{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T23:04:23Z","timestamp":1784588663053,"version":"3.55.0"},"reference-count":52,"publisher":"Georg Thieme Verlag KG","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Semin Musculoskelet Radiol"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>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.<\/jats:p>","DOI":"10.1055\/a-2811-6756","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T23:10:53Z","timestamp":1781305853000},"page":"496-504","source":"Crossref","is-referenced-by-count":0,"title":["Opportunistic Screening Based on Computed Tomography in Musculoskeletal Radiology: How and Why"],"prefix":"10.1055","volume":"30","author":[{"given":"Siddhant","family":"Dogra","sequence":"additional","affiliation":[{"name":"Department of Radiology, NYU Grossman School of Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olivia","family":"Bussey","sequence":"additional","affiliation":[{"name":"Department of Radiology, NYU Grossman School of Medicine, New York, New York, United States"},{"name":"Department of Radiology, UNC at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bari","family":"Dane","sequence":"additional","affiliation":[{"name":"Department of Radiology, NYU Grossman School of Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5482-0440","authenticated-orcid":false,"given":"Miriam A.","family":"Bredella","sequence":"additional","affiliation":[{"name":"Department of Radiology, NYU Grossman School of Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soterios","family":"Gyftopoulos","sequence":"additional","affiliation":[{"name":"Department of Radiology, NYU Grossman School of Medicine, New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2026,6,12]]},"reference":[{"issue":"05","key":"ref1","doi-asserted-by":"crossref","first-page":"e222044","DOI":"10.1148\/radiol.222044","article-title":"Opportunistic screening: Radiology Scientific Expert Panel","volume":"307","author":"P J Pickhardt","year":"2023","journal-title":"Radiology"},{"issue":"02","key":"ref2","doi-asserted-by":"crossref","first-page":"171","DOI":"10.2214\/AJR.22.28851","article-title":"Opportunistic imaging: point-increasing the value of diagnostic imaging","volume":"221","author":"M A Bredella","year":"2023","journal-title":"AJR Am J Roentgenol"},{"issue":"02","key":"ref3","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1148\/radiol.211561","article-title":"Value-added opportunistic CT screening: state of the art","volume":"303","author":"P J Pickhardt","year":"2022","journal-title":"Radiology"},{"issue":"10","key":"ref5","doi-asserted-by":"crossref","first-page":"e2537905","DOI":"10.1001\/jamanetworkopen.2025.37905","article-title":"Geographic and temporal patterns of screening for breast, cervical, and colorectal cancer in the US, 1997\u20132019","volume":"8","author":"P Pradhan","year":"2025","journal-title":"JAMA Netw Open"},{"issue":"10","key":"ref6","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.jacr.2010.06.013","article-title":"Managing incidental findings on abdominal CT: white paper of the ACR incidental findings committee","volume":"7","author":"L L Berland","year":"2010","journal-title":"J Am Coll Radiol"},{"issue":"08","key":"ref7","doi-asserted-by":"crossref","first-page":"588","DOI":"10.7326\/0003-4819-158-8-201304160-00003","article-title":"Opportunistic screening for osteoporosis using abdominal computed tomography scans obtained for other indications","volume":"158","author":"P J Pickhardt","year":"2013","journal-title":"Ann Intern Med"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"20180726","DOI":"10.1259\/bjr.20180726","article-title":"Population-based opportunistic osteoporosis screening: validation of a fully automated CT tool for assessing longitudinal BMD changes","volume":"92","author":"P J Pickhardt","year":"2019","journal-title":"Br J Radiol"},{"issue":"01","key":"ref9","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.mayocpiqo.2023.08.005","article-title":"The burden of chronic disease","volume":"8","author":"K Hacker","year":"2024","journal-title":"Mayo Clin Proc Innov Qual Outcomes"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"E15","DOI":"10.5888\/pcd22.240539","article-title":"Trends in multiple chronic conditions among US adults, by life stage, Behavioral Risk Factor Surveillance System, 2013\u20132023","volume":"22","author":"K B Watson","year":"2025","journal-title":"Prev Chronic Dis"},{"issue":"01","key":"ref12","doi-asserted-by":"crossref","first-page":"e243525","DOI":"10.1148\/radiol.243525","article-title":"Sarcopenia, obesity, and sarcopenic obesity: retrospective audit of electronic health record documentation versus automated CT analysis in 17\u2009646 patients","volume":"315","author":"J M Zambrano Chaves","year":"2025","journal-title":"Radiology"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.jpeds.2021.03.016","article-title":"Under-reporting of hepatic steatosis in children: a missed opportunity for early detection","volume":"234","author":"H Okura","year":"2021","journal-title":"J Pediatr"},{"issue":"04","key":"ref14","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1007\/s00256-025-05084-0","article-title":"Cost-effectiveness of opportunistic CT versus clinical methods for sarcopenia screening","volume":"55","author":"J Padwal","year":"2026","journal-title":"Skeletal Radiol"},{"issue":"03","key":"ref15","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.jacr.2024.10.003","article-title":"Quantifying the opportunity and economic value of bone density screening using opportunistic CT: a Medicare database analysis","volume":"22","author":"S Gyftopoulos","year":"2025","journal-title":"J Am Coll Radiol"},{"issue":"03","key":"ref16","first-page":"1181","article-title":"AI-based opportunistic CT screening of incidental cardiovascular disease, osteoporosis, and sarcopenia: cost-effectiveness analysis","volume":"48","author":"P J Pickhardt","year":"2023","journal-title":"Abdom Radiol (NY)"},{"issue":"01","key":"ref17","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1186\/s13244-020-00941-z","article-title":"Radiology in the era of value-based healthcare: a multi-society expert statement from the ACR, CAR, ESR, IS3R, RANZCR, and RSNA","volume":"11","author":"A P Brady","year":"2020","journal-title":"Insights Imaging"},{"issue":"01","key":"ref18","doi-asserted-by":"crossref","first-page":"85","DOI":"10.2214\/AJR.20.23049","article-title":"Utilizing fully automated abdominal CT-based biomarkers for opportunistic screening for metabolic syndrome in adults without symptoms","volume":"216","author":"P J Pickhardt","year":"2021","journal-title":"AJR Am J Roentgenol"},{"issue":"02","key":"ref19","doi-asserted-by":"crossref","first-page":"e250917","DOI":"10.1148\/radiol.250917","article-title":"Deep learning-based opportunistic CT osteoporosis screening and the establishment of normative values","volume":"317","author":"M Westerhoff","year":"2025","journal-title":"Radiology"},{"issue":"05","key":"ref20","doi-asserted-by":"crossref","first-page":"e230024","DOI":"10.1148\/ryai.230024","article-title":"TotalSegmentator: robust segmentation of 104 anatomic structures in CT images","volume":"5","author":"J Wasserthal","year":"2023","journal-title":"Radiol Artif Intell"},{"issue":"11","key":"ref22","doi-asserted-by":"crossref","first-page":"818","DOI":"10.7326\/M15-1361","article-title":"Treatment of low bone density or osteoporosis to prevent fractures in men and women: a clinical practice guideline update from the American College of Physicians","volume":"166","author":"A Qaseem","year":"2017","journal-title":"Ann Intern Med"},{"issue":"10","key":"ref23","doi-asserted-by":"crossref","first-page":"1881","DOI":"10.1002\/jbmr.4417","article-title":"Racial and ethnic disparities in bone health and outcomes in the United States","volume":"36","author":"S E Noel","year":"2021","journal-title":"J Bone Miner Res"},{"issue":"03","key":"ref24","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.amjmed.2016.10.018","article-title":"Trends and disparities in osteoporosis screening among women in the United States, 2008\u20132014","volume":"130","author":"C W Gillespie","year":"2017","journal-title":"Am J Med"},{"issue":"20","key":"ref25","first-page":"2185","article-title":"Hip fracture management: tailoring care for the older patient","volume":"307","author":"W W Hung","year":"2012","journal-title":"JAMA"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"117176","DOI":"10.1016\/j.bone.2024.117176","article-title":"AI-based opportunistic quantitative image analysis of lung cancer screening CTs to reduce disparities in osteoporosis screening","volume":"186","author":"F A Huber","year":"2024","journal-title":"Bone"},{"issue":"02","key":"ref27","doi-asserted-by":"crossref","first-page":"e240050","DOI":"10.1148\/ryai.240050","article-title":"Evaluating Skellytour for automated skeleton segmentation from whole-body CT images","volume":"7","author":"D C Mann","year":"2025","journal-title":"Radiol Artif Intell"},{"issue":"01","key":"ref30","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1093\/ageing\/afy169","article-title":"Sarcopenia: revised European consensus on definition and diagnosis","volume":"48","author":"A J Cruz-Jentoft","year":"2019","journal-title":"Age Ageing"},{"issue":"03","key":"ref31","first-page":"e22","article-title":"Body composition predictors of adverse postoperative events in patients undergoing surgery for long bone metastases","volume":"6","author":"P K Twining","year":"2022","journal-title":"J Am Acad Orthop Surg Glob Res Rev"},{"issue":"05","key":"ref32","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1002\/jso.26793","article-title":"Body composition predictors of mortality in patients undergoing surgery for long bone metastases","volume":"125","author":"O Q Groot","year":"2022","journal-title":"J Surg Oncol"},{"issue":"04","key":"ref33","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.spinee.2021.10.011","article-title":"Body composition predictors of mortality on CT in patients with spinal metastases undergoing surgical treatment","volume":"22","author":"M ER Bongers","year":"2022","journal-title":"Spine J Off J North Am Spine Soc"},{"issue":"09","key":"ref34","doi-asserted-by":"crossref","first-page":"e0184780","DOI":"10.1371\/journal.pone.0184780","article-title":"Sarcopenia in patients with hip fracture: a multicenter cross-sectional study","volume":"12","author":"O M Steihaug","year":"2017","journal-title":"PLoS One"},{"issue":"01","key":"ref35","doi-asserted-by":"crossref","first-page":"124","DOI":"10.2214\/AJR.21.26486","article-title":"Fully Automated deep learning tool for sarcopenia assessment on CT: L1 versus L3 vertebral level muscle measurements for opportunistic prediction of adverse clinical outcomes","volume":"218","author":"P J Pickhardt","year":"2022","journal-title":"AJR Am J Roentgenol"},{"issue":"10","key":"ref36","doi-asserted-by":"crossref","first-page":"2238","DOI":"10.1038\/s41366-021-00907-1","article-title":"Body composition predictors of outcome in patients with COVID-19","volume":"45","author":"K M Bunnell","year":"2021","journal-title":"Int J Obes"},{"issue":"12","key":"ref37","doi-asserted-by":"crossref","first-page":"e065425","DOI":"10.1136\/bmjopen-2022-065425","article-title":"Trends in body mass index, overweight and obesity among adults in the USA, the NHANES from 2003 to 2018: a repeat cross-sectional survey","volume":"12","author":"M Li","year":"2022","journal-title":"BMJ Open"},{"issue":"08","key":"ref38","doi-asserted-by":"crossref","first-page":"e347","DOI":"10.1161\/CIR.0000000000001209","article-title":"2024 heart disease and stroke statistics: a report of US and global data from the American Heart Association","volume":"149","author":"S S Martin","year":"2024","journal-title":"Circulation"},{"issue":"18","key":"ref39","doi-asserted-by":"crossref","first-page":"1996","DOI":"10.1161\/CIR.0b013e318233bc6a","article-title":"Assessing adiposity: a scientific statement from the American Heart Association","volume":"124","author":"M A Cornier","year":"2011","journal-title":"Circulation"},{"issue":"01","key":"ref40","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1038\/oby.2009.180","article-title":"Impacts of visceral adipose tissue and subcutaneous adipose tissue on metabolic risk factors in middle-aged Japanese","volume":"18","author":"R Oka","year":"2010","journal-title":"Obesity (Silver Spring)"},{"issue":"05","key":"ref41","doi-asserted-by":"crossref","first-page":"e230146","DOI":"10.1148\/ryct.230146","article-title":"Predictive value of deep learning-derived CT pectoralis muscle and adipose measurements for incident heart failure: multi-ethnic study of atherosclerosis","volume":"5","author":"Q Hathaway","year":"2023","journal-title":"Radiol Cardiothorac Imaging"},{"issue":"02","key":"ref42","doi-asserted-by":"crossref","first-page":"e13845","DOI":"10.1111\/obr.13845","article-title":"Causality of visceral adipose tissue on chronic kidney disease and renal function measure indicators, and mediation role of hypertension: Mendelian randomization study","volume":"26","author":"T Y Gao","year":"2025","journal-title":"Obes Rev"},{"issue":"03","key":"ref43","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1002\/cld.1183","article-title":"Nonalcoholic fatty liver disease: the role of visceral adipose tissue","volume":"19","author":"C L Hanlon","year":"2022","journal-title":"Clin Liver Dis (Hoboken)"},{"issue":"02","key":"ref44","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1007\/s10549-019-05467-7","article-title":"Quality and quantity of visceral fat tissue are associated with insulin resistance and survival outcomes after chemotherapy in patients with breast cancer","volume":"179","author":"T Iwase","year":"2020","journal-title":"Breast Cancer Res Treat"},{"issue":"10","key":"ref45","doi-asserted-by":"crossref","first-page":"2622","DOI":"10.1007\/s00125-012-2639-5","article-title":"The ratio of visceral to subcutaneous fat, a metric of body fat distribution, is a unique correlate of cardiometabolic risk","volume":"55","author":"B M Kaess","year":"2012","journal-title":"Diabetologia"},{"issue":"05","key":"ref46","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1139\/H08-075","article-title":"A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care","volume":"33","author":"M Mourtzakis","year":"2008","journal-title":"Appl Physiol Nutr Metab"},{"issue":"09","key":"ref47","doi-asserted-by":"crossref","first-page":"3357","DOI":"10.3390\/s22093357","article-title":"Concordance of computed tomography regional body composition analysis using a fully automated open-source neural network versus a reference semi-automated program with manual correction","volume":"22","author":"S L Gomez-Perez","year":"2022","journal-title":"Sensors (Basel)"},{"issue":"11","key":"ref48","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1016\/j.acra.2020.07.010","article-title":"Deep learning-based quantification of abdominal subcutaneous and visceral fat volume on CT images","volume":"28","author":"A T Grainger","year":"2021","journal-title":"Acad Radiol"},{"issue":"04","key":"ref49","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.jacc.2018.05.027","article-title":"Coronary calcium score and cardiovascular risk","volume":"72","author":"P Greenland","year":"2018","journal-title":"J Am Coll Cardiol"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.ahj.2025.04.019","article-title":"Opportunistic assessment of abdominal aortic calcification using artificial intelligence (AI) predicts coronary artery disease and cardiovascular events","volume":"288","author":"J S Berger","year":"2025","journal-title":"Am Heart J"},{"key":"ref51","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.atherosclerosis.2017.01.029","article-title":"Calcification of the splenic, iliac, and breast arteries and risk of all-cause and cardiovascular mortality","volume":"259","author":"E J Hendriks","year":"2017","journal-title":"Atherosclerosis"},{"issue":"02","key":"ref52","doi-asserted-by":"crossref","first-page":"173","DOI":"10.2214\/AJR.22.28954","article-title":"Opportunistic imaging: counterpoint-overdiagnosis and unclear benefit to individual patients, new inefficiencies in medical care and costs, and time-related biases","volume":"221","author":"V Kalia","year":"2023","journal-title":"AJR Am J Roentgenol"},{"issue":"05","key":"ref53","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.2214\/AJR.12.10037","article-title":"CT Hounsfield numbers of soft tissues on unenhanced abdominal CT scans: variability between two different manufacturers' MDCT scanners","volume":"203","author":"R Lamba","year":"2014","journal-title":"AJR Am J Roentgenol"},{"issue":"04","key":"ref54","first-page":"303","article-title":"The future of multimodal artificial intelligence models for integrating imaging and clinical metadata: a narrative review","volume":"31","author":"B D Simon","year":"2025","journal-title":"Diagn Interv Radiol"},{"issue":"03","key":"ref55","doi-asserted-by":"crossref","first-page":"e242362","DOI":"10.1148\/radiol.242362","article-title":"The financial, operational, and clinical advantages of generalist radiology AI","volume":"316","author":"S Dogra","year":"2025","journal-title":"Radiology"},{"issue":"01","key":"ref56","doi-asserted-by":"crossref","first-page":"4039","DOI":"10.1038\/s41467-023-39631-x","article-title":"Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs","volume":"14","author":"A Pyrros","year":"2023","journal-title":"Nat Commun"},{"issue":"02","key":"ref57","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1038\/s41571-021-00560-7","article-title":"Predicting cancer outcomes with radiomics and artificial intelligence in radiology","volume":"19","author":"K Bera","year":"2022","journal-title":"Nat Rev Clin Oncol"}],"container-title":["Seminars in Musculoskeletal Radiology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2811-6756.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T22:59:32Z","timestamp":1784588372000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2811-6756"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,12]]},"references-count":52,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2026,7,20]]},"published-print":{"date-parts":[[2026,8]]}},"URL":"https:\/\/doi.org\/10.1055\/a-2811-6756","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["1089-7860","1098-898X"],"issn-type":[{"value":"1089-7860","type":"print"},{"value":"1098-898X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,12]]}}}