HomeArtificial IntelligenceArtificial Intelligence NewsAI Detecting Dementia Years Before Symptoms Appear

AI Detecting Dementia Years Before Symptoms Appear

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Artificial intelligence could spot the early signs of dementia from a simple brain scan long before major symptoms appear – and in some cases before any symptoms appear – say Cambridge researchers.

The dementias are characterized by the accumulation of different types of proteins in the brain, which damages the brain tissue and leads to a cognitive descent. In Alzheimer’s disease, these proteins include beta-amyloid forming “plaques” grouping between neurons and affecting their function, and dew accumulating inside neurons. Molecular and cellular changes in the brain generally begin many years before no symptoms occur. Diagnosing dementia can take many months or even years. It typically requires two or three hospital visits and can involve a range of CT, PET, and MRI scans as well as invasive lumbar punctures.

A team under the direction of Professor Zoe Kourtzi at the University of Cambridge and the Alan Turing Institute, has developed machines learning tools that can recognize dementia in patients at a very early stage. With the help of the patient’s brain scan, developing Alzheimer’s development, its machine learning algorithm learned to observe the structural changes in the brain. When combined with the results of the standard storage tests, the algorithm was able to create a prognostic score that is the likelihood that the individual has Alzheimer’s disease. For patients who have light cognitive disabilities. Signs of memory loss or problems with language or visual / spatial perception: The algorithm was greater than 80% curate in the prediction of those persons developing Alzheimer’s disease. It was also able to predict the speed with which his knowledge decreases over time.

Professor 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.”

“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.”
— Professor Zoe Kourtzi, Department of Psychology

Although the algorithm has been optimized to look for signs of Alzheimer’s disease, Professor Kourzi and colleagues are now trained to recognize different forms of dementia, each of which has its own characteristic pattern of volume loss. Dr. Timothy Rittman from the Clinic Neurosciences And a consultant to the Addenbrooke Hospital, a part of Cambridge University Hospitals (CUH) NHS Foundation Trust, now a test to see if this approach is useful in a clinical environment.
“We’ve shown that this approach works in a research setting – we now need to test it in a ‘real world’ setting,” explained Dr. Rittman.

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.

Catching dementia early is important for several reasons, explained Dr. Rittman. “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.”

“If we catch the disease early enough, there are lifestyle changes we can recommend – blood pressure medication, improved diet and exercise, stopping smoking, for example – that may help slow the progression of the disease.”
— Dr. Timothy Rittman

Currently there are very few medications to treat the treatment of dementia. One of the reasons why it is often assumed that clinical trials fail because a patient has developed symptoms, it may be too late to make a big difference. The awakening of the ability to recognize individuals could therefore help researchers in a very early stage  to develop new drugs. When the process is successful, the algorithm could be extended to thousands of more patients across the country.

Living with Alzheimer’s disease

The patient of Addenbrooke, Dennis Clark, was one of the first people in the country to participate in the new study. Before blocking, the distribution director recovered by 75 year old had enjoyed his retirement with the penny woman running on vacation and walking his two dogs. Penny noticed that he started 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.”

Penny decided to call the GP for help when Dennis, who had always taken pride in his appearance, started to wear the same clothes over and over again.

“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.

“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.”

Dennis underwent an MRI scan and later that same day he and Penny received the news that his results were consistent with early onset of Alzheimer’s disease. Dennis will begin taking medication to help treat the symptoms of Alzheimer’s disease.

“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.”

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