Atrial fibrillation (AF) is the most common cardiac arrhythmia globally, affecting about 2.5% of the UK population. AF increases risk of heart failure, dementia and reduces quality-of-life. Moreover, AF patients are 5 times more likely to suffer from stroke, with 20% of AF-related strokes being fatal and another 60% leading to disability. Optimised AF treatment is therefore vital to reduce AF’s burden on the NHS and improve AF patients’ quality-of-life.
One approach for treating AF is catheter ablation. In this procedure, a catheter is positioned inside the heart to map the heart’s electrical activity, identify and ablate AF sources. Many algorithms for identifying these sources have been suggested1. These algorithms focus on detecting locations of highest heart rate or rotational cardiac activity. Success rates based on these algorithms remain at about 50%, hence the need to develop better AF source identification algorithms.
This project will develop new ways to identify AF sources based on technologies and algorithms currently used in (air) flow analysis2 and pressure fields derived from flow analysis, similar to those used for early detection of storm and tornadoes. It aims to
- develop an optimised algorithm for cardiac electrical flow analysis.
- find the potential correlation between the source of AF and fluid mechanical parameters. For this, we use the data from the heart electrical flow to reconstruct the entire electrical flow evolution with time inside the heart. The reconstruction is based on solving the governing equations of fluid flow.
- assess physiological parameters (pressure, shear stress) in personalising AF source identification to improve therapy.
- develop a Lagrangian tracking method to investigate how electrical activity at the core of the heart chamber correlates with near-wall activity, identifying the causes of chaos (storms) occurring within the heart’s electrical signal.
The project will involve programming and testing these algorithms on electrocardiogram (ECG) data. In addition, you will be conducting ECG experiments with human participants: recording and analysing heart activity. The project would suit a student with a degree in physics, engineering, or computer sciences with a good background in mathematics. You should also be interested in learning about heart rhythm diseases and heart electrophysiology.
References
1. Li X, et al. (2017). An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping. Computer methods and programs in biomedicine; 141:83-92.
2. Rouhi A, et al. (2021). Coriolis effect on centrifugal buoyancy-driven convection in a thin cylindrical shell. Journal of Fluid Mechanics; 910.
Supervisory Team:
Dr Frederique Vanheusden
Dr Amirezza Rouhi
How to apply
Please visit our how to apply page for a step-by-step guide and make an application and include the project ID in your application
Application deadline: Thursday 8 June 2023.
Interviews will take place in mid-June 2023
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