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

被引:22
|
作者
Liu, Minliang [1 ,2 ]
Liang, Liang [1 ,2 ]
Sun, Wei [1 ,2 ]
机构
[1] Georgia Inst Technol, Wallace H Coulter Dept Biomed Engn, Tissue Mech Lab, Atlanta, GA 30332 USA
[2] Emory Univ, Technol Enterprise Pk,Room 206,387 Technol Circle, Atlanta, GA 30322 USA
关键词
Constitutive parameter estimation; Multi-resolution direct search; Principal component analysis; Finite element analysis; DAMAGE EXPERIMENTS; ELASTIC PROPERTIES; SPECKLE TRACKING; HUMAN ARTERIES; IDENTIFICATION; STRESSES; TISSUES; PARAMETERS; BEHAVIOR;
D O I
10.1016/j.jmbbm.2017.10.022
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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.
引用
收藏
页码:649 / 659
页数:11
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