Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images

The purpose of this study was to evaluate a semi-automatic right ventricle segmentation method on short-axis cardiac cine MR images which segment all right ventricle contours in a cardiac phase using one seed contour. Twenty-eight consecutive short-axis, four-chamber, and tricuspid valve view cardiac cine MRI examinations of healthy volunteers were used. Two independent observers performed the manual and automatic segmentations of the right ventricles. Analyses were based on the ventricular volume and ejection fraction of the right heart chamber. Reproducibility of the manual and semi-automatic segmentations was assessed using intra- and inter-observer variability. Validity of the semi-automatic segmentations was analyzed with reference to the manual segmentations. The inter- and intra-observer variability of manual segmentations were between 0.8 and 3.2%. The semi-automatic segmentations were highly correlated with the manual segmentations (R2 0.79–0.98), with median difference of 0.9–4.8% and of 3.3% for volume and ejection fraction parameters, respectively. In comparison to the manual segmentation, the semi-automatic segmentation produced contours with median dice metrics of 0.95 and 0.87 and median Hausdorff distance of 5.05 and 7.35 mm for contours at end-diastolic and end-systolic phases, respectively. The inter- and intra-observer variability of the semi-automatic segmentations were lower than observed in the manual segmentations. Both manual and semi-automatic segmentations performed better at the end-diastolic phase than at the end-systolic phase. The investigated semi-automatic segmentation method managed to produce a valid and reproducible alternative to manual right ventricle segmentation

Non-calcified coronary atherosclerotic plaque visualization on CT:effects of contrast-enhancement and lipid-content fractions

<p>Computed tomography (CT) may characterize lipid-rich and presumably rupture-prone non-calcified coronary atherosclerotic plaque based on its Hounsfield-Unit (HU), but still inconclusively. This study aimed to evaluate factors influencing the HU-value of non-calcified plaque using software simulation. Several realistic virtual plaqueburdened coronary phantoms were constructed at 5 mu m resolution. CT scanning was simulated with settings resembling a 64-row multi-detector CT (64-MDCT) and reconstructed at 64-MDCT (0.4 mm) and MicroCT (48 mu m) resolutions. Influences of lumen contrast-enhancement, stenosis-grades, and plaque compositions on plaque visualization were analyzed. Lumen contrast-enhancement and mean plaque HU-value were positively correlated (R-2 > 0.92), with approximately the same slopes for all plaque compositions. Percentage lipid-content and mean plaque HU-value were negatively correlated (R-2 > 0.98). Stenosis-grade and noise had minimal influence on the correlations. Influence of lumen contrast-enhancement on plaque HU-value was following a specific exponentially declining pattern (y = Ae(-I >> x) + c) from the lumen border until 2-pixel radius. Outside 2-pixel radius, plaque HU-values deviated maximally 5 HU from non-contrast-enhanced reference. Thus, to avoid lumen contrast-enhancement influence, plaques should be measured outside 2-pixel radius from the lumen border. Based on the patterns found, a lumen influence correction algorithm may be developed. HU-based plaque percentage lipid-content determination might serve as an alternative plaque characterization method. However, its applicability is still hindered by many inherent limitations.</p>