Multicomponent material property characterization of atherosclerotic human carotid arteries through a Bayesian Optimization based inverse finite element approach
| Autor: | Hendrik H.G. Hansen, Ali C. Akyildiz, Su Guvenir Torun, Chris L. de Korte, Antonius F.W. van der Steen, Hakki Mert Torun, Frank J. H. Gijsen |
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| Přispěvatelé: | Cardiology |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Property (programming) Yeoh Vascular damage Radboud Institute for Health Sciences [Radboudumc 16] Finite Element Analysis Biomedical Engineering Inverse Bayesian Biomaterials symbols.namesake All institutes and research themes of the Radboud University Medical Center Finite element Humans Gaussian process Carotid Ultrasonography Bayesian optimization Plaque rupture Bayes Theorem Atherosclerosis Inflation Finite element method Plaque Atherosclerotic Nonlinear system Carotid Arteries Material constant Mechanics of Materials symbols Material properties Biomedical engineering |
| Zdroj: | Journal of the Mechanical Behavior of Biomedical Materials, 126 Journal of the Mechanical Behavior of Biomedical Materials, 126:104996. Elsevier |
| ISSN: | 1878-0180 1751-6161 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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