Researchers have developed a revolutionary method to measure how fast the brain is ageing, offering new insights into cognitive decline and neurodegenerative diseases like Alzheimer's.
The study, published in Proceedings of the National Academy of Sciences (PNAS), introduces a 3D convolutional neural network (3D-CNN) that analyzes MRI scans over time to estimate the "pace of ageing" with unprecedented accuracy.
"This could change how we track brain health," said Andrei Irimia, associate professor at USC Leonard Davis School of Gerontology. While previous methods provided a single estimate of brain age, this model compares multiple MRI scans to assess the rate of brain ageing. The model was trained on over 2,000 healthy adults, validated on 1,300 more, and tested on Alzheimer's patients, achieving just 0.16 years of error—far superior to older methods.
The study found distinct ageing patterns based on sex and age. In women, ageing was most evident in the right precentral and superior parietal lobules, while men showed changes in the left frontopolar and right supramarginal gyrus.
Age-related differences were also observed, with faster ageing in the left temporal and right occipital lobes in people in their 50s and in the central and postcentral gyri in those in their 70s.
Crucially, a faster pace of brain ageing was linked to cognitive decline, as seen in Alzheimer's patients. Among participants, those who later developed impairment had significantly higher ageing rates.
This method could serve as an early biomarker for neurodegenerative diseases, potentially enabling preventive treatments before severe cognitive decline occurs. Researchers also noted gender-based differences in brain ageing, which may help explain varying risks for neurological disorders.
Source: Hindustan Times
Bd-pratidin English/Fariha Nowshin Chinika
