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New AI tool aims to detect early signs of dementia during routine eye tests

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Professor Baljean Dhillon hold model eyeball

Data scientists and clinical researchers are working with high street opticians for the first time to develop a digital tool that can predict a person’s risk of dementia from a routine eye test.

The NeurEYE research team, which is supported by LifeArc and led by the University of Edinburgh with Glasgow Caledonian University, has collected almost a million eye scans from opticians across Scotland, forming the world’s largest data set of its kind.

The scientists will use artificial intelligence and machine learning to analyse the image data, which is already linked to patient data on demographics, treatment history and pre-existing conditions. The data is anonymised and patients can’t be identified, but it will allow researchers to find patterns that could indicate a person’s risk of developing dementia, as well as giving a broad picture of brain health.

The data will be held safely in the Scottish National Safe Haven which provides a secure platform for the research use of NHS electronic data. This resource is commissioned by Public Health Scotland and hosted by the Edinburgh International Data Facility through EPCC at the University of Edinburgh. Permission to use the data comes from the Public Benefit and Privacy Panel for Health and Social Care, a part of NHS Scotland.

World-class international support

The project is the second pathfinder funded and supported by NEURii, a first-of-its-kind global collaboration between LifeArc, the pharmaceutical company Eisai, Gates Ventures, the University of Edinburgh, and the national health data science institute Health Data Research UK. Together, the partners are giving innovative digital projects the chance to become real world solutions that could benefit millions of patients with neurodegenerative conditions like dementia. The first NEURii project, SCAN-DAN, is using brain scans and AI to predict dementia risk. The research teams are also supported by Edinburgh Innovations, the University of Edinburgh’s commercialisation service.

Professor of Clinical Ophthalmology at the University of Edinburgh and NeurEYE co-lead, Baljean Dhillon, explains: “The eye can tell us far more than we thought possible. The blood vessels and neural pathways of retina and brain are intimately related. But, unlike the brain, we can see the retina with the simple, inexpensive equipment found in every high street in the UK and beyond.”

Professor of Computational Medicine at the Usher Institute and NeurEYE co-lead Miguel Bernabeu adds: “Recent advances in artificial Intelligence promise to revolutionise medical image interpretation and disease prediction. However, in order to develop algorithms that are equitable and unbiased, we need to train them on datasets that are representative of the whole population at risk. This dataset, along with decades-long research at University of Edinburgh on safe and fair AI, can bring a step change in early detection of dementia for all.”

Opticians, now more often called optometrists, will be able to use the software subsequently developed as a predictive or diagnostic tool for conditions such as Alzheimer’s, as a triage tool to refer patients to secondary health services if signs of brain disease are spotted, and potentially as a way to monitor cognitive decline.

“Harnessing the potential of digital innovations in this way could ultimately save the NHS more than £37m a year because the hope is that it will speed up the diagnosis and treatment of neurodegenerative conditions like dementia.

“The UK, with its single healthcare provider, is also well placed to become a global leader in the development of new tests that use health data. This is why we are collaborating to advance promising digital health projects that have the potential to improve millions of lives.”

Dave Powell, Chief Scientific Officer, LifeArc

Knowing who is at risk of dementia could also accelerate the development of new treatments by identifying people who are more likely to benefit from trials and enabling better monitoring of treatment responses.

Impact for patients

Retired mechanical engineer, David Steele, whose mum has Alzheimer’s, said predictive software like this could have saved his family ten years of heartache and struggle. He says: “It took ten years for my mum to be diagnosed with Alzheimer’s.

“She was initially diagnosed with dry macular degeneration, but this masked the underlying issue that we now know to be cerebral blindness linked to Alzheimer’s. The connection between brain and eye was the missing link in her case.

“The missing diagnosis meant that my late father, who was also elderly, cared for mum throughout a difficult period without knowing what was wrong.

“If we had known, then we would have had help with the additional and demanding support that became necessary. Preventing the cliff edge, when it becomes too late for the person to understand what is wrong with them, is so important.”


Media contact

Hannah Severyn

Head of Media and PR at LifeArc