC. The simulations not only successfully reproduced realistic current–voltage (J–V) characteristics of the bilayer OSC, but also demonstrate that the two models consistently lead to same value of the apparent Langevin reduction factor. PMID:26640611

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications

PubMed Central

Gleeson, Fergus V.; Brady, Michael; Schnabel, Julia A.

2018-01-01

Abstract. Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset. PMID:29662918

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications.

PubMed

Papież, Bartłomiej W; Franklin, James M; Heinrich, Mattias P; Gleeson, Fergus V; Brady, Michael; Schnabel, Julia A

2018-04-01

Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset.

Functional CAR models for large spatially correlated functional datasets.

PubMed

Zhang, Lin; Baladandayuthapani, Veerabhadran; Zhu, Hongxiao; Baggerly, Keith A; Majewski, Tadeusz; Czerniak, Bogdan A; Morris, Jeffrey S

2016-01-01

We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on functions defined on higher dimensional domains such as images. Through simulation studies, we demonstrate that accounting for the spatial correlation in our modeling leads to improved functional regression performance. Applied to a high-throughput spatially correlated copy number dataset, the model identifies genetic markers not identified by comparable methods that ignore spatial correlations.

Utility of Quantitative Parameters from Single-Photon Emission Computed Tomography/Computed Tomography in Patients with Destructive Thyroiditis.

PubMed

Kim, Ji-Young; Kim, Ji Hyun; Moon, Jae Hoon; Kim, Kyoung Min; Oh, Tae Jung; Lee, Dong-Hwa; So, Young; Lee, Won Woo

2018-01-01

Quantitative parameters from Tc-99m pertechnetate single-photon emission computed tomography/computed tomography (SPECT/CT) are emerging as novel diagnostic markers for functional thyroid diseases. We intended to assess the utility of SPECT/CT parameters in patients with destructive thyroiditis. Thirty-five destructive thyroiditis patients (7 males and 28 females; mean age, 47.3 ± 13.0 years) and 20 euthyroid patients (6 males and 14 females; mean age, 45.0 ± 14.8 years) who underwent Tc-99m pertechnetate quantitative SPECT/CT were retrospectively enrolled. Quantitative parameters from the SPECT/CT (%uptake, standardized uptake value [SUV], thyroid volume, and functional thyroid mass [SUVmean × thyroid volume]) and thyroid hormone levels were investigated to assess correlations and predict the prognosis for destructive thyroiditis. The occurrence of hypothyroidism was the outcome for prognosis. All the SPECT/CT quantitative parameters were significantly lower in the 35 destructive thyroiditis patients compared to the 20 euthyroid patients using the same SPECT/CT scanner and protocol ( p < 0.001 for all parameters). T3 and free T4 did not correlate with any SPECT/CT parameters, but thyroid-stimulating hormone (TSH) significantly correlated with %uptake ( p = 0.004), SUVmean ( p < 0.001), SUVmax ( p = 0.002), and functional thyroid mass ( p < 0.001). Of the 35 destructive thyroiditis patients, 16 progressed to hypothyroidism. On univariate and multivariate analyses, only T3 levels were associated with the later occurrence of hypothyroidism ( p = 0.002, exp(β) = 1.022, 95% confidence interval: 1.008 - 1.035). Novel quantitative SPECT/CT parameters could discriminate patients with destructive thyroiditis from euthyroid patients, suggesting the robustness of the quantitative SPECT/CT approach. However, disease progression of destructive thyroiditis could not be predicted using the parameters, as these only correlated with TSH, but not with T3, the sole predictor of the later occurrence of hypothyroidism.

Utility of Quantitative Parameters from Single-Photon Emission Computed Tomography/Computed Tomography in Patients with Destructive Thyroiditis

PubMed Central

Kim, Ji-Young; Kim, Ji Hyun; Moon, Jae Hoon; Kim, Kyoung Min; Oh, Tae Jung; Lee, Dong-Hwa; So, Young

2018-01-01

Objective Quantitative parameters from Tc-99m pertechnetate single-photon emission computed tomography/computed tomography (SPECT/CT) are emerging as novel diagnostic markers for functional thyroid diseases. We intended to assess the utility of SPECT/CT parameters in patients with destructive thyroiditis. Materials and Methods Thirty-five destructive thyroiditis patients (7 males and 28 females; mean age, 47.3 ± 13.0 years) and 20 euthyroid patients (6 males and 14 females; mean age, 45.0 ± 14.8 years) who underwent Tc-99m pertechnetate quantitative SPECT/CT were retrospectively enrolled. Quantitative parameters from the SPECT/CT (%uptake, standardized uptake value [SUV], thyroid volume, and functional thyroid mass [SUVmean × thyroid volume]) and thyroid hormone levels were investigated to assess correlations and predict the prognosis for destructive thyroiditis. The occurrence of hypothyroidism was the outcome for prognosis. Results All the SPECT/CT quantitative parameters were significantly lower in the 35 destructive thyroiditis patients compared to the 20 euthyroid patients using the same SPECT/CT scanner and protocol (p < 0.001 for all parameters). T3 and free T4 did not correlate with any SPECT/CT parameters, but thyroid-stimulating hormone (TSH) significantly correlated with %uptake (p = 0.004), SUVmean (p < 0.001), SUVmax (p = 0.002), and functional thyroid mass (p < 0.001). Of the 35 destructive thyroiditis patients, 16 progressed to hypothyroidism. On univariate and multivariate analyses, only T3 levels were associated with the later occurrence of hypothyroidism (p = 0.002, exp(β) = 1.022, 95% confidence interval: 1.008 – 1.035). Conclusion Novel quantitative SPECT/CT parameters could discriminate patients with destructive thyroiditis from euthyroid patients, suggesting the robustness of the quantitative SPECT/CT approach. However, disease progression of destructive thyroiditis could not be predicted using the parameters, as these only correlated with TSH, but not with T3, the sole predictor of the later occurrence of hypothyroidism. PMID:29713225

TH-E-17A-07: Improved Cine Four-Dimensional Computed Tomography (4D CT) Acquisition and Processing Method

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

Castillo, S; Castillo, R; Castillo, E

2014-06-15

Purpose: Artifacts arising from the 4D CT acquisition and post-processing methods add systematic uncertainty to the treatment planning process. We propose an alternate cine 4D CT acquisition and post-processing method to consistently reduce artifacts, and explore patient parameters indicative of image quality. Methods: In an IRB-approved protocol, 18 patients with primary thoracic malignancies received a standard cine 4D CT acquisition followed by an oversampling 4D CT that doubled the number of images acquired. A second cohort of 10 patients received the clinical 4D CT plus 3 oversampling scans for intra-fraction reproducibility. The clinical acquisitions were processed by the standard phasemore » sorting method. The oversampling acquisitions were processed using Dijkstras algorithm to optimize an artifact metric over available image data. Image quality was evaluated with a one-way mixed ANOVA model using a correlation-based artifact metric calculated from the final 4D CT image sets. Spearman correlations and a linear mixed model tested the association between breathing parameters, patient characteristics, and image quality. Results: The oversampling 4D CT scans reduced artifact presence significantly by 27% and 28%, for the first cohort and second cohort respectively. From cohort 2, the inter-replicate deviation for the oversampling method was within approximately 13% of the cross scan average at the 0.05 significance level. Artifact presence for both clinical and oversampling methods was significantly correlated with breathing period (ρ=0.407, p-value<0.032 clinical, ρ=0.296, p-value<0.041 oversampling). Artifact presence in the oversampling method was significantly correlated with amount of data acquired, (ρ=-0.335, p-value<0.02) indicating decreased artifact presence with increased breathing cycles per scan location. Conclusion: The 4D CT oversampling acquisition with optimized sorting reduced artifact presence significantly and reproducibly compared to the phase-sorted clinical acquisition.« less

Home environment: association with hyperactivity/impulsivity in children with ADHD and their non-ADHD siblings

PubMed Central

Mulligan, Aisling; Anney, Richard; Butler, Louise; O’Regan, Myra; Richardson, Thomas; Tulewicz, Edyta Maria; Fitzgerald, Michael; Gill, Michael

2011-01-01

Objective We wished to ascertain if there is an association between symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD) and home environment in children with ADHD and non-ADHD siblings, controlling for other environmental measures. Method 96 children with ADHD combined type (ADHD-CT) and their siblings participated in the study. Parent and teacher Conners’ rating scales were completed and home environment was assessed using the Middle Childhood and Early Adolescent Home Observation for Measurement of the Environment (HOME). ADHD symptoms were assessed for correlation with HOME in children with ADHD-CT and non-ADHD siblings and multiple regression analysis was used to control for gender, socio-economic status, exposure to nicotine, exposure to alcohol in utero, birth weight, gestational age, pregnancy and perinatal risk factors. The presence of oppositional disorders was assessed for association with HOME score in those with ADHD-CT. The multiple regression analysis was repeated controlling for environmental factors and for oppositional disorders in those with ADHD-CT. Oppositional symptoms were assessed for correlation with HOME score in non-ADHD siblings. Results Teacher-rated hyperactive/impulsive scores correlated with HOME (r = −.27, p <.01) in children with ADHD-CT. This association remained significant when other environmental factors and oppositional disorders were controlled for. Environmental factors and gender contributed to 30% of the variance of ADHD symptoms in ADHD-CT. Parent-rated hyperactive/impulsive scores also correlated with HOME (r = −.28, p < .05) for non-ADHD siblings. An association between HOME and diagnosis of oppositional defiant disorder or CD was found for children with ADHD-CT and between HOME and oppositional symptoms in non-ADHD siblings. Conclusions The home environment has a small but significant association with hyperactive/impulsive symptoms in children with ADHD-CT and non-ADHD siblings. This association remained when other environmental factors were taken into account. Oppositional symptoms are associated with home environment in ADHD-CT and in non-ADHD siblings. PMID:22168816

Xenon-enhanced CT using subtraction CT: Basic and preliminary clinical studies for comparison of its efficacy with that of dual-energy CT and ventilation SPECT/CT to assess regional ventilation and pulmonary functional loss in smokers.

PubMed

Ohno, Yoshiharu; Yoshikawa, Takeshi; Takenaka, Daisuke; Fujisawa, Yasuko; Sugihara, Naoki; Kishida, Yuji; Seki, Shinichiro; Koyama, Hisanobu; Sugimura, Kazuro

2017-01-01

To prospectively and directly compare the capability for assessments of regional ventilation and pulmonary functional loss in smokers of xenon-ventilation CT obtained with the dual-energy CT (DE-CT) and subtraction CT (Sub-CT) MATERIALS AND METHODS: Twenty-three consecutive smokers (15 men and 8 women, mean age: 69.7±8.7years) underwent prospective unenhanced and xenon-enhanced CTs, the latter by Sub-CT and DE-CT methods, ventilation SPECT and pulmonary function tests. Sub-CT was generated from unenhanced and xenon-enhanced CT, and all co-registered SPECT/CT data were produced from SPECT and unenhanced CT data. For each method, regional ventilation was assessed by using a 11-point scoring system on a per-lobe basis. To determine the functional lung volume by each method, it was also calculated for individual sublets with a previously reported method. To determine inter-observer agreement for each method, ventilation defect assessment was evaluated by using the χ2 test with weighted kappa statistics. For evaluation of the efficacy of each method for pulmonary functional loss assessment, functional lung volume was correlated with%FEV 1 . Each inter-observer agreement was rated as substantial (Sub-CT: κ=0.69, p<0.0001; DE-CT: κ=0.64, p<0.0001; SPECT/CT: κ=0.64, p<0.0001). Functional lung volume for each method showed significant to good correlation with%FEV 1 (Sub-CT: r=0.72, p=0.0001; DE-CT: r=0.74, p<0.0001; SPECT/CT: r=0.66, p=0.0006). Xenon-enhanced CT obtained by Sub-CT can be considered at least as efficacious as that obtained by DE-CT and SPECT/CT for assessment of ventilation abnormality and pulmonary functional loss in smokers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Determination of glomerular filtration rate (GFR) from fractional renal accumulation of iodinated contrast material: a convenient and rapid single-kidney CT-GFR technique.

PubMed

Yuan, XiaoDong; Tang, Wei; Shi, WenWei; Yu, Libao; Zhang, Jing; Yuan, Qing; You, Shan; Wu, Ning; Ao, Guokun; Ma, Tingting

2018-07-01

To develop a convenient and rapid single-kidney CT-GFR technique. One hundred and twelve patients referred for multiphasic renal CT and 99mTc-DTPA renal dynamic imaging Gates-GFR measurement were prospectively included and randomly divided into two groups of 56 patients each: the training group and the validation group. On the basis of the nephrographic phase images, the fractional renal accumulation (FRA) was calculated and correlated with the Gates-GFR in the training group. From this correlation a formula was derived for single-kidney CT-GFR calculation, which was validated by a paired t test and linear regression analysis with the single-kidney Gates-GFR in the validation group. In the training group, the FRA (x-axis) correlated well (r = 0.95, p < 0.001) with single-kidney Gates-GFR (y-axis), producing a regression equation of y = 1665x + 1.5 for single-kidney CT-GFR calculation. In the validation group, the difference between the methods of single-kidney GFR measurements was 0.38 ± 5.57 mL/min (p = 0.471); the regression line is identical to the diagonal (intercept = 0 and slope = 1) (p = 0.727 and p = 0.473, respectively), with a standard deviation of residuals of 5.56 mL/min. A convenient and rapid single-kidney CT-GFR technique was presented and validated in this investigation. • The new CT-GFR method takes about 2.5 min of patient time. • The CT-GFR method demonstrated identical results to the Gates-GFR method. • The CT-GFR method is based on the fractional renal accumulation of iodinated CM. • The CT-GFR method is achieved without additional radiation dose to the patient.

Comparison of 18F-FDG PET/CT and PET/MRI in patients with multiple myeloma

PubMed Central

Sachpekidis, Christos; Hillengass, Jens; Goldschmidt, Hartmut; Mosebach, Jennifer; Pan, Leyun; Schlemmer, Heinz-Peter; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2015-01-01

PET/MRI represents a promising hybrid imaging modality with several potential clinical applications. Although PET/MRI seems highly attractive in the diagnostic approach of multiple myeloma (MM), its role has not yet been evaluated. The aims of this prospective study are to evaluate the feasibility of 18F-FDG PET/MRI in detection of MM lesions, and to investigate the reproducibility of bone marrow lesions detection and quantitative data of 18F-FDG uptake between the functional (PET) component of PET/CT and PET/MRI in MM patients. The study includes 30 MM patients. All patients initially underwent 18F-FDG PET/CT (60 min p.i.), followed by PET/MRI (120 min p.i.). PET/CT and PET/MRI data were assessed and compared based on qualitative (lesion detection) and quantitative (SUV) evaluation. The hybrid PET/MRI system provided good image quality in all cases without artefacts. PET/MRI identified 65 of the 69 lesions, which were detectable with PET/CT (94.2%). Quantitative PET evaluations showed the following mean values in MM lesions: SUVaverage=5.5 and SUVmax=7.9 for PET/CT; SUVaverage=3.9 and SUVmax=5.8 for PET/MRI. Both SUVaverage and SUVmax were significantly higher on PET/CT than on PET/MRI. Spearman correlation analysis demonstrated a strong correlation between both lesional SUVaverage (r=0.744) and lesional SUVmax (r=0.855) values derived from PET/CT and PET/MRI. Regarding detection of myeloma skeletal lesions, PET/MRI exhibited equivalent performance to PET/CT. In terms of tracer uptake quantitation, a significant correlation between the two techniques was demonstrated, despite the statistically significant differences in lesional SUVs between PET/CT and PET/MRI. PMID:26550538

Patient-Specific Circulating Tumor DNA Detection during Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

PubMed

Riva, Francesca; Bidard, Francois-Clement; Houy, Alexandre; Saliou, Adrien; Madic, Jordan; Rampanou, Aurore; Hego, Caroline; Milder, Maud; Cottu, Paul; Sablin, Marie-Paule; Vincent-Salomon, Anne; Lantz, Olivier; Stern, Marc-Henri; Proudhon, Charlotte; Pierga, Jean-Yves

2017-03-01

In nonmetastatic triple-negative breast cancer (TNBC) patients, we investigated whether circulating tumor DNA (ctDNA) detection can reflect the tumor response to neoadjuvant chemotherapy (NCT) and detect minimal residual disease after surgery. Ten milliliters of plasma were collected at 4 time points: before NCT; after 1 cycle; before surgery; after surgery. Customized droplet digital PCR (ddPCR) assays were used to track tumor protein p53 ( TP53 ) mutations previously characterized in tumor tissue by massively parallel sequencing (MPS). Forty-six patients with nonmetastatic TNBC were enrolled. TP53 mutations were identified in 40 of them. Customized ddPCR probes were validated for 38 patients, with excellent correlation with MPS ( r = 0.99), specificity (≥2 droplets/assay), and sensitivity (at least 0.1%). At baseline, ctDNA was detected in 27/36 patients (75%). Its detection was associated with mitotic index ( P = 0.003), tumor grade ( P = 0.003), and stage ( P = 0.03). During treatment, we observed a drop of ctDNA levels in all patients but 1. No patient had detectable ctDNA after surgery. The patient with rising ctDNA levels experienced tumor progression during NCT. Pathological complete response (16/38 patients) was not correlated with ctDNA detection at any time point. ctDNA positivity after 1 cycle of NCT was correlated with shorter disease-free ( P < 0.001) and overall ( P = 0.006) survival. Customized ctDNA detection by ddPCR achieved a 75% detection rate at baseline. During NCT, ctDNA levels decreased quickly and minimal residual disease was not detected after surgery. However, a slow decrease of ctDNA level during NCT was strongly associated with shorter survival. © 2016 American Association for Clinical Chemistry.

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.

Prognostic value of CtIP/RBBP8 expression in breast cancer

PubMed Central

Soria-Bretones, Isabel; Sáez, Carmen; Ruíz-Borrego, Manuel; Japón, Miguel A; Huertas, Pablo

2013-01-01

CtIP/RBBP8 is a multifunctional protein involved in transcription, DNA replication, DNA repair by homologous recombination and the G1 and G2 checkpoints. Its multiple roles are controlled by its interaction with several specific factors, including the tumor suppressor proteins BRCA1 and retinoblastoma. Both its functions and interactors point to a putative oncogenic potential of CtIP/RBBP8 loss. However, CtIP/RBBP8 relevance in breast tumor appearance, development, and prognosis has yet to be established. We performed a retrospective analysis of CtIP/RBBP8 and RB1 levels by immunohistochemistry using 384 paraffin-embedded breast cancer biopsies obtained during tumor removal surgery. We have observed that low or no expression of CtIP/RBBP8 correlates with high-grade breast cancer and with nodal metastasis. Reduction on CtIP/RBBP8 is most common in hormone receptor (HR)-negative, HER2-positive, and basal-like tumors. We observed lower levels of RB1 on those tumors with reduced CtIP/RBBP8 levels. On luminal tumors, decreased but not absence of CtIP/RBBP8 levels correlate with increased disease-free survival when treated with a combination of hormone, radio, and chemo therapies. PMID:24403251

SU-F-J-199: Predictive Models for Cone Beam CT-Based Online Verification of Pencil Beam Scanning Proton Therapy

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

Yin, L; Lin, A; Ahn, P

Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal andmore » distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.« less

The Montage architecture for grid-enabled science processing of large, distributed datasets

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Katz, Daniel S .; Prince, Thomas; Berriman, Bruce G.; Good, John C.; Laity, Anastasia C.; Deelman, Ewa; Singh, Gurmeet; Su, Mei-Hui

2004-01-01

Montage is an Earth Science Technology Office (ESTO) Computational Technologies (CT) Round III Grand Challenge investigation to deploy a portable, compute-intensive, custom astronomical image mosaicking service for the National Virtual Observatory (NVO). Although Montage is developing a compute- and data-intensive service for the astronomy community, we are also helping to address a problem that spans both Earth and Space science, namely how to efficiently access and process multi-terabyte, distributed datasets. In both communities, the datasets are massive, and are stored in distributed archives that are, in most cases, remote from the available Computational resources. Therefore, state of the art computational grid technologies are a key element of the Montage portal architecture. This paper describes the aspects of the Montage design that are applicable to both the Earth and Space science communities.

Exploring the Correlation Between Nontraditional Variables and Student Success: A Longitudinal Study.

PubMed

Strickland, Haley Perkins; Cheshire, Michelle Haney

2017-06-01

The purpose of this project was to determine whether a correlation exists between the traditional admission criteria of grade point averages with the potential admission criteria of emotional intelligence (EI) scores or critical thinking (CT) scores to predict upper division student outcomes. A quantitative, longitudinal design was selected to examine the identified variables to predict undergraduate student success. The recruiting sample included a convenience sample drawn from 112 junior-level undergraduate nursing students beginning their first of a five-semester nursing program. EI and HESI ® CT scores did not significantly correlate with main analysis variables. Although EI and CT scores were not significant in this study, it remains vital to incorporate EI and CT activities throughout the curriculum to develop students' ability to think like a nurse and, therefore, be successful in nursing practice. [J Nurs Educ. 2017;56(6):351-355.]. Copyright 2017, SLACK Incorporated.

Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening.

PubMed

Nomura, Yukihiro; Higaki, Toru; Fujita, Masayo; Miki, Soichiro; Awaya, Yoshikazu; Nakanishi, Toshio; Yoshikawa, Takeharu; Hayashi, Naoto; Awai, Kazuo

2017-02-01

This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening. We selected 85 subjects who underwent both a low-dose CT (LD-CT) scan and an additional ULD-CT scan in our lung cancer screening program for high-risk populations. The LD-CT scans were reconstructed with filtered back projection (FBP; LD-FBP). The ULD-CT scans were reconstructed with FBP (ULD-FBP), adaptive iterative dose reduction 3D (AIDR 3D; ULD-AIDR 3D), and forward projected model-based IR solution (FIRST; ULD-FIRST). CAD software for lung nodules was applied to each image dataset, and the performance of the CAD software was compared among the different IR algorithms. The mean volume CT dose indexes were 3.02 mGy (LD-CT) and 0.30 mGy (ULD-CT). For overall nodules, the sensitivities of CAD software at 3.0 false positives per case were 78.7% (LD-FBP), 9.3% (ULD-FBP), 69.4% (ULD-AIDR 3D), and 77.8% (ULD-FIRST). Statistical analysis showed that the sensitivities of ULD-AIDR 3D and ULD-FIRST were significantly higher than that of ULD-FBP (P < .001). The performance of CAD software in ULD-CT was improved by using IR algorithms. In particular, the performance of CAD in ULD-FIRST was almost equivalent to that in LD-FBP. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Audit of radiation dose delivered in time-resolved four-dimensional computed tomography in a radiotherapy department.

PubMed

Hubbard, Patricia; Callahan, Jason; Cramb, Jim; Budd, Ray; Kron, Tomas

2015-06-01

To review the dose delivered to patients in time-resolved computed tomography (4D CT) used for radiotherapy treatment planning. 4D CT is used at Peter MacCallum Cancer Centre since July 2007 for radiotherapy treatment planning using a Philips Brilliance Wide Bore CT scanner (16 slice, helical 4D CT acquisition). All scans are performed at 140 kVp and reconstructed in 10 datasets for different phases of the breathing cycle. Dose records were analysed retrospectively for 387 patients who underwent 4D CT procedures between 2007 and 2013. A total of 444 4D CT scans were acquired with the majority of them (342) being for lung cancer radiotherapy. Volume CT dose index (CTDIvol) as recorded over this period was fairly constant at approximately 20 mGy for adults. The CTDI for 4D CT for lung cancers of 19.6 ± 9.3 mGy (n = 168, mean ± 1SD) was found to be 63% higher than CTDIs for conventional CT scans for lung patients that were acquired in the same period (CTDIvol 12 ± 4 mGy, sample of n = 25). CTDI and dose length product (DLP) increased with increasing field of view; however, no significant difference between DLPs for different indications (breast, kidney, liver and lung) could be found. Breathing parameters such as breathing rate or pattern did not affect dose. 4D CT scans can be acquired for radiotherapy treatment planning with a dose less than twice the one required for conventional CT scanning. © 2015 The Royal Australian and New Zealand College of Radiologists.

Clinical evaluation of respiration-induced attenuation uncertainties in pulmonary 3D PET/CT.

PubMed

Kruis, Matthijs F; van de Kamer, Jeroen B; Vogel, Wouter V; Belderbos, José Sa; Sonke, Jan-Jakob; van Herk, Marcel

2015-12-01

In contemporary positron emission tomography (PET)/computed tomography (CT) scanners, PET attenuation correction is performed by means of a CT-based attenuation map. Respiratory motion can however induce offsets between the PET and CT data. Studies have demonstrated that these offsets can cause errors in quantitative PET measures. The purpose of this study is to quantify the effects of respiration-induced CT differences on the attenuation correction of pulmonary 18-fluordeoxyglucose (FDG) 3D PET/CT in a patient population and to investigate contributing factors. For 32 lung cancer patients, 3D-CT, 4D-PET and 4D-CT data were acquired. The 4D FDG PET data were attenuation corrected (AC) using a free-breathing 3D-CT (3D-AC), the end-inspiration CT (EI-AC), the end-expiration CT (EE-AC) or phase-by-phase (P-AC). After reconstruction and AC, the 4D-PET data were averaged. In the 4Davg data, we measured maximum tumour standardised uptake value (SUV)max in the tumour, SUVmean in a lung volume of interest (VOI) and average SUV (SUVmean) in a muscle VOI. On the 4D-CT, we measured the lung volume differences and CT number changes between inhale and exhale in the lung VOI. Compared to P-AC, we found -2.3% (range -9.7% to 1.2%) lower tumour SUVmax in EI-AC and 2.0% (range -0.9% to 9.5%) higher SUVmax in EE-AC. No differences in the muscle SUV were found. The use of 3D-AC led to respiration-induced SUVmax differences up to 20% compared to the use of P-AC. SUVmean differences in the lung VOI between EI-AC and EE-AC correlated to average CT differences in this region (ρ = 0.83). SUVmax differences in the tumour correlated to the volume changes of the lungs (ρ = -0.55) and the motion amplitude of the tumour (ρ = 0.53), both as measured on the 4D-CT. Respiration-induced CT variations in clinical data can in extreme cases lead to SUV effects larger than 10% on PET attenuation correction. These differences were case specific and correlated to differences in CT number in the lungs.

Parallelized Seeded Region Growing Using CUDA

PubMed Central

Park, Seongjin; Lee, Hyunna; Seo, Jinwook; Lee, Kyoung Ho; Shin, Yeong-Gil; Kim, Bohyoung

2014-01-01

This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests. PMID:25309619

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.

4D CT sorting based on patient internal anatomy

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Cerviño, Laura I.; Jiang, Steve B.

2009-08-01

Respiratory motion during free-breathing computed tomography (CT) scan may cause significant errors in target definition for tumors in the thorax and upper abdomen. A four-dimensional (4D) CT technique has been widely used for treatment simulation of thoracic and abdominal cancer radiotherapy. The current 4D CT techniques require retrospective sorting of the reconstructed CT slices oversampled at the same couch position. Most sorting methods depend on external surrogates of respiratory motion recorded by extra instruments. However, respiratory signals obtained from these external surrogates may not always accurately represent the internal target motion, especially when irregular breathing patterns occur. We have proposed a new sorting method based on multiple internal anatomical features for multi-slice CT scan acquired in the cine mode. Four features are analyzed in this study, including the air content, lung area, lung density and body area. We use a measure called spatial coherence to select the optimal internal feature at each couch position and to generate the respiratory signals for 4D CT sorting. The proposed method has been evaluated for ten cancer patients (eight with thoracic cancer and two with abdominal cancer). For nine patients, the respiratory signals generated from the combined internal features are well correlated to those from external surrogates recorded by the real-time position management (RPM) system (average correlation: 0.95 ± 0.02), which is better than any individual internal measures at 95% confidence level. For these nine patients, the 4D CT images sorted by the combined internal features are almost identical to those sorted by the RPM signal. For one patient with an irregular breathing pattern, the respiratory signals given by the combined internal features do not correlate well with those from RPM (correlation: 0.68 ± 0.42). In this case, the 4D CT image sorted by our method presents fewer artifacts than that from the RPM signal. Our 4D CT internal sorting method eliminates the need of externally recorded surrogates of respiratory motion. It is an automatic, accurate, robust, cost efficient and yet simple method and therefore can be readily implemented in clinical settings.

Three-dimensional photography for the evaluation of facial profiles in obstructive sleep apnoea.

PubMed

Lin, Shih-Wei; Sutherland, Kate; Liao, Yu-Fang; Cistulli, Peter A; Chuang, Li-Pang; Chou, Yu-Ting; Chang, Chih-Hao; Lee, Chung-Shu; Li, Li-Fu; Chen, Ning-Hung

2018-06-01

Craniofacial structure is an important determinant of obstructive sleep apnoea (OSA) syndrome risk. Three-dimensional stereo-photogrammetry (3dMD) is a novel technique which allows quantification of the craniofacial profile. This study compares the facial images of OSA patients captured by 3dMD to three-dimensional computed tomography (3-D CT) and two-dimensional (2-D) digital photogrammetry. Measurements were correlated with indices of OSA severity. Thirty-eight patients diagnosed with OSA were included, and digital photogrammetry, 3dMD and 3-D CT were performed. Distances, areas, angles and volumes from the images captured by three methods were analysed. Almost all measurements captured by 3dMD showed strong agreement with 3-D CT measurements. Results from 2-D digital photogrammetry showed poor agreement with 3-D CT. Mandibular width, neck perimeter size and maxillary volume measurements correlated well with the severity of OSA using all three imaging methods. Mandibular length, facial width, binocular width, neck width, cranial base triangle area, cranial base area 1 and middle cranial fossa volume correlated well with OSA severity using 3dMD and 3-D CT, but not with 2-D digital photogrammetry. 3dMD provided accurate craniofacial measurements of OSA patients, which were highly concordant with those obtained by CT, while avoiding the radiation associated with CT. © 2018 Asian Pacific Society of Respirology.

Radiation dose reduction in computed tomography perfusion using spatial-temporal Bayesian methods

NASA Astrophysics Data System (ADS)

Fang, Ruogu; Raj, Ashish; Chen, Tsuhan; Sanelli, Pina C.

2012-03-01

In current computed tomography (CT) examinations, the associated X-ray radiation dose is of significant concern to patients and operators, especially CT perfusion (CTP) imaging that has higher radiation dose due to its cine scanning technique. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) parameter as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and degrade CT perfusion maps greatly if no adequate noise control is applied during image reconstruction. To capture the essential dynamics of CT perfusion, a simple spatial-temporal Bayesian method that uses a piecewise parametric model of the residual function is used, and then the model parameters are estimated from a Bayesian formulation of prior smoothness constraints on perfusion parameters. From the fitted residual function, reliable CTP parameter maps are obtained from low dose CT data. The merit of this scheme exists in the combination of analytical piecewise residual function with Bayesian framework using a simpler prior spatial constrain for CT perfusion application. On a dataset of 22 patients, this dynamic spatial-temporal Bayesian model yielded an increase in signal-tonoise-ratio (SNR) of 78% and a decrease in mean-square-error (MSE) of 40% at low dose radiation of 43mA.

Correlation between CT-based measured renal volumes and nuclear-renography-based split renal function in living kidney donors. Clinical diagnostic utility and practice patterns.

PubMed

Diez, Alejandro; Powelson, John; Sundaram, Chandru P; Taber, Tim E; Mujtaba, Muhammad A; Yaqub, Muhammad S; Mishler, Dennis P; Goggins, William C; Sharfuddin, Asif A

2014-06-01

Living donor evaluation involves imaging to determine the choice of kidney for nephrectomy. Our aim was to study the diagnostic accuracy and correlation between CT-based volume measurements and split renal function (SRF) as measured by nuclear renography in potential living donors and its impact on kidney selection decision. We analyzed 190 CT-based volume measurements in healthy donors, of which 65 donors had a radionuclide study performed to determine SRF. There were no differences in demographics, anthropometric measurements, total volumes, eGFR, creatinine clearances between those who required a nuclear scan and those who did not. There was a significant correlation between CT-volume-measurement-based SRF and nuclear-scan-based SRF (Pearson coefficient r 0.59; p < 0.001). Furthermore, selective nuclear-based SRF allowed careful selection of donor nephrectomy, leaving the donor with the higher functioning kidney in most cases. There was also a significantly higher number of right-sided nephrectomies selected after nuclear-based SRF studies. CT-based volume measurements in living donor imaging have sufficient correlation with nuclear-based SRF. Selective use of nuclear-scan-based SRF allows careful selection for donor nephrectomy. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Crackle analysis for chest auscultation and comparison with high-resolution CT findings.

PubMed

Kawamura, Takeo; Matsumoto, Tsuneo; Tanaka, Nobuyuki; Kido, Shoji; Jiang, Zhongwei; Matsunaga, Naofumi

2003-01-01

The purpose of our study was to clarify the correlation between respiratory sounds and the high-resolution CT (HRCT) findings of lung diseases. Respiratory sounds were recorded using a stethoscope in 41 patients with crackles. All had undergone inspiratory and expiratory CT. Subjects included 18 patients with interstitial pneumonia and 23 without interstitial pneumonia. Two parameters, two-cycle duration (2CD) and initial deflection width (IDW) of the "crackle," were induced by time-expanded waveform analysis. Two radiologists independently assessed 11 HRCT findings. An evaluation was carried out to determine whether there was a significant difference in the two parameters between the presence and absence of each HRCT finding. The two parameters of crackles were significantly shorter in the interstitial pneumonia group than the non-interstitial pneumonia group. Ground-glass opacity, honeycombing, lung volume reduction, traction bronchiectasis, centrilobular nodules, emphysematous change, and attenuation and volume change between inspiratory and expiratory CT were correlated with one or two parameters in all patients, whereas the other three findings were not. Among the interstitial pneumonia group, traction bronchiectasis, emphysematous change, and attenuation and volume change between inspiratory and expiratory CT were significantly correlated with one or two parameters. Abnormal respiratory sounds were correlated with some HRCT findings.

Prevalence of upper airway obstruction in patients with apparently asymptomatic euthyroid multi nodular goitre

PubMed Central

Menon, Sunil K.; Jagtap, Varsha S.; Sarathi, Vijaya; Lila, Anurag R.; Bandgar, Tushar R.; Menon, Padmavathy S; Shah, Nalini S.

2011-01-01

Aims: To study the prevalence of upper airway obstruction (UAO) in “apparently asymptomatic” patients with euthyroid multinodular goitre (MNG) and find correlation between clinical features, UAO on pulmonary function test (PFT) and tracheal narrowing on computerised tomography (CT). Materials and Methods: Consecutive patients with apparently asymptomatic euthyroid MNG attending thyroid clinic in a tertiary centre underwent clinical examination to elicit features of UAO, PFT, and CT of neck and chest. Statistical Analysis Used: Statistical analysis was done with SPSS version 11.5 using paired t-test, Chi square test, and Fisher's exact test. P value of <0.05 was considered to be significant. Results: Fifty-six patients (52 females and four males) were studied. The prevalence of UAO (PFT) and significant tracheal narrowing (CT) was 14.3%. and 9.3%, respectively. Clinical features failed to predict UAO or significant tracheal narrowing. Tracheal narrowing (CT) did not correlate with UAO (PFT). Volume of goitre significantly correlated with degree of tracheal narrowing. Conclusions: Clinical features do not predict UAO on PFT or tracheal narrowing on CT in apparently asymptomatic patients with euthyroid MNG. PMID:21966649

Bronchiectasis: correlation of high-resolution CT findings with health-related quality of life.

PubMed

Eshed, I; Minski, I; Katz, R; Jones, P W; Priel, I E

2007-02-01

To evaluate the relationship between the severity of bronchiectatic diseases, as evident on high-resolution computed tomography (HRCT) and the patient's quality of life measured using the St George's Respiratory Questionnaire (SGRQ). Forty-six patients (25 women, 21 men, mean age: 63 years) with bronchiectatic disease as evident on recent HRCT examinations were recruited. Each patient completed the SGRQ and underwent respiratory function tests. HRCT findings were blindly and independently scored by two radiologists, using the modified Bhalla scoring system. The relationships between HRCT scores, SGRQ scores and pulmonary function tests were evaluated. The patients' total CT score did not correlate with the SGRQ scores. However, patients with more advanced disease on HRCT, significantly differed in their SGRQ scores from patients with milder bronchiectatic disease. A significant correlation was found between the CT scores for the middle and distal lung zones and the activity, impacts and total SGRQ scores. No correlation was found between CT scores and respiratory function test indices. However, a significant correlation was found between the SGRQ scores and most of the respiratory function test indices. A correlation between the severity of bronchiectatic disease as expressed in HRCT and the health-related quality of life exists in patients with a more severe bronchiectatic disease but not in patients with mild disease. Such correlation depends on the location of the bronchiectasis in the pulmonary tree.

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.

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.

Correlation between model observers in uniform background and human observers in patient liver background for a low-contrast detection task in CT

NASA Astrophysics Data System (ADS)

Gong, Hao; Yu, Lifeng; Leng, Shuai; Dilger, Samantha; Zhou, Wei; Ren, Liqiang; McCollough, Cynthia H.

2018-03-01

Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task. The human observer study was performed on CT images from 7 abdominal CT exams. A noise insertion tool was employed to synthesize CT scans at two additional dose levels. A validated lesion insertion tool was used to numerically insert metastatic liver lesions of various sizes and contrasts into both phantom and patient images. We selected 12 conditions out of 72 possible experimental conditions to evaluate the correlation at various radiation doses, lesion sizes, lesion contrasts and reconstruction algorithms. CHO with both single and multi-slice viewing modes were strongly correlated with HO. The corresponding Pearson's correlation coefficient was 0.982 (with 95% confidence interval (CI) [0.936, 0.995]) and 0.989 (with 95% CI of [0.960, 0.997]) in multi-slice and single-slice viewing modes, respectively. Therefore, this study demonstrated the potential to use the simplest single-slice CHO to assess image quality for more realistic clinically relevant CT detection tasks.

Correlation of pulmonary function and usual interstitial pneumonia computed tomography patterns in idiopathic pulmonary fibrosis.

PubMed

Arcadu, Antonella; Byrne, Suzanne C; Pirina, Pietro; Hartman, Thomas E; Bartholmai, Brian J; Moua, Teng

2017-08-01

Little is known about presenting 'inconsistent' or 'possible' usual interstitial pneumonia (UIP) computed tomography (CT) patterns advancing to 'consistent' UIP as disease progresses in idiopathic pulmonary fibrosis (IPF). We hypothesized that if 'consistent' UIP represented more advanced disease, such a pattern on presentation should also correlate with more severe pulmonary function test (PFT) abnormalities. Consecutive IPF patients (2005-2013) diagnosed by international criteria with baseline PFT and CT were included. Presenting CTs were assessed by three expert radiologists for consensus UIP pattern ('consistent', 'possible', and 'inconsistent'). Approximation of individual and combined interstitial abnormalities was also performed with correlation of interstitial abnormalities and UIP CT pattern made with PFT findings and survival. Three-hundred and fifty patients (70% male) were included with a mean age of 68.3 years. Mean percent predicted forced vital capacity (FVC%) and diffusion capacity (DLCO%) was 64% and 45.5% respectively. Older age and male gender correlated more with 'consistent' UIP CT pattern. FVC% was not associated with any UIP pattern but did correlate with total volume of radiologist assessed interstitial abnormalities. DLCO% was lower in those with 'consistent' UIP pattern. A 'consistent' UIP CT pattern was also not independently predictive of survival after correction for age, gender, FVC%, and DLCO%. PFT findings appear to correlate with extent of radiologic disease but not specific morphologic patterns. Whether such UIP patterns represent different stages of disease severity or radiologic progression is not supported by coinciding pulmonary function decline. Copyright © 2017 Elsevier Ltd. All rights reserved.

Standardized Uptake Values from PET/MRI in Metastatic Breast Cancer: An Organ-based Comparison With PET/CT

PubMed Central

Pujara, Akshat C.; Raad, Roy A.; Ponzo, Fabio; Wassong, Carolyn; Babb, James S.; Moy, Linda; Melsaether, Amy N.

2016-01-01

Quantitative standardized uptake values (SUVs) from fluorine-18 (18F) fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) are commonly used to evaluate the extent of disease and response to treatment in breast cancer patients. Recently, PET/magnetic resonance imaging (MRI) has been shown to qualitatively detect metastases from various primary cancers with similar sensitivity to PET/CT. However, quantitative validation of PET/ MRI requires assessing the reliability of SUVs from MR attenuation correction (MRAC) relative to CT attenuation correction (CTAC). The purpose of this retrospective study was to assess the utility of PET/MRI-derived SUVs in breast cancer patients by testing the hypothesis that SUVs derived from MRAC correlate well with those from CTAC. Between August 2012 and May 2013, 35 breast cancer patients (age 37–78 years, 1 man) underwent clinical 18F-FDG PET/CT followed by PET/MRI. One hundred seventy metastases were seen in 21 of 35 patients; metastases to bone in 16 patients, to liver in seven patients, and to nonaxillary lymph nodes in eight patients were sufficient for statistical analysis on an organ-specific per patient basis. SUVs in the most FDG-avid metastasis per organ per patient from PET/CT and PET/MRI were measured and compared using Pearson’s correlations. Correlations between CTAC- and MRAC-derived SUVmax and SUVmean in 31 metastases to bone, liver, and nonaxillary lymph nodes were strong overall (ρ= 0.80, 0.81). SUVmax and SUVmean correlations were also strong on an organ-specific basis in 16 bone metastases (ρ= 0.76, 0.74), seven liver metastases (ρ= 0.85, 0.83), and eight nonaxillary lymph node metastases (ρ= 0.95, 0.91). These strong organ-specific correlations between SUVs from PET/CT and PET/MRI in breast cancer metastases support the use of SUVs from PET/MRI for quantitation of 18F-FDG activity. PMID:26843433

Hybrid FDG-PET/MR compared to FDG-PET/CT in adult lymphoma patients.

PubMed

Atkinson, Wendy; Catana, Ciprian; Abramson, Jeremy S; Arabasz, Grae; McDermott, Shanaugh; Catalano, Onofrio; Muse, Victorine; Blake, Michael A; Barnes, Jeffrey; Shelly, Martin; Hochberg, Ephraim; Rosen, Bruce R; Guimaraes, Alexander R

2016-07-01

The goal of this study is to evaluate the diagnostic performance of simultaneous FDG-PET/MR including diffusion compared to FDG-PET/CT in patients with lymphoma. Eighteen patients with a confirmed diagnosis of non-Hodgkin's (NHL) or Hodgkin's lymphoma (HL) underwent an IRB-approved, single-injection/dual-imaging protocol consisting of a clinical FDG-PET/CT and subsequent FDG-PET/MR scan. PET images from both modalities were reconstructed iteratively. Attenuation correction was performed using low-dose CT data for PET/CT and Dixon-MR sequences for PET/MR. Diffusion-weighted imaging was performed. SUVmax was measured and compared between modalities and the apparent diffusion coefficient (ADC) using ROI analysis by an experienced radiologist using OsiriX. Strength of correlation between variables was measured using the Pearson correlation coefficient (r p). Of the 18 patients included in this study, 5 had HL and 13 had NHL. The median age was 51 ± 14.8 years. Sixty-five FDG-avid lesions were identified. All FDG-avid lesions were visible with comparable contrast, and therefore initial and follow-up staging was identical between both examinations. SUVmax from FDG-PET/MR [(mean ± sem) (21.3 ± 2.07)] vs. FDG-PET/CT (mean 23.2 ± 2.8) demonstrated a strongly positive correlation [r s = 0.95 (0.94, 0.99); p < 0.0001]. There was no correlation found between ADCmin and SUVmax from FDG-PET/MR [r = 0.17(-0.07, 0.66); p = 0.09]. FDG-PET/MR offers an equivalent whole-body staging examination as compared with PET/CT with an improved radiation safety profile in lymphoma patients. Correlation of ADC to SUVmax was weak, understating their lack of equivalence, but not undermining their potential synergy and differing importance.

Quantitative Computerized Two-Point Correlation Analysis of Lung CT Scans Correlates With Pulmonary Function in Pulmonary Sarcoidosis

PubMed Central

Erdal, Barbaros Selnur; Yildiz, Vedat; King, Mark A.; Patterson, Andrew T.; Knopp, Michael V.; Clymer, Bradley D.

2012-01-01

Background: Chest CT scans are commonly used to clinically assess disease severity in patients presenting with pulmonary sarcoidosis. Despite their ability to reliably detect subtle changes in lung disease, the utility of chest CT scans for guiding therapy is limited by the fact that image interpretation by radiologists is qualitative and highly variable. We sought to create a computerized CT image analysis tool that would provide quantitative and clinically relevant information. Methods: We established that a two-point correlation analysis approach reduced the background signal attendant to normal lung structures, such as blood vessels, airways, and lymphatics while highlighting diseased tissue. This approach was applied to multiple lung fields to generate an overall lung texture score (LTS) representing the quantity of diseased lung parenchyma. Using deidentified lung CT scan and pulmonary function test (PFT) data from The Ohio State University Medical Center’s Information Warehouse, we analyzed 71 consecutive CT scans from patients with sarcoidosis for whom simultaneous matching PFTs were available to determine whether the LTS correlated with standard PFT results. Results: We found a high correlation between LTS and FVC, total lung capacity, and diffusing capacity of the lung for carbon monoxide (P < .0001 for all comparisons). Moreover, LTS was equivalent to PFTs for the detection of active lung disease. The image analysis protocol was conducted quickly (< 1 min per study) on a standard laptop computer connected to a publicly available National Institutes of Health ImageJ toolkit. Conclusions: The two-point image analysis tool is highly practical and appears to reliably assess lung disease severity. We predict that this tool will be useful for clinical and research applications. PMID:22628487

11C-Methionine Positron Emission Tomography/Computed Tomography Versus 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Evaluation of Residual or Recurrent World Health Organization Grades II and III Meningioma After Treatment.

PubMed

Tomura, Noriaki; Saginoya, Toshiyuki; Goto, Hiromi

2018-04-02

The aim of this study was to determine the assessment of positron emission tomography-computed tomography using C-methionine (MET PET/CT) for World Health Organization (WHO) grades II and III meningiomas; MET PET/CT was compared with PET/CT using F-fluorodeoxy glucose (FDG PET/CT). This study was performed in 17 cases with residual and/or recurrent WHO grades II and III meningiomas. Two neuroradiologists reviewed both PET/CT scans. For agreement, the κ coefficient was measured. Difference in tumor-to-normal brain uptake ratios (T/N ratios) between 2 PET/CT scans was analyzed. Correlation between the maximum tumor size and T/N ratio in PET/CT was studied. For agreement by both reviewers, the κ coefficient was 0.51 (P < 0.05). The T/N ratio was significantly higher for MET PET/CT (3.24 ± 1.36) than for FDG PET/CT (0.93 ± 0.44) (P < 0.01). C-methionine ratio significantly correlated with tumor size (y = 8.1x + 16.3, n = 22, P < 0.05), but FDG ratio did not CONCLUSIONS: C-methionine PET/CT has superior potential for imaging of WHO grades II and III meningiomas with residual or recurrent tumors compared with FDG PET/CT.

Plasma level of cardiotrophin-1 as a prognostic predictor in patients with chronic heart failure.

PubMed

Tsutamoto, Takayoshi; Asai, Shigeru; Tanaka, Toshinari; Sakai, Hiroshi; Nishiyama, Keizo; Fujii, Masanori; Yamamoto, Takashi; Ohnishi, Masato; Wada, Atsuyuki; Saito, Yoshihiko; Horie, Minoru

2007-10-01

Cardiotrophin-1 (CT-1) is a member of the interleukin (IL-6) family of cytokines and is increased in patients with chronic heart failure (CHF). To evaluate the prognostic role of CT-1 in patients with CHF. We measured the plasma levels of CT-1, brain natriuretic peptide (BNP), and IL-6 in 125 patients with CHF. Patients were monitored for a mean follow-up period of 2.9 years. Plasma levels of CT-1 increased with severity of CHF. There was a significant negative correlation between plasma CT-1 and left ventricular ejection fraction. There was a significant correlation between plasma CT-1 and log IL-6. During the follow-up period, 37 patients died. High plasma levels of CT-1, BNP, and IL-6 were independent predictors of mortality on stepwise multivariate analysis. The hazard ratio for mortality in patients with plasma BNP>170 pg/mL and CT-1>658 fmol/mL was 2.48 (95% confidence interval, 1.217-5.060) compared to those with plasma BNP>170 pg/mL and CT-1<658 fmol/mL (p=0.0124). These findings indicate that plasma CT-1 measurement provides additional prognostic information and that combined levels of CT-1 and BNP are more accurate at predicting mortality in patients with CHF than either marker alone.

Quantification of organ motion based on an adaptive image-based scale invariant feature method

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

Paganelli, Chiara; Peroni, Marta; Baroni, Guido

2013-11-15

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application ofmore » contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.« less

Scatter correction, intermediate view estimation and dose characterization in megavoltage cone-beam CT imaging

NASA Astrophysics Data System (ADS)

Sramek, Benjamin Koerner

The ability to deliver conformal dose distributions in radiation therapy through intensity modulation and the potential for tumor dose escalation to improve treatment outcome has necessitated an increase in localization accuracy of inter- and intra-fractional patient geometry. Megavoltage cone-beam CT imaging using the treatment beam and onboard electronic portal imaging device is one option currently being studied for implementation in image-guided radiation therapy. However, routine clinical use is predicated upon continued improvements in image quality and patient dose delivered during acquisition. The formal statement of hypothesis for this investigation was that the conformity of planned to delivered dose distributions in image-guided radiation therapy could be further enhanced through the application of kilovoltage scatter correction and intermediate view estimation techniques to megavoltage cone-beam CT imaging, and that normalized dose measurements could be acquired and inter-compared between multiple imaging geometries. The specific aims of this investigation were to: (1) incorporate the Feldkamp, Davis and Kress filtered backprojection algorithm into a program to reconstruct a voxelized linear attenuation coefficient dataset from a set of acquired megavoltage cone-beam CT projections, (2) characterize the effects on megavoltage cone-beam CT image quality resulting from the application of Intermediate View Interpolation and Intermediate View Reprojection techniques to limited-projection datasets, (3) incorporate the Scatter and Primary Estimation from Collimator Shadows (SPECS) algorithm into megavoltage cone-beam CT image reconstruction and determine the set of SPECS parameters which maximize image quality and quantitative accuracy, and (4) evaluate the normalized axial dose distributions received during megavoltage cone-beam CT image acquisition using radiochromic film and thermoluminescent dosimeter measurements in anthropomorphic pelvic and head and neck phantoms. The conclusions of this investigation were: (1) the implementation of intermediate view estimation techniques to megavoltage cone-beam CT produced improvements in image quality, with the largest impact occurring for smaller numbers of initially-acquired projections, (2) the SPECS scatter correction algorithm could be successfully incorporated into projection data acquired using an electronic portal imaging device during megavoltage cone-beam CT image reconstruction, (3) a large range of SPECS parameters were shown to reduce cupping artifacts as well as improve reconstruction accuracy, with application to anthropomorphic phantom geometries improving the percent difference in reconstructed electron density for soft tissue from -13.6% to -2.0%, and for cortical bone from -9.7% to 1.4%, (4) dose measurements in the anthropomorphic phantoms showed consistent agreement between planar measurements using radiochromic film and point measurements using thermoluminescent dosimeters, and (5) a comparison of normalized dose measurements acquired with radiochromic film to those calculated using multiple treatment planning systems, accelerator-detector combinations, patient geometries and accelerator outputs produced a relatively good agreement.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

PubMed Central

Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P.; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V.; Karig, David; Fagan, William F.

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson’s correlation coefficient (r) and Jaccard’s index (J)–two of the most common metrics for correlation analysis of presence-absence data–can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson’s correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard’s index of similarity (J) can yield improvements over Pearson’s correlation coefficient. However, the standard null model for Jaccard’s index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard’s index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa. PMID:29145425

Pulmonary disease in cystic fibrosis: assessment with chest CT at chest radiography dose levels.

PubMed

Ernst, Caroline W; Basten, Ines A; Ilsen, Bart; Buls, Nico; Van Gompel, Gert; De Wachter, Elke; Nieboer, Koenraad H; Verhelle, Filip; Malfroot, Anne; Coomans, Danny; De Maeseneer, Michel; de Mey, Johan

2014-11-01

To investigate a computed tomographic (CT) protocol with iterative reconstruction at conventional radiography dose levels for the assessment of structural lung abnormalities in patients with cystic fibrosis ( CF cystic fibrosis ). In this institutional review board-approved study, 38 patients with CF cystic fibrosis (age range, 6-58 years; 21 patients <18 years and 17 patients >18 years) underwent investigative CT (at minimal exposure settings combined with iterative reconstruction) as a replacement of yearly follow-up posteroanterior chest radiography. Verbal informed consent was obtained from all patients or their parents. CT images were randomized and rated independently by two radiologists with use of the Bhalla scoring system. In addition, mosaic perfusion was evaluated. As reference, the previous available conventional chest CT scan was used. Differences in Bhalla scores were assessed with the χ(2) test and intraclass correlation coefficients ( ICC intraclass correlation coefficient s). Radiation doses for CT and radiography were assessed for adults (>18 years) and children (<18 years) separately by using technical dose descriptors and estimated effective dose. Differences in dose were assessed with the Mann-Whitney U test. The median effective dose for the investigative protocol was 0.04 mSv (95% confidence interval [ CI confidence interval ]: 0.034 mSv, 0.10 mSv) for children and 0.05 mSv (95% CI confidence interval : 0.04 mSv, 0.08 mSv) for adults. These doses were much lower than those with conventional CT (median: 0.52 mSv [95% CI confidence interval : 0.31 mSv, 3.90 mSv] for children and 1.12 mSv [95% CI confidence interval : 0.57 mSv, 3.15 mSv] for adults) and of the same order of magnitude as those for conventional radiography (median: 0.012 mSv [95% CI confidence interval : 0.006 mSv, 0.022 mSv] for children and 0.012 mSv [95% CI confidence interval : 0.005 mSv, 0.031 mSv] for adults). All images were rated at least as diagnostically acceptable. Very good agreement was found in overall Bhalla score ( ICC intraclass correlation coefficient , 0.96) with regard to the severity of bronchiectasis ( ICC intraclass correlation coefficient , 0.87) and sacculations and abscesses ( ICC intraclass correlation coefficient , 0.84). Interobserver agreement was excellent ( ICC intraclass correlation coefficient , 0.86-1). For patients with CF cystic fibrosis , a dedicated chest CT protocol can replace the two yearly follow-up chest radiographic examinations without major dose penalty and with similar diagnostic quality compared with conventional CT.

Quantitative analysis of skeletal muscle mass in patients with rheumatic diseases under glucocorticoid therapy--comparison among bioelectrical impedance analysis, computed tomography, and magnetic resonance imaging.

PubMed

Hosono, Osamu; Yoshikawa, Noritada; Shimizu, Noriaki; Kiryu, Shigeru; Uehara, Masaaki; Kobayashi, Hiroshi; Matsumiya, Ryo; Kuribara, Akiko; Maruyama, Takako; Tanaka, Hirotoshi

2015-03-01

To determine the availability of bioelectrical impedance analysis (BIA), computed tomography (CT), and magnetic resonance imaging (MRI) for measurement of skeletal muscle mass in patients with rheumatic diseases and quantitatively assess skeletal muscle loss after glucocorticoid (GC) treatment. The data from 22 patients with rheumatic diseases were retrospectively obtained. The muscle mass of body segments was measured with a BIA device in terms of skeletal muscle mass index (SMI). Cross-sectional area (CSA) was obtained from CT and MRI scans at the mid-thigh level using the image analysis program. We further assessed the data of three different measurements before and after GC treatment in 7 patients with rheumatic diseases. SMI of whole body was significantly correlated with estimated muscle volume and mid-thigh muscle CSA with CT and MRI (p < 0.01). Significant correlations between SMI and mid-thigh muscle CSA of each leg were also found (p < 0.01). All the three measurements were negatively correlated with GC dosage (p < 0.01). Significant decline in mid-thigh muscle CSA with CT and MRI was found after GC treatment in 7 patients (p < 0.02). Those patients showed significant decline in SMI of whole body after GC treatment, but not in SMI of each leg. On the other hand, significant correlations between mid-thigh muscle CSA with CT and MRI were found before and after GC treatment (p < 0.01). GC-related skeletal muscle loss could be quantitatively assessed with BIA, CT, or MRI in patients with rheumatic diseases, and CT and MRI appeared to be more accurate than BIA.

Comparative 3D micro-CT and 2D histomorphometry analysis of dental implant osseointegration in the maxilla of minipigs.

PubMed

Bissinger, Oliver; Probst, Florian Andreas; Wolff, Klaus-Dietrich; Jeschke, Anke; Weitz, Jochen; Deppe, Herbert; Kolk, Andreas

2017-04-01

The bone implant contact (BIC) has traditionally been evaluated with histological methods. Thereupon, strong correlations of two-dimensional (2D) BIC have been detected between μCT and destructive histology. However, due to the high intra-sample variability in BIC values, one histological slice is not sufficient to represent 3D BIC. Therefore, our aim has been to correlate the averaged values of 3-4 histological sections to 3D μCT. Fifty-four implants inserted into the maxilla of 14 minipigs were evaluated. Two different time points were selected to assess the 3D BIC (distance to implant: 2-5 voxels), an inner ring (6-30 voxels) and an outer ring (55-100 voxels) using μCT (voxel size: 10 μm) and to correlate the values to histomorphometry. Strong correlations (p < 0.0001; 28 days, 56 days, total) were seen between μCT and histomorphometry concerning BIC (r = 0.84, r = 0.85, r = 0.83), the inner ring (r = 0.87, r = 0.87, r = 0.88) and the outer ring (r = 0.85, r = 0.85, r = 0.88). Closer to the implant, μCT values were higher compared with histomorphometry. Although 3-4 histological slices per implant seem to predict the 3D BIC, μCT might be advantageous because of its non-destructive 3D character. The healing time may not impact on the comparability. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Comparative study evaluating the role of color Doppler sonography and computed tomography in predicting chest wall invasion by lung tumors.

PubMed

Sripathi, Smiti; Mahajan, Abhishek

2013-09-01

To analyze qualitative and quantitative parameters of lung tumors by color Doppler sonography, determine the role of color Doppler sonography in predicting chest wall invasion by lung tumors using spectral waveform analysis, and compare color Doppler sonography and computed tomography (CT) for predicting chest wall invasion by lung tumors. Between March and September 2007, 55 patients with pleuropulmonary lesions on chest radiography were assessed by grayscale and color Doppler sonography for chest wall invasion. Four patients were excluded from the study because of poor acoustic windows. Quantitative and qualitative sonographic examinations of the lesions were performed using grayscale and color Doppler imaging. The correlation between the color Doppler and CT findings was determined, and the final outcomes were correlated with the histopathologic findings. Of a total of 51 lesions, 32 were malignant. Vascularity was present on color Doppler sonography in 28 lesions, and chest wall invasion was documented in 22 cases. Computed tomography was performed in 24 of 28 evaluable malignant lesions, and the findings were correlated with the color Doppler findings for chest wall invasion. Of the 24 patients who underwent CT, 19 showed chest wall invasion. The correlation between the color Doppler and CT findings revealed that color Doppler sonography had sensitivity of 95.6% and specificity of 100% for assessing chest wall invasion, whereas CT had sensitivity of 85.7% and specificity of 66.7%. Combined qualitative and quantitative color Doppler sonography can predict chest wall invasion by lung tumors with better sensitivity and specificity than CT. Although surgery is the reference standard, color Doppler sonography is a readily available, affordable, and noninvasive in vivo diagnostic imaging modality that is complementary to CT and magnetic resonance imaging for lung cancer staging.

Correlation of corneal thickness, endothelial cell density and anterior chamber depth with ocular surface temperature in normal subjects.

PubMed

Pattmöller, Johanna; Wang, Jiong; Zemova, Elena; Seitz, Berthold; Eppig, Timo; Langenbucher, Achim; Szentmáry, Nóra

2015-09-01

To analyze corneal surface temperature profile in a young and healthy study population and to determine the impact of corneal thickness (CT), anterior chamber depth (ACD), and endothelial cell density (ECD) on surface temperature. In this prospective, single-center study 61 healthy right eyes of 61 subjects without tear film pathologies (mean age 24.9 ± 6.7 years) were recruited. Ocular surface temperature (OST) was measured with the Ocular Surface Thermographer TG-1000. From Pentacam HR CT and ACD, and from specular microscopy ECD and central corneal thickness (CCT) were acquired. From the raw measurement data (OST, CT and ACD) we extracted a) local OST the corneal center and 3mm away from the center at the 3, 6, and 9 o'clock positions, and b) Zernike parameters Z1, Z2 and Z3 to evaluate the general temperature profile within a 6mm circular area around the center. Overall, there was no correlation between OST and CT, ACD or ECD. Local OST did not correlate with CT at any measurement position. On average local OST was highest at measurement positions where CT was lowest, but without reaching statistical significance. Baseline OST was highest at thin corneal regions and temperature decay over time was smallest in those regions. Z1, Z2 and Z3 correlated well with CT. In healthy subjects corneal thickness, endothelial cell density and anterior chamber depth have no effect on corneal surface temperature. The general temperature profile seems to be influenced by the corneal thickness profile effecting a higher temperature and lower decay at thinner corneal regions. Copyright © 2014. Published by Elsevier GmbH.

Three-dimensional murine airway segmentation in micro-CT images

NASA Astrophysics Data System (ADS)

Shi, Lijun; Thiesse, Jacqueline; McLennan, Geoffrey; Hoffman, Eric A.; Reinhardt, Joseph M.

2007-03-01

Thoracic imaging for small animals has emerged as an important tool for monitoring pulmonary disease progression and therapy response in genetically engineered animals. Micro-CT is becoming the standard thoracic imaging modality in small animal imaging because it can produce high-resolution images of the lung parenchyma, vasculature, and airways. Segmentation, measurement, and visualization of the airway tree is an important step in pulmonary image analysis. However, manual analysis of the airway tree in micro-CT images can be extremely time-consuming since a typical dataset is usually on the order of several gigabytes in size. Automated and semi-automated tools for micro-CT airway analysis are desirable. In this paper, we propose an automatic airway segmentation method for in vivo micro-CT images of the murine lung and validate our method by comparing the automatic results to manual tracing. Our method is based primarily on grayscale morphology. The results show good visual matches between manually segmented and automatically segmented trees. The average true positive volume fraction compared to manual analysis is 91.61%. The overall runtime for the automatic method is on the order of 30 minutes per volume compared to several hours to a few days for manual analysis.

Real-time fusion of endoscopic views with dynamic 3-D cardiac images: a phantom study.

PubMed

Szpala, Stanislaw; Wierzbicki, Marcin; Guiraudon, Gerard; Peters, Terry M

2005-09-01

Minimally invasive robotically assisted cardiac surgical systems currently do not routinely employ 3-D image guidance. However, preoperative magnetic resonance and computed tomography (CT) images have the potential to be used in this role, if appropriately registered with the patient anatomy and animated synchronously with the motion of the actual heart. This paper discusses the fusion of optical images of a beating heart phantom obtained from an optically tracked endoscope, with volumetric images of the phantom created from a dynamic CT dataset. High quality preoperative dynamic CT images are created by first extracting the motion parameters of the heart from the series of temporal frames, and then applying this information to animate a high-quality heart image acquired at end systole. Temporal synchronization of the endoscopic and CT model is achieved by selecting the appropriate CT image from the dynamic set, based on an electrocardiographic trigger signal. The spatial error between the optical and virtual images is 1.4 +/- 1.1 mm, while the time discrepancy is typically 50-100 ms. Index Terms-Image guidance, image warping, minimally invasive cardiac surgery, virtual endoscopy, virtual reality.

Computerized method for automatic evaluation of lean body mass from PET/CT: comparison with predictive equations.

PubMed

Chan, Tao

2012-01-01

CT has become an established method for calculating body composition, but it requires data from the whole body, which are not typically obtained in routine PET/CT examinations. A computerized scheme that evaluates whole-body lean body mass (LBM) based on CT data from limited-whole-body coverage was developed. The LBM so obtained was compared with results from conventional predictive equations. LBM can be obtained automatically from limited-whole-body CT data by 3 means: quantification of body composition from CT images in the limited-whole-body scan, based on thresholding of CT attenuation; determination of the range of coverage based on a characteristic trend of changing composition across different levels and pattern recognition of specific features at strategic positions; and estimation of the LBM of the whole body on the basis of a predetermined relationship between proportion of fat mass and extent of coverage. This scheme was validated using 18 whole-body PET/CT examinations truncated at different lengths to emulate limited-whole-body data. LBM was also calculated using predictive equations that had been reported for use in SUV normalization. LBM derived from limited-whole-body data using the proposed method correlated strongly with LBM derived from whole-body CT data, with correlation coefficients ranging from 0.991 (shorter coverage) to 0.998 (longer coverage) and SEMs of LBM ranging from 0.14 to 0.33 kg. These were more accurate than results from different predictive equations, which ranged in correlation coefficient from 0.635 to 0.970 and in SEM from 0.64 to 2.40 kg. LBM of the whole body could be automatically estimated from CT data of limited-whole-body coverage typically acquired in PET/CT examinations. This estimation allows more accurate and consistent quantification of metabolic activity of tumors based on LBM-normalized standardized uptake value.

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

State-of-the-art radiological techniques improve the assessment of postoperative lung function in patients with non-small cell lung cancer.

PubMed

Ohno, Yoshiharu; Koyama, Hisanobu; Nogami, Munenobu; Takenaka, Daisuke; Onishi, Yumiko; Matsumoto, Keiko; Matsumoto, Sumiaki; Maniwa, Yoshimasa; Yoshimura, Masahiro; Nishimura, Yoshihiro; Sugimura, Kazuro

2011-01-01

The purpose of this study was to compare predictive capabilities for postoperative lung function in non-small cell lung cancer (NSCLC) patients of the state-of-the-art radiological methods including perfusion MRI, quantitative CT and SPECT/CT with that of anatomical method (i.e. qualitative CT) and traditional nuclear medicine methods such as planar imaging and SPECT. Perfusion MRI, CT, nuclear medicine study and measurements of %FEV(1) before and after lung resection were performed for 229 NSCLC patients (125 men and 104 women). For perfusion MRI, postoperative %FEV(1) (po%FEV(1)) was predicted from semi-quantitatively assessed blood volumes within total and resected lungs, for quantitative CT, it was predicted from the functional lung volumes within total and resected lungs, for qualitative CT, from the number of segments of total and resected lungs, and for nuclear medicine studies, from uptakes within total and resected lungs. All SPECTs were automatically co-registered with CTs for preparation of SPECT/CTs. Predicted po%FEV(1)s were then correlated with actual po%FEV(1)s, which were measured %FEV(1)s after operation. The limits of agreement were also evaluated. All predicted po%FEV(1)s showed good correlation with actual po%FEV(1)s (0.83≤r≤0.88, p<0.0001). Perfusion MRI, quantitative CT and SPECT/CT demonstrated better correlation than other methods. The limits of agreement of perfusion MRI (4.4±14.2%), quantitative CT (4.7±14.2%) and SPECT/CT (5.1±14.7%) were less than those of qualitative CT (6.0±17.4%), planar imaging (5.8±18.2%), and SPECT (5.5±16.8%). State-of-the-art radiological methods can predict postoperative lung function in NSCLC patients more accurately than traditional methods. Copyright © 2009 Elsevier Ireland Ltd. All rights reserved.

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.

Distinguishing the Effects of Local Point Sources from Those Caused by Upstream Nonpoint Source (NPS) Inputs: Refinement of a Watershed Development Index for New England

EPA Science Inventory

Using EMAP data from the NE Wadeable Stream Survey and state datasets (CT, ME), assessment tools were developed to predict diffuse NPS effects from watershed development and distinguish these from local impacts (point sources, contaminated sediments). Classification schemes were...

CT_50m_Wind

Science.gov Websites

development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify appears in all copies of the data. Further, the user of this data agrees to credit NREL in any

Distinguishing Betwen Effects of Local Inputs (Contaminated Sediments, Point Sources) and Upstream Diffuse Nonpoint Source Input: Refinement of a Watershed Development Index for New England

EPA Science Inventory

Assessment tools are being developed to predict diffuse NPS effects from watershed development and distinguish these from local impacts (point sources, contaminated sediments). Using EMAP data from the New England Wadeable Stream Survey and two state datasets (CT, ME), we are de...

Semi-Quantitative Analysis of Post-Transarterial Radioembolization (90)Y Microsphere Positron Emission Tomography Combined with Computed Tomography (PET/CT) Images in Advanced Liver Malignancy: Comparison With (99m)Tc Macroaggregated Albumin (MAA) Single Photon Emission Computed Tomography (SPECT).

PubMed

Rhee, Seunghong; Kim, Sungeun; Cho, Jaehyuk; Park, Jukyung; Eo, Jae Seon; Park, Soyeon; Lee, Eunsub; Kim, Yun Hwan; Choe, Jae-Gol

2016-03-01

The purpose of this study is to evaluate the correlation between pretreatment planning technetium-99m ((99m)Tc) macroaggregated albumin (MAA) SPECT images and posttreatment transarterial radioembolization (TARE) yttirum-90 ((90)Y) PET/CT images by comparing the ratios of tumor-to-normal liver counts. Fifty-two patients with advanced hepatic malignancy who underwent (90)Y microsphere radioembolization from January 2010 to December 2012 were retrospectively reviewed. Patients had undergone (99m)Tc MAA intraarterial injection SPECT for a pretreatment evaluation of microsphere distribution and therapy planning. After the administration of (90)Y microspheres, the patients underwent posttreatment (90)Y PET/CT within 24 h. For semiquantitative analysis, the tumor-to-normal uptake ratios in (90)Y PET/CT (TNR-yp) and (99m)Tc MAA SPECT (TNR-ms) as well as the tumor volumes measured in angiographic CT were obtained and analyzed. The relationship of TNR-yp and TNR-ms was evaluated by Spearman's rank correlation and Wilcoxon's matched pairs test. In a total of 79 lesions of 52 patients, the distribution of microspheres was well demonstrated in both the SPECT and PET/CT images. A good correlation was observed of between TNR-ms and TNR-yp (rho value = 0.648, p < 0.001). The TNR-yp (median 2.78, interquartile range 2.43) tend to show significantly higher values than TNR-ms (median 2.49, interquartile range of 1.55) (p = 0.012). The TNR-yp showed weak correlation with tumor volume (rho = 0.230, p = 0.041). The (99m)Tc MAA SPECT showed a good correlation with (90)Y PET/CT in TNR values, suggesting that (99m)Tc MAA can be used as an adequate pretreatment evaluation method. However, the (99m)Tc MAA SPECT image consistently shows lower TNR values compared to (90)Y PET/CT, which means the possibility of underestimation of tumorous uptake in the partition dosimetry model using (99m)Tc MAA SPECT. Considering that (99m)Tc MAA is the only clinically available surrogate marker for distribution of microsphere, we recommend measurement of tumorous uptake using (90)Y PET/CT should be included routinely in the posttherapeutic evaluation.

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets.

PubMed

Bicer, Tekin; Gürsoy, Doğa; Andrade, Vincent De; Kettimuthu, Rajkumar; Scullin, William; Carlo, Francesco De; Foster, Ian T

2017-01-01

Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

Pitfalls in interpretation of CT-values of RT-PCR in children with acute respiratory tract infections.

PubMed

Wishaupt, Jérôme O; Ploeg, Tjeerd van der; Smeets, Leo C; Groot, Ronald de; Versteegh, Florens G A; Hartwig, Nico G

2017-05-01

The relation between viral load and disease severity in childhood acute respiratory tract infections (ARI) is not fully understood. To assess the clinical relevance of the relation between viral load, determined by cycle threshold (CT) value of real-time reverse transcription-polymerase chain reaction assays and disease severity in children with single- and multiple viral ARI. 582 children with ARI were prospectively followed and tested for 15 viruses. Correlations were calculated between CT values and clinical parameters. In single viral ARI, statistically significant correlations were found between viral loads of Respiratory Syncytial Virus (RSV) and hospitalization and between viral loads of Human Coronavirus (HCoV) and a disease severity score. In multiple-viral ARI, statistically significant correlations between viral load and clinical parameters were found. In RSV-Rhinovirus (RV) multiple infections, a low viral load of RV was correlated with a high length of hospital stay and a high duration of extra oxygen use. The mean CT value for RV, HCoV and Parainfluenza virus was significantly lower in single- versus multiple infections. Although correlations between CT values and clinical parameters in patients with single and multiple viral infection were found, the clinical importance of these findings is limited because individual differences in host-, viral and laboratory factors complicate the interpretation of statistically significant findings. In multiple infections, viral load cannot be used to differentiate between disease causing virus and innocent bystanders. Copyright © 2017 Elsevier B.V. All rights reserved.

Fluorine-18-fluorodeoxyglucose positron emission tomography as an objective substitute for CT morphologic response criteria in patients undergoing chemotherapy for colorectal liver metastases.

PubMed

Nishioka, Yujiro; Yoshioka, Ryuji; Gonoi, Wataru; Sugawara, Toshitaka; Yoshida, Shuntaro; Hashimoto, Masaji; Shindoh, Junichi

2018-05-01

The computed tomography (CT) morphologic response of colorectal liver metastases (CLM) after chemotherapy is reportedly correlated with pathologic response and survival outcomes of patients undergoing surgery. However, they are rather subjective criteria and not evaluable without adequate quality of contrast-enhanced CT images. This study sought the potential use of fluorine-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) as an objective substitute for predicting pathological viability of CLM after chemotherapy. Predictive ability of tumor viability of ≤10% was compared between FDG-PET/CT and contrast-enhanced CT in 34 patients who underwent curative surgical resection for CLM after chemotherapy. The CT morphology and response were defined according to the reported criteria (Chun YS, JAMA 2009). The mean standard uptake value (SUV-mean) in CLM was significantly lower in patients with group 1 and group 2 CT morphology (median, 2.53 and 3.00, respectively) than in group 3 (median, 3.32). The tumor SUV-mean showed moderate correlation with the tumor pathologic viability (r = 0.660, P < 0.0001). A receiver operating characteristic curve analysis revealed that both the tumor SUV-mean (area under the curve [AUC], 0.916; the cut-off value, 3.00) and the CT morphology (AUC, 0.882) have excellent predictive power for ≤10% of tumor viability, while degree of tumor shrinkage showed lower predictive power (AUC, 0.692). FDG-PET shows significant correlation with pathologic viability of CLM after chemotherapy and may offer additional objective information for estimating tumor viability when the CT morphologic response is not evaluable.

68Ga-PSMA PET/CT vs. mpMRI for locoregional prostate cancer staging: correlation with final histopathology.

PubMed

Berger, I; Annabattula, C; Lewis, J; Shetty, D V; Kam, J; Maclean, F; Arianayagam, M; Canagasingham, B; Ferguson, R; Khadra, M; Ko, R; Winter, M; Loh, H; Varol, C

2018-06-01

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) can be used to locate lesions based on PSMA avidity, however guidelines on its use are limited by its infancy. We aimed to compare multiparametric magnetic resonance imaging (mpMRI) and PSMA PET/CT to prostatectomy histopathology. We conducted a chart review from February 2015 to January 2017 of 50 male patients staged for prostate cancer using PSMA PET/CT and mpMRI who then underwent radical prostatectomy. Pre-operative PSMA PET/CT and mpMRI were paired with corresponding histopathology. Correlations, sensitivity, and specificity were used for comparisons. A total of 81 lesions were confirmed by histopathology. Fifty index lesions were detected by histopathology, all of which were detected by PSMA PET/CT (100% detection), and 47 by mpMRI (94% detection). Thirty-one histologically confirmed secondary lesions were detected, 29 of which were detected by PSMA PET/CT (93.5% detection), and 16 by mpMRI (51.6% detection). PSMA had better sensitivity for index lesion localization than mpMRI (81.1 vs. 64.8%). Specificity was similar for PSMA PET/CT and mpMRI (84.6 vs. 82.7%). SUV max of index lesions ranged from 2.9 to 39.6 (M = 9.27 ± 6.41). Index lesion SUV max was positively correlated with PSA (rho = 0.48, p < 0.001) and ISUP grade (rho = 0.51, p < 0.001). PSMA-PET/CT provided superior detection of prostate cancer lesions with better sensitivity than mpMRI. PSMA-PET/CT can be used to enhance locoregional mpMRI to provide improved detection and characterization of lesions.

Comparison of mathematic models for assessment of glomerular filtration rate with electron-beam CT in pigs.

PubMed

Daghini, Elena; Juillard, Laurent; Haas, John A; Krier, James D; Romero, Juan C; Lerman, Lilach O

2007-02-01

To prospectively compare in pigs three mathematic models for assessment of glomerular filtration rate (GFR) on electron-beam (EB) computed tomographic (CT) images, with concurrent inulin clearance serving as the reference standard. This study was approved by the institutional animal care and use committee. Inulin clearance was measured in nine pigs (18 kidneys) and compared with single-kidney GFR assessed from renal time-attenuation curves (TACs) obtained with EB CT before and after infusion of the vasodilator acetylcholine. CT-derived GFR was calculated with the original and modified Patlak methods and with previously validated extended gamma variate modeling of first-pass cortical TACs. Statistical analysis was performed to assess correlation between CT methods and inulin clearance for estimation of GFR with least-squares regression analysis and Bland-Altman graphical representation. Comparisons within groups were performed with a paired t test. GFR assessed with the original Patlak method indicated poor correlation with inulin clearance, whereas GFR assessed with the modified Patlak method (P < .001, r = 0.75) and with gamma variate modeling (P < .001, r = 0.79) correlated significantly with inulin clearance and indicated an increase in response to acetylcholine. CT-derived estimates of GFR can be significantly improved by modifications in image analysis methods (eg, use of a cortical region of interest). (c) RSNA, 2007.

WE-AB-202-07: Ventilation CT: Voxel-Level Comparison with Hyperpolarized Helium-3 & Xenon-129 MRI

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

Tahir, B; Marshall, H; Hughes, P

Purpose: To compare the spatial correlation of ventilation surrogates computed from inspiratory and expiratory breath-hold CT with hyperpolarized Helium-3 & Xenon-129 MRI in a cohort of lung cancer patients. Methods: 5 patients underwent expiration & inspiration breath-hold CT. Xenon-129 & {sup 1}H MRI were also acquired at the same inflation state as inspiratory CT. This was followed immediately by acquisition of Helium-3 & {sup 1}H MRI in the same breath and at the same inflation state as inspiratory CT. Expiration CT was deformably registered to inspiration CT for calculation of ventilation CT from voxel-wise differences in Hounsfield units. Inspiration CTmore » and the Xenon-129’s corresponding anatomical {sup 1}H MRI were registered to Helium-3 MRI via the same-breath anatomical {sup 1}H MRI. This enabled direct comparison of CT ventilation with Helium-3 MRI & Xenon-129 MRI for the median values in corresponding regions of interest, ranging from finer to coarser in-plane dimensions of 10 by 10, 20 by 20, 30 by 30 and 40 by 40, located within the lungs as defined by the same-breath {sup 1}H MRI lung mask. Spearman coefficients were used to assess voxel-level correlation. Results: The median Spearman’s coefficients of ventilation CT with Helium-3 & Xenon-129 MRI for ROIs of 10 by 10, 20 by 20, 30 by 30 and 40 by 40 were 0.52, 0.56, 0.60 and 0.68 and 0.40, 0.42, 0.52 and 0.70, respectively. Conclusion: This work demonstrates a method of acquiring CT & hyperpolarized gas MRI (Helium-3 & Xenon-129 MRI) in similar breath-holds to enable direct spatial comparison of ventilation maps. Initial results show moderate correlation between ventilation CT & hyperpolarized gas MRI, improving for coarser regions which could be attributable to the inherent noise in CT intensity, non-ventilatory effects and registration errors at the voxel-level. Thus, it may be more beneficial to quantify ventilation at a more regional level.« less

Comparative effectiveness of 18F-FDG PET-CT and contrast-enhanced CT in the diagnosis of suspected large-vessel vasculitis.

PubMed

Vaidyanathan, Sriram; Chattopadhyay, Arpita; Mackie, Sarah L; Scarsbrook, Andrew

2018-06-21

Large-vessel vasculitis (LVV) is a serious illness with potentially life-threatening consequences. 18 F-FDG PET-CT has emerged as a valuable diagnostic tool in suspected LVV, combining the strengths of functional and structural imaging. This study aimed to compare the accuracy of FDG PET-CT and contrast-enhanced CT (CECT) in the evaluation of patients with LVV. A retrospective database review for LVV patients undergoing CECT and PET-CT between 2011 to 2016 yielded demographics, scan interval and vasculitis type. Qualitative and quantitative PET-CT analyses included aorta: liver FDG uptake, bespoke FDG uptake distribution scores and vascular maximum standardized uptake values (SUVmax). Quantitative CECT data were assessed wall thickness and mural/lumen ratio. ROC curves were constructed to evaluate comparative diagnostic accuracy and a correlational analysis was conducted between SUVmax and wall-thickness. 36 adults (17 LVV, 19 controls) with a mean age (range) 63 (38-89) years, of which 17 (47%) were males were included. Time interval between CT and PET was mean (standard deviation (SD)) 1.9 (1.2) months. Both SUVmax and wall-thickness demonstrated a significant difference between LVV and controls, with a mean difference (95%confidence interval (CI)) for SUVmax 1.6 (1.1, 2.0) and wall thickness 1.25 (0.68, 1.83) mm, respectively. These two parameters were significantly correlated (p < .0001, R = 0.62). The area under the curve (AUC) (95% CI) for SUVmax was 0.95 (0.88-1.00), and for mural thickening was 0.83 (0.66-0.99). FDG PET-CT demonstrated excellent accuracy whilst CECT mural thickening showed good accuracy in the diagnosis of LVV. Both parameters showed a highly significant correlation. In hospitals without access to FDG PET-CT or in patients unsuitable for PET-CT (e.g., uncontrolled diabetes) CECT offers a viable alternative for the assessment LVV. Advances in knowledge: FDG PET-CT is a highly accurate test for the diagnosis of LVV. Aorta:liver SUVmax ratio is the most specific parameter for LVV. In hospitals without PET-CT or in unsuitable patients e.g. diabetics, CECT is a viable alternative.

Diagnosing Early Ischemic Changes with the Latest-Generation Flat Detector CT: A Comparative Study with Multidetector CT.

PubMed

Maier, I L; Leyhe, J R; Tsogkas, I; Behme, D; Schregel, K; Knauth, M; Schnieder, M; Liman, J; Psychogios, M-N

2018-05-01

One-stop management of mechanical thrombectomy-eligible patients with large-vessel occlusion represents an innovative approach in acute stroke treatment. This approach reduces door-to-reperfusion times by omitting multidetector CT, using flat detector CT as pre-mechanical thrombectomy imaging. The purpose of this study was to compare the diagnostic performance of the latest-generation flat detector CT with multidetector CT. Prospectively derived data from patients with ischemic stroke with large-vessel occlusion and mechanical thrombectomy were analyzed in this monocentric study. All included patients underwent multidetector CT before referral to our comprehensive stroke center and flat detector CT in the angiography suite before mechanical thrombectomy. Diagnosis of early ischemic signs, quantified by the ASPECTS, was compared between modalities using cross tables, the Pearson correlation, and Bland-Altman plots. The predictive value of multidetector CT- and flat detector CT-derived ASPECTS for functional outcome was investigated using area under the receiver operating characteristic curve analysis. Of 25 patients, 24 (96%) had flat detector CT with sufficient diagnostic quality. Median multidetector CT and flat detector CT ASPECTSs were 7 (interquartile range, 5.5-9 and 4.25-8, respectively) with a mean period of 143.6 ± 49.5 minutes between both modalities. The overall sensitivity was 85.1% and specificity was 83.1% for flat detector CT ASPECTS compared with multidetector CT ASPECTS as the reference technique. Multidetector CT and flat detector CT ASPECTS were strongly correlated ( r = 0.849, P < .001) and moderately predicted functional outcome (area under the receiver operating characteristic curve, 0.738; P = .007 and .715; P = .069, respectively). Determination of ASPECTS on flat detector CT is feasible, showing no significant difference compared with multidetector CT ASPECTS and a similar predictive value for functional outcome. Our findings support the use of flat detector CT for emergency stroke imaging before mechanical thrombectomy to reduce door-to-groin time. © 2018 by American Journal of Neuroradiology.

Assessment of BoneTtissue Mineralization by Conventional X-ray Microcomputed tomography: Comparison with Synchrotron Radiation Microcomputed Tomography and Ash Measurements

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

Kazakia,G.; Burghardt, A.; Cheung, S.

2008-01-01

Assessment of bone tissue mineral density (TMD) may provide information critical to the understanding of mineralization processes and bone biomechanics. High-resolution three-dimensional assessment of TMD has recently been demonstrated using synchrotron radiation microcomputed tomography (SR{mu}CT); however, this imaging modality is relatively inaccessible due to the scarcity of SR facilities. Conventional desktop {mu}CT systems are widely available and have been used extensively to assess bone microarchitecture. However, the polychromatic source and cone-shaped beam geometry complicate assessment of TMD by conventional {mu}CT. The goal of this study was to evaluate {mu}CT-based measurement of degree and distribution of tissue mineralization in a quantitative,more » spatially resolved manner. Specifically, {mu}CT measures of bone mineral content (BMC) and TMD were compared to those obtained by SR{mu}CT and gravimetric methods. Cylinders of trabecular bone were machined from human femoral heads (n=5), vertebrae (n=5), and proximal tibiae (n=4). Cylinders were imaged in saline on a polychromatic {mu}CT system at an isotropic voxel size of 8 {mu}m. Volumes were reconstructed using beam hardening correction algorithms based on hydroxyapatite (HA)-resin wedge phantoms of 200 and 1200 mgHA/cm3. SR{mu}CT imaging was performed at an isotropic voxel size of 7.50 {mu}m at the National Synchrotron Light Source. Attenuation values were converted to HA concentration using a linear regression derived by imaging a calibration phantom. Architecture and mineralization parameters were calculated from the image data. Specimens were processed using gravimetric methods to determine ash mass and density. {mu}CT-based BMC values were not affected by altering the beam hardening correction. Volume-averaged TMD values calculated by the two corrections were significantly different (p=0.008) in high volume fraction specimens only, with the 1200 mgHA/cm3 correction resulting in a 4.7% higher TMD value. {mu}CT and SR{mu}CT provided significantly different measurements of both BMC and TMD (p<0.05). In high volume fraction specimens, {mu}CT with 1200 mgHA/cm3 correction resulted in BMC and TMD values 16.7% and 15.0% lower, respectively, than SR{mu}CT values. In low volume fraction specimens, {mu}CT with 1200 mgHA/cm3 correction resulted in BMC and TMD values 12.8% and 12.9% lower, respectively, than SR{mu}CT values. {mu}CT and SR{mu}CT values were well-correlated when volume fraction groups were considered individually (BMC R2=0.97-1.00; TMD R2=0.78-0.99). Ash mass and density were higher than the SR{mu}CT equivalents by 8.6% in high volume fraction specimens and 10.9% in low volume fraction specimens (p<0.05). BMC values calculated by tomography were highly correlated with ash mass (ash versus {mu}CT R2=0.96-1.00; ash versus SR{mu}CT R2=0.99-1.00). TMD values calculated by tomography were moderately correlated with ash density (ash versus {mu}CT R2=0.64-0.72; ash versus SR{mu}CT R2=0.64). Spatially resolved comparisons highlighted substantial geometric nonuniformity in the {mu}CT data, which were reduced (but not eliminated) using the 1200 mg HA/cm3 beam hardening correction, and did not exist in the SR{mu}CT data. This study represents the first quantitative comparison of {mu}CT mineralization evaluation against SR{mu}CT and gravimetry. Our results indicate that {mu}CT mineralization measures are underestimated but well-correlated with SR{mu}CT and gravimetric data, particularly when volume fraction groups are considered individually.« less

Assessment of bone tissue mineralization by conventional x-ray microcomputed tomography: Comparison with synchrotron radiation microcomputed tomography and ash measurements

PubMed Central

Kazakia, G. J.; Burghardt, A. J.; Cheung, S.; Majumdar, S.

2008-01-01

Assessment of bone tissue mineral density (TMD) may provide information critical to the understanding of mineralization processes and bone biomechanics. High-resolution three-dimensional assessment of TMD has recently been demonstrated using synchrotron radiation microcomputed tomography (SRμCT); however, this imaging modality is relatively inaccessible due to the scarcity of SR facilities. Conventional desktop μCT systems are widely available and have been used extensively to assess bone microarchitecture. However, the polychromatic source and cone-shaped beam geometry complicate assessment of TMD by conventional μCT. The goal of this study was to evaluate μCT-based measurement of degree and distribution of tissue mineralization in a quantitative, spatially resolved manner. Specifically, μCT measures of bone mineral content (BMC) and TMD were compared to those obtained by SRμCT and gravimetric methods. Cylinders of trabecular bone were machined from human femoral heads (n=5), vertebrae (n=5), and proximal tibiae (n=4). Cylinders were imaged in saline on a polychromatic μCT system at an isotropic voxel size of 8 μm. Volumes were reconstructed using beam hardening correction algorithms based on hydroxyapatite (HA)-resin wedge phantoms of 200 and 1200 mg HA∕cm3. SRμCT imaging was performed at an isotropic voxel size of 7.50 μm at the National Synchrotron Light Source. Attenuation values were converted to HA concentration using a linear regression derived by imaging a calibration phantom. Architecture and mineralization parameters were calculated from the image data. Specimens were processed using gravimetric methods to determine ash mass and density. μCT-based BMC values were not affected by altering the beam hardening correction. Volume-averaged TMD values calculated by the two corrections were significantly different (p=0.008) in high volume fraction specimens only, with the 1200 mg HA∕cm3 correction resulting in a 4.7% higher TMD value. μCT and SRμCT provided significantly different measurements of both BMC and TMD (p<0.05). In high volume fraction specimens, μCT with 1200 mg HA∕cm3 correction resulted in BMC and TMD values 16.7% and 15.0% lower, respectively, than SRμCT values. In low volume fraction specimens, μCT with 1200 mg HA∕cm3 correction resulted in BMC and TMD values 12.8% and 12.9% lower, respectively, than SRμCT values. μCT and SRμCT values were well-correlated when volume fraction groups were considered individually (BMC R2=0.97−1.00; TMD R2=0.78−0.99). Ash mass and density were higher than the SRμCT equivalents by 8.6% in high volume fraction specimens and 10.9% in low volume fraction specimens (p<0.05). BMC values calculated by tomography were highly correlated with ash mass (ash versus μCT R2=0.96−1.00; ash versus SRμCT R2=0.99−1.00). TMD values calculated by tomography were moderately correlated with ash density (ash versus μCT R2=0.64−0.72; ash versus SRμCT R2=0.64). Spatially resolved comparisons highlighted substantial geometric nonuniformity in the μCT data, which were reduced (but not eliminated) using the 1200 mg HA∕cm3 beam hardening correction, and did not exist in the SRμCT data. This study represents the first quantitative comparison of μCT mineralization evaluation against SRμCT and gravimetry. Our results indicate that μCT mineralization measures are underestimated but well-correlated with SRμCT and gravimetric data, particularly when volume fraction groups are considered individually. PMID:18697542

Ovarian torsion: diagnostic features on CT and MRI with pathologic correlation.

PubMed

Duigenan, Shauna; Oliva, Esther; Lee, Susanna I

2012-02-01

The CT and MRI features of ovarian torsion are illustrated with gross pathologic correlation. Ovarian enlargement with or without an underlying mass is the finding most frequently associated with torsion, but it is nonspecific. A twisted pedicle, although not often detected on imaging, is pathognomonic when seen. Subacute ovarian hemorrhage and abnormal enhancement is usually seen, and both features show characteristic patterns on CT and MRI. Ipsilateral uterine deviation can also be seen. Diagnostic pitfalls that may mimic ovarian torsion and observations for discriminating them are discussed.

Variation compensation and analysis on diaphragm curvature analysis for emphysema quantification on whole lung CT scans

NASA Astrophysics Data System (ADS)

Keller, Brad M.; Reeves, Anthony P.; Barr, R. Graham; Yankelevitz, David F.; Henschke, Claudia I.

2010-03-01

CT scans allow for the quantitative evaluation of the anatomical bases of emphysema. Recently, a non-density based geometric measurement of lung diagphragm curvature has been proposed as a method for the quantification of emphysema from CT. This work analyzes variability of diaphragm curvature and evaluates the effectiveness of a compensation methodology for the reduction of this variability as compared to emphysema index. Using a dataset of 43 scan-pairs with less than a 100 day time-interval between scans, we find that the diaphragm curvature had a trend towards lower overall variability over emphysema index (95% CI:-9.7 to + 14.7 vs. -15.8 to +12.0), and that the variation of both measures was reduced after compensation. We conclude that the variation of the new measure can be considered comparable to the established measure and the compensation can reduce the apparent variation of quantitative measures successfully.

Active contour based segmentation of resected livers in CT images

NASA Astrophysics Data System (ADS)

Oelmann, Simon; Oyarzun Laura, Cristina; Drechsler, Klaus; Wesarg, Stefan

2015-03-01

The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the active contour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.

Prognostic value of CtIP/RBBP8 expression in breast cancer.

PubMed

Soria-Bretones, Isabel; Sáez, Carmen; Ruíz-Borrego, Manuel; Japón, Miguel A; Huertas, Pablo

2013-12-01

CtIP/RBBP8 is a multifunctional protein involved in transcription, DNA replication, DNA repair by homologous recombination and the G1 and G2 checkpoints. Its multiple roles are controlled by its interaction with several specific factors, including the tumor suppressor proteins BRCA1 and retinoblastoma. Both its functions and interactors point to a putative oncogenic potential of CtIP/RBBP8 loss. However, CtIP/RBBP8 relevance in breast tumor appearance, development, and prognosis has yet to be established. We performed a retrospective analysis of CtIP/RBBP8 and RB1 levels by immunohistochemistry using 384 paraffin-embedded breast cancer biopsies obtained during tumor removal surgery. We have observed that low or no expression of CtIP/RBBP8 correlates with high-grade breast cancer and with nodal metastasis. Reduction on CtIP/RBBP8 is most common in hormone receptor (HR)-negative, HER2-positive, and basal-like tumors. We observed lower levels of RB1 on those tumors with reduced CtIP/RBBP8 levels. On luminal tumors, decreased but not absence of CtIP/RBBP8 levels correlate with increased disease-free survival when treated with a combination of hormone, radio, and chemo therapies. © 2013 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

EDI OCT evaluation of choroidal thickness in Stargardt disease

PubMed Central

Sodi, Andrea; Bacherini, Daniela; Caporossi, Orsola; Murro, Vittoria; Mucciolo, Dario Pasquale; Cipollini, Francesca; Passerini, Ilaria; Virgili, Gianni; Rizzo, Stanislao

2018-01-01

Purpose Choroidal thickness (CT) evaluation with EDI-OCT in Stargardt Disease (STGD), considering its possible association with some clinical features of the disease. Methods CT was evaluated in 41 STGD patients and in 70 controls. Measurements were performed in the subfoveal position and at 1000 μm nasally and temporally. CT average values in STGD and in the control group were first compared by means of Student’s T test. Then, the possible association between CT and some clinical features was evaluated by means of linear regression analysis. Considered clinical parameters were: age, age on onset, duration of the disease, visual acuity, foveal thickness, Fishman clinical phenotype, visual field loss and ERG response. Results Average CT was not significantly different between controls and STGD patients. In the STGD group the correlation between CT and age (r = 0.22, p = 0.033) and age of onset (r = 0.05, p = 0.424) was modest, while that of CT with disease duration (r = 0.30, p<0.001) was moderate. CT and foveal thickness were also significantly but modestly correlated (r = 0.15, p = 0.033). Conclusion In our series average CT is not significantly changed in STGD in comparison with the controls. Nevertheless a choroidal thinning may be identified in the more advanced stages of the disease. PMID:29304098

Multiscale and multimodality computed tomography for cortical bone analysis

NASA Astrophysics Data System (ADS)

Ostertag, A.; Peyrin, F.; Gouttenoire, P. J.; Laredo, J. D.; DeVernejoul, M. C.; Cohen Solal, M.; Chappard, C.

2016-12-01

In clinical studies, high resolution peripheral quantitative computed tomography (HR-pQCT) is used to separately evaluate cortical bone and trabecular bone with an isotropic voxel of 82 µm3, and typical cortical parameters are cortical density (D.comp), thickness (Ct.Th), and porosity (Ct.Po). In vitro, micro-computed tomography (micro-CT) is used to explore the internal cortical bone micro-structure with isotropic voxels and high resolution synchrotron radiation (SR); micro-CT is considered the ‘gold standard’. In 16 tibias and 8 femurs, HR-pQCT measurements were compared to conventional micro-CT measurements. To test modality effects, conventional micro-CT measurements were compared to SR micro-CT measurements at 7.5 µm3 SR micro-CT measurements were also tested at different voxel sizes for the femurs, specifically, 7.5 µm3 versus 2.8 µm3. D.comp (r  =  -0.88, p  <  10-3) was the parameter best correlated with porosity (Po.V/TV). The correlation was not affected by the removal of pores under 130 µm. Ct.Th was also significantly highly correlated (r  =  -0.89 p  <  10-3), while Ct.Po was correlated with its counterpart Po.V/TV (r  =  0.74, p  <  10-3). From SR micro-CT and conventional micro-CT at 7.5 µm3 in matching areas, Po.V/TV and pore diameter were underestimated in conventional micro-CT with mean  ±  standard deviation (SD) biases of  -2.5  ±  1.9% and  -0.08  ±  0.08 mm, respectively. In contrast, pore number (Po.N) and pore separation (Po.Sp) were overestimated with mean  ±  SD biases of  +0.03  ±  0.04 mm-1 and  +0.02  ±  0.04 mm, respectively. The results from the tibia and femur were similar when the results of SR micro-CT at 7.5 µm3 and 2.8 µm3 were compared. Po.V/TV, specific surface of pores (Po.S/Po.V), and Po.N were underestimated with mean biases of  -1.7  ±  0.9%, -4.6  ±  4.4 mm-1, and  -0.26  ±  0.15 mm-1, respectively. In contrast, pore spacing was overestimated at 7.5 µm3 compared to 2.8 µm3 with mean biases of 0.05  ±  0.03 mm. Cortical bone measurements from HR-pQCT images provided consistent results compared to those obtained using conventional micro-CT at the distal tibia. D.comp was highly correlated to Po.V/TV because it considers both the micro-porosity (Haversian systems) and macro-porosity (resorption lacunae) of cortical bone. The complexity of canal organization, (including shape, connectivity, and surface) are not fully considered in conventional micro-CT in relation to beam hardening and cone beam reconstruction artifacts. With the exception of Po.V/TV measurements, morphological and topological measurements depend on the characteristics of the x-ray beam, and to a lesser extent, on image resolution.

DIRBoost-an algorithm for boosting deformable image registration: application to lung CT intra-subject registration.

PubMed

Muenzing, Sascha E A; van Ginneken, Bram; Viergever, Max A; Pluim, Josien P W

2014-04-01

We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. Copyright © 2014 Elsevier B.V. All rights reserved.

Fluorine 18 fluorodeoxyglucose PET/CT volume-based indices in locally advanced non-small cell lung cancer: prediction of residual viable tumor after induction chemotherapy.

PubMed

Soussan, Michael; Cyrta, Joanna; Pouliquen, Christelle; Chouahnia, Kader; Orlhac, Fanny; Martinod, Emmanuel; Eder, Véronique; Morère, Jean-François; Buvat, Irène

2014-09-01

To study whether volume-based indices of fluorine 18 fluorodeoxyglucose positron emission tomographic (PET)/computed tomographic (CT) imaging is an accurate tool to predict the amount of residual viable tumor after induction chemotherapy in patients with locally advanced non-small cell lung cancer (NSCLC). This study was approved by institutional review board with waivers of informed consent. Twenty-two patients with locally advanced NSCLC underwent surgery after induction chemotherapy. All had pre- and posttreatment FDG PET/CT scans. CT largest diameter, CT volume, maximum standardized uptake value (SUVmax), mean SUV (SUVmean), metabolic tumor volume (TV), and total lesion glycolysis of primary tumor were calculated. Changes in tumor measurements were determined by dividing follow-up by baseline measurement (ratio index). Amounts of residual viable tumor, necrosis, fibrous tissue, inflammatory infiltrate, and Ki-67 proliferative index were estimated on resected tumor. Correlations between imaging indices and histologic parameters were estimated by using Spearman correlation coefficients or Mann-Whitney tests. No baseline or posttreatment indices correlated with percentage of residual viable tumor. TV ratio was the only index that correlated with percentage of residual viable tumor (r = 0.61 [95% confidence interval: 0.24, 0.81]; P = .003). Conversely, SUVmax and SUVmean ratios were only indices correlated with Ki-67 (r = 0.62 [95% confidence interval: 0.24, 0.82]; P = .003; and r = 0.60 [95% confidence interval: 0.21, 0.81]; P = .004, respectively). Total lesion glycolysis ratio was moderately correlated with residual viable tumor (r = 0.53 [95% confidence interval: 0.13, 0.78]; P = .01) and with Ki-67 (r = 0.57 [95% confidence interval: 0.18, 0.80]; P = .006). No ratios were correlated with presence of inflammatory infiltrate or foamy macrophages. TV and total lesion glycolysis ratios were the only indices correlated with residual viable tumor after induction chemotherapy in locally advanced NSCLC.

18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance in Lymphoma

PubMed Central

Giraudo, Chiara; Raderer, Markus; Karanikas, Georgios; Weber, Michael; Kiesewetter, Barbara; Dolak, Werner; Simonitsch-Klupp, Ingrid; Mayerhoefer, Marius E.

2016-01-01

Objectives The aim of this study was to compare 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/magnetic resonance (MR) (with and without diffusion-weighted imaging [DWI]) to 18F-FDG PET/computed tomography (CT), with regard to the assessment of nodal and extranodal involvement, in patients with Hodgkin lymphoma and non-Hodgkin lymphoma, without restriction to FDG-avid subytpes. Materials and Methods Patients with histologically proven lymphoma were enrolled in this prospective, institutional review board–approved study. After a single 18F-FDG injection, patients consecutively underwent 18F-FDG PET⁄CT and 18F-FDG PET/MR on the same day for staging or restaging. Three sets of images were analyzed separately: 18F-FDG PET/CT, 18F-FDG PET/MR without DWI, and 18F-FDG PET/MR with DWI. Region-based agreement and examination-based sensitivity and specificity were calculated for 18F-FDG PET/CT, 18F-FDG PET/MR without DWI, and 18F-FDG PET/MR DWI. Maximum and mean standardized uptake values (SUVmax, SUVmean) on 18F-FDG PET/CT and 18F-FDG PET/MR were compared and correlated with minimum and mean apparent diffusion coefficients (ADCmin, ADCmean). Results Thirty-four patients with a total of 40 examinations were included. Examination-based sensitivities for 18F-FDG PET/CT, 18F-FDG PET/MR, and 18F-FDG PET/MR DWI were 82.1%, 85.7%, and 100%, respectively; specificities were 100% for all 3 techniques; and accuracies were 87.5%, 90%, and 100%, respectively. 18F-FDG PET/CT was false negative in 5 of 40 examinations (all with mucosa-associated lymphoid tissue lymphoma), and 18F-FDG PET/MR (without DWI) was false negative in 4 of 40 examinations. Region-based percentages of agreement were 99% (κ, 0.95) between 18F-FDG PET/MR DWI and 18F-FDG PET/CT, 99.2% (κ, 0.96) between 18F-FDG PET/MR and 18F-FDG PET/CT, and 99.4% (κ, 0.97) between 18F-FDG PET/MR DWI and 18F-FDG PET/MR. There was a strong correlation between 18F-FDG PET/CT and 18F-FDG PET/MR for SUVmax (r = 0.83) and SUVmean (r = 0.81) but no significant correlation between ADCmin and SUVmax (18F-FDG PET/CT: r = 0.46, P = 0.65; 18F-FDG PET/MR: r = 0.64, P = 0.53) or between ADCmean and SUVmean (respectively, r = −0.14, P = 0.17 for the correlation with PET/CT and r = −0.14, P = 0.14 for the correlation with PET/MR). Conclusions 18F-FDG PET/MR and 18F-FDG PET/CT show a similar diagnostic performance in lymphoma patients. However, if DWI is included in the 18F-FDG PET/MR protocol, results surpass those of 18F-FDG PET/CT because of the higher sensitivity of DWI for mucosa-associated lymphoid tissue lymphomas. PMID:26784400

Correlation of quantitative dual-energy computed tomography iodine maps and abdominal computed tomography perfusion measurements: are single-acquisition dual-energy computed tomography iodine maps more than a reduced-dose surrogate of conventional computed tomography perfusion?

PubMed

Stiller, Wolfram; Skornitzke, Stephan; Fritz, Franziska; Klauss, Miriam; Hansen, Jens; Pahn, Gregor; Grenacher, Lars; Kauczor, Hans-Ulrich

2015-10-01

Study objectives were the quantitative evaluation of whether conventional abdominal computed tomography (CT) perfusion measurements mathematically correlate with quantitative single-acquisition dual-energy CT (DECT) iodine concentration maps, the determination of the optimum time of acquisition for achieving maximum correlation, and the estimation of the potential for radiation exposure reduction when replacing conventional CT perfusion by single-acquisition DECT iodine concentration maps. Dual-energy CT perfusion sequences were dynamically acquired over 51 seconds (34 acquisitions every 1.5 seconds) in 24 patients with histologically verified pancreatic carcinoma using dual-source DECT at tube potentials of 80 kVp and 140 kVp. Using software developed in-house, perfusion maps were calculated from 80-kVp image series using the maximum slope model after deformable motion correction. In addition, quantitative iodine maps were calculated for each of the 34 DECT acquisitions per patient. Within a manual segmentation of the pancreas, voxel-by-voxel correlation between the perfusion map and each of the iodine maps was calculated for each patient to determine the optimum time of acquisition topt defined as the acquisition time of the iodine map with the highest correlation coefficient. Subsequently, regions of interest were placed inside the tumor and inside healthy pancreatic tissue, and correlation between mean perfusion values and mean iodine concentrations within these regions of interest at topt was calculated for the patient sample. The mean (SD) topt was 31.7 (5.4) seconds after the start of contrast agent injection. The mean (SD) perfusion values for healthy pancreatic and tumor tissues were 67.8 (26.7) mL per 100 mL/min and 43.7 (32.2) mL per 100 mL/min, respectively. At topt, the mean (SD) iodine concentrations were 2.07 (0.71) mg/mL in healthy pancreatic and 1.69 (0.98) mg/mL in tumor tissue, respectively. Overall, the correlation between perfusion values and iodine concentrations was high (0.77), with correlation of 0.89 in tumor and of 0.56 in healthy pancreatic tissue at topt. Comparing radiation exposure associated with a single DECT acquisition at topt (0.18 mSv) to that of an 80 kVp CT perfusion sequence (2.96 mSv) indicates that an average reduction of Deff by 94% could be achieved by replacing conventional CT perfusion with a single-acquisition DECT iodine concentration map. Quantitative iodine concentration maps obtained with DECT correlate well with conventional abdominal CT perfusion measurements, suggesting that quantitative iodine maps calculated from a single DECT acquisition at an organ-specific and patient-specific optimum time of acquisition might be able to replace conventional abdominal CT perfusion measurements if the time of acquisition is carefully calibrated. This could lead to large reductions of radiation exposure to the patients while offering quantitative perfusion data for diagnosis.

SU-F-J-77: Variations in the Displacement Vector Fields Calculated by Different Deformable Image Registration Algorithms Used in Helical, Axial and Cone-Beam CT Images of a Mobile

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

Ali, I; Jaskowiak, J; Ahmad, S

Purpose: To investigate quantitatively the displacement-vector-fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone-beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies. Methods: HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water-equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobilemore » phantom are registered with the stationary CT-images using four deformable image registration algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from DIRART software. Results: The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF’s do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR-algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast-demons deviated strongly from other algorithms at large motion amplitudes. Conclusion: In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.« less

Strongly contracted canonical transformation theory

NASA Astrophysics Data System (ADS)

Neuscamman, Eric; Yanai, Takeshi; Chan, Garnet Kin-Lic

2010-01-01

Canonical transformation (CT) theory describes dynamic correlation in multireference systems with large active spaces. Here we discuss CT theory's intruder state problem and why our previous approach of overlap matrix truncation becomes infeasible for sufficiently large active spaces. We propose the use of strongly and weakly contracted excitation operators as alternatives for dealing with intruder states in CT theory. The performance of these operators is evaluated for the H2O, N2, and NiO molecules, with comparisons made to complete active space second order perturbation theory and Davidson-corrected multireference configuration interaction theory. Finally, using a combination of strongly contracted CT theory and orbital-optimized density matrix renormalization group theory, we evaluate the singlet-triplet gap of free base porphin using an active space containing all 24 out-of-plane 2p orbitals. Modeling dynamic correlation with an active space of this size is currently only possible using CT theory.

Prospective feasibility trial of radiotherapy target definition for head and neck cancer using 3-dimensional PET and CT imaging.

PubMed

Scarfone, Christopher; Lavely, William C; Cmelak, Anthony J; Delbeke, Dominique; Martin, William H; Billheimer, Dean; Hallahan, Dennis E

2004-04-01

The aim of this investigation was to evaluate the influence and accuracy of (18)F-FDG PET in target volume definition as a complementary modality to CT for patients with head and neck cancer (HNC) using dedicated PET and CT scanners. Six HNC patients were custom fitted with head and neck and upper body immobilization devices, and conventional radiotherapy CT simulation was performed together with (18)F-FDG PET imaging. Gross target volume (GTV) and pathologic nodal volumes were first defined in the conventional manner based on CT. A segmentation and surface-rendering registration technique was then used to coregister the (18)F-FDG PET and CT planning image datasets. (18)F-FDG PET GTVs were determined and displayed simultaneously with the CT contours. CT GTVs were then modified based on the PET data to form final PET/CT treatment volumes. Five-field intensity-modulated radiation therapy (IMRT) was then used to demonstrate dose targeting to the CT GTV or the PET/CT GTV. One patient was PET-negative after induction chemotherapy. The CT GTV was modified in all remaining patients based on (18)F-FDG PET data. The resulting PET/CT GTV was larger than the original CT volume by an average of 15%. In 5 cases, (18)F-FDG PET identified active lymph nodes that corresponded to lymph nodes contoured on CT. The pathologically enlarged CT lymph nodes were modified to create final lymph node volumes in 3 of 5 cases. In 1 of 6 patients, (18)F-FDG-avid lymph nodes were not identified as pathologic on CT. In 2 of 6 patients, registration of the independently acquired PET and CT data using segmentation and surface rendering resulted in a suboptimal alignment and, therefore, had to be repeated. Radiotherapy planning using IMRT demonstrated the capability of this technique to target anatomic or anatomic/physiologic target volumes. In this manner, metabolically active sites can be intensified to greater daily doses. Inclusion of (18)F-FDG PET data resulted in modified target volumes in radiotherapy planning for HNC. PET and CT data acquired on separate, dedicated scanners may be coregistered for therapy planning; however, dual-acquisition PET/CT systems may be considered to reduce the need for reregistrations. It is possible to use IMRT to target dose to metabolically active sites based on coregistered PET/CT data.

Whole-Body Computed Tomography-Based Body Mass and Body Fat Quantification: A Comparison to Hydrostatic Weighing and Air Displacement Plethysmography.

PubMed

Gibby, Jacob T; Njeru, Dennis K; Cvetko, Steve T; Heiny, Eric L; Creer, Andrew R; Gibby, Wendell A

We correlate and evaluate the accuracy of accepted anthropometric methods of percent body fat (%BF) quantification, namely, hydrostatic weighing (HW) and air displacement plethysmography (ADP), to 2 automatic adipose tissue quantification methods using computed tomography (CT). Twenty volunteer subjects (14 men, 6 women) received head-to-toe CT scans. Hydrostatic weighing and ADP were obtained from 17 and 12 subjects, respectively. The CT data underwent conversion using 2 separate algorithms, namely, the Schneider method and the Beam method, to convert Hounsfield units to their respective tissue densities. The overall mass and %BF of both methods were compared with HW and ADP. When comparing ADP to CT data using the Schneider method and Beam method, correlations were r = 0.9806 and 0.9804, respectively. Paired t tests indicated there were no statistically significant biases. Additionally, observed average differences in %BF between ADP and the Schneider method and the Beam method were 0.38% and 0.77%, respectively. The %BF measured from ADP, the Schneider method, and the Beam method all had significantly higher mean differences when compared with HW (3.05%, 2.32%, and 1.94%, respectively). We have shown that total body mass correlates remarkably well with both the Schneider method and Beam method of mass quantification. Furthermore, %BF calculated with the Schneider method and Beam method CT algorithms correlates remarkably well with ADP. The application of these CT algorithms have utility in further research to accurately stratify risk factors with periorgan, visceral, and subcutaneous types of adipose tissue, and has the potential for significant clinical application.

Variability of dental cone beam CT grey values for density estimations

PubMed Central

Pauwels, R; Nackaerts, O; Bellaiche, N; Stamatakis, H; Tsiklakis, K; Walker, A; Bosmans, H; Bogaerts, R; Jacobs, R; Horner, K

2013-01-01

Objective The aim of this study was to investigate the use of dental cone beam CT (CBCT) grey values for density estimations by calculating the correlation with multislice CT (MSCT) values and the grey value error after recalibration. Methods A polymethyl methacrylate (PMMA) phantom was developed containing inserts of different density: air, PMMA, hydroxyapatite (HA) 50 mg cm−3, HA 100, HA 200 and aluminium. The phantom was scanned on 13 CBCT devices and 1 MSCT device. Correlation between CBCT grey values and CT numbers was calculated, and the average error of the CBCT values was estimated in the medium-density range after recalibration. Results Pearson correlation coefficients ranged between 0.7014 and 0.9996 in the full-density range and between 0.5620 and 0.9991 in the medium-density range. The average error of CBCT voxel values in the medium-density range was between 35 and 1562. Conclusion Even though most CBCT devices showed a good overall correlation with CT numbers, large errors can be seen when using the grey values in a quantitative way. Although it could be possible to obtain pseudo-Hounsfield units from certain CBCTs, alternative methods of assessing bone tissue should be further investigated. Advances in knowledge The suitability of dental CBCT for density estimations was assessed, involving a large number of devices and protocols. The possibility for grey value calibration was thoroughly investigated. PMID:23255537

Corneal Thickness as a Predictor of Corneal Transplant Outcome

PubMed Central

Verdier, David D.; Sugar, Alan; Baratz, Keith; Beck, Roy; Dontchev, Mariya; Dunn, Steven; Gal, Robin L.; Holland, Edward J.; Kollman, Craig; Lass, Jonathan H.; Mannis, Mark J.; Penta, Jeffrey

2013-01-01

Purpose Assess corneal thickness (CT) and correlation with graft outcome after penetrating keratoplasty in the Cornea Donor Study. Methods 887 subjects with a corneal transplant for a moderate risk condition (principally Fuchs or pseudophakic corneal edema) had post-operative CT measurements throughout a 5 year follow up time. Relationships between baseline (recipient, donor, and operative) factors and CT were explored. Proportional hazards models were used to assess association between CT and graft failure. Relationship between CT and cell density was assessed with a longitudinal repeated measures model and Spearman correlation estimates. Results Higher longitudinal CT measurements were associated with diagnosis of pseudophakic or aphakic corneal edema (P<0.001), intraocular pressure > 25mmHg during the first post-operative month (P=0.003), white (non-Hispanic) donor race (P=0.002) and respiratory causes of donor death (P<0.001). Among those without graft failure within the first post-operative year, the 5-year cumulative incidence (±95% CI) of graft failure was 5% ± 5% in those with a 1-year CT ≤500μm, 5% ± 3% for CT 501 – 550μm, 7% ± 4% for CT 551 – 600μm and 20% ± 11% for CT >600μm. In multivariate analysis, both 1 year CT and cell density were associated with subsequent graft failure (P=0.002 and 0.009). CT increase was modestly associated with endothelial cell loss during follow up (r=-0.29). Conclusion During the first 5 years following penetrating keratoplasty, CT can serve as a predictor of graft survival. However, CT is not a substitute for cell density measurement as both measures were independently predictive of graft failure. PMID:23343949

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.

X-Ray microtomography for ant taxonomy: An exploration and case study with two new Terataner (Hymenoptera, Formicidae, Myrmicinae) species from Madagascar

PubMed Central

Fischer, Georg; Liu, Cong; Audisio, Tracy L.; Alpert, Gary D.; Fisher, Brian L.; Economo, Evan P.

2017-01-01

We explore the potential of x-ray micro computed tomography (μCT) for the field of ant taxonomy by using it to enhance the descriptions of two remarkable new species of the ant genus Terataner: T. balrog sp. n. and T. nymeria sp. n.. We provide an illustrated worker-based species identification key for all species found on Madagascar, as well as detailed taxonomic descriptions, which include diagnoses, discussions, measurements, natural history data, high-quality montage images and distribution maps for both new species. In addition to conventional morphological examination, we have used virtual reconstructions based on volumetric μCT scanning data for the species descriptions. We also include 3D PDFs, still images of virtual reconstructions, and 3D rotation videos for both holotype workers and one paratype queen. The complete μCT datasets have been made available online (Dryad, https://datadryad.org) and represent the first cybertypes in ants (and insects). We discuss the potential of μCT scanning and critically assess the usefulness of cybertypes for ant taxonomy. PMID:28328931

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.

C-arm flat detector computed tomography parenchymal blood volume imaging: the nature of parenchymal blood volume parameter and the feasibility of parenchymal blood volume imaging in aneurysmal subarachnoid haemorrhage patients.

PubMed

Kamran, Mudassar; Byrne, James V

2015-09-01

C-arm flat detector computed tomography (FDCT) parenchymal blood volume (PBV) measurements allow assessment of cerebral haemodynamics in the neurointerventional suite. This paper explores the feasibility of C-arm computed tomography (CT) PBV imaging and the relationship between the C-arm CT PBV and the MR-PWI-derived cerebral blood volume (CBV) and cerebral blood flow (CBF) parameters in aneurysmal subarachnoid haemorrhage (SAH) patients developing delayed cerebral ischemia (DCI). Twenty-six patients with DCI following aneurysmal SAH underwent a research C-arm CT PBV scan using a biplane angiography system and contemporaneous MR-PWI scan as part of a prospective study. Quantitative whole-brain atlas-based volume-of-interest analysis in conjunction with Pearson correlation and Bland-Altman tests was performed to explore the agreement between C-arm CT PBV and MR-derived CBV and CBF measurements. All patients received medical management, while eight patients (31%) underwent selective intra-arterial chemical angioplasty. Colour-coded C-arm CT PBV maps were 91% sensitive and 100% specific in detecting the perfusion abnormalities. C-arm CT rPBV demonstrated good agreement and strong correlation with both MR-rCBV and MR-rCBF measurements; the agreement and correlation were stronger for MR-rCBF relative to MR-rCBV and improved for C-arm CT PBV versus the geometric mean of MR-rCBV and MR-rCBF. Analysis of weighted means showed that the C-arm CT PBV has a preferential blood flow weighting (≈ 60% blood flow and ≈ 40% blood volume weighting). C-arm CT PBV imaging is feasible in DCI following aneurysmal SAH. PBV is a composite perfusion parameter incorporating both blood flow and blood volume weightings. That PBV has preferential (≈ 60%) blood flow weighting is an important finding, which is of clinical significance when interpreting the C-arm CT PBV maps, particularly in the setting of acute brain ischemia.

SU-E-I-04: Improving CT Quality for Radiation Therapy of Patients with High Body Mass Index Using Iterative Reconstruction Algorithms

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

Noid, G; Tai, A; Li, X

2015-06-15

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. The CT IQ for patients with a high Body Mass Index (BMI) can suffer from increased noise due to photon starvation. The purpose of this study is to investigate and to quantify the IQ enhancement for high BMI patients through the application of IR algorithms. Methods: CT raw data collected for 6 radiotherapy (RT) patients with BMI, greater than or equal to 30 were retrospectively analyzed. All CT data were acquired using a CT scanner (Somaton Definition ASmore » Open, Siemens) installed in a linac room (CT-on-rails) using standard imaging protocols. The CT data were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared and correlated with patient depth and BMI. The patient depth was defined as the largest distance from anterior to posterior along the bilateral symmetry axis. Results: IR techniques are demonstrated to preserve contrast and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is roughly doubled by adopting the highest SAFIRE strength. A significant correlation was observed between patient depth and IR noise reduction through Pearson’s correlation test (R = 0.9429/P = 0.0167). The mean patient depth was 30.4 cm and the average relative noise reduction for the strongest iterative reconstruction was 55%. Conclusion: The IR techniques produce a measureable enhancement to CT IQ by reducing the noise. Dramatic noise reduction is evident for the high BMI patients. The improved CT IQ enables more accurate delineation of tumors and organs at risk and more accuarte dose calculations for RT planning and delivery guidance. Supported by Siemens.« less

CT perfusion for determination of pharmacologically mediated blood flow changes in an animal tumor model.

PubMed

Hakimé, Antoine; Peddi, Himaja; Hines-Peralta, Andrew U; Wilcox, Carol J; Kruskal, Jonathan; Lin, Shezhang; de Baere, Thierry; Raptopoulos, Vassilios D; Goldberg, S Nahum

2007-06-01

To prospectively compare single- and multisection computed tomographic (CT) perfusion for tumor blood flow determination in an animal model. All animal protocols and experiments were approved by the institutional animal care and use committee before the study was initiated. R3230 mammary adenocarcinoma was implanted in 11 rats. Tumors (18-20 mm) were scanned with dynamic 16-section CT at baseline and after administration of arsenic trioxide, which is known to cause acute reduction in blood flow. The concentration of arsenic was titrated (0-6 mg of arsenic per kilogram of body weight) to achieve a defined blood flow reduction (0%-75%) from baseline levels at 60 minutes, as determined with correlative laser Doppler flowmetry. The mean blood flow was calculated for each of four 5-mm sections that covered the entire tumor, as well as for the entire tumor after multiple sections were processed. Measurements obtained with both methods were correlated with laser Doppler flowmetry measurements. Interobserver agreement was determined for two blinded radiologists, who calculated the percentage of blood flow reduction for the "most representative" single sections at baseline and after arsenic administration. These results were compared with the interobserver variability of the same radiologists obtained by summing blood flow changes for the entire tumor volume. Overall correlations for acute blood flow reduction were demonstrated between laser Doppler flowmetry and the two CT perfusion approaches (single-section CT, r=0.85 and r(2)=0.73; multisection CT, r=0.93 and r(2)=0.87; pooled data, P=.01). CT perfusion disclosed marked heterogeneity of blood flow, with variations of 36% +/- 13 between adjacent 5-mm sections. Given these marked differences, interobserver agreement was much lower for single-section CT (standard deviation, 0.22) than for multisection CT (standard deviation, 0.10; P=.01). Multisection CT perfusion techniques may provide an accurate and more reproducible method of tumor perfusion surveillance than comparison of single representative tumor sections. (c) RSNA, 2007.

SU-E-I-75: Evaluation of An Orthopedic Metal Artifact Reduction (O-MAR) Algorithm On Patients with Spinal Prostheses Near Spinal Tumors

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

Shen, Z; Xia, P; Djemil, T

Purpose: To evaluate the impact of a commercial orthopedic metal artifact reduction (O-MAR) algorithm on CT image quality and dose calculation for patients with spinal prostheses near spinal tumors. Methods: A CT electron density phantom was scanned twice: with tissue-simulating inserts only, and with a titanium insert replacing solid water. A patient plan was mapped to the phantom images in two ways: with the titanium inside or outside of the spinal tumor. Pinnacle and Eclipse were used to evaluate the dosimetric effects of O-MAR on 12-bit and 16-bit CT data, respectively. CT images from five patients with spinal prostheses weremore » reconstructed with and without O-MAR. Two observers assessed the image quality improvement from O-MAR. Both pencil beam and Monte Carlo dose calculation in iPlan were used for the patient study. The percentage differences between non-OMAR and O-MAR datasets were calculated for PTV-min, PTV-max, PTV-mean, PTV-V100, PTV-D90, OAR-V10Gy, OAR-max, and OAR-D0.1cc. Results: O-MAR improved image quality but did not significantly affect the dose distributions and DVHs for both 12-bit and 16- bit CT phantom data. All five patient cases demonstrated some degree of image quality improvement from O-MAR, ranging from small to large metal artifact reduction. For pencil beam, the largest discrepancy was observed for OARV-10Gy at 5.4%, while the other seven parameters were ≤0.6%. For Monte Carlo, the differences between non-O-MAR and O-MAR datasets were ≤3.0%. Conclusion: Both phantom and patient studies indicated that O-MAR can substantially reduce metal artifacts on CT images, allowing better visualization of the anatomical structures and metal objects. The dosimetric impact of O-MAR was insignificant regardless of the metal location, image bit-depth, and dose calculation algorithm. O-MAR corrected images are recommended for radiation treatment planning on patients with spinal prostheses because of the improved image quality and no need to modify current dose constraints. This work was supported by a research grant from Philips Healthcare. Paul Klahr is an employee of Philips Healthcare.« less

A comparative study of quantitative assessment with fluorine-18-fluorodeoxyglucose positron-emission tomography and endoscopic ultrasound in oesophageal cancer.

PubMed

Borakati, Aditya; Razack, Abdul; Cawthorne, Chris; Roy, Rajarshi; Usmani, Sharjeel; Ahmed, Najeeb

2018-07-01

This study aims to assess the correlation between PET/CT and endoscopic ultrasound (EUS) parameters in patients with oesophageal cancer. All patients who had complete PET/CT and EUS staging performed for oesophageal cancer at our centre between 2010 and 2016 were included. Images were retrieved and analysed for a range of parameters including tumour length, volume and position relative to the aortic arch. Seventy patients were included in the main analysis. A strong correlation was found between EUS and PET/CT in the tumour length, the volume and the position of the tumour relative to the aortic arch. Regression modelling showed a reasonable predictive value for PET/CT in calculating EUS parameters, with r higher than 0.585 in some cases. Given the strong correlation between EUS and PET parameters, fluorine-18 fluorodeoxyglucose (F-FDG) PET can provide accurate information on the length and the volume of tumour in patients who either cannot tolerate EUS or have impassable strictures.

Abdominal multi-organ CT segmentation using organ correlation graph and prediction-based shape and location priors.

PubMed

Okada, Toshiyuki; Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki; Sato, Yoshinobu

2013-01-01

The paper addresses the automated segmentation of multiple organs in upper abdominal CT data. We propose a framework of multi-organ segmentation which is adaptable to any imaging conditions without using intensity information in manually traced training data. The features of the framework are as follows: (1) the organ correlation graph (OCG) is introduced, which encodes the spatial correlations among organs inherent in human anatomy; (2) the patient-specific organ shape and location priors obtained using OCG enable the estimation of intensity priors from only target data and optionally a number of untraced CT data of the same imaging condition as the target data. The proposed methods were evaluated through segmentation of eight abdominal organs (liver, spleen, left and right kidney, pancreas, gallbladder, aorta, and inferior vena cava) from 86 CT data obtained by four imaging conditions at two hospitals. The performance was comparable to the state-of-the-art method using intensity priors constructed from manually traced data.

Evaluation of pulmonary function using single-breath-hold dual-energy computed tomography with xenon

PubMed Central

Kyoyama, Hiroyuki; Hirata, Yusuke; Kikuchi, Satoshi; Sakai, Kosuke; Saito, Yuriko; Mikami, Shintaro; Moriyama, Gaku; Yanagita, Hisami; Watanabe, Wataru; Otani, Katharina; Honda, Norinari; Uematsu, Kazutsugu

2017-01-01

Abstract Xenon-enhanced dual-energy computed tomography (xenon-enhanced CT) can provide lung ventilation maps that may be useful for assessing structural and functional abnormalities of the lung. Xenon-enhanced CT has been performed using a multiple-breath-hold technique during xenon washout. We recently developed xenon-enhanced CT using a single-breath-hold technique to assess ventilation. We sought to evaluate whether xenon-enhanced CT using a single-breath-hold technique correlates with pulmonary function testing (PFT) results. Twenty-six patients, including 11 chronic obstructive pulmonary disease (COPD) patients, underwent xenon-enhanced CT and PFT. Three of the COPD patients underwent xenon-enhanced CT before and after bronchodilator treatment. Images from xenon-CT were obtained by dual-source CT during a breath-hold after a single vital-capacity inspiration of a xenon–oxygen gas mixture. Image postprocessing by 3-material decomposition generated conventional CT and xenon-enhanced images. Low-attenuation areas on xenon images matched low-attenuation areas on conventional CT in 21 cases but matched normal-attenuation areas in 5 cases. Volumes of Hounsfield unit (HU) histograms of xenon images correlated moderately and highly with vital capacity (VC) and total lung capacity (TLC), respectively (r = 0.68 and 0.85). Means and modes of histograms weakly correlated with VC (r = 0.39 and 0.38), moderately with forced expiratory volume in 1 second (FEV1) (r = 0.59 and 0.56), weakly with the ratio of FEV1 to FVC (r = 0.46 and 0.42), and moderately with the ratio of FEV1 to its predicted value (r = 0.64 and 0.60). Mode and volume of histograms increased in 2 COPD patients after the improvement of FEV1 with bronchodilators. Inhalation of xenon gas caused no adverse effects. Xenon-enhanced CT using a single-breath-hold technique depicted functional abnormalities not detectable on thin-slice CT. Mode, mean, and volume of HU histograms of xenon images reflected pulmonary function. Xenon images obtained with xenon-enhanced CT using a single-breath-hold technique can qualitatively depict pulmonary ventilation. A larger study comprising only COPD patients should be conducted, as xenon-enhanced CT is expected to be a promising technique for the management of COPD. PMID:28099359

Evaluation of pulmonary function using single-breath-hold dual-energy computed tomography with xenon: Results of a preliminary study.

PubMed

Kyoyama, Hiroyuki; Hirata, Yusuke; Kikuchi, Satoshi; Sakai, Kosuke; Saito, Yuriko; Mikami, Shintaro; Moriyama, Gaku; Yanagita, Hisami; Watanabe, Wataru; Otani, Katharina; Honda, Norinari; Uematsu, Kazutsugu

2017-01-01

Xenon-enhanced dual-energy computed tomography (xenon-enhanced CT) can provide lung ventilation maps that may be useful for assessing structural and functional abnormalities of the lung. Xenon-enhanced CT has been performed using a multiple-breath-hold technique during xenon washout. We recently developed xenon-enhanced CT using a single-breath-hold technique to assess ventilation. We sought to evaluate whether xenon-enhanced CT using a single-breath-hold technique correlates with pulmonary function testing (PFT) results.Twenty-six patients, including 11 chronic obstructive pulmonary disease (COPD) patients, underwent xenon-enhanced CT and PFT. Three of the COPD patients underwent xenon-enhanced CT before and after bronchodilator treatment. Images from xenon-CT were obtained by dual-source CT during a breath-hold after a single vital-capacity inspiration of a xenon-oxygen gas mixture. Image postprocessing by 3-material decomposition generated conventional CT and xenon-enhanced images.Low-attenuation areas on xenon images matched low-attenuation areas on conventional CT in 21 cases but matched normal-attenuation areas in 5 cases. Volumes of Hounsfield unit (HU) histograms of xenon images correlated moderately and highly with vital capacity (VC) and total lung capacity (TLC), respectively (r = 0.68 and 0.85). Means and modes of histograms weakly correlated with VC (r = 0.39 and 0.38), moderately with forced expiratory volume in 1 second (FEV1) (r = 0.59 and 0.56), weakly with the ratio of FEV1 to FVC (r = 0.46 and 0.42), and moderately with the ratio of FEV1 to its predicted value (r = 0.64 and 0.60). Mode and volume of histograms increased in 2 COPD patients after the improvement of FEV1 with bronchodilators. Inhalation of xenon gas caused no adverse effects.Xenon-enhanced CT using a single-breath-hold technique depicted functional abnormalities not detectable on thin-slice CT. Mode, mean, and volume of HU histograms of xenon images reflected pulmonary function. Xenon images obtained with xenon-enhanced CT using a single-breath-hold technique can qualitatively depict pulmonary ventilation. A larger study comprising only COPD patients should be conducted, as xenon-enhanced CT is expected to be a promising technique for the management of COPD.

A comparative study of cranial, blunt trauma fractures as seen at medicolegal autopsy and by Computed Tomography

PubMed Central

2009-01-01

Background Computed Tomography (CT) has become a widely used supplement to medico legal autopsies at several forensic institutes. Amongst other things, it has proven to be very valuable in visualising fractures of the cranium. Also CT scan data are being used to create head models for biomechanical trauma analysis by Finite Element Analysis. If CT scan data are to be used for creating individual head models for retrograde trauma analysis in the future we need to ascertain how well cranial fractures are captured by CT scan. The purpose of this study was to compare the diagnostic agreement between CT and autopsy regarding cranial fractures and especially the precision with which cranial fractures are recorded. Methods The autopsy fracture diagnosis was compared to the diagnosis of two CT readings (reconstructed with Multiplanar and Maximum Intensity Projection reconstructions) by registering the fractures on schematic drawings. The extent of the fractures was quantified by merging 3-dimensional datasets from both the autopsy as input by 3D digitizer tracing and CT scan. Results The results showed a good diagnostic agreement regarding fractures localised in the posterior fossa, while the fracture diagnosis in the medial and anterior fossa was difficult at the first CT scan reading. The fracture diagnosis improved during the second CT scan reading. Thus using two different CT reconstructions improved diagnosis in the medial fossa and at the impact points in the cranial vault. However, fracture diagnosis in the anterior and medial fossa and of hairline fractures in general still remained difficult. Conclusion The study showed that the forensically important fracture systems to a large extent were diagnosed on CT images using Multiplanar and Maximum Intensity Projection reconstructions. Difficulties remained in the minute diagnosis of hairline fractures. These inconsistencies need to be resolved in order to use CT scan data of victims for individual head modelling and trauma analysis. PMID:19835570

Preliminary experimental results from a MARS Micro-CT system.

PubMed

He, Peng; Yu, Hengyong; Thayer, Patrick; Jin, Xin; Xu, Qiong; Bennett, James; Tappenden, Rachael; Wei, Biao; Goldstein, Aaron; Renaud, Peter; Butler, Anthony; Butler, Phillip; Wang, Ge

2012-01-01

The Medipix All Resolution System (MARS) system is a commercial spectral/multi-energy micro-CT scanner designed and assembled by the MARS Bioimaging, Ltd. in New Zealand. This system utilizes the state-of-the-art Medipix photon-counting, energy-discriminating detector technology developed by a collaboration at European Organization for Nuclear Research (CERN). In this paper, we report our preliminary experimental results using this system, including geometrical alignment, photon energy characterization, protocol optimization, and spectral image reconstruction. We produced our scan datasets with a multi-material phantom, and then applied ordered subset-simultaneous algebraic reconstruction technique (OS-SART) to reconstruct images in different energy ranges and principal component analysis (PCA) to evaluate spectral deviation among the energy ranges.

Atlas-based whole-body segmentation of mice from low-contrast Micro-CT data.

PubMed

Baiker, Martin; Milles, Julien; Dijkstra, Jouke; Henning, Tobias D; Weber, Axel W; Que, Ivo; Kaijzel, Eric L; Löwik, Clemens W G M; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2010-12-01

This paper presents a fully automated method for atlas-based whole-body segmentation in non-contrast-enhanced Micro-CT data of mice. The position and posture of mice in such studies may vary to a large extent, complicating data comparison in cross-sectional and follow-up studies. Moreover, Micro-CT typically yields only poor soft-tissue contrast for abdominal organs. To overcome these challenges, we propose a method that divides the problem into an atlas constrained registration based on high-contrast organs in Micro-CT (skeleton, lungs and skin), and a soft tissue approximation step for low-contrast organs. We first present a modification of the MOBY mouse atlas (Segars et al., 2004) by partitioning the skeleton into individual bones, by adding anatomically realistic joint types and by defining a hierarchical atlas tree description. The individual bones as well as the lungs of this adapted MOBY atlas are then registered one by one traversing the model tree hierarchy. To this end, we employ the Iterative Closest Point method and constrain the Degrees of Freedom of the local registration, dependent on the joint type and motion range. This atlas-based strategy renders the method highly robust to exceptionally large postural differences among scans and to moderate pathological bone deformations. The skin of the torso is registered by employing a novel method for matching distributions of geodesic distances locally, constrained by the registered skeleton. Because of the absence of image contrast between abdominal organs, they are interpolated from the atlas to the subject domain using Thin-Plate-Spline approximation, defined by correspondences on the already established registration of high-contrast structures (bones, lungs and skin). We extensively evaluate the proposed registration method, using 26 non-contrast-enhanced Micro-CT datasets of mice, and the skin registration and organ interpolation, using contrast-enhanced Micro-CT datasets of 15 mice. The posture and shape varied significantly among the animals and the data was acquired in vivo. After registration, the mean Euclidean distance was less than two voxel dimensions for the skeleton and the lungs respectively and less than one voxel dimension for the skin. Dice coefficients of volume overlap between manually segmented and interpolated skeleton and organs vary between 0.47+/-0.08 for the kidneys and 0.73+/-0.04 for the brain. These experiments demonstrate the method's effectiveness for overcoming exceptionally large variations in posture, yielding acceptable approximation accuracy even in the absence of soft-tissue contrast in in vivo Micro-CT data without requiring user initialization. Copyright 2010 Elsevier B.V. All rights reserved.

SparseCT: interrupted-beam acquisition and sparse reconstruction for radiation dose reduction

NASA Astrophysics Data System (ADS)

Koesters, Thomas; Knoll, Florian; Sodickson, Aaron; Sodickson, Daniel K.; Otazo, Ricardo

2017-03-01

State-of-the-art low-dose CT methods reduce the x-ray tube current and use iterative reconstruction methods to denoise the resulting images. However, due to compromises between denoising and image quality, only moderate dose reductions up to 30-40% are accepted in clinical practice. An alternative approach is to reduce the number of x-ray projections and use compressed sensing to reconstruct the full-tube-current undersampled data. This idea was recognized in the early days of compressed sensing and proposals for CT dose reduction appeared soon afterwards. However, no practical means of undersampling has yet been demonstrated in the challenging environment of a rapidly rotating CT gantry. In this work, we propose a moving multislit collimator as a practical incoherent undersampling scheme for compressed sensing CT and evaluate its application for radiation dose reduction. The proposed collimator is composed of narrow slits and moves linearly along the slice dimension (z), to interrupt the incident beam in different slices for each x-ray tube angle (θ). The reduced projection dataset is then reconstructed using a sparse approach, where 3D image gradients are employed to enforce sparsity. The effects of the collimator slits on the beam profile were measured and represented as a continuous slice profile. SparseCT was tested using retrospective undersampling and compared against commercial current-reduction techniques on phantoms and in vivo studies. Initial results suggest that SparseCT may enable higher performance than current-reduction, particularly for high dose reduction factors.

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

PubMed

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

2018-04-18

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

Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study.

PubMed

Kim, Hyungjin; Park, Chang Min; Song, Yong Sub; Lee, Sang Min; Goo, Jin Mo

2014-05-01

To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. CT scans were performed on a chest phantom containing various nodules (10 and 12mm; +100, -630 and -800HU) at 120kVp with tube current-time settings of 10, 20, 50, and 100mAs. Each CT was reconstructed using filtered back projection (FBP), iDose(4) and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p>0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose(4) at all radiation dose settings (p<0.05). Semi-automated nodule volumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Three-Dimensional Printing of X-Ray Computed Tomography Datasets with Multiple Materials Using Open-Source Data Processing

ERIC Educational Resources Information Center

Sander, Ian M.; McGoldrick, Matthew T.; Helms, My N.; Betts, Aislinn; van Avermaete, Anthony; Owers, Elizabeth; Doney, Evan; Liepert, Taimi; Niebur, Glen; Liepert, Douglas; Leevy, W. Matthew

2017-01-01

Advances in three-dimensional (3D) printing allow for digital files to be turned into a "printed" physical product. For example, complex anatomical models derived from clinical or pre-clinical X-ray computed tomography (CT) data of patients or research specimens can be constructed using various printable materials. Although 3D printing…

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

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

Young, S; Lo, P; Hoffman, J

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modulesmore » in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range of acquisition and reconstruction parameters present in the clinical environment. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less

SU-E-I-88: Realistic Pathological Simulations of the NCAT and Zubal Anthropomorphic Models, Based on Clinical PET/CT Data.

PubMed

Papadimitroulas, P; Loudos, G; Le Maitre, A; Efthimiou, N; Visvikis, D; Nikiforidis, G; Kagadis, G C

2012-06-01

In the present study a patient-specific dataset of realistic PET simulations was created, taking into account the variability of clinical oncology data. Tumor variability was tested in the simulated results. A comparison of the produced simulated data was performed to clinical PET/CT data, for the validation and the evaluation of the procedure. Clinical PET/CT data of oncology patients were used as the basis of the simulated variability inserting patient-specific characteristics in the NCAT and the Zubal anthropomorphic phantoms. GATE Monte Carlo toolkit was used for simulating a commercial PET scanner. The standard computational anthropomorphic phantoms were adapted to the CT data (organ shapes), using a fitting algorithm. The activity map was derived from PET images. Patient tumors were segmented and inserted in the phantom, using different activity distributions. The produced simulated data were reconstructed using the STIR opensource software and compared to the original clinical ones. The accuracy of the procedure was tested in four different oncology cases. Each pathological situation was illustrated simulating a) a healthy body, b) insertion of the clinical tumor with homogenous activity, and c) insertion of the clinical tumor with variable activity (voxel-by-voxel) based on the clinical PET data. The accuracy of the presented dataset was compared to the original PET/CT data. Partial Volume Correction (PVC) was also applied in the simulated data. In this study patient-specific characteristics were used in computational anthropomorphic models for simulating realistic pathological patients. Voxel-by-voxel activity distribution with PVC within the tumor gives the most accurate results. Radiotherapy applications can utilize the benefits of the accurate realistic imaging simulations, using the anatomicaland biological information of each patient. Further work will incorporate the development of analytical anthropomorphic models with motion and cardiac correction, combined with pathological patients to achieve high accuracy in tumor imaging. This research was supported by the Joint Research and Technology Program between Greece and France; 2009-2011 (protocol ID: 09FR103). © 2012 American Association of Physicists in Medicine.

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

PubMed

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

2016-09-01

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

Automated synthesis, insertion and detection of polyps for CT colonography

NASA Astrophysics Data System (ADS)

Sezille, Nicolas; Sadleir, Robert J. T.; Whelan, Paul F.

2003-03-01

CT Colonography (CTC) is a new non-invasive colon imaging technique which has the potential to replace conventional colonoscopy for colorectal cancer screening. A novel system which facilitates automated detection of colorectal polyps at CTC is introduced. As exhaustive testing of such a system using real patient data is not feasible, more complete testing is achieved through synthesis of artificial polyps and insertion into real datasets. The polyp insertion is semi-automatic: candidate points are manually selected using a custom GUI, suitable points are determined automatically from an analysis of the local neighborhood surrounding each of the candidate points. Local density and orientation information are used to generate polyps based on an elliptical model. Anomalies are identified from the modified dataset by analyzing the axial images. Detected anomalies are classified as potential polyps or natural features using 3D morphological techniques. The final results are flagged for review. The system was evaluated using 15 scenarios. The sensitivity of the system was found to be 65% with 34% false positive detections. Automated diagnosis at CTC is possible and thorough testing is facilitated by augmenting real patient data with computer generated polyps. Ultimately, automated diagnosis will enhance standard CTC and increase performance.

Dynamic re-weighted total variation technique and statistic Iterative reconstruction method for x-ray CT metal artifact reduction

NASA Astrophysics Data System (ADS)

Peng, Chengtao; Qiu, Bensheng; Zhang, Cheng; Ma, Changyu; Yuan, Gang; Li, Ming

2017-07-01

Over the years, the X-ray computed tomography (CT) has been successfully used in clinical diagnosis. However, when the body of the patient to be examined contains metal objects, the image reconstructed would be polluted by severe metal artifacts, which affect the doctor's diagnosis of disease. In this work, we proposed a dynamic re-weighted total variation (DRWTV) technique combined with the statistic iterative reconstruction (SIR) method to reduce the artifacts. The DRWTV method is based on the total variation (TV) and re-weighted total variation (RWTV) techniques, but it provides a sparser representation than TV and protects the tissue details better than RWTV. Besides, the DRWTV can suppress the artifacts and noise, and the SIR convergence speed is also accelerated. The performance of the algorithm is tested on both simulated phantom dataset and clinical dataset, which are the teeth phantom with two metal implants and the skull with three metal implants, respectively. The proposed algorithm (SIR-DRWTV) is compared with two traditional iterative algorithms, which are SIR and SIR constrained by RWTV regulation (SIR-RWTV). The results show that the proposed algorithm has the best performance in reducing metal artifacts and protecting tissue details.

Cardiovascular imaging environment: will the future be cloud-based?

PubMed

Kawel-Boehm, Nadine; Bluemke, David A

2017-07-01

In cardiovascular CT and MR imaging large datasets have to be stored, post-processed, analyzed and distributed. Beside basic assessment of volume and function in cardiac magnetic resonance imaging e.g., more sophisticated quantitative analysis is requested requiring specific software. Several institutions cannot afford various types of software and provide expertise to perform sophisticated analysis. Areas covered: Various cloud services exist related to data storage and analysis specifically for cardiovascular CT and MR imaging. Instead of on-site data storage, cloud providers offer flexible storage services on a pay-per-use basis. To avoid purchase and maintenance of specialized software for cardiovascular image analysis, e.g. to assess myocardial iron overload, MR 4D flow and fractional flow reserve, evaluation can be performed with cloud based software by the consumer or complete analysis is performed by the cloud provider. However, challenges to widespread implementation of cloud services include regulatory issues regarding patient privacy and data security. Expert commentary: If patient privacy and data security is guaranteed cloud imaging is a valuable option to cope with storage of large image datasets and offer sophisticated cardiovascular image analysis for institutions of all sizes.

Semi-automatic 3D lung nodule segmentation in CT using dynamic programming

NASA Astrophysics Data System (ADS)

Sargent, Dustin; Park, Sun Young

2017-02-01

We present a method for semi-automatic segmentation of lung nodules in chest CT that can be extended to general lesion segmentation in multiple modalities. Most semi-automatic algorithms for lesion segmentation or similar tasks use region-growing or edge-based contour finding methods such as level-set. However, lung nodules and other lesions are often connected to surrounding tissues, which makes these algorithms prone to growing the nodule boundary into the surrounding tissue. To solve this problem, we apply a 3D extension of the 2D edge linking method with dynamic programming to find a closed surface in a spherical representation of the nodule ROI. The algorithm requires a user to draw a maximal diameter across the nodule in the slice in which the nodule cross section is the largest. We report the lesion volume estimation accuracy of our algorithm on the FDA lung phantom dataset, and the RECIST diameter estimation accuracy on the lung nodule dataset from the SPIE 2016 lung nodule classification challenge. The phantom results in particular demonstrate that our algorithm has the potential to mitigate the disparity in measurements performed by different radiologists on the same lesions, which could improve the accuracy of disease progression tracking.

Image segmentation evaluation for very-large datasets

NASA Astrophysics Data System (ADS)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Evaluation of MLACF based calculated attenuation brain PET imaging for FDG patient studies

NASA Astrophysics Data System (ADS)

Bal, Harshali; Panin, Vladimir Y.; Platsch, Guenther; Defrise, Michel; Hayden, Charles; Hutton, Chloe; Serrano, Benjamin; Paulmier, Benoit; Casey, Michael E.

2017-04-01

Calculating attenuation correction for brain PET imaging rather than using CT presents opportunities for low radiation dose applications such as pediatric imaging and serial scans to monitor disease progression. Our goal is to evaluate the iterative time-of-flight based maximum-likelihood activity and attenuation correction factors estimation (MLACF) method for clinical FDG brain PET imaging. FDG PET/CT brain studies were performed in 57 patients using the Biograph mCT (Siemens) four-ring scanner. The time-of-flight PET sinograms were acquired using the standard clinical protocol consisting of a CT scan followed by 10 min of single-bed PET acquisition. Images were reconstructed using CT-based attenuation correction (CTAC) and used as a gold standard for comparison. Two methods were compared with respect to CTAC: a calculated brain attenuation correction (CBAC) and MLACF based PET reconstruction. Plane-by-plane scaling was performed for MLACF images in order to fix the variable axial scaling observed. The noise structure of the MLACF images was different compared to those obtained using CTAC and the reconstruction required a higher number of iterations to obtain comparable image quality. To analyze the pooled data, each dataset was registered to a standard template and standard regions of interest were extracted. An SUVr analysis of the brain regions of interest showed that CBAC and MLACF were each well correlated with CTAC SUVrs. A plane-by-plane error analysis indicated that there were local differences for both CBAC and MLACF images with respect to CTAC. Mean relative error in the standard regions of interest was less than 5% for both methods and the mean absolute relative errors for both methods were similar (3.4%  ±  3.1% for CBAC and 3.5%  ±  3.1% for MLACF). However, the MLACF method recovered activity adjoining the frontal sinus regions more accurately than CBAC method. The use of plane-by-plane scaling of MLACF images was found to be a crucial step in order to obtain improved activity estimates. Presence of local errors in both MLACF and CBAC based reconstructions would require the use of a normal database for clinical assessment. However, further work is required in order to assess the clinical advantage of MLACF over CBAC based method.

In vivo spatial correlation between (18)F-BPA and (18)F-FDG uptakes in head and neck cancer.

PubMed

Kobayashi, Kazuma; Kurihara, Hiroaki; Watanabe, Yoshiaki; Murakami, Naoya; Inaba, Koji; Nakamura, Satoshi; Wakita, Akihisa; Okamoto, Hiroyuki; Umezawa, Rei; Takahashi, Kana; Igaki, Hiroshi; Ito, Yoshinori; Yoshimoto, Seiichi; Shigematsu, Naoyuki; Itami, Jun

2016-09-01

Borono-2-(18)F-fluoro-phenylalanine ((18)F-BPA) has been used to estimate the therapeutic effects of boron neutron capture therapy (BNCT), while (18)F-fluorodeoxyglucose ((18)F-FDG) is the most commonly used positron emission tomography (PET) radiopharmaceutical in a routine clinical use. The aim of the present study was to evaluate spatial correlation between (18)F-BPA and (18)F-FDG uptakes using a deformable image registration-based technique. Ten patients with head and neck cancer were recruited from January 2014 to December 2014. All patients underwent whole-body (18)F-BPA PET/computed tomography (CT) and (18)F-FDG PET/CT within a 2-week period. For each patient, (18)F-BPA PET/CT and (18)F-FDG PET/CT images were aligned based on a deformable image registration framework. The voxel-by-voxel spatial correlation of standardized uptake value (SUV) within the tumor was analyzed. Our image processing framework achieved accurate and validated registration results for each PET/CT image. In 9/10 patients, the spatial distribution of SUVs between (18)F-BPA and (18)F-FDG showed a significant, positive correlation in the tumor volume. Deformable image registration-based voxel-wise analysis demonstrated a spatial correlation between (18)F-BPA and (18)F-FDG uptakes in the head and neck cancer. A tumor sub-volume with a high (18)F-FDG uptake may predict high accumulation of (18)F-BPA. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Correlation among far-infrared reflection modes, crystal structures and dielectric properties of Ba(Zn{sub 1/3}Nb{sub 2/3})O{sub 3}–CaTiO{sub 3} ceramics

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

Shi, Feng, E-mail: sf751106@sina.com.cn; Sun, Haiqing; Liu, Hongquan

Highlights: • Crystal symmetry decreases with CT concentration from cubic to hexagonal structure. • Lattice constants as well as the ordered degree change with CT concentration. • Ordered structures turn from 1:1 to 1:2 ordering with change of crystal structures. • There is a correlation between FIR phonon modes and dielectric properties. • There is a correlation between FIR phonon modes and crystal structures. - Abstract: Ba(Zn{sub 1/3}Nb{sub 2/3})O{sub 3} (BZN)–CaTiO{sub 3} (CT) microwave dielectric ceramics were synthesized at 1395 °C for 4 h using conventional solid-state sintering technique with different CT contents. The ceramics were characterized by X-ray diffractionmore » (XRD) and far-infrared reflection (FIR) spectroscopy to evaluate correlations among crystal structures, dielectric properties, and infrared modes. XRD results showed that crystal symmetry decreased with increased CT concentration from cubic to hexagonal structure, and lattice constants and ordered degree changed accordingly. Ordered phases transformed from 1:1 to 1:2 ordered structure with crystal-structure change. FIR results demonstrated that two new IR active modes appeared at 300 cm{sup −1}, and another new mode appeared at 600 cm{sup −1} for the x ≥ 0.60 sample, which agreed with the change in crystal structures as confirmed by XRD results. Correlations between FIR modes and dielectric properties were established.« less

Automated assessment of breast tissue density in non-contrast 3D CT images without image segmentation based on a deep CNN

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Kano, Takuya; Koyasu, Hiromi; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Matsuo, Masayuki; Fujita, Hiroshi

2017-03-01

This paper describes a novel approach for the automatic assessment of breast density in non-contrast three-dimensional computed tomography (3D CT) images. The proposed approach trains and uses a deep convolutional neural network (CNN) from scratch to classify breast tissue density directly from CT images without segmenting the anatomical structures, which creates a bottleneck in conventional approaches. Our scheme determines breast density in a 3D breast region by decomposing the 3D region into several radial 2D-sections from the nipple, and measuring the distribution of breast tissue densities on each 2D section from different orientations. The whole scheme is designed as a compact network without the need for post-processing and provides high robustness and computational efficiency in clinical settings. We applied this scheme to a dataset of 463 non-contrast CT scans obtained from 30- to 45-year-old-women in Japan. The density of breast tissue in each CT scan was assigned to one of four categories (glandular tissue within the breast <25%, 25%-50%, 50%-75%, and >75%) by a radiologist as ground truth. We used 405 CT scans for training a deep CNN and the remaining 58 CT scans for testing the performance. The experimental results demonstrated that the findings of the proposed approach and those of the radiologist were the same in 72% of the CT scans among the training samples and 76% among the testing samples. These results demonstrate the potential use of deep CNN for assessing breast tissue density in non-contrast 3D CT images.

Parental mood during pregnancy and post-natally is associated with offspring risk of Tourette syndrome or chronic tics: prospective data from the Avon Longitudinal Study of Parents and Children (ALSPAC).

PubMed

Ben-Shlomo, Y; Scharf, J M; Miller, L L; Mathews, C A

2016-04-01

Little is known about risk factors for Tourette syndrome (TS) and chronic tic disorders (CT) but maternal psychological morbidity in pregnancy may be associated with TS/CT. We examined whether pre- and post-natal parental anxiety and/or depression are associated with risk of TS/CT in the Avon Longitudinal Study of Parents and Children. We compared self-reported anxiety and depression measures collected prospectively at four time points (18 and 32 weeks prenatally, and 8 weeks and 8 months post-natally) among parents of children who subsequently met criteria for TS/CT at 13 years of age as compared to other children from the cohort. We adjusted for various socioeconomic measures and tested both for time period-specific exposure and chronic exposure using multivariable logistic regression models. 122 children had TS/CT (50 TS, 72 CT) and 5968 children had no tics. In crude analyses, both pre- and post-natal maternal anxiety and depression, but only post-natal paternal depression at 8 months, showed associations with TS/CT. In the final, adjusted multivariable models, chronic maternal anxiety (odds ratio 2.17, 95% CI 1.23, 3.84, p = 0.007) and pre-natal maternal depression (odds ratio 1.86, 95% CI 1.02, 3.39, p = 0.04) showed associations with TS/CT though the latter was consistent with chance (p = 0.07) after adjustment for past maternal depression. We find associations between maternal psychological morbidity pre- and post-natally and risk of future TS/CT in offspring. These associations may reflect either shared genetic susceptibility or a pre-natal exposure. Further work is required to see if these findings can be replicated in larger datasets.

Application of a novel metal artifact correction algorithm in flat-panel CT after coil embolization of brain aneurysms: intraindividual comparison.

PubMed

Buhk, J-H; Groth, M; Sehner, S; Fiehler, J; Schmidt, N O; Grzyska, U

2013-09-01

To evaluate a novel algorithm for correcting beam hardening artifacts caused by metal implants in computed tomography performed on a C-arm angiography system equipped with a flat panel (FP-CT). 16 datasets of cerebral FP-CT acquisitions after coil embolization of brain aneurysms in the context of acute subarachnoid hemorrhage have been reconstructed by applying a soft tissue kernel with and without a novel reconstruction filter for metal artifact correction. Image reading was performed in multiplanar reformations (MPR) in average mode on a dedicated radiological workplace in comparison to the preinterventional native multisection CT (MS-CT) scan serving as the anatomic gold standard. Two independent radiologists performed image scoring following a defined scale in direct comparison of the image data with and without artifact correction. For statistical analysis, a random intercept model was calculated. The inter-rater agreement was very high (ICC = 86.3 %). The soft tissue image quality and visualization of the CSF spaces at the level of the implants was substantially improved. The additional metal artifact correction algorithm did not induce impairment of the subjective image quality in any other brain regions. Adding metal artifact correction to FP-CT in an acute postinterventional setting helps to visualize the close vicinity of the aneurysm at a generally consistent image quality. © Georg Thieme Verlag KG Stuttgart · New York.

Micro-CTvlab: A web based virtual gallery of biological specimens using X-ray microtomography (micro-CT)

PubMed Central

Faulwetter, Sarah; Chatzinikolaou, Eva; Michalakis, Nikitas; Filiopoulou, Irene; Minadakis, Nikos; Panteri, Emmanouela; Perantinos, George; Gougousis, Alexandros; Arvanitidis, Christos

2016-01-01

Abstract Background During recent years, X-ray microtomography (micro-CT) has seen an increasing use in biological research areas, such as functional morphology, taxonomy, evolutionary biology and developmental research. Micro-CT is a technology which uses X-rays to create sub-micron resolution images of external and internal features of specimens. These images can then be rendered in a three-dimensional space and used for qualitative and quantitative 3D analyses. However, the online exploration and dissemination of micro-CT datasets are rarely made available to the public due to their large size and a lack of dedicated online platforms for the interactive manipulation of 3D data. Here, the development of a virtual micro-CT laboratory (Micro-CTvlab) is described, which can be used by everyone who is interested in digitisation methods and biological collections and aims at making the micro-CT data exploration of natural history specimens freely available over the internet. New information The Micro-CTvlab offers to the user virtual image galleries of various taxa which can be displayed and downloaded through a web application. With a few clicks, accurate, detailed and three-dimensional models of species can be studied and virtually dissected without destroying the actual specimen. The data and functions of the Micro-CTvlab can be accessed either on a normal computer or through a dedicated version for mobile devices. PMID:27956848

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.

Correlation between PET/CT parameters and KRAS expression in colorectal cancer.

PubMed

Chen, Shang-Wen; Chiang, Hua-Che; Chen, William Tzu-Liang; Hsieh, Te-Chun; Yen, Kuo-Yang; Chiang, Shu-Fen; Kao, Chia-Hung

2014-08-01

The objective of this study was to correlate the association between mutated KRAS and wild-type colorectal cancer (CRC) by using various F-FDG PET-related parameters. One hundred twenty-one CRC patients who had undergone preoperative PET/CT were included in this study. Several PET/CT-related parameters, including SUVmax and various thresholds of metabolic tumor volume, total lesion glycolysis, and PET/CT-based tumor width, were measured. Tumor- and PET/CT-related parameters were correlated with genomic expression between KRAS mutant and wild-type groups, using a Mann-Whitney U test and logistic regression analysis. Colorectal cancer tumors with a mutated KRAS exhibited higher SUVmax and an increased accumulation of FDG among several threshold methods. Multivariate analysis showed that SUVmax and using a 40% threshold level for maximal uptake of TW (TW40%) were the 2 predictors of KRAS mutations. The odds ratio was 1.23 for SUVmax (P = 0.02; 95% confidence interval, 1.01-1.52) and 1.15 for TW40% (P = 0.02; 95% confidence interval, 1.02-1.30). The accuracy of SUVmax for predicting mutated KRAS was higher in patients with colon or sigmoid colon cancers, whereas it was TW40% in those with rectal cancers. SUVmax and TW40% were associated in CRC with KRAS mutations. PET/CT parameters can supplement genomic analysis to determine KRAS expression in CRC.

[CT morphometry for calcaneal fractures and comparison of the Zwipp and Sanders classifications].

PubMed

Andermahr, J; Jesch, A B; Helling, H J; Jubel, A; Fischbach, R; Rehm, K E

2002-01-01

The aim of the study is to correlate the CT-morphological changes of fractured calcaneus and the classifications of Zwipp and Sanders with the clinical outcome. In a retrospective clinical study, the preoperative CT scans of 75 calcaneal fractures were analysed. The morphometry of the fractures was determined by measuring height, length diameter and calcaneo-cuboidal angle in comparison to the intact contralateral side. At a mean of 38 months after trauma 44 patients were clinically followed-up. The data of CT image morphometry were correlated with the severity of fracture classified by Zwipp or Sanders as well as with the functional outcome. There was a good correlation between the fracture classifications and the morphometric data. Both fracture classifying systems have a predictive impact for functional outcome. The more exacting and accurate Zwipp classification considers the most important cofactors like involvement of the calcaneo-cuboidal joint, soft tissue damage, additional fractures etc. The Sanders classification is easier to use during clinical routine. The Zwipp classification includes more relevant cofactors (fracture of the calcaneo-cuboidal-joint, soft tissue swelling, etc.) and presents a higher correlation to the choice of therapy. Both classification systems present a prognostic impact concerning the clinical outcome.

Tactile sensor is useful for estimating liver hardness and liver fibrosis compared with ultrasonography and computed tomography.

PubMed

Suzuki, Satoshi; Watanabe, Yohei; Yazawa, Takashi; Ishigame, Teruhide; Sassa, Motoki; Monma, Tomoyuki; Takawa, Tadashi; Kumamoto, Kensuke; Nakamura, Izumi; Ohoki, Shinji; Hatakeyama, Yuichi; Sakuma, Hiroshi; Ono, Toshiyuki; Omata, Sadao; Takenoshita, Seiichi

2014-01-01

We examined whether conventional ultrasonography (US) and computed tomography (CT) were useful to evaluate liver hardness and hepatic fibrosis by comparing the results with those obtained by a tactile sensor using rats with liver fibrosis. We used 44 Wistar rats in which liver fibrosis was induced by intraperitoneal administration of thioacetamide. The CT and US values of each liver were measured before laparotomy. After laparotomy, a tactile sensor was used to measure liver hardness. We prepared Azan stained sections of each excised liver specimen and calculated the degree of liver fibrosis (HFI: hepatic fibrosis index) by computed color image analysis. The stiffness values and HFI showed a positive correlation (r=0.690, p<0.001), as did the tactile values and HFI (r=0.709, p<0.001).In addition, the stiffness and tactile values correlated positively with each other (r=0.814, p<0.001). There was no correlation between the CT values and HFI, as well as no correlation between the US values and HFI. We confirmed that it was difficult to evaluate liver hardness and HFI by CT or US examination, and considered that, at present, a tactile sensor is useful method for evaluating HFI.

Comparison of Tc-99m GSA scintigraphy and CT volumetry for evaluation in portal vein embolization.

PubMed

Kono, Yumiko; Kariya, Shuji; Komemushi, Atsushi; Nakatani, Miyuki; Yoshida, Rie Yagi; Suzuki, Satoshi; Ha-Kawa, Sung Kil; Utsunomiya, Keita; Ueno, Yasuhiro; Satoi, Sohei; Kaibori, Masaki; Kon, Masanori; Tanigawa, Noboru

2014-08-01

To determine the correlation of the rate of change of each future remnant liver (FRL) before and after portal vein embolization (PVE), by CT volumetry and Tc-99m galactosyl human serum albumin scintigraphy (GSA scintigraphy). From December 2007 to July 2012, ten patients underwent PVE before hepatic resection. CT volumetry and GSA scintigraphy were performed before and after PVE. The FRL was divided at Cantlie's line for CT volumetry, and volume change rates before and after PVE were calculated. The maximum removal rate (Rmax) was calculated using a radiopharmacokinetic model in GSA scintigraphy. The FRL Rmax change rates before and after PVE were calculated. The correlation between the volume change rates and the Rmax change rates was analyzed. The FRL volume change rate was 1.28 ± 0.26 (mean ± SD); the FRL hypertrophied in all patients significantly (p = 0.005). The FRL Rmax change rate was 1.66 ± 0.75; excluding one patient, there was significant FRL Rmax increase (p = 0.022). Although both increased significantly, no correlation between the volume change rate and the Rmax change rate was observed. No correlation was observed between the FRL volume rate and the Rmax rate.

Optimization of hybrid iterative reconstruction level in pediatric body CT.

PubMed

Karmazyn, Boaz; Liang, Yun; Ai, Huisi; Eckert, George J; Cohen, Mervyn D; Wanner, Matthew R; Jennings, S Gregory

2014-02-01

The objective of our study was to attempt to optimize the level of hybrid iterative reconstruction (HIR) in pediatric body CT. One hundred consecutive chest or abdominal CT examinations were selected. For each examination, six series were obtained: one filtered back projection (FBP) and five HIR series (iDose(4)) levels 2-6. Two pediatric radiologists, blinded to noise measurements, independently chose the optimal HIR level and then rated series quality. We measured CT number (mean in Hounsfield units) and noise (SD in Hounsfield units) changes by placing regions of interest in the liver, muscles, subcutaneous fat, and aorta. A mixed-model analysis-of-variance test was used to analyze correlation of noise reduction with the optimal HIR level compared with baseline FBP noise. One hundred CT examinations were performed of 88 patients (52 females and 36 males) with a mean age of 8.5 years (range, 19 days-18 years); 12 patients had both chest and abdominal CT studies. Radiologists agreed to within one level of HIR in 92 of 100 studies. The mean quality rating was significantly higher for HIR than FBP (3.6 vs 3.3, respectively; p < 0.01). HIR caused minimal (0-0.2%) change in CT numbers. Noise reduction varied among structures and patients. Liver noise reduction positively correlated with baseline noise when the optimal HIR level was used (p < 0.01). HIR levels were significantly correlated with body weight and effective diameter of the upper abdomen (p < 0.01). HIR, such as iDose(4), improves the quality of body CT scans of pediatric patients by decreasing noise; HIR level 3 or 4 is optimal for most studies. The optimal HIR level was less effective in reducing liver noise in children with lower baseline noise.

Intra-tumour 18F-FDG uptake heterogeneity decreases the reliability on target volume definition with positron emission tomography/computed tomography imaging.

PubMed

Dong, Xinzhe; Wu, Peipei; Sun, Xiaorong; Li, Wenwu; Wan, Honglin; Yu, Jinming; Xing, Ligang

2015-06-01

This study aims to explore whether the intra-tumour (18) F-fluorodeoxyglucose (FDG) uptake heterogeneity affects the reliability of target volume definition with FDG positron emission tomography/computed tomography (PET/CT) imaging for nonsmall cell lung cancer (NSCLC) and squamous cell oesophageal cancer (SCEC). Patients with NSCLC (n = 50) or SCEC (n = 50) who received (18)F-FDG PET/CT scanning before treatments were included in this retrospective study. Intra-tumour FDG uptake heterogeneity was assessed by visual scoring, the coefficient of variation (COV) of the standardised uptake value (SUV) and the image texture feature (entropy). Tumour volumes (gross tumour volume (GTV)) were delineated on the CT images (GTV(CT)), the fused PET/CT images (GTV(PET-CT)) and the PET images, using a threshold at 40% SUV(max) (GTV(PET40%)) or the SUV cut-off value of 2.5 (GTV(PET2.5)). The correlation between the FDG uptake heterogeneity parameters and the differences in tumour volumes among GTV(CT), GTV(PET-CT), GTV(PET40%) and GTV(PET2.5) was analysed. For both NSCLC and SCEC, obvious correlations were found between uptake heterogeneity, SUV or tumour volumes. Three types of heterogeneity parameters were consistent and closely related to each other. Substantial differences between the four methods of GTV definition were found. The differences between the GTV correlated significantly with PET heterogeneity defined with the visual score, the COV or the textural feature-entropy for NSCLC and SCEC. In tumours with a high FDG uptake heterogeneity, a larger GTV delineation difference was found. Advance image segmentation algorithms dealing with tracer uptake heterogeneity should be incorporated into the treatment planning system. © 2015 The Royal Australian and New Zealand College of Radiologists.

Validation of CBCT for the computation of textural biomarkers

NASA Astrophysics Data System (ADS)

Paniagua, Beatriz; Ruellas, Antonio C.; Benavides, Erika; Marron, Steve; Wolford, Larry; Cevidanes, Lucia

2015-03-01

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr- CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr- CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

68Ga-PSMA-11 Dynamic PET/CT Imaging in Primary Prostate Cancer.

PubMed

Sachpekidis, Christos; Kopka, Klaus; Eder, Matthias; Hadaschik, Boris A; Freitag, Martin T; Pan, Leyun; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2016-11-01

The aim of our study is to assess the pharmacokinetics and biodistribution of Ga-PSMA-11 in patients suffering from primary prostate cancer (PC) by means of dynamic and whole-body PET/CT. Twenty-four patients with primary, previously untreated PC were enrolled in the study. All patients underwent dynamic PET/CT (dPET/CT) scanning of the pelvis and whole-body PET/CT studies with Ga-PSMA-11. The evaluation of dPET/CT studies was based on qualitative evaluation, SUV calculation, and quantitative analysis based on two-tissue compartment modeling and a noncompartmental approach leading to the extraction of fractal dimension (FD). A total of 23/24 patients (95.8%) were Ga-PSMA-11 positive. In 9/24 patients (37.5%), metastatic lesions were detected. PC-associated lesions demonstrated the following mean values: SUVaverage = 14.3, SUVmax = 23.4, K1 = 0.24 (1/min), k3 = 0.34 (1/min), influx = 0.15 (1/min), and FD = 1.27. The parameters SUVaverage, SUVmax, k3, influx, and FD derived from PC-associated lesions were significantly higher than respective values derived from reference prostate tissue. Time-activity curves derived from PC-associated lesions revealed an increasing Ga-PSMA-11 accumulation during dynamic PET acquisition. Correlation analysis revealed a moderate but significant correlation between PSA levels and SUVaverage (r = 0.60) and SUVmax (r = 0.57), and a weak but significant correlation between Gleason score and SUVaverage (r = 0.33) and SUVmax (r = 0.28). Ga-PSMA-11 PET/CT confirmed its capacity in detecting primary PC with a detection rate of 95.8%. Dynamic PET/CT studies of the pelvis revealed an increase in tracer uptake in PC-associated lesions during the 60 minutes of dynamic PET acquisition, a finding with potential applications in anti-PSMA approaches.

Plasma Cardiotrophin-1 as a Marker of Hypertension and Diabetes-Induced Target Organ Damage and Cardiovascular Risk

PubMed Central

Gamella-Pozuelo, Luis; Fuentes-Calvo, Isabel; Gómez-Marcos, Manuel A.; Recio-Rodriguez, José I.; Agudo-Conde, Cristina; Fernández-Martín, José L.; Cannata-Andía, Jorge B.; López-Novoa, José M.; García-Ortiz, Luis; Martínez-Salgado, Carlos

2015-01-01

Abstract The search for biomarkers of hypertension and diabetes-induced damage to multiple target organs is a priority. We analyzed the correlation between plasma cardiotrophin-1 (CT-1), a chemokine that participates in cardiovascular remodeling and organ fibrosis, and a wide range of parameters currently used to diagnose morphological and functional progressive injury in left ventricle, arteries, and kidneys of diabetic and hypertensive patients, in order to validate plasma levels of CT-1 as clinical biomarker. This is an observational study with 93 type 2-diabetic patients, 209 hypertensive patients, and 82 healthy controls in which we assessed the following parameters: plasma CT-1, basal glycaemia, systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), left ventricular hypertrophy (LVH by electrocardiographic indexes), peripheral vascular disease (by pulse wave velocity—PWV, carotid intima-media thickness—C-IMT, and ankle-brachial index—ABI), and renal impairment (by microalbuminuria, albumin/creatinine urinary ratio, plasma creatinine concentrations, and glomerular filtration rate). Hypertensive or diabetic patients have higher plasma CT-1 than control patients. CT-1 positively correlates with basal glycaemia, SBP, DBP, PP, LVH, arterial damage (increased IMT, decreased ABI), and early renal damage (microalbuminuria, elevated albumin/creatinine ratio). CT-1 also correlates with increased 10-year cardiovascular risk. Multiple linear regression analysis confirmed that CT-1 was associated with arterial injury assessed by PWV, IMT, ABI, and cardiac damage evaluated by Cornell voltage duration product. Increases in plasma CT-1 are strongly related to the intensity of several parameters associated to target organ damage supporting further investigation of its diagnostic capacity as single biomarker of cardiovascular injury and risk and, possibly, of subclinical renal damage. PMID:26222851

Radiotracer Imaging Allows for Noninvasive Detection and Quantification of Abnormalities in Angiosome Foot Perfusion in Diabetic Patients With Critical Limb Ischemia and Nonhealing Wounds

PubMed Central

Alvelo, Jessica L.; Papademetris, Xenophon; Mena-Hurtado, Carlos; Jeon, Sangchoon; Sumpio, Bauer E.; Sinusas, Albert J.

2018-01-01

Background: Single photon emission computed tomography (SPECT)/computed tomography (CT) imaging allows for assessment of skeletal muscle microvascular perfusion but has not been quantitatively assessed in angiosomes, or 3-dimensional vascular territories, of the foot. This study assessed and compared resting angiosome foot perfusion between healthy subjects and diabetic patients with critical limb ischemia (CLI). Additionally, the relationship between SPECT/CT imaging and the ankle–brachial index—a standard tool for evaluating peripheral artery disease—was assessed. Methods and Results: Healthy subjects (n=9) and diabetic patients with CLI and nonhealing ulcers (n=42) underwent SPECT/CT perfusion imaging of the feet. CT images were segmented into angiosomes for quantification of relative radiotracer uptake, expressed as standardized uptake values. Standardized uptake values were assessed in ulcerated angiosomes of patients with CLI and compared with whole-foot standardized uptake values in healthy subjects. Serial SPECT/CT imaging was performed to assess uptake kinetics of technetium-99m-tetrofosmin. The relationship between angiosome perfusion and ankle–brachial index was assessed via correlational analysis. Resting perfusion was significantly lower in CLI versus healthy subjects (P=0.0007). Intraclass correlation coefficients of 0.95 (healthy) and 0.93 (CLI) demonstrated excellent agreement between serial perfusion measurements. Correlational analysis, including healthy and CLI subjects, demonstrated a significant relationship between ankle–brachial index and SPECT/CT (P=0.01); however, this relationship was not significant for diabetic CLI patients only (P=0.2). Conclusions: SPECT/CT imaging assesses regional foot perfusion and detects abnormalities in microvascular perfusion that may be undetectable by conventional ankle–brachial index in patients with diabetes mellitus. SPECT/CT may provide a novel approach for evaluating responses to targeted therapies. PMID:29748311

Comparison of peripapillary choroidal thickness measurements via spectral domain optical coherence tomography with and without enhanced depth imaging.

PubMed

Ayyildiz, Onder; Kucukevcilioglu, Murat; Ozge, Gokhan; Koylu, Mehmet Talay; Ozgonul, Cem; Gokce, Gokcen; Mumcuoglu, Tarkan; Durukan, Ali Hakan; Mutlu, Fatih Mehmet

2016-05-01

To compare peripapillary choroidal thickness (PP-CT) measurements using a spectral domain optical coherence tomography (SD-OCT) device with and without enhanced depth imaging (EDI). Sixty healthy subjects aged from 18 to 40 years were included in this study. PP-CTs were measured in the right eyes by manual segmentation via SD-OCT both with and without EDI. The intraclass correlation coefficient (ICC) for each technique and comparison of PP-CT measurements between two techniques were evaluated. The correlation between retinal nerve fiber layer (RNFL) thickness and PP-CT was also explored on images of SD-OCT without EDI. The PP-CT measurements of 55 subjects were evaluated. The ICC was 0.999 (95% CI: 0.998-1.0, p < 0.001) for SD-OCT with EDI and 0.996 (95% CI: 0.995-0.997, p < 0.001) for SD-OCT without EDI. The mean PP-CT measurements in all regions and the overall mean PP-CT measurements between the two techniques were not different (p > 0.05). Additionally, there was no correlation between RNFL thickness and PP-CT (r = -0.109; p = 0.335). The PP-CT measurements via SD-OCT without EDI were consistent with the measurements via SD-OCT with EDI. Ophthalmologists who do not have access to EDI technology can use images of SD-OCT without EDI to measure the peripapillary choroid for research purposes. However, thicker peripapillary choroids cannot be measured using this technique and require further modifications or newer technologies, such as SD-OCT with EDI.

Validation of CBCT for the computation of textural biomarkers

PubMed Central

Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

2015-01-01

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA. PMID:26085710

Validation of CBCT for the computation of textural biomarkers.

PubMed

Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

2015-03-17

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

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

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

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

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

Incremental Role of Mammography in the Evaluation of Gynecomastia in Men Who Have Undergone Chest CT.

PubMed

Sonnenblick, Emily B; Salvatore, Mary; Szabo, Janet; Lee, Karen A; Margolies, Laurie R

2016-08-01

The purpose of this study was to determine whether additional breast imaging is clinically valuable in the evaluation of patients with gynecomastia incidentally observed on CT of the chest. In a retrospective analysis, 62 men were identified who had a mammographic diagnosis of gynecomastia and had also undergone CT within 8 months (median, 2 months). We compared the imaging findings of both modalities and correlated them with the clinical outcome. Gynecomastia was statistically significantly larger on mammograms than on CT images; however, there was a high level of concordance in morphologic features and distribution of gynecomastia between mammography and CT. In only one case was gynecomastia evident on mammographic but not CT images, owing to cachexia. Two of the 62 men had ductal carcinoma, which was obscured by gynecomastia. Both of these patients had symptoms suggesting malignancy. The appearance of gynecomastia on CT scans and mammograms was highly correlated. Mammography performed within 8 months of CT is unlikely to reveal cancer unless there is a suspicious clinical finding or a breast mass eccentric to the nipple. Men with clinical symptoms of gynecomastia do not need additional imaging with mammography to confirm the diagnosis if they have undergone recent cross-sectional imaging.

Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data.

PubMed

Ooi, Chia Huey; Chetty, Madhu; Teng, Shyh Wei

2006-06-23

Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gene expression-based tissue classification while improving accuracy at the same time. Surprisingly, this does not appear to be the case for all multiclass microarray datasets. The reason is that many feature selection techniques applied on microarray datasets are either rank-based and hence do not take into account correlations between genes, or are wrapper-based, which require high computational cost, and often yield difficult-to-reproduce results. In studies where correlations between genes are considered, attempts to establish the merit of the proposed techniques are hampered by evaluation procedures which are less than meticulous, resulting in overly optimistic estimates of accuracy. We present two realistically evaluated correlation-based feature selection techniques which incorporate, in addition to the two existing criteria involved in forming a predictor set (relevance and redundancy), a third criterion called the degree of differential prioritization (DDP). DDP functions as a parameter to strike the balance between relevance and redundancy, providing our techniques with the novel ability to differentially prioritize the optimization of relevance against redundancy (and vice versa). This ability proves useful in producing optimal classification accuracy while using reasonably small predictor set sizes for nine well-known multiclass microarray datasets. For multiclass microarray datasets, especially the GCM and NCI60 datasets, DDP enables our filter-based techniques to produce accuracies better than those reported in previous studies which employed similarly realistic evaluation procedures.

Computed tomography and clinical outcome in patients with severe traumatic brain injury.

PubMed

Stenberg, Maud; Koskinen, Lars-Owe D; Jonasson, Per; Levi, Richard; Stålnacke, Britt-Marie

2017-01-01

To study: (i) acute computed tomography (CT) characteristics and clinical outcome; (ii) clinical course and (iii) Corticosteroid Randomisation after Significant Head Injury acute calculator protocol (CRASH) model and clinical outcome in patients with severe traumatic brain injury (sTBI). Initial CT (CT i ) and CT 24 hours post-trauma (CT 24 ) were evaluated according to Marshall and Rotterdam classifications. Rancho Los Amigos Cognitive Scale-Revised (RLAS-R) and Glasgow Outcome Scale Extended (GOSE) were assessed at three months and one year post-trauma. The prognostic value of the CRASH model was evaluated. Thirty-seven patients were included. Marshall CT i and CT 24 were significantly correlated with RLAS-R at three months. Rotterdam CT 24 was significantly correlated with GOSE at three months. RLAS-R and the GOSE improved significantly from three months to one year. CRASH predicted unfavourable outcome at six months for 81% of patients with bad outcome and for 85% of patients with favourable outcome according to GOSE at one year. Neither CT nor CRASH yielded clinically useful predictions of outcome at one year post-injury. The study showed encouragingly many instances of significant recovery in this population of sTBI. The combination of lack of reliable prognostic indicators and favourable outcomes supports the case for intensive acute management and rehabilitation as the default protocol in the cases of sTBI.

Calibration Transfer in LIBS and Raman Spectroscopy for Planetary Applications

NASA Astrophysics Data System (ADS)

Dyar, M. D.; Thomas, B. F.; Parente, M.; Gemp, I.; Mullen, T. H.

2017-12-01

Planetary scientists rely on spectral libraries and instrument reproducibility to interpret results from missions. Major investments have been made into assembling libraries, but they often naively assume that spectra of single crystals versus powders and from varying instruments will be the same. Calibration transfer (CT) seeks to algorithmically resolve discrepancies among datasets from different instruments or conditions. It offers the ability to align suites of spectra with a small number of common samples, allowing better models to be built with combined data sets. LIBS and Raman data present different challenges for CT. Quantitative geochemical analyses by LIBS spectroscopy are limited by lack of consistency among repeated laser shots and across instruments. Many different factors affect the presence/absence of emission lines and their intensities, such as laser power/plasma temperature, angle of incidence, detector sensitivity/resolution. To overcome these, models in which disparate datasets are projected into a joint low-dimensional subspace where all data can be aligned before quantitative analysis, such as Correlation Analysis for Domain Adaptation (CADA), have proven very effective. They require some overlap between the populations of spectra to be aligned. For example, prediction of SiO2 on 80 samples from two different LIBS labs show errors of ±16-29 wt.% when the training and test sets have no overlap, and ±4.94 wt% SiO2 when CADA is used. Uncorrected Earth-Mars spectral differences are likely to cause errors with the same order of magnitude. As with other types of reflectance spectroscopy, Raman data are plagued by differences among single crystal/powder samples and laser wavelength that affect peak intensities, and by spectral offsets from instruments with varying resolution and wavenumber alignment schemes. These problems persist even within the archetypal RRUFF database. Pre-processing transformation functions such as optimized baseline removal, normalization, squashing, and smoothing improve mineral matching accuracy. Alignment methods can record shifts between corresponding peaks from the same mineral from pairs of instruments. By considering many pairs of minerals, corrections at each energy increment can be determined, creating a transfer function to align the data.

WE-G-207-06: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Physical Phantom and Clinical Patient Images

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

Dhou, S; Cai, W; Hurwitz, M

2015-06-15

Purpose: Respiratory-correlated cone-beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra- and inter-fractional changes. We develop a method to generate patient-specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery. Methods: Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCAmore » coefficients iteratively through comparison of the cone-beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions. Results: 4DCBCT-based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time. Conclusion: This study showed the feasibility of deriving 4DCBCT-based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT-based motion models were found to account for the 3D non-rigid motion of the patient anatomy during treatment and have the potential to localize tumor and other patient anatomical structures at treatment time even when inter-fractional changes occur. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc., Palo Alto, CA. The project was also supported, in part, by Award Number R21CA156068 from the National Cancer Institute.« less

SU-E-J-149: Establishing the Relationship Between Pre-Treatment Lung Ventilation, Dose, and Toxicity Outcome

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

Mistry, N; D'Souza, W; Sornsen de Koste, J

2014-06-01

Purpose: Recently, there has been an interest in incorporating functional information in treatment planning especially in thoracic tumors. The rationale is that healthy lung regions need to be spared from radiation if possible to help achieve better control on toxicity. However, it is still unclear whether high functioning regions need to be spared or have more capacity to deal with the excessive radiation as compared to the compromised regions of the lung. Our goal with this work is to establish the tools by which we can establish a relationship between pre-treatment lung function, dose, and radiographic outcomes of lung toxicity.more » Methods: Treatment planning was performed using a single phase of a 4DCT scan, and follow-up anatomical CT scans were performed every 3 months for most patients. In this study, we developed the pipeline of tools needed to analyze such a large dataset, while trying to establish a relationship between function, dose, and outcome. Pre-treatment lung function was evaluated using a recently published technique that evaluates Fractional Regional Ventilation (FRV). All images including the FRV map and the individual follow-up anatomical CT images were all spatially matched to the planning CT using a diffusion based Demons image registration algorithm. Change in HU value was used as a metric to capture the effects of lung toxicity. To validate the findings, a radiologist evaluated the follow-up anatomical CT images and scored lung toxicity. Results: Initial experience in 1 patient shows a relationship between the pre-treatment lung function, dose and toxicity outcome. The results are also correlated to the findings by the radiologist who was blinded to the analysis or dose. Conclusion: The pipeline we have established to study this enables future studies in large retrospective studies. However, the tools are dependent on the fidelity of 4DCT reconstruction for accurate evaluation of regional ventilation. Patent Pending for the technique presented in this work to evaluate FRV incorporating mass correction.« less

Volumetric dynamic oxygen-enhanced MRI (OE-MRI): comparison with CT Brody score and lung function in cystic fibrosis patients.

PubMed

Martini, K; Gygax, C M; Benden, C; Morgan, A R; Parker, G J M; Frauenfelder, T

2018-04-13

To demonstrate, in patients with cystic fibrosis (CF), the correlation between three-dimensional dynamic oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements and computed tomography Brody score (CF-CT) and lung function testing (LFT). Twenty-one patients (median age, 25 years; female, n = 8) with a range of CF lung disease and five healthy volunteers (median age, 31 years; female, n = 2) underwent OE-MRI performed on a 1.5-T MRI scanner. Coronal volumes were acquired while patients alternately breathed room air and 100% oxygen. Pre-oxygen T 1 was measured. Dynamic series of T 1 -weighted volumes were then obtained while breathing oxygen. T 1 -parameter maps were generated and the following OE-MRI parameters were measured: oxygen uptake (ΔPO 2max ), wash-in time and wash-out time. High-resolution CT and LFT were performed. The relationship between CF-CT, LFT and OE-MRI parameters were evaluated using Pearson correlation for the whole lung and regionally. Mean CF-CT was 24.1±17.1. Mean ΔPO 2max and mean wash-in as well as skewness of wash-out showed significant correlation with CF-CT (ΔPO 2max : r = -0.741, p < 0.001; mean wash-in: r = 0.501, p = 0.017; skewness of wash-out: r = 0.597, p = 0.001). There was significant correlation for the whole lung and regionally between LFT parameters and OE-MR (ΔPO 2max : r = 0.718, p < 0.001; wash-in: r = -0.576, p = 0.003; wash-out skewness: r = -0.552, p = 0.004). Functional lung imaging using OE-MRI has the capability to assess the severity of CF lung disease and shows a significant correlation with LFT and CF-CT. • Oxygen-enhanced MRI might play a future role in evaluation and follow-up of cystic fibrosis. • Heterogeneity of parameter maps reflects localised functional impairment in cystic fibrosis. • Avoidance of cumulative radiation burden in CF is feasible using OE-MRI.

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

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

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were usedmore » to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.« less

Quantitative in vivo CT arthrography of the human osteoarthritic knee to estimate cartilage sulphated glycosaminoglycan content: correlation with ex-vivo reference standards.

PubMed

van Tiel, J; Siebelt, M; Reijman, M; Bos, P K; Waarsing, J H; Zuurmond, A-M; Nasserinejad, K; van Osch, G J V M; Verhaar, J A N; Krestin, G P; Weinans, H; Oei, E H G

2016-06-01

Recently, computed tomography arthrography (CTa) was introduced as quantitative imaging biomarker to estimate cartilage sulphated glycosaminoglycan (sGAG) content in human cadaveric knees. Our aim was to assess the correlation between in vivo CTa in human osteoarthritis (OA) knees and ex vivo reference standards for sGAG and collagen content. In this prospective observational study 11 knee OA patients underwent CTa before total knee replacement (TKR). Cartilage X-ray attenuation was determined in six cartilage regions. Femoral and tibial cartilage specimens harvested during TKR were re-scanned using equilibrium partitioning of an ionic contrast agent with micro-CT (EPIC-μCT), which served as reference standard for sGAG. Next, cartilage sGAG and collagen content were determined using dimethylmethylene blue (DMMB) and hydroxyproline assays. The correlation between CTa X-ray attenuation, EPIC-μCT X-ray attenuation, sGAG content and collagen content was assessed. CTa X-ray attenuation correlated well with EPIC-μCT (r = 0.76, 95% credibility interval (95%CI) 0.64 to 0.85). CTa correlated moderately with the DMMB assay (sGAG content) (r = -0.66, 95%CI -0.87 to -0.49) and to lesser extent with the hydroxyproline assay (collagen content) (r = -0.56, 95%CI -0.70 to -0.36). Outcomes of in vivo CTa in human OA knees correlate well with sGAG content. Outcomes of CTa also slightly correlate with cartilage collagen content. Since outcomes of CTa are mainly sGAG dependent and despite the fact that further validation using hyaline cartilage of other joints with different biochemical composition should be conducted, CTa may be suitable as quantitative imaging biomarker to estimate cartilage sGAG content in future clinical OA research. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Correlation of 18F-FDG uptake on PET/CT with Ki67 immunohistochemistry in pre-treatment epithelial ovarian cancer.

PubMed

Mayoral, M; Paredes, P; Saco, A; Fusté, P; Perlaza, P; Tapias, A; Fernandez-Martinez, A; Vidal, L; Ordi, J; Pavia, J; Martinez-Roman, S; Lomeña, F

Standardised uptake value (SUV) and volumetric parameters such as metabolic tumour volume (MTV) and total lesion glycolysis (TLG) from 18 F-FDG PET/CT are useful criteria for disease prognosis in pre-operative and post-treatment epithelial ovarian cancer (EOC). Ki67 is another prognostic biomarker in EOC, associated with tumour aggressiveness. The aim of this study is to evaluate the association between 18 F-FDG PET/CT measurements and Ki67 in pre-treatment EOC to determine if PET/CT parameters could non-invasively predict tumour aggressiveness. A pre-treatment PET/CT was performed on 18 patients with suspected or newly diagnosed EOC. Maximum SUV (SUVmax), mean SUV (SUVmean), whole-body MTV (wbMTV), and whole-body TLG (wbTLG) with a threshold of 30% and 40% of the SUVmax were obtained. Furthermore, Ki67 index (mean and hotspot) was estimated in tumour tissue specimens. Immunohistochemical findings were correlated with PET parameters. The mean age was 57.0 years old (standard deviation 13.6 years). A moderate correlation was observed between mean Ki67 index and SUVmax (r=0.392), SUVmean 30% (r=0.437), and SUVmean 40% (r=0.443), and also between hotspot Ki67 index and SUVmax (r=0.360), SUVmean 30% (r=0.362) and SUVmean 40% (r=0.319). There was a weaker correlation, which was inversely negative, between mean and hotspot Ki67 and volumetric PET parameters. However, no statistical significant differences were found for any correlations. SUVmax and SUVmean were moderately correlated with Ki67 index, whereas volumetric PET parameters overall, showed a weaker correlation. Thus, SUVmax and SUVmean could be used to assess tumour aggressiveness in pre-treatment EOC. Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Evaluation of multifunctional imaging parameters in gastro-oesophageal cancer using F-18-FDG-PET/CT with integrated perfusion CT.

PubMed

Sah, Bert-Ram; Leissing, Christian A; Delso, Gaspar; Ter Voert, Edwin E; Krieg, Stefan; Leibl, Sebastian; Schneider, Paul M; Reiner, Cäcilia S; Hüllner, Martin W; Veit-Haibach, Patrick

2018-05-10

Positron emission tomography (PET) / computed tomography (CT) is among the most frequently used imaging modalities for initial staging of gastro-oesophageal (GE) cancer, whereas CT-perfusion (CTP) provides different multiparametric information. This proof of concept study compares CTP- and PET-parameters in patients with GE cancer to evaluate correlations and a possible prognostic value of a combined PET/CTP imaging procedure. A total of 31 patients with F-18-FDG-PET/CT and CTP studies were prospectively analysed. Patients had adenocarcinoma (n = 22) and oesophageal squamous cell carcinoma (SCC, n = 9). Imaging was performed before start of treatment. CTP parameters [blood flow (BF), blood volume (BV), mean transit time (MTT)] and metabolic parameters [(maximum and mean standardised uptake values and standard deviation (SUVmax, SUVmean, SUVsd), metabolic tumour volume (MTV) and tumour lesion glycolysis (TLG)], as well as flow metabolic product [FMP (BF × SUVmax)] were determined and their relationship was compared. Additionally their association to clinical parameters (differentiation grading, staging, HER2-status, follow-up status) and to histopathological regression (post-neoadjuvant regression grading) was evaluated. Correlation between parameters of both modalities was significant between MTT and MTV (r = 0.375, p = 0.038); no other significant correlation was found. Patients with complete histopathological regression showed significantly lower BF and BV than patients with nearly complete or partial response. TLG and regression grading showed significant correlation with staging. All other quantitative parameters for CTP and PET data did not correlate significantly with histopathological regression grading, differentiation or staging. The combination of PET and CTP parameters (FMP) showed no significant prognostic value. Significant correlations were only found between MTT and MTV, which indicates a possible perfusional/metabolic coupling. Therefore, pre-therapeutic CTP and PET- parameters provide complementary information about the pre-therapeutic tumour status and are not interchangeable. Only CTP parameters might be able to predict complete histopathological regression. On the other hand, only PET parameters are correlated with staging.