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Multiscale Modeling of Cardiovascular Flows for Clinical Decision Support

机译:用于临床决策支持的心血管流量的多尺度建模

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摘要

Patient-specific cardiovascular simulations can provide clinicians with predictive tools, fill current gaps in clinical imaging capabilities, and contribute to the fundamental understanding of disease progression. However, clinically relevant simulations must provide not only local hemodynamics, but also global physiologic response. This necessitates a dynamic coupling between the Navier-Stokes solver and reduced-order models of circulatory physiology, resulting in numerical stability and efficiency challenges. In this review, we discuss approaches to handling the coupled systems that arise from cardiovascular simulations, including recent algorithms that enable efficient large-scale simulations of the vascular system. We maintain particular focus on multiscale modeling algorithms for finite element simulations. Because these algorithms give rise to an ill-conditioned system of equations dominated by the coupled boundaries, we also discuss recent methods for solving the linear system of equations arising from these systems. We then review applications that illustrate the potential impact of these tools for clinical decision support in adult and pediatric cardiology. Finally, we offer an outlook on future directions in the field for both modeling and clinical application.
机译:特定于患者的心血管模拟可以为临床医生提供预测工具,填补临床成像功能方面的空白,并有助于对疾病进展的基本了解。但是,临床相关的模拟不仅必须提供局部血流动力学,还必须提供整体生理反应。这就需要在Navier-Stokes求解器和循环生理的降阶模型之间进行动态耦合,从而导致数值稳定性和效率挑战。在这篇综述中,我们讨论了处理由心血管模拟产生的耦合系统的方法,包括能够对血管系统进行有效大规模模拟的最新算法。我们特别关注用于有限元模拟的多尺度建模算法。由于这些算法产生了由耦合边界控制的方程组的病态系统,因此我们还将讨论解决由这些系统引起的方程组线性系统的最新方法。然后,我们将审查说明这些工具对成人和儿科心脏病学临床决策支持的潜在影响的应用程序。最后,我们对建模和临床应用领域的未来方向提供了展望。

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