{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T03:26:02Z","timestamp":1793676362515,"version":"4.5.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"13","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Anna Marie and Christian Rasmussen\u2019s Memorial Foundation","award":["Anna Marie and Christian Rasmussen\u2019s Memorial Foundation"],"award-info":[{"award-number":["Anna Marie and Christian Rasmussen\u2019s Memorial Foundation"]}]},{"name":"J\u00f8rgen and Gisela Thrane\u2019s Philanthropic Research Foundation","award":["J\u00f8rgen and Gisela Thrane\u2019s Philanthropic Research Foundation"],"award-info":[{"award-number":["J\u00f8rgen and Gisela Thrane\u2019s Philanthropic Research Foundation"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Nucl Med Mol Imaging"],"published-print":{"date-parts":[[2026,11]]},"abstract":"Abstract<\/jats:title>\n \n Purpose<\/jats:title>\n \n Manual quantification of joint metabolism and inflammation with PET is time-consuming and difficult to standardize due to ambiguous joint boundaries. We aimed to develop an automatic joint segmentation method that efficiently and reliably quantifies activity in weight-bearing joints using [\n 18<\/jats:sup>\n F]fluorodeoxyglucose (FDG) and sodium [\n 18<\/jats:sup>\n F]fluoride (NaF) PET\/computed tomography (PET\/CT).\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Segmentations were generated from CT scans using the TotalSegmentator model. From these, 30 weight-bearing joints were segmented by identifying the region between adjacent bones within a set distance threshold. Scans of healthy volunteers were analyzed (75 with FDG, 80 with NaF). Mean standardized uptake value (SUVmean) was calculated for each joint region, and Pearson correlation analysis was used to evaluate relationships with age and body mass index (BMI). Benjamini\u2013Hochberg false discovery rate (FDR) correction was applied within each tracer\u2013covariate family.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The automated approach reduced segmentation time from 30 to ~\u20091.5\u00a0min per scan. Joint ROI volumes generated independently from the two PET\/CT sessions of the same participant were highly concordant (median\n r<\/jats:italic>\n \u2009=\u20090.98, median intraclass correlation coefficient 0.94). After false discovery rate correction, NaF uptake was positively correlated with BMI in the thoracic (T3-T6, T7-T8, T9-T11) and lumbosacral (L5-S1) intervertebral discs (IVDs) and in the sacroiliac (SI), hip and knee joints, and positively with age in the cervical IVDs (C1-C2, C3-C7), with negative age correlations at T4-T5, T6-T7, L1-L2 and in both SI joints (all q\u2009<\u20090.05). FDG uptake was positively correlated with BMI in the IVDs from C1-T6 (other than T1-T2) and T9-S1, in both SI joints, the left hip and both knees, and with age in both knees, and negatively with age at T2-T3 and in both SI joints (all q\u2009<\u20090.05). Associations meeting\n p<\/jats:italic>\n \u2009<\u20090.05 but not q\u2009<\u20090.05 are identified in Tables\u00a02, 3, 4 and 5. The positive cervical NaF-age associations arise in the only joints where SUVmean was appreciably correlated with ROI size and are therefore reported as provisional.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n Our segmentation approach rapidly quantifies joint metabolism and revealed significant associations between PET tracer uptake, BMI, and age. It offers a standardized framework for future PET\/CT joint analysis.<\/jats:p>\n <\/jats:sec>\n \n Clinical trial registration<\/jats:title>\n \n Cardiovascular Molecular Calcification Assessed by 18\u00a0F-NaF PET\/CT (CAMONA), ClinicalTrials.gov NCT01724749.\n https:\/\/clinicaltrials.gov\/study\/NCT01724749<\/jats:ext-link>\n .\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1007\/s00259-026-08139-z","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T02:50:29Z","timestamp":1787280629000},"page":"7715-7728","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automated joint segmentation enables quantitative molecular imaging of degeneration with [\u00b9\u2078F]FDG and [\u00b9\u2078F]NaF PET\/CT"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4156-4449","authenticated-orcid":false,"given":"William K.","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiv","family":"Patil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darshil H.","family":"Patel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuorui","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ondrej","family":"Fanta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Om H.","family":"Gandhi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas J.","family":"Werner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Poul F.","family":"H\u00f8ilund-Carlsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2442-7901","authenticated-orcid":false,"given":"Abass","family":"Alavi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,21]]},"reference":[{"key":"8139_CR1","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.arr.2017.07.004","volume":"40","author":"M Rahmati","year":"2017","unstructured":"Rahmati M, Nalesso G, Mobasheri A, Mozafari M. 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