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ArticleOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2025

Age- and sex-related changes in proximal humeral volumetric BMD assessed via chest CT with a deep learning-based segmentation model.

Shihuai Li, Chong Tang, Hongda Zhang, Chi Ma, Yuanzhi Weng, Bo Chen, Shenghao Xu, Hao Xu, Fausto Giunchiglia, Weijia William Lu and 2 more

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Article in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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12 authors.

Shihuai LiOrthopedic Medical Center, The Second Hospital of Jilin University, 4026 Yatai Street, Changchun, 130041, China.
Chong TangCollege of Computer Science and Technology, Jilin University, Changchun, China.
Hongda ZhangCollege of Computer Science and Technology, Jilin University, Changchun, China.
Chi MaOrthopedic and Traumatology, The University of Hong Kong, Hong Kong, China.
Yuanzhi WengOrthopedic and Traumatology, The University of Hong Kong, Hong Kong, China.
Bo ChenOrthopedic Medical Center, The Second Hospital of Jilin University, 4026 Yatai Street, Changchun, 130041, China.
Shenghao XuOrthopedic Medical Center, The Second Hospital of Jilin University, 4026 Yatai Street, Changchun, 130041, China.
Hao XuCollege of Computer Science and Technology, Jilin University, Changchun, China.
Fausto GiunchigliaDipartimento Di Ingegneria E Scienza Dell'Informazione, University of Trento, Trento, Italy.
Weijia William LuOrthopedic and Traumatology, The University of Hong Kong, Hong Kong, China.
Deming GuoOrthopedic Medical Center, The Second Hospital of Jilin University, 4026 Yatai Street, Changchun, 130041, China. guodm91@jlu.edu.cn.ORCID http://orcid.org/0009-0009-7919-076X
Yanguo QinOrthopedic Medical Center, The Second Hospital of Jilin University, 4026 Yatai Street, Changchun, 130041, China. qinyg@jlu.edu.cn.

Funding

Jilin Scientific and Technological Development Program 20230204075YYJilin Scientific and Technological Development Program 20240305034YYthe Key Project of the National Natural Science Foundation of China U21A20390the Scientific and Technological Research Project of Jilin Provincial Department of Education JJKH20250174KJthe Special Foundation for Science and Technology Innovation of Jilin Province YDZJ202501ZYTS090
6 · The paper itself

Abstract

Accurate assessment of proximal humeral volumetric bone mineral density (vBMD) is essential for surgical planning in shoulder pathology. However, age-related changes in proximal humeral vBMD remain poorly characterized. This study developed a deep learning-based method to assess proximal humeral vBMD and identified sex-specific age-related changes. It also demonstrated that lumbar spine vBMD is not a valid substitute. PURPOSE: This study aimed to develop a deep learning-based method for proximal humeral vBMD assessment and to investigate its age- and sex-related changes, as well as its correlation with lumbar spine vBMD.

methodsAn nnU-Net-based deep learning pipeline was developed to automatically segment the proximal humerus on chest CT scans from 2,675 adults. Segmentation performance was assessed using the Dice Similarity Coefficient (DSC), Intersection over Union (IoU), 95th-percentile Hausdorff Distance (95HD), and Average Symmetric Surface Distance (ASSD). Phantom-calibrated vBMD-total, trabecular, and BMAT-corrected trabecular-was quantified for each subject. Age-related distributions were modeled with generalized additive models for location, scale, and shape (GAMLSS) to generate sex-specific P3-P97 percentile curves. Lumbar spine vBMD was measured in 1460 individuals for correlation analysis.

resultsSegmentation was highly accurate (DSC 98.42 ± 0.20%; IoU 96.89 ± 0.42%; 95HD 1.12 ± 0.37 mm; ASSD 0.94 ± 0.31 mm). In males, total, trabecular, and BMAT-corrected trabecular vBMD declined approximately linearly from early adulthood. In females, a pronounced inflection occurred at ~ 40-45 years: values were stable or slightly rising beforehand, then all percentiles dropped steeply and synchronously, indicating accelerated menopause-related loss. In females, vBMD declined earlier in the lumbar spine than in the proximal humerus. Correlations between proximal humeral and lumbar spine vBMD were low to moderate overall and weakened after age 50.

conclusionWe present a novel, automated method for quantifying proximal humeral vBMD from chest CT, revealing distinct, sex-specific aging patterns. Males' humeral vBMD declines linearly, while females experience an earlier, accelerated loss. Moreover, the peak humeral vBMD in females occurs later than that of the lumbar spine, and spinal measurements cannot reliably substitute for humeral BMD in clinical assessment.

Indexed as

AgingBone DensityDeep LearningHumerusAdultAgedAged, 80 and overFemaleHumansLumbar VertebraeMaleMiddle AgedRadiography, ThoracicSex FactorsTomography, X-Ray ComputedYoung AdultBone mineral densityDeep learningLumbar spineOsteoporosisProximal humerus

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.