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简单的心房颤动关键区域识别模型。

Simple model for identifying critical regions in atrial fibrillation.

机构信息

The Blackett Laboratory, Imperial College London, London SW7 2BW, United Kingdom.

Center for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom.

出版信息

Phys Rev Lett. 2015 Jan 16;114(2):028104-28104. doi: 10.1103/physrevlett.114.028104.

Abstract

Atrial fibrillation (AF) is the most common abnormal heart rhythm and the single biggest cause of stroke. Ablation, destroying regions of the atria, is applied largely empirically and can be curative but with a disappointing clinical success rate. We design a simple model of activation wave front propagation on an anisotropic structure mimicking the branching network of heart muscle cells. This integration of phenomenological dynamics and pertinent structure shows how AF emerges spontaneously when the transverse cell-to-cell coupling decreases, as occurs with age, beyond a threshold value. We identify critical regions responsible for the initiation and maintenance of AF, the ablation of which terminates AF. The simplicity of the model allows us to calculate analytically the risk of arrhythmia and express the threshold value of transversal cell-to-cell coupling as a function of the model parameters. This threshold value decreases with increasing refractory period by reducing the number of critical regions which can initiate and sustain microreentrant circuits. These biologically testable predictions might inform ablation therapies and arrhythmic risk assessment.

摘要

心房颤动(AF)是最常见的异常心律,也是中风的单一最大原因。消融术,即破坏心房的区域,主要是凭经验应用,可以是治愈性的,但临床成功率令人失望。我们设计了一个简单的激活波前传播模型,该模型模拟心肌细胞的分支网络,具有各向异性结构。这种现象动力学和相关结构的综合,展示了当横向细胞间耦合随着年龄的增长而降低,超过阈值时,AF 如何自发出现。我们确定了负责 AF 起始和维持的关键区域,消融这些区域可以终止 AF。该模型的简单性允许我们通过分析计算心律失常的风险,并将横向细胞间耦合的阈值表示为模型参数的函数。随着不应期的增加,通过减少可以引发和维持微折返电路的关键区域的数量,该阈值值降低。这些可通过生物学验证的预测可以为消融治疗和心律失常风险评估提供信息。

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