AI project aims to fully use healthcare data
● Multi-million-pound project to unlock potential in 30 million clinical images
A £4.4 million groundbreaking health project will use artificial intelligence (AI) to scan 30 million clinical images, including X-rays and MRI scans, to search for warning signs of disease in the pictures.
This will allow doctors in the future to make use of this information in routine care, greatly enhancing the clinical utility of routine scans.
The initiative, led by the University of Dundee, aims to turn the picture database into a powerful research tool to help tackle health conditions, including lung cancer and dementia.
Each year millions of clinical images such as X-rays, CT, MRI, ultrasound, nuclear medicine and retinal images are generated in the NHS in Scotland and stored in the national imaging database.
Researchers said while the images contain important clinical information, they also contain potential information about the health of the individual which is not made use of.
The PICTURES project is led by Dundee in conjunction with the universities of Edinburgh and Abertay and NHS Scotland. The project has been funded by the Medical Research Council, Engineering and Physical Sciences Research Council and other partners to develop the technology to unlock the additional potential of these images.
Dr Emily Jefferson, director of the Health Informatics Centre at Dundee University, said: “Clinical images are now core diagnostic technologies. These images can support many important areas of research to improve any or all diagnosis, monitoring of disease progression and response to treatment.
“Access to the vast bank of ‘real world’ images can offer a huge boost to research into major diseases and conditions, and that is what we are looking to develop through the PICTURES study, initially using lung cancer and dementia as exemplar projects.”
The project has three main elements. The core project will research and develop the underlying technologies, allowing researchers to work on vast amounts of data in a secure environment and protect individual patient information.
This technology will in turn support two medical exemplar projects, which will prove and showcase the capabilities of the research database.
The first project will develop a method to detect warning signs of coronary artery disease and lung cancer using AI to check patients’ CT chest scans.
It will work with international experts from industry partner Aidence – an Amsterdam-based start-up specialising in the interpretation of medical images – to convert the research into a clinical tool that can be used to support doctors on the frontline in the NHS. The second project will use AI methods to predict individual patient risk of future dementia using MRI brain scans, genetic data and medical records.
Prof Edwin Van Beek of the University of Edinburgh said: “It is exciting to be able to develop AI tools to enhance the diagnostic potential of CT scans in the chest and MRI scans of the brain, which don’t routinely assess cardiac or dementia risk.”