Mayo Clinic researchers are using artificial intelligence (AI) combined with a modern 3D body volume scanner
— originally developed for the clothing industry
— to help physicians predict the risk and severity of metabolic syndrome. According to findings published in the European Heart Journal
— Digital Health, the combination of the tools offers physicians a more precise alternative to other disease risk measurement units, such as body mass index (BMI) and waist-to-hip ratio.
Metabolic syndrome can lead to heart attack, stroke and other serious health problems and affects more than one-third of the U.S. population and one-quarter of the world population. There are no universally accepted screening strategies for this disease. However, researchers found that using a 3D body volume scanner in combination with imaging technology and algorithms developed by Mayo Clinic can help physicians offer a more accurate method for identifying people with the syndrome, as well as those at increased risk of developing it.
To develop the tool, researchers trained and validated an AI model on 1,280 volunteers who underwent an examination that included 3D body volume scans, standardized clinical questionnaires, blood tests and traditional body shape measurements. Frontal and side view images were captured via a mobile app from Select Research called myBVI on an additional 133 volunteers to further test the tool's ability to determine if they had metabolic syndrome and, if so, how severe it was.
People with metabolic syndrome typically have an apple-shaped figure, meaning they carry most of their weight on their abdomen. Diagnosis of metabolic syndrome is based on laboratory tests, blood pressure and body shape measurements, but there are no universally accepted routine screening strategies because these measurements are not always available or reproducible in the same way.
