Fractionated Atrial Electrograms Identify Sites of Autonomic Responses During Pulmonary Vein Isolation: Insights for Cardioneuroablation

Abstract

Background

Cardioneuroablation (CNA) targets atrial ganglionated plexuses (GP) to treat vagally mediated bradyarrhythmias. Automated electrogram fractionation mapping has been proposed as a surrogate tool for GP localization, but optimal parameter settings remain undefined. We aimed to systematically evaluate automated fractionation mapping parameters and their association with autonomic responses during ablation.

Methods

Data from 26 patients were analyzed, including 12 patients undergoing atrial fibrillation (AF) ablation in sinus rhythm and 14 patients undergoing CNA. Using high-density electroanatomical mapping, three predefined values were tested for each fractionation parameter—signal width, refractoriness, and amplitude threshold—yielding 27 automated configurations. A purely anatomical localization strategy was also evaluated. In the AF cohort, all configurations were systematically assessed, generating 336 fractionation maps and 870 ablation sites. Autonomic response during radiofrequency delivery was defined as an absolute RR interval change > 10%. Selected high-performing configurations were subsequently evaluated in the CNA cohort (614 ablation sites).

Results

In the AF cohort, 25 of 27 configurations showed a significant association with autonomic response. After Bonferroni correction, 15 configurations remained significant. The configuration with signal width 15 ms, refractoriness 25 ms, and amplitude threshold 0.05 mV demonstrated the highest sensitivity, although several configurations showed comparable performance. When evaluated in the CNA cohort, this configuration yielded a sensitivity of 74.1% and specificity of 73.9%.

Conclusions

This pilot study provides a reproducible framework for evaluating automated fractionation mapping parameters associated with autonomic responses during CNA. The findings support biologically plausible parameter–performance relationships and identify parameter ranges potentially suitable for procedural use.