AI Article Synopsis

  • The paper introduces a new method for characterizing the mechanical properties of atherosclerotic tissue using finite element simulations, which considers the tissue's heterogeneous and nonlinear behavior.
  • This method improves upon existing ones by incorporating diverse tissue types into the analysis and has been validated through computer simulations that demonstrated low error rates in recovering material parameters.
  • Tests showed that even in the presence of noise, the method remained robust, suggesting it could significantly enhance the accuracy of material parameter recovery in studies of cardiovascular health.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602310PMC
http://dx.doi.org/10.1038/s41598-021-01874-3DOI Listing

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