Department of Computer Science, Universidade Federal de São João del-Rei, São João del-Rei, Brazil.
Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil.
Sci Rep. 2018 Nov 6;8(1):16392. doi: 10.1038/s41598-018-34304-y.
Ectopic beats are known to be involved in the initiation of a variety of cardiac arrhythmias. Although their location may vary, ectopic excitations have been found to originate from infarct areas, regions of micro-fibrosis and other heterogeneous tissues. However, the underlying mechanisms that link ectopic foci to heterogeneous tissues have yet to be fully understood. In this work, we investigate the mechanism of micro-reentry that leads to the generation of ectopic beats near infarct areas using a patient-specific heart model. The patient-specific geometrical model of the heart, including scar and peri-infarct zones, is obtained through magnetic resonance imaging (MRI). The infarct region is composed of ischemic myocytes and non-conducting cells (fibrosis, for instance). Electrophysiology is captured using an established cardiac myocyte model of the human ventricle modified to describe ischemia. The simulation results clearly reveal that ectopic beats emerge from micro-reentries that are sustained by the heterogeneous structure of the infarct regions. Because microscopic information about the heterogeneous structure of the infarct regions is not available, Monte-Carlo simulations are used to identify the probabilities of an infarct region to behave as an ectopic focus for different levels of ischemia and different percentages of non-conducting cells. From the proposed model, it is observed that ectopic beats are generated when a percentage of non-conducting cells is near a topological metric known as the percolation threshold. Although the mechanism for micro-reentries was proposed half a century ago to be a source of ectopic beats or premature ventricular contractions during myocardial infarction, the present study is the first to reproduce this mechanism in-silico using patient-specific data.
异位搏动被认为与多种心律失常的发生有关。尽管异位兴奋的部位可能不同，但已经发现异位兴奋起源于梗死区、微纤维化区和其他异质组织。然而，将异位灶与异质组织联系起来的潜在机制尚未完全理解。在这项工作中，我们使用患者特定的心脏模型研究导致梗死区附近异位搏动的微折返机制。心脏的患者特定几何模型，包括疤痕和梗死周边区，通过磁共振成像（MRI）获得。梗死区由缺血心肌细胞和非传导细胞（如纤维化）组成。使用经过修改以描述缺血的人类心室的已建立的心肌细胞模型来捕获电生理学。模拟结果清楚地表明，异位搏动源于由梗死区的异质结构维持的微折返。由于梗死区的异质结构的微观信息不可用，因此使用蒙特卡罗模拟来确定不同程度的缺血和不同百分比的非传导细胞使梗死区表现为异位灶的概率。从提出的模型中可以观察到，当非传导细胞的百分比接近称为渗流阈值的拓扑度量时，就会产生异位搏动。尽管微折返机制早在半个世纪前就被提出是心肌梗死后异位搏动或室性期前收缩的来源，但本研究首次使用患者特定数据在计算机上重现了这一机制。
