Heart MRI scan showing the fat area detected by the AI tool. Credit: Queen Mary, University of London
A team led by researchers from Queen Mary University of London has developed a new artificial intelligence (AI) tool capable of automatically measuring the amount of fat around the heart based on MRI scans.
With the new tool, the team was able to show that a larger amount of fat around the heart is linked to a significantly higher risk of diabetes, regardless of a person’s age, gender and body mass index.
The research is published in the journal Frontiers in Cardiovascular Medicine and is the result of funding from the CAP-AI program led by Barts Life Sciences, a research and innovation partnership between Queen Mary University of London and Barts Health NHS Trust .
The distribution of fat in the body can affect a person’s risk for various diseases. The commonly used measure of body mass index (BMI) mainly reflects the accumulation of fat under the skin and not around the internal organs. In particular, there is evidence that fat accumulation around the heart may be a predictor of heart disease and has been linked to a number of conditions including atrial fibrillation, diabetes, and coronary artery disease.
The lead researcher Dr. Zahra Raisi-Estabragh of Queen Mary’s William Harvey Research Institute said, “Unfortunately, measuring the amount of fat around the heart manually is challenging and time-consuming. As a result, nobody has been able to.” to investigate this thoroughly in studies on large groups of people.
“To address this problem, we invented an AI tool that can be applied to standard MRI scans of the heart to automatically and quickly get a measurement of the adipose tissue around the heart in less than three seconds. This tool can be used by future researchers to learn about the relationships between adipose tissue around the heart and disease risk, but also possibly in the future as part of standard hospital care. “
The research team tested the AI algorithm’s ability to interpret images from cardiac MRI scans of more than 45,000 people, including participants from the UK Biobank, a database of health information from over half a million participants across the UK. The team found that in these images, the AI tool could accurately determine the amount of fat around the heart and also calculate a patient’s risk of diabetes.
Dr. Queen Mary’s Andrew Bard, who led technical development, added, “The AI tool also has a built-in method of calculating the uncertainty of its own results so that it can be said to have an impressive ability to do its own homework to mark. “
Professor Steffen Petersen of Queen Mary’s William Harvey Research Institute, who oversaw the project, said, “This novel tool has great utility for future research and, if clinical benefit is demonstrated, it can be used in clinical practice to improve patient care will value the value of interdisciplinary collaborations in medical research, particularly in cardiovascular imaging. ”
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More information:
Andrew Bard et al., Automated Quality-Controlled Cardiovascular Magnetic Resonance Pericardial Fat Quantification Using a Convolutional Neural Network in the UK Biobank, Frontiers in Cardiovascular Medicine (2021). DOI: 10.3389 / fcvm.2021.677574 Provided by Queen Mary, University of London
Quote: AI predicts diabetes risk by measuring fat levels around the heart (2021 July 7), accessed July 7, 2021 from https://medicalxpress.com/news/2021-07-ai-diabetes-fat-heart. html
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