Image: Scientists used AI techniques and big data to develop an algorithm capable of recognizing the signatures of dementia two years before its onset, using a single amyloid PET scan of the brain (Photo courtesy of McGill University).
Scientists from the Douglas Mental Health University Institute’s Translational Neuroimaging Laboratory at McGill University (Quebec, Canada) have used artificial intelligence techniques and big data to develop an algorithm capable of recognizing the signatures of dementia two years before its onset, using a single amyloid PET scan of the brain of patients at risk of developing Alzheimer’s disease.
The researchers drew on data available through the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a global research effort in which participating patients agree to complete a variety of imaging and clinical assessments. Hundreds of amyloid PET scans of MCI patients from the ADNI database were used to train the team’s algorithm to identify which patients would develop dementia, with an accuracy of 84%, before symptom onset. The team of researchers at McGill is carrying out further research to find other biomarkers for dementia that could be incorporated into the algorithm in order to improve the software’s prediction capabilities. The researchers are also currently conducting further testing to validate the algorithm in different patient cohorts, particularly those with concurrent conditions such as small strokes.
The technology is expected to change the way physicians manage patients and greatly accelerate treatment research into Alzheimer’s disease. “By using this tool, clinical trials could focus only on individuals with a higher likelihood of progressing to dementia within the time frame of the study. This will greatly reduce the cost and the time necessary to conduct these studies,” said Dr. Serge Gauthier, co-lead author and Professor of Neurology & Neurosurgery and Psychiatry at McGill.