Training an AI to early detect dementia with big data

Data scientists and clinical researchers will use brain scans from the entire Scottish population to build a software tool that they hope will be able to predict a person’s risk of dementia.

The team of 20, from the Universities of Edinburgh and Dundee, has approval to use a unique, large data set made up of CT and MRI brain scans from patients in Scotland from 2008 to 2018, representing 1.6 million images. Approval comes from the Public Benefit and Privacy Panel for Health and Social Care, a part of NHS Scotland.

The team will then use artificial intelligence and machine learning to analyse the image data alongside linked health records such as demographics and treatment history, without patients being identifiable, to find patterns that could indicate a person’s risk of developing dementia. The ultimate aim is to build a digital healthcare tool that radiologists can use when scanning for other conditions to determine a person’s dementia risk, and to diagnose early stages of related diseases, such as Alzheimer’s.

Isolating a patient group with a high risk of dementia will enable the development of more precise treatments for various types of dementia, mostly Alzheimer’s and vascular dementia. The data will be held safely in the Scottish National Safe Haven, commissioned by Public Health Scotland, which provides a secure platform for the research use of NHS electronic data.

Former journalist Willy Gilder, 71, from Edinburgh, was diagnosed with Alzheimer’s three years ago. He said, “We know that 45% of dementia cases are preventable, and The Lancet has published a list of risk factors including smoking, obesity and air pollution. If you know you’re at risk, you can make changes that are going to improve your brain health. Because I was diagnosed early, I know that keeping very mentally active, for example, is going to help me. Possible new treatments in development for Alzheimer’s are likely to work in the early stages of the disease, which is why early diagnosis is important. With long waiting lists for diagnosis, as well as relatively low funding for dementia research in general compared to cancer, a project like this to predict a person’s risk is extremely important.”

The project, called Scottish AI in Neuroimaging to predict Dementia and Neurodegenerative Disease (SCAN-DAN), is one of three ‘pathfinders’ from global research collaboration NEURii, which launched a year ago. Comprising global pharmaceutical company Eisai, Gates Ventures, the University of Edinburgh, national health data science organisation Health Data Research UK and medical research charity LifeArc, NEURii aims to translate world-class data, neurology and digital sciences into projects that can enhance quality of life for people living with dementia.

This new data set will be of great use to neurological researchers. And, should we establish a successful proof of concept, we will have a suite of software tools that are smoothly and unobtrusively integrated with routine radiology operations, that assist clinical decision-making and flag the risk of dementia as early as possible
Emanuele Trucco

The NEURii collaboration provides funding and expertise to the pathfinder projects to remove barriers to getting digital health tools to market. The research teams are also supported by Edinburgh Innovations, the University of Edinburgh’s commercialisation service.

Professor Will Whiteley, of the University of Edinburgh’s Centre for Clinical Brain Sciences, is co-leading the SCAN-DAN project. He said, “Better use of simple brain scans to predict dementia will lead to better understanding of dementia and potentially earlier diagnosis of its causes, which in turn will make development of new treatments easier. Currently treatments for dementia are expensive, scarce and of uncertain value. If we can collect data from a large group of people at high risk, who then give their consent to take part in trials, we can really start to develop new treatments. Working with NEURii really gives us the potential for patient impact – to build something that actually makes it into practice. Often modelling doesn’t go anywhere, but motivation from the NEURii team to develop a useful product really concentrates the mind.”

Professor Emanuele Trucco, an expert in AI and medical imaging at the University of Dundee and SCAN-DAN co-lead, said, “Scotland and the UK are at the forefront of clinical data research, building on the unique National Health Service patient number – called the CHI number in Scotland, as well as the structure, security and good governance of the Scottish National Safe Haven, amongst other data organisations such as the UK Biobank. This new data set will be of great use to neurological researchers. And, should we establish a successful proof of concept, we will have a suite of software tools that are smoothly and unobtrusively integrated with routine radiology operations, that assist clinical decision-making and flag the risk of dementia as early as possible.”

The project is backed by the NEURii partner organisations. Dr Ricardo Sáinz Fuertes, Global Director of Digital Health Solutions at Eisai and Programme Director for NEURii, said, “The spirit of NEURii is to fulfil the promise of data science for healthcare. Within a year, we plan to support SCAN-DAN through to proof of concept by removing obstacles to commercialisation and providing whatever’s needed, be it funding, collaborations or legal or regulatory input. We are joining forces globally, in a way that hasn’t been done before, to provide innovative digital projects with the chance of becoming solutions to complex neurodegenerative disorders like dementia.”

Source: University of Dundee

28.08.2024