We introduce a multiphysics and geometric multiscale computational model, suitable to describe the hemodynamics of the whole human heart, driven by a four-chamber electromechanical model. We first present a study on the calibration of the biophysically detailed RDQ20 activation model (Regazzoni et al., 2020) that is able to reproduce the physiological range of hemodynamic biomarkers. Then, we demonstrate that the ability of the force generation model to reproduce certain microscale mechanisms, such as the dependence of force on fiber shortening velocity, is crucial to capture the overall physiological mechanical and fluid dynamics macroscale behavior. This motivates the need for using multiscale models with high biophysical fidelity, even when the outputs of interest are relative to the macroscale. We show that the use of a high-fidelity electromechanical model, combined with a detailed calibration process, allows us to achieve remarkable biophysical fidelity in terms of both mechanical and hemodynamic quantities. Indeed, our electromechanical-driven CFD simulations - carried out on an anatomically accurate geometry of the whole heart - provide results that match the cardiac physiology both qualitatively (in terms of flow patterns) and quantitatively (when comparing in silico results with biomarkers acquired in vivo). We consider the pathological case of left bundle branch block, and we investigate the consequences that an electrical abnormality has on cardiac hemodynamics thanks to our multiphysics integrated model. The computational model that we propose can faithfully predict a delay and an increasing wall shear stress in the left ventricle in the pathological condition. The interaction of different physical processes in an integrated framework allows us to faithfully describe and model this pathology, by capturing and reproducing the intrinsic multiphysics nature of the human heart.
翻译:我们引入了多物理学和几何多尺度的计算模型, 适合描述整个人类心脏的热动力学, 由四相电动电动机械模型驱动。 我们首先提出生物物理上详细的RDQ20激活模型校准( REgazzoni等人, 2020), 该模型能够复制热动力生物标志的生理范围。 然后, 我们证明, 部队生成模型复制某些微尺度机制的能力, 比如对纤维缩短速度的依赖性, 这对于捕捉整个生理机械和流动动态宏观行为至关重要。 这促使需要使用具有高度生物物理可靠性的多尺度模型, 即使相关产出与宏观尺度相对。 我们显示, 使用高纤维性电子机械模型, 再加上详细的校准过程, 使我们能够在模型模型的机械和肝动力学数量上实现惊人的生物可靠性。 事实上, 我们的电机动卡FD模拟, 可以在一个数学上准确的物理模型中进行计算。 我们的心电动和心电流的计算结果, 在心脏的物理上, 我们的心电物理上, 和心脏的物理上, 的物理上, 的物理上, 的物理上, 将一个物理上, 的物理上, 的物理上, 将一个物理上, 的物理上, 分析结果, 我们的物理上,, 将一个心脏的物理上,,,,,, 和心脏的物理上,,,,,,,, 将一个物理上,, 的物理上,, 分析,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,