Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation

Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent disease—require repeat procedures. Clinicians need more precise, patient‑specific maps of electrical substrates to improve first‑pass success. Researchers have now developed improved “digital twin” heart models that aim to guide more targeted treatment.

Led by Queen Mary University of London and published in The Journal of Physiology on June 16, 2026, the cross‑university study shows how patient‑specific computational models could support treatment planning for atrial fibrillation. Investigators built detailed three‑dimensional digital models for nine patients to simulate arrhythmia behavior and anticipate outcomes before ablation. The models are designed to localize arrhythmogenic circuits pre‑procedure and inform targeted lesion strategies.

Each model was calibrated three ways to test how input data shape target identification. One calibration used MRI scans that detect heart scarring. A second used electrical voltage measurements recorded during catheter mapping. A third used conduction velocity, defined as the speed of impulse propagation across atrial tissue. The team then compared how these inputs influenced identification of potential ablation targets in the same patients.

Electrical inputs—voltage and conduction speed—consistently identified more and different targets than imaging alone, indicating that models built only from magnetic resonance imaging may miss relevant pathways. The findings point toward a hybrid approach that integrates imaging with electroanatomic data as the most promising path to refine patient‑specific guidance for ablation. This framework lays the scientific groundwork for combined‑data calibration of personalized models.

The collaboration included Royal Brompton & Harefield Hospital (Guy’s and St Thomas’ National Health Service Foundation Trust), Imperial College London, King’s College London, the University of Leeds, and IHU Liryc (Bordeaux). Atrial fibrillation affects more than 1.5 million people in the United Kingdom, and repeat ablation is common in persistent cases because electrical changes are diffuse and difficult to map in a single procedure. The investigators note that personalized computer modeling remains in the research phase and is not part of routine clinical care.

“We found that MRI scans of the heart are valuable, but they don't tell the whole story. This study compared three types of clinical data, imaging and two types of electroanatomic mapping data, and found that each captures a different dimension of how atrial fibrillation behaves in an individual heart. Relying on any single source means missing part of the picture. Combining all three within a single personalized model is the most promising path toward more accurate, targeted ablation for persistent AF patients,” said Dr. Mahmoud Ehnesh, postdoctoral research assistant at Queen Mary University of London.

“If you have a persistent irregular heartbeat (Atrial Fibrillation) and are considering ablation, personalized computer modeling may one day help surgeons plan your procedure more precisely, but this technology is still in the research phase and not yet part of routine clinical care,” said Dr. Caroline Roney, reader in computational medicine at Queen Mary University of London.

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