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J Mech Behav Biomed Mater. 2018 Jan;77:649-659. doi: 10.1016/j.jmbbm.2017.10.022. Epub 2017 Oct 20.

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

Author information

1
Tissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.
2
Tissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States. Electronic address: wei.sun@bme.gatech.edu.

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.

KEYWORDS:

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

PMID:
29101897
PMCID:
PMC5696095
DOI:
10.1016/j.jmbbm.2017.10.022
[Indexed for MEDLINE]
Free PMC Article

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