Cusimano N, Gizzi A, Fenton F H, Filippi S, Gerardo-Giorda L
Basque Center for Applied Mathematics, Alameda de Mazarredo 14, 48009 Bilbao, Spain.
Department of Engineering, University of Rome Campus Bio-Medico, via A. del Portillo 21, 00128 Rome, Italy.
Commun Nonlinear Sci Numer Simul. 2020 May;84. doi: 10.1016/j.cnsns.2019.105152. Epub 2019 Dec 25.
Microscopic structural features of cardiac tissue play a fundamental role in determining complex spatio-temporal excitation dynamics at the macroscopic level. Recent efforts have been devoted to the development of mathematical models accounting for non-local spatio-temporal coupling able to capture these complex dynamics without the need of resolving tissue heterogeneities down to the micro-scale. In this work, we analyse in detail several important aspects affecting the overall predictive power of these modelling tools and provide some guidelines for an effective use of space-fractional models of cardiac electrophysiology in practical applications. Through an extensive computational study in simplified computational domains, we highlight the robustness of models belonging to different categories, i.e., physiological and phenomenological descriptions, against the introduction of non-locality, and lay down the foundations for future research and model validation against experimental data. A modern genetic algorithm framework is used to investigate proper parameterisations of the considered models, and the crucial role played by the boundary assumptions in the considered settings is discussed. Several numerical results are provided to support our claims.
心脏组织的微观结构特征在宏观层面决定复杂的时空兴奋动力学方面起着根本性作用。最近的研究致力于开发考虑非局部时空耦合的数学模型，这些模型能够捕捉这些复杂动力学，而无需将组织异质性解析到微观尺度。在这项工作中，我们详细分析了影响这些建模工具整体预测能力的几个重要方面，并为在实际应用中有效使用心脏电生理学的空间分数模型提供了一些指导方针。通过在简化计算域中的广泛计算研究，我们强调了不同类别模型（即生理和现象学描述）对引入非局部性的鲁棒性，并为未来针对实验数据的研究和模型验证奠定了基础。使用现代遗传算法框架来研究所考虑模型的适当参数化，并讨论了在所考虑设置中边界假设所起的关键作用。提供了几个数值结果来支持我们的观点。
