###Optimising MRI Quantitative Conductivity Mapping of the Brain for Large Clinical Studies of Disease
Project ID: 2228bd1056 (You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Medical Physics and Biomedical Engineering
Lead Supervisor: Karin Shmueli
Project Summary:
Magnetic resonance imaging (MRI) quantitative conductivity mapping (QCM) is a recently developed technique that reveals changes in ion concentration and blood oxygenation and could give new insights into the pathological processes underlying several neurological diseases. Although QCM shows promise for brain tumours, it has not yet been applied in many clinical research studies. Therefore, it is important to optimise QCM techniques so that conductivity maps can be calculated to provide new understanding in large MRI studies of people with brain diseases.
You will be supervised by Professor Karin Shmueli, an internationally recognised expert in MRI physics and a pioneer of quantitative magnetic susceptibility mapping. Prof. Shmueli has successfully supervised 6 doctoral students and leads a group of 9 researchers with a collaborative programme involving UK and international scientists and clinicians. Your subsidiary supervisor will be Dr Rimona Weil, Wellcome senior fellow and consultant neurologist, leading the Vision in Parkinson’s disease group using advanced neuroimaging techniques to track disease severity in Parkinson’s.
You will be optimising MRI QCM processing pipelines we have developed to calculate brain conductivity maps in several large MRI studies including a longitudinal birth cohort study of healthy ageing and dementia (~500 subjects), a Tanzanian study at 1.5 Tesla in ~200 young people with sickle cell anaemia (and 40 healthy controls), a Parkinson’s study of 100 patients (and 35 controls), and a study of 36 people with temporal lobe epilepsy (and 27 controls). You will overcome challenges such as noisy input images by testing new noise removal techniques.
We are looking for someone who is excited to learn MRI conductivity mapping. You will enjoy applying physical and mathematical principles and implementing computation for image processing to solve practical problems and yield new information to help us understand the biophysical processes underlying ageing, and a range of brain diseases.