首页> 外文会议>Statistical atlases and computational models of the heart: imaging and modelling challenges. >EP Challenge - STACOM'11: Forward Approaches to Computational Electrophysiology Using MRI-Based Models and In-Vivo CARTO Mapping in Swine Hearts
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EP Challenge - STACOM'11: Forward Approaches to Computational Electrophysiology Using MRI-Based Models and In-Vivo CARTO Mapping in Swine Hearts

机译:EP挑战-STACOM'11:在猪心脏中使用基于MRI的模型和活体CARTO映射进行计算电生理学的正向方法

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Our broad aim is to integrate experimental measurements (electro-cardiographic and MR) and cardiac computer models, for a better understanding of transmural wave propagation in individual hearts. In this paper, we first describe the acquisition and processing of the data provided to the EP simulation challenge organized at STACOM'11. The measurements were obtained in two swine hearts (I.e., one healthy and one with chronic infarction) and comprise in-vivo electro-anatomical CARTO maps (e.g., surfacic endo-/epicardial depolarization maps and bipolar voltage maps recorded in sinus rhythm), and high-resolution ex-vivo diffusion-weighted DW-MR images (voxel size < 1mm~3). We briefly detail how we built anisotropic 3D MRI-based models for these two hearts, with fiber directions obtained using DW-MRI methods (which also allowed for infarct identification). We then focus on applications in cardiac modelling concerning propagation of depolarization wave, by employing forward mathematical approaches. Specifically, we present simulation results for the depolarization wave using a fast, macroscopic monodomain formalism (I.e., the two-variable Aliev-Panfilov model) and comparisons with measured depolarization times. We also include simulations obtained using the healthy heart and a simple Eikonal model, as well as a complex bidomain model. The results demonstrate small differences between computed isochrones using these computer models; specifically, we calculated a mean error + S.D. of 2.8 ± 1.67 ms between Aliev-Panfilov and Eikonal models, and 6.1 ± 3.9 ms between Alie-Panfilov and bidomain models, respectively.
机译:我们的主要目标是整合实验测量(心电图和MR)和心脏计算机模型,以更好地了解透壁波在各个心脏中的传播。在本文中,我们首先描述为STACOM'11组织的EP模拟挑战提供的数据的获取和处理。测量是在两个猪心脏(即,一个健康的人和一个患有慢性梗塞的人)中获得的,包括体内电解剖CARTO图(例如,以窦性心律记录的表面心内膜/心外膜去极化图和双极电压图),以及高分辨率离体扩散加权DW-MR图像(体素大小<1mm〜3)。我们简要详细介绍了如何为这两个心脏建立基于各向异性3D MRI的模型,并使用DW-MRI方法(也可以用于梗塞识别)获得纤维方向。然后,我们通过采用正向数学方法,重点研究心脏模型中有关去极化波传播的应用。具体来说,我们使用快速的宏观单域形式主义(即二变量Aliev-Panfilov模型)给出了去极化波的仿真结果,并与测得的去极化时间进行了比较。我们还包括使用心脏健康和简单的Eikonal模型以及复杂的双域模型获得的模拟。结果表明,使用这些计算机模型计算出的等时线之间存在微小差异;具体来说,我们计算了平均误差+标准误差。在Aliev-Panfilov模型和Eikonal模型之间分别为2.8±1.67 ms和Alie-Panfilov模型与双域模型之间分别为6.1±3.9 ms。

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