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AI program detects Alzheimer’s years before confirmed diagnosis

Artificial intelligence (AI) will be able to spot early signs of Alzheimer’s disease years before a patient would normally be diagnosed, research has shown.

Example of fluorine 18 fluorodeoxyglucose PET images from Alzheimer’s Disease Neuroimaging Initiative set preprocessed with the grid method. Credit: Radiological Society of North America.

Published in the journal Radiology, the new study shows a self-learning computer program able to recognise features in brain scans which are too subtle for humans to see.

“Differences in the pattern of glucose uptake in the brain are very subtle and diffuse,” said study co-author Jae Ho Sohn, M.D., from the Radiology & Biomedical Imaging Department at the University of California in San Francisco (UCSF). “People are good at finding specific biomarkers of disease, but metabolic changes represent a more global and subtle process.”

After analysing more than 40 patients, the system was able to detect the beginnings of Alzheimer on an average of more than six years before they were formally diagnosed.

“We were very pleased with the algorithm’s performance,” Dr Sohn said. “It was able to predict every single case that advanced to Alzheimer’s disease.”

The doctor warned they are aware their independent test set was small and needed further validation with a larger multi-institutional prospective study. However, he also stretched the algorithm could be a useful tool to complement the work of radiologists — especially together with other biochemical and imaging tests — in helping to provide new opportunities for early therapeutic intervention.

“If we diagnose Alzheimer’s disease when all the symptoms have manifested, the brain volume loss is so significant that it’s too late to intervene,” he said. “If we can detect it earlier, that’s an opportunity for investigators to potentially find better ways to slow down or even halt the disease process.”

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