Researchers at the Mayo Clinic in Rochester, Minnesota, have discovered a new way of accurately measuring metabolic health using artificial intelligence (AI) and a 3D body scanner initially developed for clothing designs.
According to a news report published by Cardiovascular Business, the new approach can help evaluate one’s metabolic health precisely and identify potential risks of diabetes, cardiovascular illnesses, and other adverse cardiovascular conditions.
Unlike the traditional waist-to-hip ratio or the widely used body mass index (BMI), the new technique, whose findings were shared in the European Heart Journal – Digital Health, has proven to give more accurate results about a person’s cardiovascular conditions and associated risks.
New Metabolic Health Measuring Technique Beat BMI
The research involved training an advanced AI model with data from about 1,300 individuals who volunteered to be scanned using a 3D body-volume scanner which was originally being used to design pieces of clothing, then subjected to a series of measurements and tests.
To further understand the effectiveness and accuracy of the new techniques, the researchers also used front- and side-view images taken by 133 volunteers using myBVI mobile phone app. After analysis, the new technique proved more accurate in detecting individuals with higher risks of metabolic syndrome than waist-to-hip ratio and BMI.
The first author, Betsy Medina Inojosa, MD, a researcher at Mayo Clinic, underscored the need for a reliable, repeatable measuring technique for metabolic syndrome risk and their severity levels, adding that BMI and bioimpedance scales are inaccurate in measuring body fat and muscle, while body scans are not widely available.
Mayo Clinic’s research shows that clinicians can also use the AI model for insight and to help patients seek better outcomes for their health.
