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The method, developed by a team from the Queen Mary University of London in the UK and Monash University in Australia, involves a neurobiological model that analyzes brain scans captured byIn tests, the model was more than 80 percent accurate at predicting the development of dementia.
The test included brain scans of 81 individuals, who were undiagnosed at the time but who later went on to develop dementia, as well as 1,030 matched controls. Using their model, the team was able to spot signs of dementia in some brains up to nine years ahead of time. TheAs well as hitting that 80 percent accuracy rate, the technique could also predict when a dementia diagnosis would be made, within a two-year margin.
"Using these analysis techniques with large datasets we can identify those at high dementia risk, and also learn which environmental risk factors pushed these people into a high-risk zone,"The researchers also linked risk factors for Alzheimer's, such as genetics and social isolation, to changes in DMN connectivity. Knowing what triggers these neurobiological conditions is going to be vital in the search for a cure.
Another scenario where the analysis technique is going to be helpful will be in the study of people whose brains show signs of dementia, but whomuch later on. Understanding why this happens should teach us more about how the condition progresses and how it might be slowed down. "We hope that the measure of brain function that we have developed will allow us to be much more precise about whether someone is actually going to develop dementia, and how soon, so that we can identify whether they might benefit from future treatments,"
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