Literature DB >> 29101897

Estimation of in vivo mechanical properties of the aortic wall: A multi-resolution direct search approach.

Minliang Liu1, Liang Liang1, Wei Sun2.   

Abstract

The patient-specific biomechanical analysis of the aorta requires in vivo mechanical properties of individual patients. Existing approaches for estimating in vivo material properties often demand high computational cost and mesh correspondence of the aortic wall between different cardiac phases. In this paper, we propose a novel multi-resolution direct search (MRDS) approach for estimation of the nonlinear, anisotropic constitutive parameters of the aortic wall. Based on the finite element (FE) updating scheme, the MRDS approach consists of the following three steps: (1) representing constitutive parameters with multiple resolutions using principal component analysis (PCA), (2) building links between the discretized PCA spaces at different resolutions, and (3) searching the PCA spaces in a 'coarse to fine' fashion following the links. The estimation of material parameters is achieved by minimizing a node-to-surface error function, which does not need mesh correspondence. The method was validated through a numerical experiment by using the in vivo data from a patient with ascending thoracic aortic aneurysm (ATAA), the results show that the number of FE iterations was significantly reduced compared to previous methods. The approach was also applied to the in vivo CT data from an aged healthy human patient, and using the estimated material parameters, the FE-computed geometry was well matched with the image-derived geometry. This novel MRDS approach may facilitate the personalized biomechanical analysis of aortic tissues, such as the rupture risk analysis of ATAA, which requires fast feedback to clinicians.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Constitutive parameter estimation; Finite element analysis; Multi-resolution direct search; Principal component analysis

Mesh:

Year:  2017        PMID: 29101897      PMCID: PMC5696095          DOI: 10.1016/j.jmbbm.2017.10.022

Source DB:  PubMed          Journal:  J Mech Behav Biomed Mater        ISSN: 1878-0180


  42 in total

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6.  An improved panoramic digital image correlation method for vascular strain analysis and material characterization.

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Authors:  T Christian Gasser; Ray W Ogden; Gerhard A Holzapfel
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8.  A simple, effective and clinically applicable method to compute abdominal aortic aneurysm wall stress.

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9.  Local mechanical and structural properties of healthy and diseased human ascending aorta tissue.

Authors:  Nusrat Choudhury; Olivier Bouchot; Leonie Rouleau; Dominique Tremblay; Raymond Cartier; Jagdish Butany; Rosaire Mongrain; Richard L Leask
Journal:  Cardiovasc Pathol       Date:  2008-03-05       Impact factor: 2.185

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  3 in total

1.  Estimation of in vivo constitutive parameters of the aortic wall using a machine learning approach.

Authors:  Minliang Liu; Liang Liang; Wei Sun
Journal:  Comput Methods Appl Mech Eng       Date:  2018-12-28       Impact factor: 6.756

Review 2.  Recent Advances in Biomechanical Characterization of Thoracic Aortic Aneurysms.

Authors:  Hannah L Cebull; Vitaliy L Rayz; Craig J Goergen
Journal:  Front Cardiovasc Med       Date:  2020-05-12

3.  Identification of in vivo nonlinear anisotropic mechanical properties of ascending thoracic aortic aneurysm from patient-specific CT scans.

Authors:  Minliang Liu; Liang Liang; Fatiesa Sulejmani; Xiaoying Lou; Glen Iannucci; Edward Chen; Bradley Leshnower; Wei Sun
Journal:  Sci Rep       Date:  2019-09-10       Impact factor: 4.996

  3 in total

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