Strain estimation in aortic roots from 4D echocardiographic images using medial modeling and deformable registration

Aggarwal, A. , Mortensen, P., Hao, J., Kaczmarczyk, Ł. , Cheung, A. T., Al Ghofaily, L., Gorman, R. C., Desai, N. D., Bavaria, J. E. and Pouch, A. M. (2023) Strain estimation in aortic roots from 4D echocardiographic images using medial modeling and deformable registration. Medical Image Analysis, 87, 102804. (doi: 10.1016/j.media.2023.102804) (PMID:37060701)

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Abstract

Even though the central role of mechanics in the cardiovascular system is widely recognized, estimating mechanical deformation and strains in-vivo remains an ongoing practical challenge. Herein, we present a semi-automated framework to estimate strains from four-dimensional (4D) echocardiographic images and apply it to the aortic roots of patients with normal trileaflet aortic valves (TAV) and congenital bicuspid aortic valves (BAV). The method is based on fully nonlinear shell-based kinematics, which divides the strains into in-plane (shear and dilatational) and out-of-plane components. The results indicate that, even for size-matched non-aneurysmal aortic roots, BAV patients experience larger regional shear strains in their aortic roots. This elevated strains might be a contributing factor to the higher risk of aneurysm development in BAV patients. The proposed framework is openly available and applicable to any tubular structures.

Item Type:Articles
Additional Information:This work was supported by the Chan Zuckerberg Initiative 2020-219012 grant, the Institute of Physics and Engineering in Medicine, and the National Heart Lung and Blood Institute (K01-HL141643, R01-HL163202).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Kaczmarczyk, Professor Lukasz and Mortensen, Mr Peter and Aggarwal, Dr Ankush
Authors: Aggarwal, A., Mortensen, P., Hao, J., Kaczmarczyk, Ł., Cheung, A. T., Al Ghofaily, L., Gorman, R. C., Desai, N. D., Bavaria, J. E., and Pouch, A. M.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
College of Science and Engineering > School of Mathematics and Statistics > Mathematics
Journal Name:Medical Image Analysis
Publisher:Elsevier
ISSN:1361-8415
ISSN (Online):1361-8423
Published Online:01 April 2023
Copyright Holders:Copyright © 2023 Elsevier B.V.
First Published:First published in Medical Image Analysis 87: 102804
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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