Key result
Bayesian-optimized finite element modeling characterizes ex-vivo atherosclerotic human carotids with ~4% mean error.
Why the study?
Carotid plaque rupture causes ischemic stroke and correlates with high plaque stresses, but critical information on multicomponent material properties of atherosclerotic carotid arteries remains lacking.
A novel Bayesian Optimization-based inverse finite element approach successfully characterized the multicomponent material properties of human atherosclerotic carotid arteries ex-vivo, showing potential for patient-specific rupture risk assessment.
Answers are grounded in this paper and cite their sources.
May support ex-vivo carotid modeling; leaves open in-vivo validation for patient-specific rupture risk assessment.
OBJECTIVE: Plaque rupture in atherosclerotic carotid arteries is a main cause of ischemic stroke and it is correlated with high plaque stresses. Hence, analyzing stress patterns is essential for plaque specific rupture risk assessment. However, the critical information of the multicomponent material properties of atherosclerotic carotid arteries is still lacking greatly. This work aims to characterize component-wise material properties of atherosclerotic human carotid arteries under (almost) physiological loading conditions. METHODS: An inverse finite element modeling (iFEM) framework was developed to characterize fibrous intima and vessel wall material properties of 13 cross sections from five carotids. The novel pipeline comprised ex-vivo inflation testing, pre-clinical high frequency ultrasound for deriving plaque deformations, pre-clinical high-magnetic field magnetic resonance imaging, finite element modeling, and a sample efficient machine learning based Bayesian Optimization. RESULTS: The nonlinear Yeoh constants for the fibrous intima and wall layers were successfully obtained. The optimization scheme of the iFEM reached the global minimum with a mean error of 3.8% in 133 iterations on average. The uniqueness of the results were confirmed with the inverted Gaussian Process (GP) model trained during the iFEM protocol. CONCLUSION: The developed iFEM approach combined with the inverted GP model successfully predicted component-wise material properties of intact atherosclerotic human carotids ex-vivo under physiological-like loading conditions. SIGNIFICANCE: We developed a novel iFEM framework for the nonlinear, component-wise material characterization of atherosclerotic arteries and utilized it to obtain human atherosclerotic carotid material properties. The developed iFEM framework has great potential to be advanced for patient-specific in-vivo application.
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Torun et al. (2021) studied Atherosclerotic human carotid arteries (n=5). Inverse finite element modeling (iFEM) framework with Bayesian Optimization was evaluated on Component-wise material properties (nonlinear Yeoh constants) and optimization mean error. An inverse finite element modeling framework using Bayesian Optimization successfully characterized the nonlinear material properties of intact atherosclerotic human carotids ex-vivo with a mean error of 3.8%.
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