Department of Physiology, Maastricht University, the Netherlands (P.P., S.Z., A.v.H., S.V.).
Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.).
Circ Arrhythm Electrophysiol. 2018 Oct;11(10):e005858. doi: 10.1161/CIRCEP.117.005858.
Several recent studies suggest rotors detected by phase mapping may act as main drivers of persistent atrial fibrillation. However, the electrophysiological nature of detected rotors remains unclear. We performed a direct, 1:1 comparison between phase and activation time mapping in high-density, epicardial, direct-contact mapping files of human atrial fibrillation.
Thirty-eight unipolar electrogram files of 10 s duration were recorded in patients with atrial fibrillation (n=20 patients) using a 16×16 electrode array placed on the epicardial surface of the left atrial posterior wall or the right atrial free wall. Phase maps and isochrone wave maps were constructed for all recordings. For each detected phase singularity (PS) with a lifespan of >1 cycle length, the corresponding conduction pattern was investigated in the isochrone wave maps.
When using sinusoidal recomposition and Hilbert Transform, 138 PSs were detected. One hundred and four out of 138 PSs were detected within 1 electrode distance (1.5 mm) from a line of conduction block between nonrotating wavefronts detected by activation mapping. Far fewer rotating wavefronts were detected when rotating activity was identified based on wave mapping (18 out of 8219 detected waves). Fourteen out of these 18 cases were detected as PSs in phase mapping. Phase analysis of filtered electrograms produced by simulated wavefronts separated by conduction block also identified PSs on the line of conduction block.
PSs identified by phase analysis of filtered epicardial electrograms colocalize with conduction block lines identified by activation mapping. Detection of PSs using phase analysis has a low specificity for identifying rotating wavefronts during human atrial fibrillation using activation mapping.
最近的几项研究表明,相位图检测到的转子可能是持续性心房颤动的主要驱动因素。然而,检测到的转子的电生理性质仍不清楚。我们在人类心房颤动的高密度、心外膜、直接接触图记录的相图和激活时间图之间进行了直接的 1:1 比较。
使用放置在心外膜左心房后壁或右心房游离壁上的 16×16 电极阵列,在 10 秒内记录 20 名患者的 38 个单极电图文件。为所有记录构建相图和等时波图。对于每个具有 >1 个心动周期长度的寿命的检测到的相位奇点 (PS),在等时波图中研究相应的传导模式。
使用正弦重新合成和希尔伯特变换时,检测到 138 个 PS。在激活图检测到非旋转波前之间的传导阻滞线 1 个电极距离 (1.5mm) 内检测到 138 个 PS 中的 104 个。根据波图识别旋转活动时,检测到的旋转波前要少得多 (8219 个检测波中的 18 个)。这 18 个案例中的 14 个在相位图中被检测为 PS。通过模拟波前之间的传导阻塞分离的滤波电图的相位分析也在传导阻塞线上识别了 PS。
滤波心外膜电图相位分析识别的 PS 与激活图识别的传导阻滞线共定位。使用相位分析检测 PS 对使用激活图识别人类心房颤动期间的旋转波前的特异性较低。