Institution
University College London
Scientific title
Improving predictions of upper limb recovery after stroke with structural brain imaging
Principal Investigator
Dr Nick Ward
Region
Status
Active
Grant value
£141,813.00
Research ID
TSA 2017-04

Description of research

Stroke survivors and their relatives consistently ask for information about how much recovery can be expected. Healthcare professionals currently have few reliable data with which to make accurate predictions about the extent of a patient's recovery.

This can lead to uncertainty about what to expect from rehabilitation for stroke survivors, their families, and also for the clinicians treating the stroke survivor. Recent work tells us that those with a mildly or moderately affected upper limb at the time of stroke can expect to regain 70% of the function that was lost.

However, in those with a severely affected upper limb at the time of stroke the outlook is much more uncertain, with some doing well and others having little or no recovery. It is believed that the ability to predict the extent of upper limb recovery will dramatically improve by using information about the size and shape of brain damage that can now be obtain from routinely acquired brain scans.

A recent study was able to successfully predict differences in movement ability after stroke by applying modern mathematical tools to analyse whole brain imaging. This study will use the same approach with magnetic resonance brain imaging (MRI) recorded within 72-hours after stroke to test whether we can improve current predictions of upper limb outcome six months later.

Accuracy of predictions made with and without MRI data will be compared, with this approach re-tested in a separate group of stroke patients in order to check the findings.

Lastly, the meaning of these predictions will be conveyed to stroke survivors in terms of how much recovery can be expected for daily activities.

The ability to accurately predict functional outcomes after stroke will be useful for stroke survivors and their families, for planning rehabilitation but also for better design of clinical trials of rehabilitation treatments in future.

Project duration

24 months

Share