Abstract

We propose four novel mathematical models, describing the microscopic mechanisms of force generation in the cardiac muscle tissue, which are suitable for multiscale numerical simulations of cardiac electromechanics. Such models are based on a biophysically accurate representation of the regulatory and contractile proteins in the sarcomeres. Our models, unlike most of the sarcomere dynamics models that are available in the literature and that feature a comparable richness of detail, do not require the time-consuming Monte Carlo method for their numerical approximation. Conversely, the models that we propose only require the solution of a system of PDEs and/or ODEs (the most reduced of the four only involving 20 ODEs), thus entailing a significant computational efficiency. By focusing on the two models that feature the best trade-off between detail of description and identifiability of parameters, we propose a pipeline to calibrate such parameters starting from experimental measurements available in literature. Thanks to this pipeline, we calibrate these models for room-temperature rat and for body-temperature human cells. We show, by means of numerical simulations, that the proposed models correctly predict the main features of force generation, including the steady-state force-calcium and force-length relationships, the length-dependent prolongation of twitches and increase of peak force, the force-velocity relationship. Moreover, they correctly reproduce the Frank-Starling effect, when employed in multiscale 3D numerical simulation of cardiac electromechanics.

Highlights

  • Cardiovascular mathematical and numerical models are increasingly used, with a twofold role [1,2,3,4,5,6]

  • We show the results of numerical simulations obtained with the SE-ODE and myosin filaments (MF)-ODE models, performed under different experimental settings

  • The codes implementing the models proposed in this paper and used to produce the results presented are freely available in the following online repository: https://github.com/FrancescoRegazzoni/cardiac-activation

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Summary

Introduction

Cardiovascular mathematical and numerical models are increasingly used, with a twofold role [1,2,3,4,5,6]. The construction of an integrated mathematical and numerical model of cardiac electromechanics (EM) is a remarkably arduous task This is mainly due to the multiphysics (due to the interplay of biochemistry, electricity, solid mechanics, fluid dynamics) and multiscale nature of the heart: characteristic spatial scales range from nanometers to centimeters and the temporal ones from microseconds to seconds. This makes it difficult to devise computationally efficient and accurate algorithms for a plurality of mathematical models featuring a broad degree of details [5, 7,8,9,10,11]

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