Development and implementation of high-resolution imaging techniques and post-processing methods for hyperpolarised magnetic resonance imaging
LEAD SUPERVISOR: Prof Fergus Gleeson, Department of Oncology
Co-supervisors: Prof Damian Tyler, Oxford Centre for Magnetic Resonance Research and Dr James Grist, Department of Physiology, Anatomy, and Genetics
Commercial partner: GE Healthcare, Chalfont St Giles
Hyperpolarised magnetic resonance imaging (HMRI) is a powerful clinical tool enabling non-invasive imaging and physiology quantification of disease that is not possible with other imaging techniques. Using HMRI, we are working towards the MRC strategic priority of early disease detection, exploring the otherwise invisible damage in the lungs of patients post-COVID-19 and the metabolic alterations associated with neurological diseases such as Multiple Sclerosis, as well as enabling precision medicine, through the identification of early treatment response to new therapies in patients with diabetic cardiac disease.
One of the major hurdles to the clinical adoption of HMRI is the need for faster and higher resolution imaging acquisitions, and more reliable post-processing methods for image interpretation and analysis. Accelerated acquisition methods will enable the acquisition of imaging data from patients that struggle with holding their breath, which is required for some hyperpolarised imaging. Higher spatial resolution imaging will help localise disease more accurately within the body, improving its correlation with conventional MRI and CT.
We have worked with GE Healthcare for several years to develop the software and hardware required for hyperpolarised imaging, in particular Dr Rolf Schulte, who has provided a very flexible software package ‘fidall’ used world-wide for the acquisition and post-processing of hyperpolarised imaging data. We have recently upgraded the MRI systems at Oxford to 2 state-of-the-art GE Premier MRI scanners, ideally suited for further development and application of hyperpolarised imaging. The student will be given time to travel to Munich to work alongside Dr Schulte, learning both technical programming skills (required for the in-depth knowledge of MRI system operation needed in this project) and gaining insight into industrial practice. Combining the clinical expertise of Professors Tyler and Gleeson with the in-depth technical knowledge of Dr Schulte, this project provides a perfect combination of skills to continue to develop this exciting clinical technology.
The application of the methods that will be developed by the student will be for both Idiopathic Pulmonary Fibrosis and Multiple Sclerosis. These diseases are common, detectable in an early clinical phase, with a significant morbidity and mortality. We have funding and ethics to assess the early response of these diseases to therapy in a cohort of patients with hyperpolarised imaging. The final focus of this project will be to ensure that all methods are clinically useable, enabling the incorporation of our technologies into clinical workflow, by running all reconstruction and processing on the MRI scanner and ensuring images are ready for radiological interpretation and quantification on conventional hospital DICOM viewers.
The aims of the project are:
1) Work with both Oxford University and GE Healthcare to develop novel MRI acquisition methods using k-space under-sampling to speed up current imaging approaches.
2) Develop novel model-free and model-based post-processing methods for the accurate quantification of healthy metabolism and lung function, and changes in pathology before and acutely after therapy in Idiopathic Pulmonary Fibrosis and Multiple Sclerosis.
3) Ensure all methods are clinically useful through the implementation of on-system reconstruction and processing for radiological interpretation and quantification.
Apply using course: DPhil in Oncology