A new artificial intelligence (AI) model that analyses magnetic resonance imaging (MRI) brain scans has been developed by a team from the University of Southern California.
It could be used to accurately capture cognitive decline linked to neurodegenerative diseases, such as Alzheimer’s, much earlier than previous methods, they claim.
Using a novel AI model to analyse scans, the researchers can detect subtle brain anatomy markers that are otherwise very difficult to detect and that correlate with cognitive decline.
“Our study harnesses the power of deep learning to identify areas of the brain that are ageing in ways that reflect a cognitive decline that may lead to Alzheimer’s,” said Andrei Irimia, corresponding author of the study.
“People age at different rates, and so do tissue types in the body. We know this colloquially when we say, ‘So-and-so is forty, but looks thirty. The same idea applies to the brain. The brain of a forty-year-old may look as ‘young’ as the brain of a thirty-year-old, or it may look as ‘old’ as that of a sixty-year-old.”
Irimia and his team collated the brain MRIs of 4681 cognitively normal participants, some of whom went on to develop cognitive decline or Alzheimer’s disease later in life.
Using these data, they created an AI model called a neural network to predict participants’ ages from their brain MRIs.
The results show that the team’s model can predict the true (chronological) ages of cognitively normal participants with an average absolute error of 2.3 years.
Image Credit | iStock