Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers
Journal
Computer Methods in Applied Mechanics and Engineering
ISSN
0045-7825
Date Issued
2020
Author(s)
F. Levrero-Florencio
F. Margara
E. Zacur
A. Bueno-Orovio
Z.J. Wang
A. Santiago
J. Aguado-Sierra
G. Houzeaux
V. Grau
D. Kay
M. Vázquez
R. Ruiz-Baier
B. Rodriguez
DOI
https://doi.org/10.1016/j.cma.2019.112762
Abstract
The human heart beats as a result of multiscale nonlinear dynamics coupling subcellular to whole organ processes, achieving
electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great
degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation
software.
In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular
electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The
biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key
novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation–contraction and
active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in
a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200%−1000% variations
in key parameters result in changes in clinically-relevant mechanical biomarkers ranging from diseased to healthy values in
clinical studies. Furthermore mechanical biomarkers are primarily affected by only one or two parameters. Specifically, ejection
fraction is dominated by the scaling parameter of the active tension model and its scaling parameter in the normal direction
(kort 2); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered (Pej) and the compliance
of the Windkessel fluid model (C); and the longitudinal fractional shortening is dominated by the fibre angle (φ) and kort 2.
The wall thickening does not seem to be clearly dominated by any of the considered input parameters.
electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great
degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation
software.
In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular
electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The
biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key
novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation–contraction and
active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in
a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200%−1000% variations
in key parameters result in changes in clinically-relevant mechanical biomarkers ranging from diseased to healthy values in
clinical studies. Furthermore mechanical biomarkers are primarily affected by only one or two parameters. Specifically, ejection
fraction is dominated by the scaling parameter of the active tension model and its scaling parameter in the normal direction
(kort 2); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered (Pej) and the compliance
of the Windkessel fluid model (C); and the longitudinal fractional shortening is dominated by the fibre angle (φ) and kort 2.
The wall thickening does not seem to be clearly dominated by any of the considered input parameters.
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