Background: Magnetic resonance (MR) imaging is frequently used to diagnose arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D). However, the reliability of various MR imaging features for diagnosing ARVC/D is unknown. The purpose of this study was to determine which morphologic MR imaging features have the greatest interobserver reliability for diagnosing ARVC/D. Methods: Forty-five sets of films of cardiac MR images were sent to 8 radiologists and 5 cardiologists with experience in this field. There were 7 cases of definite ARVC/D as defined by the Task Force criteria. Six cases were controls. The remaining 32 cases had MR imaging because of clinical suspicion of ARVC/D. Readers evaluated the images for the presence of (a) right ventricle (RV) enlargement, (b) RV abnormal morphology, (c) left ventricle enlargement, (d) presence of high T₁ signal (fat) in the myocardium, and (e) location of high T₁ signal (fat) on a Likert scale with formatted responses. Results: Readers indicated that the Task Force ARVC/D cases had significantly more (χ² = 119.93, d.f. = 10, p < 0.0001) RV chamber size enlargement (58%) than either the suspected ARVC/D (12%) or no ARVC/D (14%) cases. When readers reported the RV chamber size as enlarged they were significantly more likely to report the case as ARVC/D present (χ²⁼ 33.98, d.f. = 1, p < 0.0001). When readers reported the morphology as abnormal they were more likely to diagnose the case as ARVC/D present (χ² = 78.4, d.f. = 1, p < 0.0001), and the Task Force ARVC/D (47%) cases received significantly more abnormal reports than either suspected ARVC/D (20%) or non-ARVC/D (15%) cases. There was no significant difference between patient groups in the reported presence of high signal intensity (fat) in the RV (χ² = 0.9, d.f. = 2, p > 0.05). Conclusions: Reviewers found that the size and shape of abnormalities in the RV are key MR imaging discriminates of ARVD. Subsequent protocol development and multicenter trials need to address these parameters. Essential steps in improving accuracy and reducing variability include a standardized acquisition protocol and standardized analysis with dynamic cine review of regional RV function and quantification of RV and left ventricle volumes.

Multidetector CT (MDCT) with 64-slice capability continues to gain momentum for cardiovascular imaging. Beyond images of coronary arteries, it also provides reliable information on left ventricular structure and function, cardiac venous anatomy, the pulmonary venous system, and right ventricular function-all aspects important in the management of heart failure patients. Potential unique applications in heart failure include cardiac dyssynchrony evaluation, assessing cardiomyopathies, and post-transplant annual follow-up. This review details the multiple applications and limitations of MDCT in the heart failure population, including comparison with other commonly used imaging modalities such as echocardiography and MRI.

Aortic aneurysms are the 13 th leading cause of death in the United States. In standard clinical practice, assessing the progression of disease in the aorta, as well as the risk of aneurysm rupture, is based on measurements of aortic diameter. We propose a method for automatically segmenting the aortic vessel border allowing the calculation of aortic diameters on CTA acquisitions which is accurate and fast, allowing clinicians more time for their evaluations. While segmentation of aortic lumen is straightforward in CTA, segmentation of the outer vessel wall (epithelial layer) in a diseased aorta is difficult; furthermore, no clinical tool currently exists to perform this task. The difficulties are due to the similarities in intensity of surrounding tissue (and thrombus due to lack of contrast agent uptake), as well as the complications from bright calcium deposits.Our overall method makes use of a centerline for the purpose of resampling the image volume into slices orthogonal to the vessel path. This centerline is computed semi-automatically via a distance transform. The difficult task of automatically segmenting the aortic border on the orthogonal slices is performed via a novel variation of the isoperimetric algorithm which incorporates circular constraints (priors). Our method is embodied in a prototype which allows the loading and registration of two datasets simultaneously, facilitating longitudinal comparisons. Both the centerline and border segmentation algorithms were evaluated on four patients, each with two volumes acquired 6 months to 1.5 years apart, for a total of eight datasets. Results showed good agreement with clinicians' findings.

No abstract

No abstract