Virtual Heart-Based Prediction of Ablation Outcomes in Persistent Atrial Fibrillation Based on Non-Pulmonary Vein Drivers.

Background

Clinical outcomes of driver-targeted ablation in persistent atrial fibrillation (AF) have been inconsistent, underscoring the need for virtual heart-based approaches to characterize AF driver dynamics and guide ablation strategies. We used virtual heart models from a large persistent AF cohort to define electrophysiological features of extra-pulmonary vein drivers associated with rhythm outcomes after AF ablation.

Methods

We analyzed left atrial virtual heart models integrating cardiac computed tomography and electroanatomical maps in 165 patients with persistent AF from the CUVIA-AF2 study (Clinical Usefulness of Virtual Ablation Guided Catheter Ablation of Atrial Fibrillation 2). During a 34-second virtual AF simulation, stable phase singularities (PSs) were identified by PS lasting ≥2 s within a 10-mm diameter. Dominant frequency (DF) was assessed over 3 consecutive 6-second intervals to evaluate temporal stability. The maximal slope of the action potential duration restitution curve was derived via virtual ramp pacing (200-120 ms). All markers were evaluated across 6 extra-pulmonary vein regions. Associations among stable PS, DF, maximal slope of the action potential duration restitution curve, low-voltage area (<0.5 mV), and 1-year rhythm outcomes were analyzed.

Results

Stable PS at extra-pulmonary vein regions was observed in 124 (75%) patients; of these, 43 (34.7%) showed stable DF, and 81 (65.3%) had meandering DF. In regional analysis of the virtual heart models, areas containing stable PS with stable DF showed a higher maximal slope of the action potential duration restitution curve (1.41±0.80 versus 1.09±0.60; P<0.001) and greater local virtual low-voltage burden (2.96±3.23% versus 2.10±2.75%) than regions with stable PS with meandering DF. Stable PS with stable DF correlated with higher AF recurrence at 1-year follow-up (log-rank P=0.002; adjusted hazard ratio, 5.78 [95% CI, 2.18-15.3]). A predictive model including stable PS and DF showed an apparent area under the curve of 0.765 for recurrence prediction.

Conclusions

Stable PS with stable DF identified in virtual heart models was associated with adverse model-derived regional substrate features and higher recurrence rates after ablation. Virtual heart-based identification of these markers may improve prediction of ablation response in persistent AF, warranting prospective validation.