基于Granger因果分析的心房颤动转子识别和机制研究

Atrial fibrillation(AF) is a common arrhythmia severely affecting human health. Although AF seems random and chaotic, spatial and temporal organization beneath the irregular rhythm is suggested by ample evidences. Recently, mapping and ablation of rotors emerge as a focus of AF research. However, many basic problems remain unsolved, partly attributed to lack of safe and reliable mapping technique. Especially, activation mapping can not be accurately performed from irregular recordings during AF with existing tools. Granger causality is a well developed method for time series analysis of irregular signals in economics and neuroscience, and we hypothesize that it can be successfully applicated in identification of atrial activation sequence during AF. This study will apply Granger causality to recordings collected by simultaneous high-intensity mapping of the isolated sheep heart during AF, to facilitate activation mapping under irregular rhythm. Consequently, stable rotors can be identified, and their role in AF maintainance can be studied thereby. This study will provide a basis for further investigation of human rotors and development of mechanistic ablation strategy.

心房颤动（房颤）是严重危害人类健康的常见心律失常。种种证据提示，房颤表面上的不规则下实际上掩盖着一定程度的规律性。其中，转子标测和消融是最近房颤研究的热点，但由于缺乏安全、可信的标测手段，很多基本问题仍存在较大争议。尤其是房颤律下各点标测的电信号不规则，现有方法难以可靠地判断心房激动顺序。Granger因果分析是一种在经济学和神经科学中用于紊乱信号时序分析的成熟方法，我们设想，它亦可能有助于房颤律下心房电激动顺序的判断。本课题拟在离体羊心脏房颤模型中通过高密度同步标测采集心房各处电生理信号，再应用Granger因果分析进行处理，获得房颤律下的心房电激动顺序图，从中筛选稳定转子并研究其在房颤维持中的作用，从而为进一步开展人类转子标测研究和探索更具针对性的导管消融方案打下基础。

心房颤动（房颤）是严重危害人类健康的常见心律失常。以心腔内激动顺序为基础的心内电生理研究是心律失常研究的重要方式，但房颤律下各点标测的电信号不规则，现有方法难以可靠地判断心房激动顺序。Granger因果分析是一种用于紊乱信号时序分析的成熟方法。在本课题中，我们将其用于房颤律下心房电激动顺序的判断，取得的主要进展包括：1）逐点采集电生理信号的同步化；2）在猪房颤模型和临床房颤三维标测数据中应用Granger因果分析判断心房激动顺序；3）房颤律下转子或其它折返激动形式的识别。本课题将有助于进一步探索临床房颤机制及相关消融策略。