AI Case Study
Clinicial researchers at Imperial College London and the University of Edinburgh develop machine learning based software that could speed up treatment of patients showing signs of stroke or dementia
Scientists at Imperial College London and the University of Edinburgh have created a new software to improve stroke and dementia diagnosis in brain scans. With the use of machine learning the program is able to identify one the commonest causes of stroke and dementia, small vessel disease, more accurately than current methods. The researchers state that this technology may aid clinicians at administering the best treatment to patients more quickly and predicting a person's likelihood of developing dementia.
Industry
Public And Social Sector
Education And Academia
Project Overview
"New software, created by scientists at Imperial College London and the University of Edinburgh, has been able to identify and measure the severity of small vessel disease, one of the commonest causes of stroke and dementia. The study, published in Radiology, took place at Charing Cross Hospital, part of Imperial College Healthcare NHS Trust.
The study used historical data of 1082 CT scans of stroke patients across 70 hospitals in the UK between 2000-2014, including cases from the Third International Stroke Trial. The software identified and measured a marker of SVD, and then gave a score indicating how severe the disease was ranging from mild to severe. The researchers then compared the results to a panel of expert doctors who estimated SVD severity from the same scans. The level of agreement of the software with the experts was as good as agreements between one expert with another.
Additionally, in 60 cases they obtained MRI and CT in the same subjects, and used the MRI to estimate the exact amount of SVD. This showed that the software is 85 per cent accurate at predicting how severe SVD is.
The team are now using similar methods to measure the amount of brain shrinkage and other types of conditions commonly diagnosed on brain CT
The study was funded by a National Institute for Health Research i4i Invention for Innovation award, and a National Institute for Health Research Imperial Biomedical Research Centre grant (NIHR BRC)."
Reported Results
"Researchers say that this technology can help clinicians to administer the best treatment to patients more quickly in emergency settings - and predict a person’s likelihood of developing dementia. The development may also pave the way for more personalised medicine."
Technology
Function
R And D
Core Research And Development
Background
"Small vessel disease (SVD) is a very common neurological disease in older people that reduces blood flow to the deep white matter connections of the brain, damaging and eventually killing the brain cells. It causes stroke and dementia as well as mood disturbance. SVD increases with age but is accelerated by hypertension and diabetes.
At the moment, doctors diagnose SVD by looking for changes to white matter in the brain during MRI or CT scans. However, this relies on a doctor gauging from the scan how far the disease has spread. In CT scans it is often difficult to decide where the edges of the SVD are, making it difficult to estimate the severity of the disease, explains Dr Bentley.
Although MRI can detect and measure SVD more sensitively it is not the most common method used due to scanner availability, and suitability for emergency or older patients."
Benefits
Data
CT scans