ArticleJournal of thoracic disease2017
Cine-CMR partial voxel segmentation demonstrates increased aortic stiffness among patients with Marfan syndrome.
Article in Journal of thoracic disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Unreliable Estimation of Aortic Pulse Wave Velocity Provided by the Mobil-O-Graph Algorithm-Based System in Marfan Syndrome.Journal of the American Heart Association · 2019Article
- Artificial Intelligence Will Transform Cardiac Imaging-Opportunities and Challenges.Frontiers in cardiovascular medicine · 2019Review
- Sex Chromosome Complement Defines Diffuse Versus Focal Angiotensin II-Induced Aortic Pathology.Arteriosclerosis, thrombosis, and vascular biology · 2018Article
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7 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundStandard 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.
methodsRoutine 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.
resultsSixty 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
conclusionsThe 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.
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