Development of measurements of subtle blood-brain barrier damage in MS

Now closed

Primary supervisor: Prof Geoff JM Parker
Secondary supervisors: Prof Claudia Wheeler-Kingshott, Prof Olga Ciccarelli

Project summary
A 4-year PhD studentship is available in the UCL Centre for Medical Image Computing, working closely with the Neuroinflammation Department at UCL’s Institute of Neurology. The funding covers an annual tax free stipend (£17009) and tuition fees. 
As the studentship is partially funded by the EPSRC the standard EPSRC eligibility criteria apply, please see EPSRC website for further details. The successful candidate will join the UCL CDT in Medical Imaging cohort and benefit from the activities and events organised by the centre.

Background
Multiple sclerosis (MS) is a progressive disease that causes severe damage to the central nervous system and disability. MS is characterised by inflammation, which causes damage to the blood brain barrier (BBB), which in normal circumstances serves to protect the brain from potential toxins and pathogens in the blood. Detection of subtle BBB disruption may therefore provide an early sign of acute attacks or provide insight into the mechanism of slow progression of the condition. Recent work has shown the MRI measurements of water exchange across the BBB provides a quantitative tool to detect subtle BBB damage and that these measurements may be more sensitive than previously proposed approaches.

Research Aims
This project will investigate new approaches to detecting subtle BBB damage using MRI. The student will develop optimised MRI acquisition protocols to detect water exchange, using the 3 T MRI scanner based at UCL’s Institute of Neurology, drawing on methods including relaxometry, diffusion MRI, arterial spin labelling and dynamic contrast-enhanced MRI. Computational models of the evolution of the MRI signal will be developed to extract quantitative estimates of the permeability of the BBB to water. The novel methods developed during this project will be evaluated for suitability for potential future inclusion in clinical trials in MS, and may ultimately help to inform and improve future treatments for MS patients.

Requirements
Applicants are expected to have a first degree in Physics, Computer Science or Biomedical Engineering or relevant Physical Sciences based subject passed at 2:1 level (UK system or equivalent) or above. 
Good working knowledge of C++ and/or Python and/or MATLAB is desirable. Some experience with medical imaging is also desirable.

To Apply: Please send a CV and Covering Letter expressing your interest to Professor Geoffrey Parker ucacgp1@ucl.ac.uk

APPLICATION CLOSING DATE: 31 July 2019