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A multiscale finite element model of left ventricular mechanics incorporating baroreflex regulation.

Authors :
Sharifi H
Lee LC
Campbell KS
Wenk JF
Source :
Computers in biology and medicine [Comput Biol Med] 2024 Jan; Vol. 168, pp. 107690. Date of Electronic Publication: 2023 Nov 11.
Publication Year :
2024

Abstract

Cardiovascular function is regulated by a short-term hemodynamic baroreflex loop, which tries to maintain arterial pressure at a normal level. In this study, we present a new multiscale model of the cardiovascular system named MyoFE. This framework integrates a mechanistic model of contraction at the myosin level into a finite-element-based model of the left ventricle pumping blood through the systemic circulation. The model is coupled with a closed-loop feedback control of arterial pressure inspired by a baroreflex algorithm previously published by our team. The reflex loop mimics the afferent neuron pathway via a normalized signal derived from arterial pressure. The efferent pathway is represented by a kinetic model that simulates the net result of neural processing in the medulla and cell-level responses to autonomic drive. The baroreflex control algorithm modulates parameters such as heart rate and vascular tone of vessels in the lumped-parameter model of systemic circulation. In addition, it spatially modulates intracellular Ca <superscript>2+</superscript> dynamics and molecular-level function of both the thick and the thin myofilaments in the left ventricle. Our study demonstrates that the baroreflex algorithm can maintain arterial pressure in the presence of perturbations such as acute cases of altered aortic resistance, mitral regurgitation, and myocardial infarction. The capabilities of this new multiscale model will be utilized in future research related to computational investigations of growth and remodeling.<br />Competing Interests: Declaration of competing interest None of the authors have any commercial or other interest that are in conflict with the integrity of this work.<br /> (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
168
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
37984204
Full Text :
https://doi.org/10.1016/j.compbiomed.2023.107690