{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T01:53:56Z","timestamp":1781747636709,"version":"3.54.5"},"reference-count":30,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T00:00:00Z","timestamp":1781654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Tomography"],"abstract":"<jats:p>Objectives: To evaluate the diagnostic performance of automated vertebral trabecular Hounsfield unit (HU) measurements derived from routine fluorodeoxyglucose positron emission tomography\/computed tomography (FDG PET\/CT) for identifying low bone density. Methods: This retrospective study included 131 consecutive women (mean age, 53.5 \u00b1 9.6 years) undergoing health screening with FDG PET\/CT and dual-energy X-ray absorptiometry (DXA) between January 2020 and December 2024. A deep learning-based model (TotalSegmentator) automatically segmented the lumbar vertebrae (L1\u2013L4). HU-based metrics in trabecular regions were calculated, and their correlations with DXA-derived bone mineral density (BMD) were assessed. Diagnostic performance was evaluated using receiver operating characteristic analysis. A multivariable logistic regression model incorporating mean HU, age, and body mass index was developed and internally validated using bootstrap resampling. Results: According to WHO criteria, 47 of 131 participants (35.9%) had low bone density. Mean HU demonstrated strong diagnostic performance (area under the curve [95% confidence interval]: L1, 0.861 [0.800\u20130.923]; L2, 0.852 [0.788\u20130.915]; L3, 0.861 [0.800\u20130.921]; L4, 0.845 [0.781\u20130.909]). L1 mean HU provided the most balanced performance (sensitivity, 0.851; specificity, 0.750); L3 mean HU was slightly inferior. L1 mean HU was strongly correlated with BMD (r = 0.821, p &lt; 0.001). In multivariable analysis, mean HU independently predicted low bone density (odds ratio: 0.949, p &lt; 0.001). The model achieved an accuracy of 0.786 and demonstrated favorable calibration performance. Conclusions: The automated assessment of vertebral trabecular HU from routine FDG PET\/CT provides a reliable and highly efficient method for screening low bone density without additional radiation exposure or cost.<\/jats:p>","DOI":"10.3390\/tomography12060089","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T00:49:42Z","timestamp":1781743782000},"page":"89","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Opportunistic Screening for Low Bone Density Using Automated Vertebral Trabecular CT Attenuation from Low-Dose CT Acquired During FDG PET\/CT: A Single-Center Retrospective Study"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5352-9425","authenticated-orcid":false,"given":"Hyun-Kyeong","family":"Yuk","sequence":"first","affiliation":[{"name":"Department of Radiology, Daejeon Eulji Medical Center, Daejeon 35233, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6916-3375","authenticated-orcid":false,"given":"Sung-Hoon","family":"Oh","sequence":"additional","affiliation":[{"name":"Department of Radiology, Daejeon Eulji Medical Center, Daejeon 35233, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3703-9796","authenticated-orcid":false,"given":"Do-Hoon","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon 35233, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/S0140-6736(18)32112-3","article-title":"Osteoporosis","volume":"393","author":"Compston","year":"2019","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s00198-018-4704-5","article-title":"European guidance for the diagnosis and management of osteoporosis in postmenopausal women","volume":"30","author":"Kanis","year":"2019","journal-title":"Osteoporos. 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