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

Переход к цифровым двойникам для прецизионной сердечной электрофизиологии: преодоление технических и клинических проблем
Melania Buonocunto, Alexander Jung, Stefan Meier, Jordi Heijman
2026-05-04

ablation planningcardiac digital twinsmechanistic simulationspersistent atrial fibrillationprecision cardiac electrophysiology
INTRODUCTION: 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. AREAS COVERED: 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. EXPERT OPINION: 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.
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Artificial intelligence may be more cost-effective for some precision-medicine applications, whereas digital twins are likely most valuable when mechanistic insight is required.
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Cardiac digital twins are personalized computational models integrating patient-specific data with mechanistic simulations to replicate electrical heart activity.
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Digital twins can potentially predict disease risk and optimize therapy planning, including identifying ablation targets for persistent atrial fibrillation.
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Major barriers include model development, patient-data recording and integration, clinical validation, implementation pathways, and potentially substantial costs.
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Progress in anatomical and functional twinning, data availability, and computational power is moving cardiac digital twins toward possible clinical implementation.

personalized cardiac digital twins—patient-specific computer models of the electrical activity of individual hearts

their technical and clinical development, integration of patient-specific data with mechanistic simulations, and clinical value for precision electrophysiology and therapy planning

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2026-05-04
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Melania Buonocunto
Alexander Jung
Stefan Meier
Jordi Heijman
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