Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.

Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.
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DOI:
10.1038/s41598-022-20745-z
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发表时间:
2022-10-04
期刊:
影响因子:
4.6
通讯作者:
Clayton, Richard H.
Clayton, Richard H.
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Coveney, Sam;Roney, Caroline H.;Corrado, Cesare;Wilkinson, Richard D.;Oakley, Jeremy E.;Niederer, Steven A.;Clayton, Richard H.

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心脏的电兴奋和恢复模型已经变得越来越详细,但尚未在临床环境中常规使用来指导对患者的个性化干预。主要挑战之一是根据标准临床程序期间对患者进行的有限测量来校准模型。在这项工作中,我们提出了一种新颖的框架,用于使用心脏兴奋性的局部测量来对心脏左心房的电生理学参数进行概率校准。参数场表示为流形上的高斯过程,并通过从局部参数值映射到测量值的代理函数与测量值相关联。然后获得参数场的后验分布。我们表明,我们的方法可以恢复用于生成有效不应期的局部综合测量的参数场。我们的方法适用于通过临床方案收集的其他测量类型,更广泛地适用于模型参数在多个方面变化的校准。
Models of electrical excitation and recovery in the heart have become increasingly detailed, but have yet to be used routinely in the clinical setting to guide personalized intervention in patients. One of the main challenges is calibrating models from the limited measurements that can be made in a patient during a standard clinical procedure. In this work, we propose a novel framework for the probabilistic calibration of electrophysiology parameters on the left atrium of the heart using local measurements of cardiac excitability. Parameter fields are represented as Gaussian processes on manifolds and are linked to measurements via surrogate functions that map from local parameter values to measurements. The posterior distribution of parameter fields is then obtained. We show that our method can recover parameter fields used to generate localised synthetic measurements of effective refractory period. Our methodology is applicable to other measurement types collected with clinical protocols, and more generally for calibration where model parameters vary over a manifold.
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