Seitz Julien, Horvilleur Jérôme, Lacotte Jérôme, Mouhoub Yamina, Salerno Fiorella, Moynagh Anouska, O H-Ici Darach, Monchi Mehran, Curel Laurence, Pisapia Andre
The Institut Cardiovasculaire Paris Sud, Hôpital Privé Jacques Cartier, 6 Avenue du Noyer Lambert, 91300 Massy, France.
Hôpital Saint Joseph, 26 Bd de Louvain, 13008 Marseille, France.
J Atr Fibrillation. 2013 Aug 31;6(2):673. doi: 10.4022/jafib.673. eCollection 2013 Aug-Sep.
Up until recently complex fractionated atrial electrogram (CFAE) ablation has been considered as time consuming and its achievement as challenging, especially for non experimented operators. Moreover, results of substrate ablation based on CFAE detection in atrial fibrillation (AF) are very disparate, mainly because of the operator's subjective electrogram visual analysis and the difficult distinction between CFAEs really involved in AF perpetuation from other CFAE. Automatic detection provided by 3D mapping system (CARTO® algorithm) can be helpful but is not selective enough, drawing too wide CFAE areas. We sought to demonstrate a better selectivity of a new CFAE algorithm setting in order to better discriminate CFAEs really involved in AF perpetuation from other CFAE. A population of 32 patients (60.4±12.7 years) with paroxysmal (n=3) AF (PAF), persistent (n=16) AF (PeAF) or long-standing persistent (n=13) AF (LSPeAF), and AF history =56±65 months, underwent CFAE ablation based on visual analysis. Before ablation, left atrium CFAE mapping was performed on CARTO® shortest complex interval (SCI) algorithm and reanalyzed after ablation with the two different settings: nominal (SCI 60-120ms/0.05-0.15mV) vs. customized setting (SCI 30-40ms/0,04-0.15mV). CFAE areas automatically detected by both settings (CFAE-CARTO® areas) were respectively measured. The decision to ablate CFAE was only based upon the operator's electrogram visual analysis taken as reference because of high AF termination rate (93.7%) due to operator's CFAE selection experience. These ablation points drawn reference-CFAE areas involved in AF perpetuation (ablation point=60mm) allowing to compare the selectivity of the two previous automatic maps. With the customized CARTO® SCI setting, we observed a significant reduction of CFAE areas detected by CARTO® (CFAE-CARTO® areas) and of the ablated CFAE surface inside non-CFAE CARTO® areas, (30.6±20.5cm2 vs. 68.8±24.5cm2, p<0.0001, and 1.86±1.82% vs. 3±3%, p=0.003). Furthermore the proportion of ablated areas/detected CFAE-CARTO® areas were higher with customized setting (38.2±19.6% vs. 20.4±17.5%, p=0.008). This new customized CFAE algorithm setting is significantly more selective than the nominal one and allows an automated detection of CFAE really involved in AF perpetuation truer to an efficient experienced operator's electrogram visual analysis.
直到最近,复杂碎裂心房电图(CFAE)消融仍被认为耗时且具有挑战性,尤其是对于缺乏经验的术者而言。此外,基于房颤(AF)中CFAE检测的基质消融结果差异很大,主要是因为术者对电图的主观视觉分析,以及难以区分真正参与房颤持续的CFAE与其他CFAE。三维标测系统(CARTO®算法)提供的自动检测可能有所帮助,但选择性不足,绘制的CFAE区域过大。我们试图证明一种新的CFAE算法设置具有更好的选择性,以便更好地区分真正参与房颤持续的CFAE与其他CFAE。32例患者(年龄60.4±12.7岁),包括阵发性房颤(PAF,n = 3例)、持续性房颤(PeAF,n = 16例)或长期持续性房颤(LSPeAF,n = 13例),房颤病史为56±65个月,接受了基于视觉分析的CFAE消融。消融前,使用CARTO®最短复合间期(SCI)算法进行左心房CFAE标测,并在消融后用两种不同设置重新分析:标称设置(SCI 60 - 120ms/0.05 - 0.15mV)与定制设置(SCI 30 - 40ms/0.04 - 0.15mV)。分别测量两种设置自动检测到的CFAE区域(CFAE - CARTO®区域)。由于术者对CFAE的选择经验使房颤终止率较高(93.7%),因此消融CFAE的决定仅基于术者的电图视觉分析作为参考。这些绘制的消融点构成了参与房颤持续的参考CFAE区域(消融点 = 60mm),从而能够比较之前两种自动标测图的选择性。采用定制的CARTO® SCI设置时,我们观察到CARTO®检测到的CFAE区域(CFAE - CARTO®区域)以及非CFAE CARTO®区域内消融的CFAE面积显著减少(分别为30.6±20.5cm² 与68.8±24.5cm²,p < 0.0001;以及1.86±1.82% 与3±3%,p = 0.003)。此外,定制设置下消融面积/检测到的CFAE - CARTO®区域的比例更高(38.2±19.6% 与20.4±17.5%,p = 0.008)。这种新的定制CFAE算法设置比标称设置具有显著更高的选择性,并且能够更真实地自动检测到真正参与房颤持续的CFAE,类似于经验丰富的术者进行的高效电图视觉分析。