Developing a computational tool to predict the optimal location for arterio-venous fistula (AVF) creation in end stage renal failure and haemodialysis patients
Self-funded PhD students only
School of Mechanical and Design Engineering
Applications accepted all year round
The work on this project will:
- be a joint collaboration between the Cardiovascular Engineering Research Laboratory (CERL) based at the School of Mechanical and Design Engineering, and the Vascular Assessment Unit at the Queen Alexandra Hospital (Portsmouth Hospitals NHS Trust)
Each year, around 5,400 new patients with kidney failure receive haemodialysis treatment across England, Wales and Northern Ireland NHS Trusts. For an effective filtration, haemodialysis machines require access to the patient’s blood supply in large flow volumes.
Since neither arteries nor veins on their own can provide the required blood flow rate (typically >600 ml/min), a connection between a vein and an artery is surgically created in patients prior to starting haemodialysis. This connection is called an an Arterio-Venous Fistula (AVF). The AVF is then used as the access point between the patient’s blood stream and the haemodialysis machine.
Currently, a consultant surgeon mainly relies on their experience to create the AVF at a site that they believe will result in the required flow rate. However, according to the UK Renal Registry latest annual report (2016), on average only 27.8% of patients successfully start their haemodialysis treatment with an AVF. Clinical assessment alone does not reliably predict which location in patients’ vasculature will result in a successful first time creation of an AVF, and this is the problem which our research project aims to address.
The principal aim of this project is to demonstrate proof of concept for a predictive computational tool to inform the surgeon of the optimal location for creating an AVF in end stage renal failure and haemodialysis patients. The computer model will use the clinical scans of the patients’ lower and upper arm vasculature as input, and will simulate the blood flow in AVFs at different locations along the arm vasculature over the scanned area in silico.
Based on these simulations, the optimal AVF site which produces the maximum flow-rate will be established. To calibrate and validate the modelling outcome, an in vitro setup of the patient’s local vasculature will be developed, using a Harvard Apparatus® Series 1400 Pulsatile Blood Pump, commercially available silicon or 3D printed extensible tubes to mimic the arteries/veins and water as the working fluid, where an AVF will be created and placed in the setup at the position predicted by the model. The AVF output flow rate measured by the experimental setup will then be compared with the model as a primary means of validation.
This project will be a joint collaboration between the Cardiovascular Engineering Research Laboratory (CERL) based at the School of Mechanical and Design Engineering, and the Vascular Assessment Unit at the Queen Alexandra Hospital (Portsmouth Hospitals NHS Trust). Patient specific data will be provided by the QA Hospital, and the model predictions will be fed-back to their consultants. As a secondary means of validation, the model outputs will be compared against the independent assessment of the surgeons, and in cases of mismatch, additional calibration methods will be devised.
- You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in Medical Engineering, Mechanical Engineering or a similar discipline.
- In exceptional cases, we may consider equivalent professional experience and/or Qualifications.
- English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
We’d welcome applications from candidates with knowledge of a CAD software, MATLAB programming, and prior experience with fluidics experimental setups.
How to apply
We’d encourage you to contact Dr Afshin Anssari-Benam (firstname.lastname@example.org) or Dr Andrea Bucchi (email@example.com) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, you can use our online application form and select ‘Mechanical and Design Engineering’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.
Our ‘How to Apply’ page offers further guidance on the PhD application process.
Please note: to be considered for this self-funded PhD opportunity you must quote project code ENGN4670219 UK/EU students and ENGN4850219 International students when applying.