Abstract
BACKGROUND: Standard cine-cardiac magnetic resonance (CMR) imaging is commonly used to evaluate cardiac structure, geometry and function. Prior studies have shown that automated segmentation via partial voxel interpolation (PVI) accurately quantifies phantom-based cardiac chamber volumes and necropsy left ventricular myocardial mass. Despite this, the applicability and usefulness of PVI in the determination of physiologic parameters of the aorta such as aortic stiffness has yet to be investigated. METHODS: Routine CMR was conducted with a 1.5T (GE) scanner with pulse sequences similar to that of standard CMR (parameters: TR 3.4 msec, TE 1.14 msec, flip angle 60°, temporal resolution ~30-40 msec). Views were obtained in standard cardiac-oriented longitudinal or axial views (2, 3 and 4 chambers). Within non-dilated regions of the descending thoracic aorta, aortic area was quantified via a novel PVI automated process (LV-METRIC), which discerns relative amounts of blood pool in each voxel. Aortic stiffness, as calculated from brachial artery pulse pressure and aortic area at maximal and minimal dimensions, was evaluated in 60 total segments (one segment per patient). All segments were in the descending aorta and were not aneurysmal. RESULTS: Sixty patients in total were studied, including 50 that had genetically-related aortic disorder [35 bicuspid aortic valve (BAV), 15 Marfan syndrome (MFS)]. Ten normal controls without aortic disease were included for comparison purposes. All patients (n=60) had evaluable CMR images for assessment of the descending aorta with use of automated segmentation. Patients with BAV and MFS were similar to controls in age, systolic blood pressure, brachial artery pulse pressure, smoking status or hypercholesterolemia (all P=NS). There were more women (P<0.001), lower body mass index (P=0.008), and greater height (P<0.001) in the MFS cohort compared to BAV and controls. Descending aortic area in either systole (maximal) or diastole (minimal) was similar among all three cohorts. However, change in aortic area (ΔArea) throughout the cardiac cycle was substantially lower in MFS than control subjects (P<0.001). In contrast, change in aortic area throughout the cardiac cycle was not significantly different between BAV vs. controls (P=0.62). Aortic stiffness was increased among MFS patients versus control subjects (P=0.014). When comparing MFS to BAV subjects, a comparable trend was observed (P=0.09). No statistical difference was evident in aortic stiffness in patients with BAV versus control subjects (P=0.29). CONCLUSIONS: The application of PVI to standard CMR imaging can assess abnormal descending aorta functional indices in normal caliber segments in MFS subjects. Future prospective studies with larger subject populations are warranted to further determine the overall utility of automated aortic segmentation as a possible early biomarker of aortic dysfunction before overt dilatation.