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Development of a novel probabilistic algorithm for localization of rotors during atrial fibrillation

机译:一种新的概率算法在心房颤动期间转子定位的概率算法

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Atrial fibrillation (AF) is an irregular heart rhythm that can lead to stroke and other heart-related complications. Catheter ablation has been commonly used to destroy triggering sources of AF in the atria and consequently terminate the arrhythmia. However, efficient and accurate localization of the AF sustaining sources known as rotors is a major challenge in catheter ablation. In this paper, we developed a novel probabilistic algorithm that can adaptively guide a Lasso diagnostic catheter to locate the center of a rotor. Our algorithm uses a Bayesian updating approach to search for and locate rotors based on the characteristics of electrogram signals collected at every catheter placement. The algorithm was evaluated using a 10 × 10 cm 2 D atrial tissue simulation of the Nygren human atrial cell model and was able to successfully guide the catheter to the rotor center in 3.37 ± 1.05 (mean±std) steps (including placement at the center) when starting from any location on the tissue. Our novel automated algorithm can potentially play a significant role in patient-specific ablation of AF sources and increase the success of AF elimination procedures.
机译:心房颤动(AF)是一种不规则的心律,可以导致中风和其他心脏相关的并发症。导管消融通常用于破坏区域内的AF的触发源,从而终止心律失常。然而,称为转子的AF可持续源的高效和准确定位是导管消融中的主要挑战。在本文中,我们开发了一种新颖的概率算法,其可以自适应地引导套索诊断导管以定位转子的中心。我们的算法使用贝叶斯更新方法来根据在每个导管放置时收集的电测信号的特性来搜索和定位转子。使用Nygren人心房细胞模型的10×10cm 2d风耳间组织模拟评估该算法,能够以3.37±1.05(平均值±STD)步骤成功地将导管引导到转子中心(包括放置在中心)从组织上的任何位置开始时。我们的新型自动化算法可能在特定于患者的AF来源中发挥重要作用,并增加AF消除程序的成功。

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