An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging

Abstract The increasing prevalence of finite element (FE) simulations in the study of atherosclerosis has spawned numerous inverse FE methods for the mechanical characterization of diseased tissue in vivo. Current approaches are however limited to either homogenized or simplified material representa...

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Autores principales:	Bharath Narayanan, Max L. Olender, David Marlevi, Elazer R. Edelman, Farhad R. Nezami
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6ce8759c696d4d83bbdd883d4a5833b4
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spelling	oai:doaj.org-article:6ce8759c696d4d83bbdd883d4a5833b42021-11-21T12:24:41ZAn inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging10.1038/s41598-021-01874-32045-2322https://doaj.org/article/6ce8759c696d4d83bbdd883d4a5833b42021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-01874-3https://doaj.org/toc/2045-2322Abstract The increasing prevalence of finite element (FE) simulations in the study of atherosclerosis has spawned numerous inverse FE methods for the mechanical characterization of diseased tissue in vivo. Current approaches are however limited to either homogenized or simplified material representations. This paper presents a novel method to account for tissue heterogeneity and material nonlinearity in the recovery of constitutive behavior using imaging data acquired at differing intravascular pressures by incorporating interfaces between various intra-plaque tissue types into the objective function definition. Method verification was performed in silico by recovering assigned material parameters from a pair of vessel geometries: one derived from coronary optical coherence tomography (OCT); one generated from in silico-based simulation. In repeated tests, the method consistently recovered 4 linear elastic (0.1 ± 0.1% error) and 8 nonlinear hyperelastic (3.3 ± 3.0% error) material parameters. Method robustness was also highlighted in noise sensitivity analysis, where linear elastic parameters were recovered with average errors of 1.3 ± 1.6% and 8.3 ± 10.5%, at 5% and 20% noise, respectively. Reproducibility was substantiated through the recovery of 9 material parameters in two more models, with mean errors of 3.0 ± 4.7%. The results highlight the potential of this new approach, enabling high-fidelity material parameter recovery for use in complex cardiovascular computational studies.Bharath NarayananMax L. OlenderDavid MarleviElazer R. EdelmanFarhad R. NezamiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bharath Narayanan Max L. Olender David Marlevi Elazer R. Edelman Farhad R. Nezami An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
description	Abstract The increasing prevalence of finite element (FE) simulations in the study of atherosclerosis has spawned numerous inverse FE methods for the mechanical characterization of diseased tissue in vivo. Current approaches are however limited to either homogenized or simplified material representations. This paper presents a novel method to account for tissue heterogeneity and material nonlinearity in the recovery of constitutive behavior using imaging data acquired at differing intravascular pressures by incorporating interfaces between various intra-plaque tissue types into the objective function definition. Method verification was performed in silico by recovering assigned material parameters from a pair of vessel geometries: one derived from coronary optical coherence tomography (OCT); one generated from in silico-based simulation. In repeated tests, the method consistently recovered 4 linear elastic (0.1 ± 0.1% error) and 8 nonlinear hyperelastic (3.3 ± 3.0% error) material parameters. Method robustness was also highlighted in noise sensitivity analysis, where linear elastic parameters were recovered with average errors of 1.3 ± 1.6% and 8.3 ± 10.5%, at 5% and 20% noise, respectively. Reproducibility was substantiated through the recovery of 9 material parameters in two more models, with mean errors of 3.0 ± 4.7%. The results highlight the potential of this new approach, enabling high-fidelity material parameter recovery for use in complex cardiovascular computational studies.
format	article
author	Bharath Narayanan Max L. Olender David Marlevi Elazer R. Edelman Farhad R. Nezami
author_facet	Bharath Narayanan Max L. Olender David Marlevi Elazer R. Edelman Farhad R. Nezami
author_sort	Bharath Narayanan
title	An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
title_short	An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
title_full	An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
title_fullStr	An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
title_full_unstemmed	An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
title_sort	inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6ce8759c696d4d83bbdd883d4a5833b4
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An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging

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