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.

Correction of lumen contrast-enhancement influence on non-calcified coronary atherosclerotic plaque quantification on CT.

Lumen contrast-enhancement influences non-calcified atherosclerotic plaque Hounsfield-unit (HU) values in computed tomography (CT). This study aimed to construct and validate an algorithm to correct for this influence. Three coronary vessel phantoms with 1, 2, and 4 mm circular hollow lumina; with normal and plaque-infested walls were scanned simultaneously in oil using a dual-source CT scanner. Scanning was repeated as the lumina were alternately filled with water and four contrast solutions (100-400 HU, at 100 HU intervals). Images were reconstructed at 0.4 mm x-y pixel size. Pixel-by-pixel comparisons of contrast-enhanced and non-contrast-enhanced images confirmed exponential declining patterns in lumen contrast-enhancement influence on wall HU-values from the lumen border (y = Ae(-λx) + c). The median difference of the inside and outside 2-pixel radius part of the contrast-enhanced coronary phantom wall to the reference (non-contrast-enhanced images) was 45 and 2 HU, respectively. Based on the lumen contrast-enhancement influence patterns, a generalized correction algorithm was formulated. Application of the generalized correction algorithm to the inside 2-pixel radius part of the wall reduced the median difference to the reference to 4 HU. In conclusion, lumen contrast-enhancement influence on the vessel wall can be defined by an exponential approximation, allowing correction of the CT density of the vessel wall closest to the lumen. With this correction, a more accurate determination of vessel wall composition can be made.

A meta analysis and hierarchical classification of HU-based atherosclerotic plaque characterization criteria.

BACKGROUND: Many computed tomography (CT) studies have reported that lipid-rich, presumably rupture-prone atherosclerotic plaques can be characterized according to their Hounsfield Unit (HU) value. However, the published HU-based characterization criteria vary considerably. The present study aims to systematically analyze these values and empirically derive a hierarchical classification of the HU-based criteria which can be referred in clinical situation. MATERIAL AND METHODS: A systematic search in PubMed and Embase for publications with HU-criteria to characterize lipid-rich and fibrous atherosclerotic plaques resulted in 36 publications, published between 1998 and 2011. The HU-criteria were systematically analyzed based on the characteristics of the reporting study. Significant differences between HU-criteria were checked using Student's t-test. Subsequently, a hierarchical classification of HU-criteria was developed based on the respective study characteristics. RESULTS: No correlation was found between HU-criteria and the reported lumen contrast-enhancement. Significant differences were found for HU-criteria when pooled according to the respective study characteristics: examination type, vessel type, CT-vendor, detector-rows, voltage-setting, and collimation-width. The hierarchical classification resulted in 21 and 22 CT attenuation value categories, for lipid-rich and fibrous plaque, respectively. More than 50% of the hierarchically classified HU-criteria were significantly different. CONCLUSION: In conclusion, variations in the reported CT attenuation values for lipid-rich and fibrous plaque are so large that generalized values are unreliable for clinical use. The proposed hierarchical classification can be used to determine reference CT attenuation values of lipid-rich and fibrous plaques for the local setting.

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

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 µm 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 µm) 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(-λx) + 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.

Small calcified coronary atherosclerotic plaque simulation model: minimal size and attenuation detectable by 64-MDCT and MicroCT.

Zero calcium score may not reflect the absence of calcifications as small calcifications could be missed. This study aimed to evaluate minimal size and minimal attenuation of coronary calcifications detectable by computed tomography (CT) and to determine the minimal spatial resolution required for detecting calcification onset. Using open source CT simulation software, CTSim(©), several 50%-stenotic coronary artery phantoms were designed with 5 µm resolution, realistic morphology and tissue-specific Hounsfield Unit (HU) values. The plaque had an attenuation resembling fibrous plaque and contained a single calcification. X-ray projections were simulated with settings resembling non-contrast-enhanced 64 multi detector-row CT (64-MDCT). Scanning and reconstruction were simulated with spatial resolution of a 64-MDCT (0.4mm) and of a MicroCT (48 µm). Starting from a single calcium granule, the calcification was simulated to grow in size and attenuation until it could be detected using clinically accepted calcium determination scheme on MicroCT and 64-MDCT images. The smallest coronary calcifications detectable at MicroCT and 64-MDCT, which had a realistic attenuation (-1,024 to 3,072 HU), were of 25 µm and 215 µm diameter, respectively. The area was overestimated 7.7 and 8.8 times, respectively. Calcifications with smaller size need to have an unrealistically high attenuation to be detectable by 64-MDCT. In conclusion, 64-MDCT is only able to detect coronary calcifications with minimal diameter of 215 µm. Consequently, early onset of calcification in coronary plaque will remain invisible when using CT and a zero calcium score can not exclude the presence of coronary calcification.

Quantitative image analysis for the detection of motion artefacts in coronary artery computed tomography.

Multi detector-row CT (MDCT), the current preferred method for coronary artery disease assessment, is still affected by motion artefacts. To rule out motion artefacts, qualitative image analysis is usually performed. Our study aimed to develop a quantitative image analysis for motion artefacts detection as an added value to the qualitative analysis. An anthropomorphic moving heart phantom with adjustable heart-rate was scanned on 64-MDCT and dual-source-CT. A new software technique was developed which detected motion artefacts in the coronaries and also in the myocardium, where motion artefacts are more apparent; with direct association to the qualitative analysis. The new quantitative analysis managed to detect motion artefacts in phantom scans and relate them to artefact-induced vessel stenoses. Quantifying these artefacts at corresponding locations in the myocardium, artefact-induced vessel stenosis findings could be avoided. In conclusion, the quantitative analysis together with the qualitative analysis rules out artefact-induced stenosis.

Ultrasonography to quantify hepatic fat content: validation by 1H magnetic resonance spectroscopy.

An abundance of fat stored within the liver, or steatosis, is the beginning of a broad hepatological spectrum, usually referred to as fatty liver disease (FLD). For studies on FLD, quantitative hepatic fat ultrasonography would be an appealing study modality. Objective of this study was to develop a technique for quantifying hepatic fat content by ultrasonography and validate this using proton magnetic resonance spectroscopy ((1)H MRS) as gold standard. Eighteen white volunteers (BMI range 21.0-42.9) were scanned by both ultrasonography and (1)H MRS. Altered ultrasound characteristics, present in the case of FLD, were assessed using a specially developed software program. Various attenuation and textural based indices of FLD were extracted from ultrasound images. Using linear regression analysis, the predictive power of several models (consisting of both attenuation and textural based measures) on log 10-transformed hepatic fat content by (1)H MRS were investigated. The best quantitative model was compared with a qualitative ultrasonography method, as used in clinical care. A model with four ultrasound characteristics could modestly predict the amount of liver fat (adjusted explained variance 43.2%, P = 0.021). Expanding the model to seven ultrasound characteristics increased adjusted explained variance to 60% (P = 0.015), with r = 0.789 (P < 0.001). Comparing this quantitative model with qualitative ultrasonography revealed a significant advantage of the quantitative model in predicting hepatic fat content (P < 0.001). This validation study shows that a combination of computer-assessed ultrasound measures from routine ultrasound images can be used to quantitatively assess hepatic fat content.