Analysis of CT scans in people who undergo imaging for health screening can identify individuals at risk of type 2 diabetes, according to a study published today in Radiology , a journal of the Radiological Society of North America (RSNA). Researchers said the findings underscore CT's value in opportunistic imaging-;the use of information from routine imaging examinations to learn more about a patient's overall health. For the new study, researchers evaluated the ability of automated CT-derived markers to predict diabetes and associated conditions.
Given the significant burden of diabetes and its complications, we aimed to explore whether automated and precise imaging analyses could enhance early detection and risk stratification beyond conventional methods." Seungho Ryu, M.D.
, Ph.D., study senior author from the Kangbuk Samsung Hospital at Sungkyunkwan University School of Medicine in Seoul, South Korea The study group included 32,166 adults ages 25 years or older who underwent health screening with 18F-fluorodeoxyglucose ( 18 F-FDG) PET/CT.
Dr. Ryu and colleagues used clinically validated deep learning algorithms to analyze the CT images. The algorithms enabled 3D segmentation and quantification of various body components such as visceral fat, subcutaneous fat, muscle mass, liver density and aortic calcium.
Diabetes prevalence was 6% at baseline and incidence was 9% during the 7.3-year median follow-up. Automated multiorgan CT analysis identified individuals at high risk of.