Related Experiment Video
Updated: Sep 28, 2025
Non-fluoroscopic Catheter Tracking for Fluoroscopy Reduction in Interventional Electrophysiology
Published on: May 26, 2015
Atrial fibrillation mechanisms before and after pulmonary vein isolation characterized by noncontact charge density
Fang-Zhou Liu1, Junaid A B Zaman2, Ashkan Ehdaie3
1Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China; Cedars Sinai Smidt Heart Institute, Los Angeles, California.
Background:
The interaction of the pulmonary vein (PV) and putative nonpulmonary triggers of atrial fibrillation (AF) remains unclear and has yet to translate into patient-tailored ablation strategies.
Objective:
The purpose of this study was to use noncontact mapping to detail the global conduction patterns in paroxysmal and persistent AF and how they are modified during PV ablation.
Methods:
Forty patients during AF ablation underwent mapping using a noncontact catheter (AcQMap, Acutus Medical, Inc., Carlsbad, CA) before and after PV isolation (PVI). Propagation history maps were analyzed postprocedure for each patient to categorize conduction patterns into focal, organized reentrant, and disorganized patterns (F-Patterns, O-Patterns, and D-Patterns, respectively).
Results:
Activation patterns identified by using a noncontact mapping system can be subclassified from 3 main patterns into subtypes (macroreentrant and localized reentrant [MR and LR] subtypes and disorganized 1 and disorganized 2 [D1 and D2] subtypes). Persistent AF demonstrated more D-Patterns and less O-Patterns and F-Patterns than did paroxysmal AF. In addition, patients with PAF inducible after PVI demonstrated a higher region number and higher prevalence of MR subtypes than did those noninducible. PVs remained the critical region and included almost one-third of all patterns across any AF types. PVI was effective to eliminate PV-related functional phenotypes and affected recurrence with other patterns.
Conclusion:
Activation patterns identified using AcQMap can be classified into 3 main patterns (F-Patterns, O-Patterns, and D-Patterns) as well as subtypes (MR and LR subtypes and D1 and D2 subtypes). PerAF was different from PAF in demonstrating a higher region number and higher prevalence of D-Patterns but a lower region number and lower prevalence of O-Patterns and F-Patterns.
