Abstract
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.
Highlights
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
Such generalizability is precluded by the great variance in atherosclerotic mechanical properties between and within patients[19,21], which directly impact the stresses predicted by subsequent FE s imulations[22]
The inverse FE method accurately recovered linear elastic and Yeoh material parameters over 8 runs, with the optimal parameter vector ( Y∗ ) determined by the optimization routine closely matching the vector of assigned parameters ( Yassigned ) (Fig. 4)
Summary
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. Fluid–structure interaction (FSI) simulations have been used to ascertain the impact of plaque heterogeneity on atherosclerotic g rowth[9] In all cases, such high-fidelity atherosclerotic vascular modeling is predicated on the availability of detailed in vivo morphology of tissue components and their physiologically adherent constitutive material properties. Two-dimensional (2D) inverse studies of diseased arteries recovered single-parameter constitutive behavior of atherosclerotic tissue, matching displacement fields presumed available through elastographic imaging[23,24,25,26] These pioneering studies were limited by their inability to capture the complex multidimensional linked stress–strain relationships in the cardiovascular system due to the use of single parameter constitutive m odels[27]. The 2D nature of these works necessarily could not incorporate out-of-plane stresses, neglecting effects of physiologic undulations of the vessel wall and the 3D motion of the heart itself
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