Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Vaud, Switzerland.
Sci Rep. 2021 Nov 18;11(1):22540. doi: 10.1038/s41598-021-01874-3.
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.
有限元（FE）模拟在动脉粥样硬化研究中的应用日益广泛，催生了许多用于体内病变组织力学特性反演的 FE 方法。然而，当前的方法仅限于均匀化或简化的材料表示。本文提出了一种新方法，通过在目标函数定义中纳入各种斑块内组织类型之间的界面，在使用不同血管内压力采集的成像数据恢复本构行为时，考虑组织异质性和材料非线性。通过从一对血管几何形状中恢复指定的材料参数，对方法进行了计算机模拟验证：一个源自冠状动脉光学相干断层扫描（OCT）；一个来自基于计算机的仿真。在重复测试中，该方法始终能够一致地恢复 4 个线性弹性（0.1±0.1%误差）和 8 个非线性超弹性（3.3±3.0%误差）材料参数。在噪声敏感性分析中，还突出了方法的稳健性，线性弹性参数在 5%和 20%噪声下的平均误差分别为 1.3±1.6%和 8.3±10.5%。通过在另外两个模型中恢复 9 个材料参数，验证了方法的可重复性，平均误差为 3.0±4.7%。研究结果突出了这种新方法的潜力，为在复杂心血管计算研究中使用高精度的材料参数恢复提供了可能。
