Dandapani, S., Gundiah, N., Luo, X.Y. et al. (1 more author) (2017) A constrained mixture model of the left ventricle and its application to simulating myocardial infarction. In: Proceedings of the 5th International Conference on Computational & Mathematical Biomedical Engineering. 5th International Conference on Computational & Mathematical Biomedical Engineering, 10-12 Apr 2017, Pittsburgh, United States. CMBE , pp. 1273-1276. ISBN 978-0-9562914-4-8
Abstract
Myocardial infarction results in a change to the mechanical environment of the left ventricle (LV). Consequently, following an MI, both the localised infarct region and the LV will remodel. Computational models may help us to predict whether the remodelling will have a deleterious impact on LV mechanical function. We model the left venticle as a nonlinear elastic spherical membrane using a constrained mixture approach. Constituents are configured in the loaded configuration to optimise the mechanical function of the heart. First, we illustrate a conceptual model of the healthy ventricle and its adaption to altered mechanical loading. We then consider its application to simulate myocardial infarction: an immediate loss of myocytes is prescribed and we simulate the growth and remodelling of the infarct.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors. |
Keywords: | growth and remodelling; cardiac biomechanics; myocardial infarction |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/N014642/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Oct 2017 14:43 |
Last Modified: | 19 Dec 2022 13:37 |
Published Version: | http://www.compbiomed.net/2017/cmbe-proceedings.ht... |
Status: | Published |
Publisher: | CMBE |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:122756 |