Scientists have developed an artificial intelligence system that can accurately identify signs of Alzheimer's disease almost 10 years before clinical symptoms appear. Researchers from University of Bari in Italy developed a machine-learning algorithm to discern structural changes in the brain caused by Alzheimer's disease. Using MRI scans, the system detected early signs with 84 per cent accuracy by identifying changes in how regions of the brain are connected.
They trained the algorithm using 67 MRI scans, 38 of which were from people who had Alzheimer's and 29 from healthy controls, the 'New Scientist' reported. The idea was to teach the algorithm to correctly classify and discriminate between diseased and healthy brains, researchers said. The team then tested the algorithm on a second set of scans from 148 subjects. Of these, 52 were healthy, 48 had Alzheimer's disease and 48 had mild cognitive impairment (MCI) but were known to have developed Alzheimer's disease 2.5 to nine years later.
The system distinguished between a healthy brain and one with Alzheimer's with an accuracy of 86 per cent. Crucially, it could also tell the difference between healthy brains and those with MCI with an accuracy of 84 per cent. This shows that the algorithm could identify changes in the brain that lead to Alzheimer's almost a decade before clinical symptoms appear.
"Nowadays, cerebrospinal fluid analyses and brain imaging using radioactive tracers can tell us to what extent the brain is covered with plaques and tangles, and are able to predict relatively accurately who is at high risk of developing Alzheimer's 10 years later," La Rocca said. In contrast, the new technique can distinguish with similar accuracy between brains that are normal and the brains of people with MCI who will go on to develop Alzheimer's disease in about a decade but using a simpler, cheaper and non-invasive technique.
