Personal tools

You are here: Home / Research / Biomedical Measurement & Modelling / PUMMA / Stroke


Stroke is one of the most pressing clinical problems today. Stroke is the third biggest killer in the UK and the leading cause of disability, yet resources for stroke research and treatment are only a fraction of those for heart disease. There is now a greater realisation that more needs to be done to improve stroke outcome, but diagnosing the type and severity of stroke and initiating treatment within a few hours is an enormous clinical (and Engineering) challenge. A new Acute Vascular Imaging Centre (OxAVIC) has recently opened at the John Radcliffe Hospital in Oxford, where patients will be seen as soon as possible following stroke.

We work very closely with clinical colleagues at OxAVIC within the Nuffield Department of Medicine and imaging colleagues at the FMRIB centre. Interpreting clinical data, designing new clinical measurements and trying to help to predict outcome are the key components of our work. For example, non-invasive measurement of cerebral blood flow depends upon the use of Arterial Spin Labelling (ASL) together with accurate models and analysis. We are currently working on pH imaging in MRI, which will shortly be used in acute stroke patients for the first time to see whether this is helpful in predicting outcome. We are also constructing a detailed model of stroke, based on imaging data, to help to predict tissue response to stroke and hence to help clinicians in making decisions about what treatment to adopt for individual stroke patients.

One of the most important features of this is the microvasculature (all the millions of tiny vessels). Understanding how these vessels connect and thus supply oxygen, particularly when the supply is interrupted or reduced, is very important. Only very recently has the experimental data become available, so we have started to model this part of the brain's anatomy. This kind of discrete model governs the tissue behaviour at a very small scale, but understanding how this scales up in terms of both flow and metabolism to regions of brain tissue is highly complex. However, by relating this to clinical data opens up the possibility of gaining valuable clinical information about this part of the brain for the first time.