AI technique can boost brain scans to predict Alzheimer early

AI technique can boost brain scans to predict Alzheimer early

However, early diagnosis has proven to be challenging.

Although the cause behind the progressive brain disorder remains unconfimed yet, various research has linked the disease process to changes in metabolism, as shown by glucose uptake in certain regions of the brain. "People are good at finding specific biomarkers of disease, but metabolic changes represent a more global and subtle process".

Boffins from the University of California trained the computer using more than 2,100 scans from 1,002 patients.

"Deep learning" AI involves a computer programme acquiring knowledge by example, in much the same way as humans do. These PET scans can detect metabolic activities from all parts of the brain by showing uptake of a radioactive glucose compound that is administered by injection into the blood stream. This way, the AI managed to see all the patterns that corresponded to Alzheimer's disease.

They then applied the algorithm to brain scans of another 40 patients and identified those who later went on to develop Alzheimer's. Researchers trained the deep learning algorithm on 90 percent of the dataset and then tested it on the remaining 10 percent of the dataset. "We hypothesized that the deep learning algorithm could detect features or patterns that are not evident on standard clinical review of images and thereby improve the final diagnostic classification of individuals".

Jae Ho Sohn, a member of the research team, said they tested the system on 40 scans that were completely new to the algorithm.

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"We were very pleased with the algorithm's performance".

The AI system detected every single patient that eventually developed Alzheimer's from brain scans taken an average of six years before a person's diagnosis was made.

He says that in a best case scenario, the algorithm could start appearing in the health service in three years.

Diagnosing Alzheimer's is no easy task and, so far, research has only managed to link the disease process to metabolism changes shown by glucose uptake in certain regions of the brain but even knowing this, the changes are, more often than not, hard to recognize.

Although he cautioned that their independent test set was small and needs further validation with a larger multi-institutional prospective study, Dr. Sohn said that the algorithm could be a useful tool to complement the work of radiologists - especially in conjunction with other biochemical and imaging tests - in providing an opportunity for early therapeutic intervention. "This study highlights the potential of machine learning to assist with the early detection of diseases like Alzheimer's, but the findings will need to be confirmed in much larger groups of people before we can properly assess the power of this approach", she said.

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