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Noninvasive identification of atrial fibrillation drivers: Simulation and patient data evaluation

机译:心房颤动驱动程序的非侵入性识别:模拟和患者数据评估

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Identification of atrial drivers as singularity points by using the inverse problem of electrocardiography is being used to guide atrial fibrillation (AF) ablation. However, the ability of the inverse problem to reconstruct fibrillation patterns and identify AF drivers has not been validated. Position of AF drivers was compared between recorded and inverse computed EGMs by making use of (1) realistic mathematical models and (2) simultaneous endocardial and body surface recordings during AF ablation procedures. Atrial drivers were defined as the areas with the highest dominant frequencies (HDF) or at the sites with a higher incidence of long-lasting phase singularities (PS). On simulation data, HDF analysis allowed the identification of the chamber that harboured the AF source in 30 out of 30 of the models evaluated vs. 26 out of 30 models for PS analysis. On patient data, solution of the inverse problem only allowed identifying atrial drivers on the correct atrial chamber by HDF analysis (2 out of 2 patients vs. 0 out of 2 patients for PS analysis). Identification of atrial sources by solving the inverse problem of the electrocardiography is more reliably accomplished based HDF than on PS detection.
机译:通过使用心电图学的逆问题将心房驱动器识别为奇点,已被用于引导房颤(AF)消融。然而,反问题重构纤颤模式和识别房颤驱动者的能力尚未得到验证。通过在AF消融过程中利用(1)现实的数学模型和(2)同时记录心内膜和体表,在记录的EGM和反向计算的EGM之间比较了AF驾驶员的位置。心房驱动器定义为具有最高主导频率(HDF)的区域或位于具有长相奇异点(PS)的位置。在仿真数据上,HDF分析可以在30个评估模型中的30个中识别出装有AF源的腔室,而PS分析则在30个模型中确定26个。在患者数据上,反问题的解决方案仅允许通过HDF分析(在2例患者中2例与2例患者中0例进行PS分析)在正确的心房中识别出心房驱动因素。基于HDF的解决心电图逆问题的心源识别比基于PS检测更可靠。

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