Efficient estimation of cardiac conductivities: A proper generalized decomposition approach
Efficient estimation of cardiac conductivities: A proper generalized decomposition approach
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DOI：
10.1016/j.jcp.2020.109810
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发表时间：
2020-12-15
影响因子：
4.1
通讯作者：
Veneziani, Alessandro
中科院分区：
文献类型：
--
作者：
Barone, Alessandro;Carlino, Michele Giuliano;Veneziani, Alessandro
虽然数学建模在电生理学中的潜在突破性作用已被证明用于心脏消融或导管消融等治疗，但由于需要准确的定制电导率识别，因此无法在临床中广泛使用。数据同化技术一般用于确定无法直接测量的参数，特别是在患者特定环境中。然而，它们可能需要计算。这与临床时间表和要分析的患者数量相冲突。本文采用了F. Chinesta和他的合作者在过去的15年中，称为适当的广义分解（PGD），以加速心脏电动力学建模所需的心脏电导率的估计。具体来说，我们诉诸单域逆电导率问题（MICP）深入研究的文献中，在过去的五年。我们提供了一个重要的概念证明，PGD是在合理的时间内解决MICP的突破。由于PGD依赖于离线/在线范例，并且不需要高保真解决方案的任何初步知识，我们表明PGD在线阶段实时估计二维和三维情况下的电导率，包括患者特定的心室。(C)2020爱思唯尔公司All rights reserved.
While the potential groundbreaking role of mathematical modeling in electrophysiology has been demonstrated for therapies like cardiac resynchronization or catheter ablation, its extensive use in clinics is prevented by the need of an accurate customized conductivity identification. Data assimilation techniques are, in general, used to identify parameters that cannot be measured directly, especially in patient-specific settings. Yet, they may be computationally demanding. This conflicts with the clinical timelines and volumes of patients to analyze. In this paper, we adopt a model reduction technique, developed by F. Chinesta and his collaborators in the last 15 years, called Proper Generalized Decomposition (PGD), to accelerate the estimation of the cardiac conductivities required in the modeling of the cardiac electrical dynamics. Specifically, we resort to the Monodomain Inverse Conductivity Problem (MICP) deeply investigated in the literature in the last five years. We provide a significant proof of concept that PGD is a breakthrough in solving the MICP within reasonable timelines. As PGD relies on the offline/online paradigm and does not need any preliminary knowledge of the high-fidelity solution, we show that the PGD online phase estimates the conductivities in real-time for both two-dimensional and three-dimensional cases, including a patient-specific ventricle. (C) 2020 Elsevier Inc. All rights reserved.