Medical Research Project

3D heart modelling for personalised ablation

The development of a new AI-supported model for imaging the heart based on data from over 700 people with atrial fibrillation, allow ablation to be more personalised to individual patients.

In progress
19/06/2025
Atrial fibrillation
West Midlands
Awarded amount: £189,096
Grant scheme: NET
Institution: Oxford University Hospitals NHS Foundation Trust
Principle Investigator: Professor Timothy Betts

Atrial fibrillation (AF) is the most common heart rhythm problem in adults. It occurs when abnormal electrical activity in the heart’s upper chambers (the atriums) causes the heart to beat irregularly. This irregular rhythm makes the heart beat less efficiently and increases the risk of stroke, heart failure, and death.

One of the main treatments for AF is catheter ablation, which involves inserting thin, flexible tubes into the heart to apply either heat or cold energy to specific areas of the atriums. This creates scarring that blocks the abnormal electrical signals, helping to restore a regular heart rhythm. However, for many patients, especially those with persistent AF, where irregular rhythms last more than seven days, a single ablation procedure is not enough. In these cases, atrial remodelling (structural changes in the atriums) makes the condition harder to treat, and multiple procedures may be needed. To address this, Professor Tim Betts (Principal Investigator and Clinical Lead), Dr Abhirup Banerjee (Technical Lead), and Dr Alexander Sharp (Clinical Research Fellow and DPhil Student) are developing a novel method for modelling changes in the atriums of people with AF. Their computer-generated models will use data from over 700 individuals who have undergone catheter ablation and will follow three stages to analyse changes in atrial structure and function. The first step is the creation of a 3D model of the atrium, to study how remodelling affects atrium shape in AF patients. The second step is combining the electrical activity of the heart with these models, to understand the relationship between shape and function. Finally, the team will develop an AI-supported computer programme that will enable doctors to use this data to personalise and improve ablation treatments. These models will also be made available to researchers around the world to enable further advancement in AF research.

The goal of this project is to understand more about how AF changes the atrium over time, and why certain people may have better results from ablation than others. This will allow for better, more personalised, treatment options for patients going forward – not only for those who have already undergone catheter ablation, but also for those who have been newly diagnosed. This will lead to fewer people undergoing repeat ablations and allow more people with AF to benefit from the procedure, improving quality of life and decreasing the risk of serious AF complications.

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