Project 460558

The population living with dementia in Canada is >500,000 and will increase significantly in the following decades. There are significant health and economic benefits associated with the early detection of dementia, which could also help patients commence treatments sooner, deferring more severe health impacts. Unfortunately, there is no validated clinical biomarker that can detect dementia reliably before the appearance of symptoms. There is much evidence that changes in brain imaging can appear 10-15 years in advance of dementia. There is no commercial procedure to automatically analyze and make future predictions from routine brain images acquired on asymptomatic patients. Our research represents an innovation in managing individuals who are at risk of converting to dementia. This research addresses the challenge of developing a biomarker, based on the Artificial Intelligence analysis of routinely acquired, to automatically detect early dementia. By assessing subtle changing patterns in the brain, such as the occurrence of white matter (WM) change, our approach will focus on people in mid-to-later life and make accurate predictions of those individuals who subsequently will eventually progress through MCI to dementia. However, understanding normal health aging is a crucial step to identify the normal degeneration of the brain and how it differs from abnormal cognitive behaviour. We have been awarded with a Evolve2Innovate grant where we identify the presence of WM changes and how they are related to dementia prediction. The capacity to make predictions very early in the evolution of dementia will be revolutionary, where the impacts will include: (1) providing individuals at risk with advanced warning of progression to dementia; (2) Allow health insurance companies to predict future disease status more accurately. From a public health standpoint, the first impact is the most universal and likely to bring critical changes at the level of individual patients.