Electrographic flow mapping for atrial fibrillation: theoretical basis and preliminary observations.
Document Type
Article
Publication Date
6-2023
Publication Title
Journal of interventional cardiac electrophysiology
Abstract
Ablation strategies remain poorly defined for persistent atrial fibrillation (AF) patients with recurrence despite intact pulmonary vein isolation (PVI). As the ability to perform durable PVI improves, the need for advanced mapping to identify extra-PV sources of AF becomes increasingly evident. Multiple mapping technologies attempt to localize these self-sustained triggers and/or drivers responsible for initiating and/or maintaining AF; however, current approaches suffer from technical limitations. Electrographic flow (EGF) mapping is a novel mapping method based on well-established principles of optical flow and fluid dynamics. It enables the full spatiotemporal reconstruction of organized wavefront propagation within the otherwise chaotic and disorganized electrical conduction of AF. Given the novelty of EGF mapping and relative unfamiliarity of most clinical electrophysiologists with the mathematical principles powering the EGF algorithm, this paper provides an in-depth explanation of the technical/mathematical foundations of EGF mapping and demonstrates clinical applications of EGF mapping data and analyses. Starting with a 64-electrode basket catheter, unipolar EGMs are recorded and processed using an algorithm to visualize the electrographic flow and highlight the location of high prevalence AF "source" activity. The AF sources are agnostic to the specific mechanisms of source signal generation.
Volume
66
Issue
4
First Page
1015
Last Page
1028
Recommended Citation
Haines DE, Kong MH, Ruppersberg P, Haeusser P, Avitall B, Torok TS, et al Electrographic flow mapping for atrial fibrillation: theoretical basis and preliminary observations. J Interv Card Electrophysiol. 2023 Jun;66(4):1015-1028. doi: 10.1007/s10840-022-01308-8. PMID: 35969338.
DOI
10.1007/s10840-022-01308-8
ISSN
1572-8595
PubMed ID
35969338