###Model-based reconstruction of arterial spin labelled MRI for improved measurement of cerebral perfusion in neurological disease
Project ID: 2228bd1223 (You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Queen Square Institute of Neurology
Lead Supervisor: Healthcare Technologies
Project Summary:
Advanced neuroimaging methods provide a unique opportunity to develop completely non-invasive early biomarkers of neurodegeneration, which directly inform clinical diagnosis, treatment approaches and trials of new therapies. In this project, we will combine optimised acquisition techniques with physics-based image reconstruction and machine learning approaches, to develop a novel MR method for quantitative whole brain mapping of cerebral blood flow (CBF), a physiological parameter known to change in a region-specific manner in various neurological diseases. Existing methods suffer from poor SNR, sensitivity to patient motion, and inaccuracies caused by disrupted cerebral haemodynamics. We will tackle these problems by: i. Introducing robust undersampled acquisition techniques, able to capture whole brain images rapidly in a single snapshot (~ a few hundred ms) ii. Developing a model-based image reconstruction framework to combine a series of snapshot imaging volumes acquired with different scanning parameters, leveraging the known complementarity of the undersampled data and enabling direct estimation of CBF and other key haemodynamic parameters.
This work will provide a step change for physiological MR of the brain, and fits within our broader research scope of developing imaging and biofluid based disease biomarkers, which can be used synergistically to significantly improve our ability to treat neurological disorders.