Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg·Bad Krozingen, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, USA.
Comput Biol Med. 2022 Jul;146:105579. doi: 10.1016/j.compbiomed.2022.105579. Epub 2022 May 3.
Ventricular arrhythmias are the leading cause of mortality in patients with ischemic heart diseases, such as myocardial infarction (MI). Computational simulation of cardiac electrophysiology provides insights into these arrhythmias and their treatment. However, only sparse information is available on crucial model parameters, for instance, the anisotropic intracellular electrical conductivities. Here, we introduced an approach to estimate these conductivities in normal and MI hearts. We processed and analyzed images from confocal microscopy of left ventricular tissue of a rabbit MI model to generate 3D reconstructions. We derived tissue features including the volume fraction of myocytes (V), gap junctions-containing voxels (V), and fibrosis (V). We generated models of the intracellular space and intercellular coupling. Applying numerical methods for solving Poisson's equation for stationary electrical currents, we calculated normal (σ), longitudinal (σ), and transverse (σ) intracellular conductivities. Using linear regression analysis, we assessed relationships of conductivities to tissue features. V and V were reduced in MI vs. control, but V was increased. Both σ and σ were lower in MI than in control. Differences of σ between control and MI were not significant. We found strong positive relationships of σ with V and V, and a strong negative relationship with V. The relationships of σ with these tissue features were similar but less pronounced. Our study provides quantitative insights into the intracellular conductivities in the normal and MI heart. We suggest that our study establishes a framework for the estimation of intracellular electrical conductivities of myocardium with various pathologies.
室性心律失常是缺血性心脏病（如心肌梗死）患者死亡的主要原因。心脏电生理学的计算模拟为这些心律失常及其治疗提供了深入了解。然而，对于关键模型参数（例如各向异性细胞内电导率）的信息却很少。在这里，我们提出了一种估计正常和 MI 心脏中这些电导率的方法。我们处理和分析了来自兔 MI 模型左心室组织共聚焦显微镜的图像，以生成 3D 重建。我们得出了包括心肌细胞体积分数（V）、含缝隙连接的体素（V）和纤维化（V）在内的组织特征。我们生成了细胞内空间和细胞间耦合的模型。应用求解静止电流泊松方程的数值方法，我们计算了正常（σ）、纵向（σ）和横向（σ）细胞内电导率。通过线性回归分析，我们评估了电导率与组织特征之间的关系。与对照组相比，MI 中的 V 和 V 降低，但 V 增加。MI 中的 σ 和 σ 均低于对照组。对照组和 MI 之间的 σ 差异不显著。我们发现 σ 与 V 和 V 呈强正相关，与 V 呈强负相关。σ 与这些组织特征之间的关系相似，但不那么明显。我们的研究提供了对正常和 MI 心脏细胞内电导率的定量见解。我们建议我们的研究为估计具有各种病理的心肌细胞内电导率建立了一个框架。
