Physics of Fluids - Publications

A fast computational model for the electrophysiology of the whole human heart

arΧiv
Journal of Computational Physics 457, 111084 (2022)

Authors

	G. Del Corso
	Roberto Verzicco
	Francesco Viola

BibTeΧ

@article{DELCORSO2022111084,
title = {A fast computational model for the electrophysiology of the whole human heart},
journal = {Journal of Computational Physics},
volume = {457},
pages = {111084},
year = {2022},
issn = {0021-9991},
doi = {https://doi.org/10.1016/j.jcp.2022.111084},
url = {https://www.sciencedirect.com/science/article/pii/S0021999122001462},
author = {Giulio {Del Corso} and Roberto Verzicco and Francesco Viola},
keywords = {Electrophysiology, Bidomain equations, Heart modeling, GPU computing},
abstract = {In this study we present a novel computational model for unprecedented simulations of the whole cardiac electrophysiology. According to the heterogeneous electrophysiologic properties of the heart, the whole cardiac geometry is decomposed into a set of coupled conductive media having different topology and electrical conductivities: (i) a network of slender bundles comprising a fast conduction atrial network, the AV‚Äìnode and the ventricular bundles; (ii) the Purkinje network; and (iii) the atrial and ventricular myocardium. The propagation of the action potential in these conductive media is governed by the bidomain/monodomain equations, which are discretized in space using an in‚Äìhouse finite volume method and coupled to three different cell models, the Courtemanche model [1] for the atrial myocytes, the Stewart model [2] for the Purkinje Network and the ten Tusscher‚ÄìPanfilov model [3] for the ventricular myocytes. The developed numerical model correctly reproduces the cardiac electrophysiology of the whole human heart in healthy and pathologic conditions and it can be tailored to study and optimize resynchronization therapies or invasive surgical procedures. Importantly, the whole solver is GPU‚Äìaccelerated using CUDA Fortran providing an unprecedented speedup, thus opening the way for systematic parametric studies and uncertainty quantification analyses.}
}