Progress has been made on a medical research project that aims to build a software tool to predict a person’s risk of dementia.

A team of 20 scientists and clinical researchers from the Universities of Edinburgh and Dundee have been granted approval to use 1.6 million images of CT and MRI brain scans, in their project to predict the dementia risk of patients. The huge data set of brain scans will be that of the entire Scottish population between 2008 and 2018, with the data to be safely held in the Scottish National Safe Haven.

The project, called Scottish AI in Neuroimaging to predict Dementia and Neurodegenerative Disease (SCAN-DAN), aims to predict dementia risks through the use of artificial intelligence and machine learning, to compare the brain scans to linked brain records such as demographics and treatment history. This can be used to identify patterns that could indicate a persons risk of dementia. 

The access to data was approved by the Public Benefit and Privacy Panel for Health and Social Care, and the research will be conducted with patients being unidentifiable. Professor Emanuele Trucco, who is an expert in AI and medical imaging at the University of Dundee and co-leader of SCAN-DAN, said on the security of the data: “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.”

He added: “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.”

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SCAN-DAN is a “pathfinder” project funded by NEURii, a year-old global research collaboration, which aims to use world class health data to create projects that help enhance the quality of life for people living with dementia. It achieves this by providing funding and expertise to “pathfinder projects”, which helps to remove financial barriers that may prevent digital tools from getting on the market.

These projects, as well as SCAN-DAN, include pharmaceutical company Eisai, Health Data Research UK, medical research charity LifeArc, and even Bill Gates think-tank Gates Ventures, which aims to combat climate change and Alziemers, as well as aid the move to clean energy.

Global Director of Digital Health Solutions at Eisai and Programme Director for NEURii, Dr Ricardo Sáinz Fuertes, elaborated on the purpose of the collaboration: “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.”

The overall aim for the project is to build a digital healthcare tool for radiologists, which they can use to determine a patients risk of dementia, as well as diagnose related illnesses such as Alzheimer’s, when scanning for other conditions. Explaining why identifying early signs of dementia are so important, Willy Gilder, who is 71 and was diagnosed with Alzheimer’s three years ago, said: “We know that 45 per cent 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.”

As well as analysing patient’s risk of the disease, identifying a patient group with a high risk of dementia would help researchers to develop more precise treatments for various types of dementia, such as Alziemer’s and vascular dementia.

Professor Bill Whiteley of the University of Edinburgh’s Centre for Clinical Brain Sciences, who is co-leading SCAN-DAN, elaborated: “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.”