Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations.

Computing in cardiology Pub Date : 2013-10-01
Caroline Mendonca Costa, Elena Hoetzl, Bernardo Martins Rocha, Anton J Prassl, Gernot Plank
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Abstract

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios.

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心脏电生理模拟的自动参数化策略。
在医学成像、图像分割和数值技术的最新进展的推动下,心室电生理的计算机模型越来越精细地解释了解剖和生物物理细节。然而,考虑到涉及的大量模型参数,参数化提出了一个重大挑战。在实验和建模相结合的研究中,最低要求是在模型和实验或患者数据之间的激活和复极序列上取得良好的一致性。在这项研究中,我们提出了一些基本的技术来帮助确定匹配激活序列的双域参数。实现了一种迭代参数化算法,以确定产生规定速度的适当体电导率。此外,提出了一种通过规定各向异性比将计算得到的体电导率分解为单个双畴电导率的方法。
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