AI model predicts diabetes risk using MRI results
Researchers have developed a new AI model capable of predicting a person’s overall risk of diabetes, sharing their work in Frontiers in Cardiovascular Medicine.
The team’s model reviews a patient’s MRI results and measures the amount of fat surrounding their heart. They tested the advanced algorithm on more than 45,000 scans included in the UK Biobank database, noting that it achieved an impressive accuracy.
In addition, the AI tool has a built-in quality control feature that can warn users when an especially high level of uncertainty surrounds its findings.
“Unfortunately, manual measurement of the amount of fat around the heart is challenging and time-consuming,” co-author Dr. Zahra Raisi-Estabragh, a specialist at the William Harvey Research Institute at Queen Mary University of London, said in a prepared statement. “For this reason, to date, no one has been able to investigate this thoroughly in studies of large groups of people. To address this problem, we’ve invented an AI tool that can be applied to standard heart MRI scans to obtain a measure of the fat around the heart automatically and quickly, in under three seconds. This tool can be used by future researchers to discover more about the links between the fat around the heart and disease risk, but also potentially in the future, as part of a patient’s standard care in hospital.”
“This novel tool has high utility for future research and, if clinical utility is demonstrated, may be applied in clinical practice to improve patient care,” senior author Steffen Petersen, a professor at Queen Mary, said in the same statement. “This work highlights the value of cross-disciplinary collaborations in medical research, particularly within cardiovascular imaging.”
The group’s full analysis is available here.
Michael has more than 18 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.