Opportunistic Screening Based on Computed Tomography in Musculoskeletal Radiology: How and Why.
Authors
Affiliations (2)
Affiliations (2)
- Department of Radiology, NYU Grossman School of Medicine, New York, New York, United States.
- Department of Radiology, UNC at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States.
Abstract
With the rapid growth of the use of computed tomography, advances in artificial intelligence enable opportunistic screening, the systematic extraction of clinically meaningful biomarkers from imaging scans performed for other indications. Modeling studies demonstrate that opportunistic screening can be highly cost effective by enabling early intervention and preventing complications such as osteoporotic fractures. Musculoskeletal radiologists are uniquely positioned to contribute to this paradigm shift because routine examinations frequently include vertebrae, skeletal muscle, adipose tissue, and vasculature, all structures that provide quantitative data on bone mineral density, sarcopenia, adiposity, and cardiovascular risk. However, widespread implementation faces challenges, such as the need for prospective outcomes data, normative reference standards, workflow integration, and clear pathways for clinical follow-up. This review examines the rationale, technical foundations, key applications, and challenges for opportunistic screening in musculoskeletal radiology.