Artificial intelligence (AI) could be used to detect cognitive decline linked to neurodegenerative diseases such as Alzheimer’s much earlier than current methods, according to research from the University of Southern California (USC).
The team behind the study developed an AI model that analyses magnetic resonance imaging (MRI) brain scans to detect subtle brain anatomy markers that are otherwise very difficult to identify and that correlate with cognitive decline. These markers offer an “unprecedented glimpse into human cognition”, said Andrei Irimia, assistant professor of gerontology at the USC Leonard Davis School of Gerontology and corresponding author of the study.
Irimia and his team collected the brain MRIs of 4,681 cognitively normal participants, some of whom developed cognitive decline or Alzheimer’s later in life. They used the data to create an AI model called a neural network to predict participants’ ages from their brain MRIs. The researchers compared the perceived (biological) brain ages with the actual (chronological) ages of the study participants. The greater the difference between the two, the worse the participants’ cognitive scores, which reflect Alzheimer’s risk.
The results showed that the team’s model can predict the true (chronological) ages of cognitively normal participants with an average absolute error of 2.3 years, which is about one year more accurate than an existing, award-winning model for brain age estimation that used a different neural network architecture. “Interpretable AI can become a powerful tool for assessing the risk for Alzheimer’s and other neurocognitive diseases,” said Irimia. “The earlier we can identify people at high risk for Alzheimer’s disease, the earlier clinicians can intervene with treatment options, monitoring, and disease management.”
The new model also revealed sex-specific differences in how aging varies across brain regions. According to the study, certain parts of the brain age faster in males than in females, and vice versa. Males, who are at higher risk of motor impairment due to Parkinson’s disease, experience faster aging in the brain’s motor cortex, an area responsible for motor function. On the other hand, females tend to have faster aging in the brain’s temporal lobe, which is responsible for memory and emotion processing. These findings highlight the importance of considering sex as a factor in neurodegenerative disease risk assessments.
The findings have been published in the journal Proceedings of the National Academy of Sciences, offer an unprecedented glimpse into human cognition.