학술논문
Spatial concentration and distribution of phase singularities in human atrial fibrillation: Insights for the AF mechanism
Document Type
Report
Author
Source
Journal of Arrhythmia. August 2021, Vol. 37 Issue 4, p922, 9 p.
Subject
Language
English
ISSN
1880-4276
Abstract
Abbreviations INTRODUCTION Atrial fibrillation (AF) is characterized by irregular, disorganized electrical activation of the atrium.[sup.1] A defining characteristic of AF is the presence of unstable local re‐entrant circuits that form [...]
: Background: Atrial fibrillation (AF) is characterized by the repetitive regeneration of unstable rotational events, the pivot of which are known as phase singularities (PSs). The spatial concentration and distribution of PSs have not been systematically investigated using quantitative statistical approaches. Objectives: We utilized a geospatial statistical approach to determine the presence of local spatial concentration and global clustering of PSs in biatrial human AF recordings. Methods: 64‐electrode conventional basket (~5 min, n = 18 patients, persistent AF) recordings were studied. Phase maps were produced using a Hilbert‐transform based approach. PSs were characterized spatially using the following approaches: (i) local “hotspots” of high phase singularity (PS) concentration using Getis‐Ord Gi* (Z ≥ 1.96, P ≤.05) and (ii) global spatial clustering using Moran's I (inverse distance matrix). Results: Episodes of AF were analyzed from basket catheter recordings (H: 41 epochs, 120 000 s, n = 18 patients). The Getis‐Ord Gi* statistic showed local PS hotspots in 12/41 basket recordings. As a metric of spatial clustering, Moran's I showed an overall mean of 0.033 (95% CI: 0.0003‐0.065), consistent with the notion of complete spatial randomness. Conclusion: Using a systematic, quantitative geospatial statistical approach, evidence for the existence of spatial concentrations (“hotspots”) of PSs were detectable in human AF, along with evidence of spatial clustering. Geospatial statistical approaches offer a new approach to map and ablate PS clusters using substrate‐based approaches.
: Background: Atrial fibrillation (AF) is characterized by the repetitive regeneration of unstable rotational events, the pivot of which are known as phase singularities (PSs). The spatial concentration and distribution of PSs have not been systematically investigated using quantitative statistical approaches. Objectives: We utilized a geospatial statistical approach to determine the presence of local spatial concentration and global clustering of PSs in biatrial human AF recordings. Methods: 64‐electrode conventional basket (~5 min, n = 18 patients, persistent AF) recordings were studied. Phase maps were produced using a Hilbert‐transform based approach. PSs were characterized spatially using the following approaches: (i) local “hotspots” of high phase singularity (PS) concentration using Getis‐Ord Gi* (Z ≥ 1.96, P ≤.05) and (ii) global spatial clustering using Moran's I (inverse distance matrix). Results: Episodes of AF were analyzed from basket catheter recordings (H: 41 epochs, 120 000 s, n = 18 patients). The Getis‐Ord Gi* statistic showed local PS hotspots in 12/41 basket recordings. As a metric of spatial clustering, Moran's I showed an overall mean of 0.033 (95% CI: 0.0003‐0.065), consistent with the notion of complete spatial randomness. Conclusion: Using a systematic, quantitative geospatial statistical approach, evidence for the existence of spatial concentrations (“hotspots”) of PSs were detectable in human AF, along with evidence of spatial clustering. Geospatial statistical approaches offer a new approach to map and ablate PS clusters using substrate‐based approaches.