Digital heart twins could improve atrial fibrillation treatment planning

The study found that the accuracy of these personalised models depends critically on the type of clinical data used to build them.

The team constructed detailed 3D digital heart models for nine patients and calibrated each model in three separate ways: using MRI scans that detect heart scarring, using electrical voltage measurements recorded during a cardiac mapping procedure, and using conduction velocity, a measure of how quickly the heart's electrical signal travels across different tissue regions.

Critically, electrical data, both voltage and conduction speed, consistently identified more and different targets than MRI data, suggesting that models relying solely on imaging may be working with an incomplete picture.

The findings point clearly toward combining all three data types within a single hybrid model as the most promising path forward and lay the scientific foundation for doing so.

Senior author Dr Caroline Roney, Reader in Computational Medicine at Queen Mary University of London, said: "If you have a persistent irregular heartbeat (Atrial Fibrillation) and are considering ablation, personalised computer modelling 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."

The team working on Comparative Multimodal Calibration of Patient-Specific Atrial Fibrillation models included researchers at Queen Mary University of London, Royal Brompton & Harefield Hospital (Guy's and St Thomas' NHS Foundation Trust), Imperial College London, King's College London, the University of Leeds, and IHU Liryc (Bordeaux).

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Queen Mary University of London

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