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Updated: May 5, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Bridging hemodynamics, tissue mechanics, and pathophysiology in coronary artery disease: A new agent-based model with
Jeremy Warren1, Anna Corti2, Clark A Meyer1
1Department of Bioengineering, University of Texas at Dallas, Richardson TX 75080, USA.
Abstract:
We introduce a new multi-physics, multi-scale modeling approach to understand plaque progression during coronary artery disease. Prior works have coupled agent-based models (ABMs) with finite element analysis (FEA) or computational fluid dynamics (CFD) to study the individual contributions of tissue mechanics or hemodynamics to plaque growth. However, these approaches could not simultaneously capture the dynamic interplay between all three domains that drive plaque development. This study aims to present a novel method that merges hemodynamics via CFD, biological processes via ABM, and biomechanics via FEA into a single multi-scale, multi-physics simulation (CAFe). A description of the mechanisms and modeling approaches utilized in the CAFe model is provided, as well as preliminary exploration of the model's capabilities in idealized healthy and stenosed coronary artery models. A volumetric 3D tetrahedral mesh of the artery is shared between CFD, ABM, and FEA to simulate geometrical and biological changes with continuity and consistency. The CFD and FEA modules, implemented with FEBio, calculate the wall shear stress and structural stress and strain, respectively. These biomechanical values are passed to the ABM, implemented in MATLAB, which simulates vascular remodeling using molecular diffusion, cell migration, equations for cellular processes, and volumetric growth to update the geometry. Initial results using CAFe suggest atherosclerotic arteries seek to maintain a hemodynamic threshold through preferential growth and remodeling downstream of a stenosis. The innovative approach described herein marks a significant step forward in predictive modeling of CAD progression and paves the way for powerful coupling of the spatiotemporal-dependent remodeling paradigms exhibited by the disease.
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