PhD Studentship: CFD Study of Novel Fistula Health Monitoring for Dialysis Patients

Supervisors: Dr Yongmann Chung, Dr Bjorn Stinner, Professor Charles Hutchinson (WMS)

Start date: 03 April 2023

Duration: 3.5 years

The project:

To administer dialysis, arteriovenous (AV) fistulae are made as a passage through which blood can flow out to be filtered, and clean blood can be passed back to the patients. With an average lifespan of 5 years, ultimately, all AV fistulae will fail. This can cause disruption to dialysis and requires an operation to create a new AV fistula. These can cause anxiety and physical and mental stress on the dialysis patient. This project aims to develop a new health monitoring system involving ultrasound imaging of AV fistula to ensure they are still functioning optimally. This ultrasound scan will be done on dialysis patients in Royal Berkshire Hospital during their regular dialysis visits. In addition to ultrasound scanning, we will create a 3D fistula imaging model for each patient to better understand the dynamics of blood flow in the AV fistula. This research will help detect signs of fistula failure before it happens so that early interventions can be made to prolong fistula function. This can significantly ease the physical and emotional burden on dialysis patients and improve the outcome of fistula dialysis.

This project is sponsored by Kidney Research UK with Dr Yongmann Chung, and his interdisciplinary team (Dr Bjorn Stinner at Mathematics, Professor Charles Hutchinson at Warwick Medical School and Dr Farhan Ahmed at Royal Berkshire Hospital). This collaboration project will involve working with dialysis patients and will use an ultrasound machine to scan the patient's fistulae during their regular hospital visits. The use of ultrasound scanning is safe, cost effective and has low risk in relation to the frequency to which scans will be done. Based on ultrasound imaging, we will use Computational Fluid Dynamics (CFD) to better understand the dynamics of the way blood flows in the AV fistula. Through ultrasound scanning, a 3D fistula imaging model for each individual patient will be created and used for CFD study. This is hoped to help to explain the potential success or failure of fistula function and show early signs of fistula failure.

For further information, please email Y.M.Chung@warwick.ac.uk

Eligibility:

Candidates must have a 1st or 2.1 honours degree in Engineering. Prior experience with CFD, machine learning, and medical imaging will be particularly useful but not essential.

Funding:

The award will cover tuition fees at the UK fee level, plus a tax-free stipend of £17,668.00 per annum for 3.5 years of full-time study. International students are welcome to apply but must meet the fee difference themselves.

How to apply:

Candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area to www.warwick.ac.uk/engpgr/ymc1/appcv/. If this initial application is successful, we will invite you to make a formal application for study. All candidates must fulfil the University of Warwick entry criteria and obtain an unconditional offer before commencing enrolment.

Advert information