AI could detect dementia after single brain scan

Friday 13 Aug 2021

Researchers are trialling an artificial intelligence (AI) system that can potentially diagnose dementia after a single brain scan.

The team, led by Professor Zoe Kourtzi, a Fellow at The Alan Turing Institute and a Professor of Computational Cognitive Neuroscience at the University of Cambridge, has developed machine learning tools that can detect dementia in patients at a very early stage. Using brain scans from patients who went on to develop Alzheimer’s, their machine learning algorithm learnt to spot structural changes in the brain. When combined with the results from standard memory tests, the algorithm was able to provide a prognostic score – that is, the likelihood of the individual having Alzheimer’s disease.

Currently, it can take several scans and tests to diagnose the disease. For those patients presenting with mild cognitive impairment – signs of memory loss or problems with language or visual/spatial perception – the algorithm was over 80% accurate in predicting those individuals who went on to develop Alzheimer’s disease. It was also able to predict how fast their cognition will decline over time.

MRI brain scan of healthy volunteer (Credit: Timothy Rittman)
MRI brain scan of healthy volunteer (Credit: Timothy Rittman)
MRI brain scan of Alzheimer's patient (Credit: TImothy Rittman)
MRI brain scan of Alzheimer's patient (Credit: TImothy Rittman)


Professor Zoe Kourtzi said: “We have trained machine learning algorithms to spot early signs of dementia by looking for patterns of grey matter loss – essentially, wearing away – in the brain. When we combine this with standard memory tests, we can predict whether an individual will show slower or faster decline in their cognition.

She goes on to say “We’ve even been able to identify some patients who were not yet showing any symptoms, but went on to develop Alzheimer’s. In time, we hope to be able to identify patients as early as five to ten years before they show symptoms as part of a health check.”

Although the algorithm has been optimised to look for signs of Alzheimer’s disease, Professor Kourtzi and colleagues are now training it to recognise different forms of dementia, each of which has its own characteristic pattern of volume loss.

Dr Timothy Rittman from the Department of Clinical Neurosciences and a consultant at Addenbrooke’s Hospital, part of Cambridge University Hospitals (CUH) NHS Foundation Trust, is now leading a trial to look at whether this approach is useful in a clinical setting.

To date around 80 patients have taken part in the trial, which was run by CUH, Cambridgeshire and Peterborough NHS Foundation Trust and two NHS trusts in Brighton.

There are currently very few drugs available to help treat dementia. One of the reasons that clinical trials often fail is because it is thought that once a patient has developed symptoms, it may be too late to make a major difference. Having the ability to identify individuals at a very early stage could therefore help researchers develop new medicines.

If the trial is successful, the algorithm could be rolled out to thousands more patients across the country.

This article has been adapted from a piece originally featured on the University of Cambridge’s website. Reporting by BBC Science Correspondent Pallab Ghosh was featured in a BBC article and also an accompanying interview on BBC Breakfast on Tuesday 10 August 2021.

Pallab Ghosh interviewing Zoe Kourtzi on BBC Breakfast
Pallab Ghosh interviewing Zoe Kourtzi on BBC Breakfast

Read more about the related Turing project AI for precision mental health: Data-driven healthcare solutions.

Professor Zoe Kourtzi

Turing Fellow, Professor of Cognitive Computational Neuroscience at the University of Cambridge and Turing University Lead - Cambridge