A brain scan that gives one age for the whole brain might be missing the point.
Researchers at the University of Southern California have developed an AI-based method that maps how old different parts of the brain appear, and they say it could help spot dementia earlier by showing where aging is happening faster than expected.
The study found, for the first time, how patterns of neurodegeneration in specific brain regions relate to changes in cognitive function as people get older.
The team, led by Andrei Irimia, trained a deep learning model using MRI scans from 14,748 cognitively healthy adults aged 19 to 100. The scans gave the model a baseline for measuring local brain age, or how old specific regions of the brain appear.
Researchers then tested the model on MRI scans from more than 1,900 participants in the Alzheimer’s Disease Neuroimaging Initiative, including cognitively normal adults, people with mild cognitive impairment and people with Alzheimer’s disease.
When applied to scans from people with mild cognitive impairment and Alzheimer’s disease, the model showed “distinct” patterns of accelerated aging in brain regions known to be affected early in neurodegeneration.
Rather than assigning a single brain age, the method measures local brain age at the voxel level, the three-dimensional units that make up an MRI scan. The researchers said that produces a much more detailed picture of structural aging across the brain.
Irimia said: “Not all brain regions age at the same rate.
“Some areas appear to be more resilient, while others are more vulnerable to aging and disease.
“By measuring local brain aging , we can identify where the brain is aging faster than expected and how those changes relate to cognitive function.”
The research was published in the Proceedings of the National Academy of Sciences.
Across healthy adults, the model found the frontal and temporal lobes appeared biologically older than the parietal and occipital regions. The frontal and temporal lobes are involved in decision-making, memory and other higher cognitive functions, while the parietal and occipital regions are involved in spatial awareness and sensory processing functions.
The researchers also found the brain’s right hemisphere tended to show slightly more advanced aging than the left, and that pattern remained in both right-handed and left-handed participants.
As cognitive impairment progressed, the differences became more pronounced.
Compared with cognitively normal adults, participants with mild cognitive impairment or Alzheimer’s disease showed “significantly older” local brain ages in structures affected early by Alzheimer’s, including the hippocampus, amygdala and several deep brain regions involved in memory and cognitive processing.
The team also found that older local brain age was linked to poorer performance on cognitive assessments. The strongest relationships appeared in people with Alzheimer’s disease.
Irimia said: “This more nuanced understanding of how the brain ages could pave the way for earlier identification of dementia, a better understanding of what factors affect risk and new ideas for treatment approaches.”
The researchers said the approach may also help track disease progression or assess if experimental therapies are slowing degeneration in targeted brain regions.
Irimia said the method is still a research tool. He said it was trained mainly on research-quality MRI data and needs more validation using more diverse clinical datasets before it could be used in routine patient care.
He said: “Brain aging isn’t uniform.
“By understanding how individual regions age, as well as how those patterns differ from person to person, we’re moving toward a much more precise understanding of healthy aging and neurodegenerative disease.”
He added: “Ultimately, that could help us identify people at risk earlier and develop more personalized approaches to preserving brain health.”
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