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基于图像的心房解剖和电激活模型:用于研究心房性心律失常的计算平台。

Image-based model of atrial anatomy and electrical activation: a computational platform for investigating atrial arrhythmia.

机构信息

Auckland Bioengineering Institute, University of Auckland, Auckland 1142, New Zealand.

出版信息

IEEE Trans Med Imaging. 2013 Jan;32(1):18-27. doi: 10.1109/TMI.2012.2227776. Epub 2012 Nov 19.

Abstract

Computer models provide a powerful platform for investigating mechanisms that underlie atrial rhythm disturbances. We have used novel techniques to build a structurally-detailed, image-based model of 3-D atrial anatomy. A volume image of the atria from a normal sheep heart was acquired using serial surface macroscopy, then smoothed and down-sampled to 50 μm(3) resolution. Atrial surface geometry was identified and myofiber orientations were estimated throughout by eigen-analysis of the 3-D image structure tensor. Sinus node, crista terminalis, pectinate muscle, Bachman's bundle, and pulmonary veins were segmented on the basis of anatomic characteristics. Heterogeneous electrical properties were assigned to this structure and electrical activation was simulated on it at 100 μm(3) resolution, using both biophysically-detailed and reduced-order cell activation models with spatially-varying membrane kinetics. We confirmed that the model reproduced key features of the normal spread of atrial activation. Furthermore, we demonstrate that vulnerability to rhythm disturbance caused by structural heterogeneity in the posterior left atrium is exacerbated by spatial variation of repolarization kinetics across this region. These results provide insight into mechanisms that may sustain paroxysmal atrial fibrillation. We conclude that image-based computer models that incorporate realistic descriptions of atrial myofiber architecture and electrophysiologic properties have the potential to analyse and identify complex substrates for atrial fibrillation.

摘要

计算机模型为研究导致心房节律紊乱的机制提供了一个强大的平台。我们使用了新颖的技术来构建一个基于结构的、详细的三维心房解剖图像模型。使用连续表面宏观法获取正常绵羊心脏的心房容积图像,然后对其进行平滑和下采样至 50 μm(3)的分辨率。通过对三维图像结构张量的特征分析来识别心房表面几何形状,并估计整个心肌纤维的方向。根据解剖特征对窦房结、终嵴、梳状肌、Bachman 束和肺静脉进行分割。对该结构赋予不均匀的电特性,并使用具有空间变化膜动力学的详细生物物理和简化细胞激活模型,在 100 μm(3)的分辨率上对其进行电激活模拟。我们证实该模型再现了正常心房激活传播的关键特征。此外,我们还证明了左心房后外侧结构异质性引起的节律紊乱的易感性会因该区域复极动力学的空间变化而加剧。这些结果为维持阵发性心房颤动的机制提供了深入的了解。我们得出结论,基于图像的计算机模型,将心房肌纤维结构和电生理特性的真实描述结合在一起,具有分析和识别心房颤动复杂底物的潜力。

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