ArticleJournal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing2025
AI-guided spatiotemporal dispersion mapping for individualized ablation in an all-comer cohort with atrial fibrillation.
Article in Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Artificial intelligence-guided pulsed field ablation for persistent atrial fibrillation: automated peak frequency mapping predicts termination sites and durable rhythm control.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2026Article
- Automatic Localization of Stable Highest Dominant Frequency Area in AF Patients Based on Spatial Aggregation.Bioengineering (Basel, Switzerland) · 2026Article
- Targeting the Substrate: Mechanism-Based Ablation Strategies for Persistent Atrial Fibrillation.Journal of clinical medicine · 2025Review
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12 authors.
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Abstract
backgroundArtificial intelligence (AI)-guided spatiotemporal dispersion (stD) mapping has been shown to improve outcomes in patients with persistent atrial fibrillation (AF). However, the relationship between stD mapping and markers of atrial cardiomyopathy, dispersion patterns in paroxysmal versus persistent AF, stability of dispersion regions, and stD-guided ablation-related outcomes in all-comer cohorts remain elusive.
methodsIn this retrospective single-center analysis, AF patients underwent high-density electroanatomical mapping alongside multiple instances of stD mapping using VOLTA AF Explorer software. Pulmonary vein isolation (PVI) and targeted ablation of left atrial dispersion regions were performed. Clinical, echocardiographic, biomarker, and low-voltage area (LVA) data were collected as markers of left atrial remodeling.
resultsstD mapping identified dispersion in 92% of patients. Mean time since AF diagnosis was 7 ± 1 years. Overall, 58% of patients showed dispersion exclusively co-localizing with low-voltage areas, while 42% had dispersion extending into intermediate or normal voltage regions. Dispersion burden correlated strongly with LVA extent and other remodeling markers such as NT-proBNP and LAVI. Persistent AF patients exhibited a significantly higher number of dispersion sites compared to paroxysmal AF. Dispersion patterns remained largely consistent before and after cardioversion in persistent AF, with the posterior left atrial wall emerging as a common hotspot. At follow-up, AF recurred in 33% of paroxysmal and 60% of persistent AF patients who had dispersion ablation limited to the left atrium. Despite these recurrences, most patients reported an improvement in symptomatic burden.
conclusionAI-guided stD mapping effectively identifies atrial remodeling beyond classical voltage-derived substrate, supporting its potential as a useful adjunctive tool in AF characterization.
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