Li Xin, Chu Gavin S, Almeida Tiago P, Vanheusden Frederique J, Salinet João, Dastagir Nawshin, Mistry Amar R, Vali Zakariyya, Sidhu Bharat, Stafford Peter J, Schlindwein Fernando S, Ng G André
Department of Cardiovascular Science, University of Leicester, Leicester, United Kingdom.
School of Engineering, University of Leicester, Leicester, United Kingdom.
Front Physiol. 2021 Mar 12;12:649486. doi: 10.3389/fphys.2021.649486. eCollection 2021.
Identifying targets for catheter ablation remains challenging in persistent atrial fibrillation (persAF). The dominant frequency (DF) of atrial electrograms during atrial fibrillation (AF) is believed to primarily reflect local activation. Highest DF (HDF) might be responsible for the initiation and perpetuation of persAF. However, the spatiotemporal behavior of DF remains not fully understood. Some DFs during persAF were shown to lack spatiotemporal stability, while others exhibit recurrent behavior. We sought to develop a tool to automatically detect recurrent DF patterns in persAF patients. Non-contact mapping of the left atrium (LA) was performed in 10 patients undergoing persAF HDF ablation. 2,048 virtual electrograms (vEGMs, EnSite Array, Abbott Laboratories, USA) were collected for up to 5 min before and after ablation. Frequency spectrum was estimated using fast Fourier transform and DF was identified as the peak between 4 and 10 Hz and organization index (OI) was calculated. The HDF maps were identified per 4-s window and an automated pattern recognition algorithm was used to find recurring HDF spatial patterns. Dominant patterns (DPs) were defined as the HDF pattern with the highest recurrence. DPs were found in all patients. Patients in atrial flutter after ablation had a single DP over the recorded time period. The time interval (median [IQR]) of DP recurrence for the patients in AF after ablation (7 patients) decreased from 21.1 s [11.8 49.7 s] to 15.7 s [6.5 18.2 s]. The DF inside the DPs presented lower temporal standard deviation (0.18 ± 0.06 Hz vs. 0.29 ± 0.12 Hz, < 0.05) and higher OI (0.35 ± 0.03 vs. 0.31 ± 0.04, < 0.05). The atrial regions with the highest proportion of HDF region were the septum and the left upper pulmonary vein. Multiple recurrent spatiotemporal HDF patterns exist during persAF. The proposed method can identify and quantify the spatiotemporal repetition of the HDFs, where the high recurrences of DP may suggest a more organized rhythm. DPs presented a more consistent DF and higher organization compared with non-DPs, suggesting that DF with higher OI might be more likely to recur. Recurring patterns offer a more comprehensive dynamic insight of persAF behavior, and ablation targeting such regions may be beneficial.
在持续性心房颤动(persAF)中,确定导管消融的靶点仍然具有挑战性。心房颤动(AF)期间心房电图的主导频率(DF)被认为主要反映局部激活。最高主导频率(HDF)可能是持续性房颤起始和持续的原因。然而,DF的时空行为仍未完全了解。持续性房颤期间的一些DF显示缺乏时空稳定性,而其他DF则表现出反复出现的行为。我们试图开发一种工具来自动检测持续性房颤患者中反复出现的DF模式。对10例接受持续性房颤HDF消融的患者进行了左心房(LA)的非接触式标测。在消融前后最多5分钟内收集了2048个虚拟心电图(vEGM,EnSite Array,美国雅培实验室)。使用快速傅里叶变换估计频谱,将DF确定为4至10Hz之间的峰值,并计算组织指数(OI)。每4秒窗口识别一次HDF图,并使用自动模式识别算法来寻找反复出现的HDF空间模式。主导模式(DP)被定义为复发率最高的HDF模式。在所有患者中均发现了DP。消融后发生心房扑动的患者在记录时间段内有单一的DP。消融后仍处于房颤状态的患者(7例)DP复发的时间间隔(中位数[四分位间距])从21.1秒[11.8 49.7秒]降至15.7秒[6.5 18.2秒]。DP内的DF呈现出较低的时间标准差(0.18±0.06Hz对0.29±0.12Hz,P<0.05)和较高的OI(0.35±0.03对0.31±0.04,P<0.05)。HDF区域比例最高的心房区域是房间隔和左上肺静脉。持续性房颤期间存在多种反复出现的时空HDF模式。所提出的方法可以识别和量化HDF的时空重复性,其中DP的高复发率可能表明节律更规整。与非DP相比,DP呈现出更一致的DF和更高的组织化程度,这表明具有更高OI的DF可能更有可能复发。反复出现的模式为持续性房颤行为提供了更全面的动态见解,针对这些区域进行消融可能是有益的。