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An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure

Ankush Aggarwal Orcid Logo, Michael S. Sacks

Biomechanics and Modeling in Mechanobiology, Volume: 15, Issue: 4, Pages: 909 - 932

Swansea University Author: Ankush Aggarwal Orcid Logo

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DOI (Published version): 10.1007/s10237-015-0732-7

Abstract

Determining the biomechanical behavior of heart valve leaflet tissues in a noninvasive manner remains an important clinical goal. While advances in 3D imaging modalities have made in vivo valve geometric data available, optimal methods to exploit such information in order to obtain functional inform...

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Published in: Biomechanics and Modeling in Mechanobiology
ISSN: 1617-7959
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa26112
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first_indexed 2016-02-11T02:01:20Z
last_indexed 2018-02-09T05:07:43Z
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spelling 2018-01-08T10:30:41.6922812 v2 26112 2016-02-10 An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure 33985d0c2586398180c197dc170d7d19 0000-0002-1755-8807 Ankush Aggarwal Ankush Aggarwal true false 2016-02-10 EEN Determining the biomechanical behavior of heart valve leaflet tissues in a noninvasive manner remains an important clinical goal. While advances in 3D imaging modalities have made in vivo valve geometric data available, optimal methods to exploit such information in order to obtain functional information remain to be established. Herein we present and evaluate a novel leaflet shape-based framework to estimate the biomechanical behavior of heart valves from surface deformations by exploiting tissue structure. We determined accuracy levels using an “ideal” in vitro dataset, in which the leaflet geometry, strains, mechanical behavior, and fibrous structure were known to a high level of precision. By utilizing a simplified structural model for the leaflet mechanical behavior, we were able to limit the number of parameters to be determined per leaflet to only two. This approach allowed us to dramatically reduce the computational time and easily visualize the cost function to guide the minimization process. We determined that the image resolution and the number of available imaging frames were important components in the accuracy of our framework. Furthermore, our results suggest that it is possible to detect differences in fiber structure using our framework, thus allowing an opportunity to diagnose asymptomatic valve diseases and begin treatment at their early stages. Lastly, we observed good agreement of the final resulting stress–strain response when an averaged fiber architecture was used. This suggests that population-averaged fiber structural data may be sufficient for the application of the present framework to in vivo studies, although clearly much work remains to extend the present approach to in vivo problems. Journal Article Biomechanics and Modeling in Mechanobiology 15 4 909 932 1617-7959 Heart valves, Inverse model, Semilunar leaflets,Tissue microstructure 31 8 2016 2016-08-31 10.1007/s10237-015-0732-7 http://link.springer.com/article/10.1007/s10237-015-0732-7 COLLEGE NANME Engineering COLLEGE CODE EEN Swansea University 2018-01-08T10:30:41.6922812 2016-02-10T12:41:53.4740449 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Ankush Aggarwal 0000-0002-1755-8807 1 Michael S. Sacks 2
title An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
spellingShingle An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
Ankush Aggarwal
title_short An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
title_full An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
title_fullStr An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
title_full_unstemmed An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
title_sort An inverse modeling approach for semilunar heart valve leaflet mechanics: exploitation of tissue structure
author_id_str_mv 33985d0c2586398180c197dc170d7d19
author_id_fullname_str_mv 33985d0c2586398180c197dc170d7d19_***_Ankush Aggarwal
author Ankush Aggarwal
author2 Ankush Aggarwal
Michael S. Sacks
format Journal article
container_title Biomechanics and Modeling in Mechanobiology
container_volume 15
container_issue 4
container_start_page 909
publishDate 2016
institution Swansea University
issn 1617-7959
doi_str_mv 10.1007/s10237-015-0732-7
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
url http://link.springer.com/article/10.1007/s10237-015-0732-7
document_store_str 0
active_str 0
description Determining the biomechanical behavior of heart valve leaflet tissues in a noninvasive manner remains an important clinical goal. While advances in 3D imaging modalities have made in vivo valve geometric data available, optimal methods to exploit such information in order to obtain functional information remain to be established. Herein we present and evaluate a novel leaflet shape-based framework to estimate the biomechanical behavior of heart valves from surface deformations by exploiting tissue structure. We determined accuracy levels using an “ideal” in vitro dataset, in which the leaflet geometry, strains, mechanical behavior, and fibrous structure were known to a high level of precision. By utilizing a simplified structural model for the leaflet mechanical behavior, we were able to limit the number of parameters to be determined per leaflet to only two. This approach allowed us to dramatically reduce the computational time and easily visualize the cost function to guide the minimization process. We determined that the image resolution and the number of available imaging frames were important components in the accuracy of our framework. Furthermore, our results suggest that it is possible to detect differences in fiber structure using our framework, thus allowing an opportunity to diagnose asymptomatic valve diseases and begin treatment at their early stages. Lastly, we observed good agreement of the final resulting stress–strain response when an averaged fiber architecture was used. This suggests that population-averaged fiber structural data may be sufficient for the application of the present framework to in vivo studies, although clearly much work remains to extend the present approach to in vivo problems.
published_date 2016-08-31T03:31:13Z
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score 11.013148

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