A data-driven surrogate model for fluid-structure interaction in carotid arteries with plaque

Keywords

Advanced Numerical Methods for Scientific Computing
Computational Medicine for the Cardiocirculatory System
Living Systems and Precision Medicine
Code:
13/2020
Title:
A data-driven surrogate model for fluid-structure interaction in carotid arteries with plaque
Date:
Thursday 20th February 2020
Author(s):
Pozzi S.; Domanin M.; Forzenigo L.; Votta E.; Zunino P.; Redaelli A.; Vergara C.
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Abstract:
In this work, we propose a surrogate model for the Fluid-Structure Interaction (FSI) problem for the study of blood dynamics in carotid arteries in presence of plaque. This model is based on the integration with subject-specific data and clinical imaging. In more detail, we propose to model the atherosclerotic plaque as part of the tissues surrounding the vessel wall through the application of an elastic support boundary condition on the external surface of the structure model. In order to characterize the plaque and other surrounding tissues, such as the close-by jugular vein, the elastic parameter of the boundary condition was spatially differentiated. The values of these parameters were estimated by minimizing the discrepancies between computed vessel wall displacements and reference values obtained from CINE Magnetic Resonance Imaging (MRI) data. As a first application of the method, we considered three subjects with a degree of stenosis greater than 70%. We found that accounting for both plaque and jugular vein in the estimation of the elastic parameters increases the accuracy. In particular, in all patients, mismatches between computed and in vivo measured wall displacements were 1-2 orders of magnitude lower than the spatial resolution of the original MRI data. These results confirmed the validity of the proposed surrogate model.