Automated iterative neutrosophic lung segmentation for image analysis in thoracic computed tomography

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134994/1/mp2679.pd

Automatic multiscale enhancement and segmentation of pulmonary vessels in CT pulmonary angiography images for CAD applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135074/1/mp4558.pd

Best-Quality Vessel Identification Using Vessel Quality Measure in Multiple-Phase Coronary CT Angiography

The detection of stenotic plaques strongly depends on the quality of the coronary arterial tree imaged with coronary CT angiography (cCTA). However, it is time consuming for the radiologist to select the best-quality vessels from the multiple-phase cCTA for interpretation in clinical practice. We are developing an automated method for selection of the best-quality vessels from coronary arterial trees in multiple-phase cCTA to facilitate radiologist’s reading or computerized analysis. Our automated method consists of vessel segmentation, vessel registration, corresponding vessel branch matching, vessel quality measure (VQM) estimation, and automatic selection of best branches based on VQM. For every branch, the VQM was calculated as the average radial gradient. An observer preference study was conducted to visually compare the quality of the selected vessels. 167 corresponding branch pairs were evaluated by two radiologists. The agreement between the first radiologist and the automated selection was 76% with kappa of 0.49. The agreement between the second radiologist and the automated selection was also 76% with kappa of 0.45. The agreement between the two radiologists was 81% with kappa of 0.57. The observer preference study demonstrated the feasibility of the proposed automated method for the selection of the best-quality vessels from multiple cCTA phases

Pulmonary function measures predict mortality differently in IPF versus combined pulmonary fibrosis and emphysema

The composite physiologic index (CPI) was derived to represent the extent of fibrosis on high-resolution computed tomography (HRCT), adjusting for emphysema in patients with idiopathic pulmonary fibrosis (IPF). We hypothesised that longitudinal change in CPI would better predict mortality than forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) or diffusing capacity of the lung for carbon monoxide (DLCO) in all patients with IPF, and especially in those with combined pulmonary fibrosis and emphysema (CPFE). Cox proportional hazard models were performed on pulmonary function data from IPF patients at baseline (n=321), 6 months (n=211) and 12 months (n=144). Presence of CPFE was determined by HRCT. A five-point increase in CPI over 12 months predicted subsequent mortality (HR 2.1, p=0.004). At 12 months, a 10% relative decline in FVC, a 15% relative decline in DLCO or an absolute increase in CPI of five points all discriminated median survival by 2.1 to 2.2 yrs versus patients with lesser change. Half our cohort had CPFE. In patients with moderate/severe emphysema, only a 10% decline in FEV1 predicted mortality (HR 3.7, p=0.046). In IPF, a five-point increase in CPI over 12 months predicts mortality similarly to relative declines of 10% in FVC or 15% in DLCO. For CPFE patients, change in FEV1 was the best predictor of mortality.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91949/1/2011 ERJ - Pulmonary function measures predict mortality differently in IPF versus combined pulmonary fibrosis and emphysema.pd

Computerized detection of noncalcified plaques in coronary CT angiography: Evaluation of topological soft gradient prescreening method and luminal analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135084/1/mp5958.pd

Computerized analysis of coronary artery disease: Performance evaluation of segmentation and tracking of coronary arteries in CT angiograms

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134780/1/mp0294.pd

Intrathoracic Fat Measurements Using Multidetector Computed Tomography (MDCT): Feasibility and Reproducibility

Intrathoracic fat volume, more specifically, epicardial fat volume, is an emerging imaging biomarker of adverse cardiovascular events. The purpose of this work is to show the feasibility and reproducibility of intrathoracic fat volume measurement applied to contrast-enhanced multidetector computed tomography images. A retrospective cohort study of 62 subjects free of cardiovascular disease (55% females, age = 49 ± 11 years) conducted from 2008 to 2011 formed the study group. Intrathoracic fat volume was defined as all fat voxels measuring −50 to −250 Hounsfield Unit within the intrathoracic cavity from the level of the pulmonary artery bifurcation to the heart apex. The intrathoracic fat was separated into epicardial and extrapericardial fat by tracing the pericardium. The measurements were obtained by 2 readers and compared for interrater reproducibility. The fat volume measurements for the study group were 141 ± 72 cm3 for intrathoracic fat, 58 ± 27 cm3 for epicardial fat, and 84 ± 50 cm3 for extrapericardial fat. There was no statistically significant difference in intrathoracic fat volume measurements between the 2 readers, with correlation coefficients of 0.88 (P = .55) for intrathoracic fat volume and −0.12 (P = .33) for epicardial fat volume. Voxel-based measurement of intrathoracic fat, including the separation into epicardial and extrapericardial fat, is feasible and highly reproducible from multidetector computed tomography scans

Effect of CT scanning parameters on volumetric measurements of pulmonary nodules by 3D active contour segmentation: a phantom study

"The purpose of this study is to investigate the effects of CT scanning and reconstruction parameters on automated segmentation and volumetric measurements of nodules in CT images. Phantom nodules of known sizes were used so that segmentation accuracy could be quantified in comparison to ground-truth volumes. Spherical nodules having 4.8, 9.5 and 16 mm diameters and 50 and 100 mg cc[?]1 calcium contents were embedded in lung-tissue-simulating foam which was inserted in the thoracic cavity of a chest section phantom. CT scans of the phantom were acquired with a 16-slice scanner at various tube currents, pitches, fields-of-view and slice thicknesses. Scans were also taken using identical techniques either within the same day or five months apart for study of reproducibility. The phantom nodules were segmented with a three-dimensional active contour (3DAC) model that we previously developed for use on patient nodules. The percentage volume errors relative to the ground-truth volumes were estimated under the various imaging conditions. There was no statistically significant difference in volume error for repeated CT scans or scans taken with techniques where only pitch, field of view, or tube current (mA) were changed. However, the slice thickness significantly (p < 0.05) affected the volume error. Therefore, to evaluate nodule growth, consistent imaging conditions and high resolution should be used for acquisition of the serial CT scans, especially for smaller nodules. Understanding the effects of scanning and reconstruction parameters on volume measurements by 3DAC allows better interpretation of data and assessment of growth. Tracking nodule growth with computerized segmentation methods would reduce inter- and intraobserver variabilities."http://deepblue.lib.umich.edu/bitstream/2027.42/64233/1/pmb8_5_009.pd