Vascular Territory Map
Dynamic angiography above the circle of Willis
Combined angiography and perfusion imaging: angiographic reconstruction
Combined angiography and perfusion imaging: perfusion reconstruction
- Sir Henry Dale Fellow
- Head of Neurovascular Imaging
- WIN MRI Graduate Program Director
Now recruiting a Postdoctoral Researcher in Ultra-High Field MRI!
Please see here for more information.
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.
Time-encoded golden angle radial arterial spin labeling: simultaneous acquisition of angiography and perfusion data
van der Plas MCE. et al, (2021), NMR in Biomedicine
Single-dose effects of Citalopram on neural responses to affective stimuli in borderline personality disorder: A randomized clinical trial.
Paret C. et al, (2021), Biol Psychiatry Cogn Neurosci Neuroimaging
Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge.
Raman B. et al, (2021), EClinicalMedicine, 31
Study Protocol: The Heart and Brain Study.
Suri S. et al, (2021), Front Physiol, 12
Designing and comparing optimized pseudo-continuous Arterial Spin Labeling protocols for measurement of cerebral blood flow.
Woods JG. et al, (2020), Neuroimage, 223
A Frequency-Domain Machine Learning Method for Dual-Calibrated fMRI Mapping of Oxygen Extraction Fraction (OEF) and Cerebral Metabolic Rate of Oxygen Consumption (CMRO2)
Germuska M. et al, (2020), Frontiers in Artificial Intelligence, 3
Highly accelerated vessel-selective arterial spin labeling angiography using sparsity and smoothness constraints.
Schauman SS. et al, (2020), Magn Reson Med, 83, 892 - 905