Scientists have created a computer program said to predict the chances of brain cells dying as the result of a stroke. The program may allow doctors to refine the use of brain saving stroke drugs.
The computer software, which uses artificial intelligence techniques, rapidly combines several new types of images obtained by magnetic resonance imaging (MRI) into a map of the brain allowing physicians to assess the risk of brain damage with high specificity and sensitivity.
‘That is a major accomplishment because previously it took 20 to 30 minutes to pour through all the MRI data and determine what it all meant,’ said A. Gregory Sorensen, M.D., senior author of the report, associate professor of radiology at Harvard Medical School and associate director of the nuclear magnetic resonance centre at Massachusetts General Hospital.
Currently, standard computerised tomographic (CT) scans use X-rays to generate an image of the brain to determine whether leaking or ruptured blood vessels caused a stroke.
If the CT scan is negative for a hemorrhagic stroke, it is likely that it has been caused by an obstructed blood vessel (ischemic). Blood clots can be dissolved by a tissue plasminogen activator (tPA) but the drug is only recommended for use within three hours of a stroke occurring.
‘All neurologists struggle with the fact that they have these guidelines for groups of patients, but they are faced with treating a single patient,’ said Sorensen. ‘They want to know how they can adapt general guidelines to the specific patient in front of them.’
That is precisely what the computer program is meant to do. ‘Instead of having people wade through five or eight different MRI images, we simplified this into a single risk image,’ he said.
The computer breaks the advanced MRI brain scan into distinct cubes that are about one-tenth of an inch in diameter. Two key pieces of information are measured for each cube.
One tells whether blood flow through vessels in the area is blocked. The other indicates whether the brain tissue is living or dying. Both these types of MRI scans are advanced techniques developed in the past few years.
Combining this and other data, the computer is said to provide an estimate of the likelihood that an area of the brain will die if not treated. The risk map is based on actual stroke cases and their outcomes. The researchers selected imaging and other data from 14 patients who had suffered a stroke in a major brain artery – the middle cerebral artery – and did not receive thrombolytic or neuroprotective therapy.
‘We actually knew what happened to these 14 patients, so we could train the program to be a good predictor,’ Sorensen said. ‘We haven’t perfected it yet so that it is a bedside tool, but we are in the process of doing that.’
The researchers also see the technique as useful for testing the efficacy of new stroke drugs. Once the software’s predictive powers are proven highly accurate, Sorensen suggests that it will speed testing and reduce the number of patients needed in studies. Both could reduce the cost of developing new stroke drugs.