Moving toward digital twins for precision cardiac electrophysiology: overcoming technical and clinical challenges

Precision cardiac electrophysiology seeks to provide healthcare strategies tailored to the individual patient. The concept of digital twins is fundamental to this approach. Digital twins in cardiac electrophysiology are personalized computer models that replicate the electrical activity of patients' hearts. By integrating patient-specific data with mechanistic simulations, they can predict disease risk and help optimize therapy planning.

This narrative review summarizes the state-of-the-art of cardiac digital twins, including advances in anatomical and functional twinning, as well as illustrative case studies. It then discusses key technical/clinical challenges, focusing on model development, data recording and integration, and pathways toward clinical implementation.

Fueled by growing data availability and advances in computational power, the vision of cardiac digital twins is moving from theoretical concept to potential clinical reality. For instance, digital twins could guide ablation in patients with persistent atrial fibrillation by identifying potential targets through computer simulations. However, given the potentially substantial costs, identifying patient groups and clinical applications in which digital twins provide the greatest value is essential. In parallel, artificial intelligence-based precision medicine may offer a more cost-effective and efficient alternative for certain scenarios, while digital twins likely remain most valuable when mechanistic insight is required.