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We are currently advertising for two funded DPhil (PhD) positions, in collaboration with Peter Jezzard, Mark Chiew and Siemens Healthcare! Please do get in touch if you are interested:

Highly Accelerated Magnetic Resonance Angiography using Deep Learning

Development of Methods to Assess Intracranial Vessel Stiffness as a Measure of Vascular Disease

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My research focusses on the development of novel non-invasive MRI methods which visualise blood flowing through the arteries that feed the brain and the resulting perfusion of the brain tissue. Much of my initial research focussed on developing techniques which allow blood from individual feeding arteries to be followed through the vascular tree. In addition to providing information about the structural and functional status of each artery, these methods allow the assessment of "collateral blood flow". This is when the main feeding artery to a certain brain region becomes blocked or significantly narrowed, but the flow of blood from secondary arteries maintains perfusion in this brain region, preventing a significant stroke. The presence or absence of collateral flow can be important in deciding between potential treatment options in patients with arterial disease. These vessel-selective strategies also have applications in diseases where the arterial source of blood flow is important, such as tumours and arteriovenous malformations.

In my previous five year research fellowship from the Royal Academy of Engineering, I aimed to address one of the key downsides to these imaging techniques, which is that obtaining 3D time-resolved images of the arteries as well as maps of tissue perfusion is time-consuming, and therefore difficult to apply in a clinical setting. I designed a single scan which can track the flow of blood through the arteries, all the way into the tissue, thereby providing both sets of information at the same time. I used recently developed acquisition and image reconstruction methods to accelerate this process, allowing images to be acquired in a fraction of the time normally required.

I have recently been awarded a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society, to develop new brain blood flow imaging methods using a powerful ultra-high field MRI scanner. There are a series of technical challenges to overcome to make these methods efficient and robust, but once these have been overcome, highly sensitive measurements of brain blood flow will be possible. I plan to use this improved sensitivity to obtain very high spatial and temporal resolution information, as well as examine blood flow to the white matter of the brain, which is extremely challenging using conventional scanners, but has relevance to a broad range of conditions, including dementia.

I will continue to trial existing techniques and new methods, as they emerge, in collaboration with clinical colleagues in a range of patient groups, including those with stroke, arteriovenous malformation and vascular cognitive impairment. I hope that this will show the potential utility of these techniques for understanding the progression of these diseases, and in the longer term help with diagnosis, prognosis and therapeutic planning in these patients.