Addenbrooke’s patients in Cambridge involved in trial using AI to diagnose Alzheimer’s disease
Addenbrooke’s patient Dennis Clark has become one of the first people in the country to take part in a new trial that is exploring whether artificial intelligence (AI) can be used to aid the diagnosis and treatment of Alzheimer’s.
Diagnosing the disease and dementia can take many months, with two or three hospital visits required for a range of CT, PET and MRI scans, along with invasive lumber punctures.
But scientists and doctors hope AI could provide a one-stop diagnosis, enabling patients to begin treatment more quickly.
About 80 patients have taken part in the trial run by Cambridge University Hospitals (CUH), Cambridgeshire and Peterborough NHS Foundation Trust and two NHS trusts in Brighton.
Dennis, a 75-year-old retired sales director, underwent an MRI scan on July 21 and later that day he and wife Penny received the news that his results were consistent with early onset of Alzheimer’s.
Penny said: “We are very grateful to Addenbrooke’s and would recommend other people take up trials as well. Quicker diagnosis means Dennis will be able to start medication that will hopefully delay his disease. It also means we can plan for the future and start to accept what is happening.”
Before lockdown, Dennis had been enjoying his retirement, going on holiday and walking his two dogs. But Penny noticed he was starting to forget things.
“If I asked him to do something, he would do the opposite. Then when we went out for a meal – which we didn’t do for a long time because of lockdown – he couldn’t remember how to pay for anything,” she said.
She called the GP when Dennis, who always had pride in his appearance, started to wear the same clothes repeatedly.
“The GP did a quick test over the phone and said Dennis needed to be referred. I had heard Addenbrooke’s had a very comprehensive memory unit, so I was really pleased that we were able to be referred there,” said Penny.
“We had an initial consultation and we were asked if we wanted to go down the research route, which I was really keen for Dennis to do because it doesn’t just help him, it helps others as well.”
He was referred to the QMIN-MC trial, which is testing a machine learning algorithm developed by Prof Zoe Kourtzi, research lead at the Alan Turing Institute. It trains itself to diagnose patients by looking at MRI brain scans to identify patterns and combines these findings with the results of standard memory tests.
Prof Kourtzi, from Cambridge's Department of Psychology, said: “We have trained machine learning algorithms to spot very early signs of dementia just 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.
“We’ve even been able to identify some patients who were not yet showing any symptoms, but went on to develop Alzheimer’s.”
While optimised to look for signs of Alzheimer’s disease, Prof Kourtzi and colleagues are training the algorithm to recognise different forms of dementia, each of which has its own characteristic pattern of volume loss.
Addenbrooke’s consultant and clinical lead for the trial, Dr Timothy Rittman, said: “Traditionally, when we look at patient scans we are looking for patterns to be able to help us exclude things like strokes and brain tumours. The computer can do this much more comprehensively than any human, helping to give us not only a more accurate diagnosis, but also a prognosis as well.
“With a better prognosis we can identify how quickly a patient is moving away from the normal pattern of the disease and amend their treatment and care accordingly.”
Earlier diagnosis can be helpful for a number of reasons.
“When patients begin to experience memory and cognitive problems, this can understandably be a very difficult time. Being able to provide an accurate diagnosis gives them clarity and, depending on the diagnosis, can either ease their minds or help them and their loved ones put preparations in place for the longer term,” said Dr Ritmann.
If the 500-person trial is a success, the system could be rolled out to thousands nationwide and save the NHS half a billion pounds over five years.