NTU's Fully-funded PhD Studentship Scheme 2023
Project ID: S&T22
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.
We hypothesise that the electric flow inside the heart is correlated with the events at the heart surface. Thus, AF must be correlated with the mechanical properties at the heart surface (e.g. pressure, shear stress). This research aims to explore these correlations. Towards this aim, the following directions are pursued in this research:
- acquire the velocity field signal near the heart surface from the direct measurements of electrical signals measured at the surface
- use this velocity field signal to reconstruct the entire electrical flow evolution with time inside the heart by solving the governing equations of fluid flow. Given the complexity of heart geometry, the promising approach of Neeteson and Rival2 is employed for flow reconstruction.
- find the potential correlation between the source of AF and fluid mechanical parameters (e.g. pressure, shear stress), and compare this new approach with the existing algorithms.
- use a Lagrangian particle tracking method to relate the events at the core of the heart chamber to those near the wall.
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.
1.Li X, et al. (2017). Computer methods and programs in biomedicine; 141:83-92.
2.Neeteson, N.J. and Rival, D.E. (2015). Experiments in Fluids, 56,1-13.
Dr Frederique Vanheusden
Dr Amirreza Rouhi
For the eligibility criteria, visit our studentship application page.
How to apply
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Fees and funding
This is part of NTU's 2023 fully-funded PhD Studentship Scheme.
Guidance and support
Application guidance can be found on our studentship application page.