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An inverse fitting strategy to determine the constrained mixture model parameters: application in patient-specific aorta.

Authors :
Navarrete Á
Utrera A
Rivera E
Latorre M
Celentano DJ
García-Herrera CM
Source :
Frontiers in bioengineering and biotechnology [Front Bioeng Biotechnol] 2023 Nov 20; Vol. 11, pp. 1301988. Date of Electronic Publication: 2023 Nov 20 (Print Publication: 2023).
Publication Year :
2023

Abstract

The Constrained Mixture Model (CMM) is a novel approach to describe arterial wall mechanics, whose formulation is based on a referential physiological state. The CMM considers the arterial wall as a mixture of load-bearing constituents, each of them with characteristic mass fraction, material properties, and deposition stretch levels from its stress-free state to the in-vivo configuration. Although some reports of this model successfully assess its capabilities, they barely explore experimental approaches to model patient-specific scenarios. In this sense, we propose an iterative fitting procedure of numerical-experimental nature to determine material parameters and deposition stretch values. To this end, the model has been implemented in a finite element framework, and it is calibrated using reported experimental data of descending thoracic aorta. The main results obtained from the proposed procedure consist of a set of material parameters for each constituent. Moreover, a relationship between deposition stretches and residual strain measurements (opening angle and axial stretch) has been numerically proved, establishing a strong consistency between the model and experimental data.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2023 Navarrete, Utrera, Rivera, Latorre, Celentano and García-Herrera.)

Details

Language :
English
ISSN :
2296-4185
Volume :
11
Database :
MEDLINE
Journal :
Frontiers in bioengineering and biotechnology
Publication Type :
Academic Journal
Accession number :
38053847
Full Text :
https://doi.org/10.3389/fbioe.2023.1301988