Digital twin for atrial fibrillation: fundamentals, current advances, challenges and future perspectives

• Digital twins enable patient-specific virtual heart models for AF treatment • Personalized simulations optimize atrial fibrillation ablation procedures • Advances in biophysical modelling enhance precision in AF treatment • Digital twin technology could transform personalized cardiac care management Atrial fibrillation (AF) is a common arrhythmia that increases the risk of stroke, heart failure, and other cardiovascular complications due to blood clot formation. While catheter ablation is a key treatment, its effectiveness is often limited by patient-specific variations, leading to recurrence. Recent studies show increasing precision and adaptability in using digital twin technology for AF ablation. Digital twins create patient-specific virtual heart models based on anatomical and physiological data, offering a promising approach for personalized ablation simulations. This review examines the role of digital twin technology in AF ablation, focusing on its foundational principles, recent advancements, and potential future directions. We critically assessed key components of digital twin models, including biophysical modeling and personalized data acquisition, highlighting their contributions to more precise and tailored treatment strategies. However, challenges remain, such as improving model accuracy, overcoming limited data availability, and developing regulatory frameworks for safe and effective clinical implementation. Addressing these challenges could lead to a transformative shift in the personalized management of AF, with broader implications for cardiac care.