Abdominal computed tomography (CT) scans performed for any indication provide data on body composition that can be used in risk stratification for future adverse events and overall survival. Noting that there's been a paucity of such prevention research in studies supported by the National Institutes of Health, researchers compared the prognostic ability of fully automated CT-based body composition biomarkers with that of established clinical parameters for presymptomatic prediction of future cardiovascular events and overall survival in a cohort of healthy adults. The abdominal CT scans had been performed as part of colorectal cancer screening and prevention efforts.

Fully automated CT-based algorithms were used to quantify five measures: aortic calcification, muscle density, visceral-to-subcutaneous fat ratio, liver fat, and bone mineral density. In addition to patient age and sex, the clinical parameters considered were the data inputs necessary for the Framingham risk score (such as blood pressure, cholesterol level, and smoking status) and body-mass index.

After a median follow-up of 8.8 years, 1,831 (20%) of 9,223 asymptomatic adults experienced adverse clinical events, including myocardial infarction, cerebrovascular accident, congestive heart failure, and death. Significant differences were found for all CT biomarkers in patients with versus those without adverse events. In general, multivariate combinations of CT biomarkers further improved prediction over clinical measures.

The authors point out that CT scans were performed without contrast and that they are validating the use of these automated tools in a cohort of patients who had CT with and without contrast, as well as in more racially diverse screening populations.