Key result
Digital twins provide a framework to personalize persistent AF ablation, but clinical outcomes remain unproven.
Why the study?
Catheter ablation for persistent atrial fibrillation often yields suboptimal outcomes due to empirical lesion sets that fail to address patient-specific remodeling and limitations in current mapping systems to simulate wavefront propagation or predict recurrence.
Does a personalized ablation strategy using digital twins reduce recurrence in patients undergoing catheter ablation for persistent atrial fibrillation?
Does a personalized ablation strategy using digital twins reduce recurrence in patients undergoing catheter ablation for persistent atrial fibrillation?
Digital twins are proposed to personalize ablation strategies and address suboptimal outcomes in persistent atrial fibrillation, though no study data is provided in the truncated abstract.
Answers are grounded in this paper and cite their sources.
Current mapping systems limit dynamic simulation in PeAF ablation; leaves open whether advanced modeling improves recurrence prediction.
Catheter ablation for persistent atrial fibrillation (PeAF) often yields suboptimal outcomes, likely because of relatively empirical ablation lesion sets which often fail to address patient-specific structural and electrical remodeling. Current electroanatomical mapping systems provide high-fidelity imaging data, but still have the limitations to simulate dynamic wavefront propagation or prediction of recurrence after catheter ablation.
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Khanolkar et al. (2026) studied Persistent atrial fibrillation. Personalized ablation strategy using digital twins was evaluated. The provided abstract outlines the rationale for using digital twins to personalize catheter ablation for persistent atrial fibrillation, but reports no clinical data, outcomes, or pilot results.
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