"This opportunistic use of additional CT-based biomarkers provides objective value to what doctors are already doing," said Perry J. Pickhardt, M.D., of the University of Wisconsin School of Medicine & Public Health, lead and corresponding author of the study. "This automated process requires no additional time, effort, or radiation exposure to patients, yet these prognostic measures could one day impact patient health through presymptomatic detection of elevated cardiovascular or other health risks."

This research builds on prior efforts designing AI algorithms that Dr. Summers has undertaken in his lab in the NIH Clinical Center's Radiology and Imaging Sciences Department and his previous collaboration with Dr. Pickhardt to develop, train, test, and validate fully automated algorithms for measuring body composition using abdominal CT. The researchers plan to test the approach in other studies, including more racially diverse populations.


This study was supported by the NIH Intramural Research Program, and it used the high-performance computing capabilities of the NIH Biowulf cluster.


About the NIH Clinical Center:
The NIH Clinical Center is the clinical research hospital for the National Institutes of Health. Through clinical research, clinician-investigators translate laboratory discoveries into better treatments, therapies and interventions to improve the nation's health.


About the National Institutes of Health (NIH):
NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases.

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