Levrero-Florencio F, Margara F, Zacur E, Bueno-Orovio A, Wang Z J, Santiago A, Aguado-Sierra J, Houzeaux G, Grau V, Kay D, Vázquez M, Ruiz-Baier R, Rodriguez B
Department of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
Department of Engineering Science, University of Oxford, Oxford OX3 7DQ, United Kingdom.
Comput Methods Appl Mech Eng. 2020 Apr 1;361:112762. doi: 10.1016/j.cma.2019.112762.
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 ( ); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered ( ) and the compliance of the Windkessel fluid model ( ); and the longitudinal fractional shortening is dominated by the fibre angle ( ) and . The wall thickening does not seem to be clearly dominated by any of the considered input parameters. In summary, this study presents in detail the description and implementation of a human-based coupled electromechanical modelling and simulation framework, and a high performance computing study on the sensitivity of mechanical biomarkers to key model parameters. The tools and knowledge generated enable future investigations into disease and drug action on human ventricles.
人类心脏的跳动是多尺度非线性动力学将亚细胞过程与整个器官过程耦合的结果，实现了电生理驱动的机械收缩。心脏计算建模与仿真在基础生物物理过程的数学模型以及仿真软件的开发方面都已达到了很高的成熟度。在本研究中，我们详细描述了一个基于人体生理的、完全耦合的心室机电建模与仿真框架，以及一项聚焦于其力学特性的敏感性分析。该模型从离子层面到整个器官的生物物理细节对于未来疾病和药物作用的模拟至关重要。关键创新点包括最先进的基于人体的电生理膜动力学、兴奋 - 收缩和主动收缩模型的耦合，以及纳入一个预应力模型，以便在动态状态下对心室进行预应力和预加载。通过高性能计算仿真，我们证明关键参数50%至200%、1000%的变化会导致临床相关力学生物标志物在临床研究中从患病值变为健康值。此外，力学生物标志物主要仅受一两个参数的影响。具体而言，射血分数主要由主动张力模型的缩放参数及其法向缩放参数主导；收缩末期压力主要由射血期触发时的压力以及风箱流体模型的顺应性主导；纵向缩短分数主要由纤维角度和主导。壁增厚似乎不受任何所考虑的输入参数的明显主导。总之，本研究详细介绍了基于人体的耦合机电建模与仿真框架的描述与实现，以及关于力学生物标志物对关键模型参数敏感性的高性能计算研究。所生成的工具和知识为未来对人类心室疾病和药物作用的研究提供了支持。
