Towards a Computational Framework for Modeling the Impact of Aortic Coarctations Upon Left Ventricular Load

Abstract

Computational fluid dynamics (CFD) models of blood flow in the left ventricle (LV) and aorta are important tools for analyzing the mechanistic links between myocardial deformation and flow patterns. Typically, the use of image-based kinematic CFD models prevails in applications such as predicting the acute response to interventions which alter LV afterload conditions. However, such models are limited in their ability to analyze any impacts upon LV load or key biomarkers known to be implicated in driving remodeling processes as LV function is not accounted for in a mechanistic sense. This study addresses these limitations by reporting on progress made toward a novel electro-mechano-fluidic (EMF) model that represents the entire physics of LV electromechanics (EM) based on first principles. A biophysically detailed finite element (FE) model of LV EM was coupled with a FE-based CFD solver for moving domains using an arbitrary Eulerian-Lagrangian (ALE) formulation. Two clinical cases of patients suffering from aortic coarctations (CoA) were built and parameterized based on clinical data under pre-treatment conditions. For one patient case simulations under post-treatment conditions after geometric repair of CoA by a virtual stenting procedure were compared against pre-treatment results. Numerical stability of the approach was demonstrated by analyzing mesh quality and solver performance under the significantly large deformations of the LV blood pool. Further, computational tractability and compatibility with clinical time scales were investigated by performing strong scaling benchmarks up to 1536 compute cores. The overall cost of the entire workflow for building, fitting and executing EMF simulations was comparable to those reported for image-based kinematic models, suggesting that EMF models show potential of evolving into a viable clinical research tool.

A computationally efficient physiologically comprehensive 3D–0D closed-loop model of the heart and circulation

“…The computational cost imposed by higher resolution EM models requires efficient numerical solvers. Strong scaling characteristics of our numerical framework were reported in detail previously [ 41 , 82 ]. The compute times reported in Section 3.4 indicate that setup and assembly time were the dominating factors during the initial passive inflation (loading) phase while for the subsequent coupled 3D–0D EM simulations of a heart beat solver time was the predominant part of total CPU time.…”

Automating Model Generation for Image-Based Cardiac Flow Simulation

“…The first approach tracks the deformation of the heart from timeresolved imaging and imposes this motion to the fluidic domains inside the heart, which leads to a deforming-domain CFD problem [8][9][10][11][12][13]. The second approach couples electrophysiology, structural mechanics, and fluid dynamics in the heart so that the heart motion is solved for rather than measured [14][15][16]. This second approach is formidable and is generally unnecessary if the purpose of the model is to derive intracardiac hemodynamics.…”

Impact of Aortic Stenosis on Myofiber Stress: Translational Application of Left Ventricle-Aortic Coupling Simulation

“…Advances in computational modeling techniques now enable AS to be studied from a cardiovascular systems perspective. LV-aortic coupling is a concept that describes the inter-dependency of the LV and the aorta/systemic blood vessels that impact cardiovascular function ( Karabelas et al, 2018 ; Shavik et al, 2018 ; Ikonomidis et al, 2019 ). Multi-domain models of the human heart and circulatory system now offer a complete mechanistic model of the ventricles, aortic valve, and vasculature, making it ideally suited to investigate AS ( Baillargeon et al, 2014 ; Genet et al, 2014 , 2016 ; Dabiri et al, 2018 ; Sack et al, 2018b ; Ghosh et al, 2020 ).…”