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- Publisher Website: 10.1007/s00198-024-07047-y
- Scopus: eid_2-s2.0-85186851112
- PMID: 38459138
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Article: Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation
Title | Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation |
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Authors | |
Keywords | Bone mineral density Humeral proximal Phantom-less QCT |
Issue Date | 9-Mar-2024 |
Publisher | Springer |
Citation | Osteoporosis International, 2024, v. 35, n. 6, p. 1049-1059 How to Cite? |
Abstract | Purpose: This study aimed to apply a newly developed semi-automatic phantom-less QCT (PL-QCT) to measure proximal humerus trabecular bone density based on chest CT and verify its accuracy and precision. Methods: Subcutaneous fat of the shoulder joint and trapezius muscle were used as calibration references for PL-QCT BMD measurement. A self-developed algorithm based on a convolution map was utilized in PL-QCT for semi-automatic BMD measurements. CT values of ROIs used in PL-QCT measurements were directly used for phantom-based quantitative computed tomography (PB-QCT) BMD assessment. The study included 376 proximal humerus for comparison between PB-QCT and PL-QCT. Two sports medicine doctors measured the proximal humerus with PB-QCT and PL-QCT without knowing each other’s results. Among them, 100 proximal humerus were included in the inter-operative and intra-operative BMD measurements for evaluating the repeatability and reproducibility of PL-QCT and PB-QCT. Results: A total of 188 patients with 376 shoulders were involved in this study. The consistency analysis indicated that the average bias between proximal humerus BMDs measured by PB-QCT and PL-QCT was 1.0 mg/cc (agreement range – 9.4 to 11.4; P > 0.05, no significant difference). Regression analysis between PB-QCT and PL-QCT indicated a good correlation (R-square is 0.9723). Short-term repeatability and reproducibility of proximal humerus BMDs measured by PB-QCT (CV: 5.10% and 3.41%) were slightly better than those of PL-QCT (CV: 6.17% and 5.64%). Conclusions: We evaluated the bone quality of the proximal humeral using chest CT through the semi-automatic PL-QCT system for the first time. Comparison between it and PB-QCT indicated that it could be a reliable shoulder BMD assessment tool with acceptable accuracy and precision. Summary: This study developed and verify a semi-automatic PL-QCT for assessment of proximal humeral bone density based on CT to assist in the assessment of proximal humeral osteoporosis and development of individualized treatment plans for shoulders. |
Persistent Identifier | http://hdl.handle.net/10722/347275 |
ISSN | 2023 Impact Factor: 4.2 2023 SCImago Journal Rankings: 1.111 |
DC Field | Value | Language |
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dc.contributor.author | Guo, De Ming | - |
dc.contributor.author | Weng, Yuan Zhi | - |
dc.contributor.author | Yu, Ze Hao | - |
dc.contributor.author | Li, Shi Huai | - |
dc.contributor.author | Qu, Wen Rui | - |
dc.contributor.author | Liu, Xiao Ning | - |
dc.contributor.author | Qi, Huan | - |
dc.contributor.author | Ma, Chi | - |
dc.contributor.author | Tang, Xiong Feng | - |
dc.contributor.author | Li, Rui Yan | - |
dc.contributor.author | Han, Qinghe | - |
dc.contributor.author | Xu, Hao | - |
dc.contributor.author | Lu, Weijia William | - |
dc.contributor.author | Qin, Yan Guo | - |
dc.date.accessioned | 2024-09-20T00:31:08Z | - |
dc.date.available | 2024-09-20T00:31:08Z | - |
dc.date.issued | 2024-03-09 | - |
dc.identifier.citation | Osteoporosis International, 2024, v. 35, n. 6, p. 1049-1059 | - |
dc.identifier.issn | 0937-941X | - |
dc.identifier.uri | http://hdl.handle.net/10722/347275 | - |
dc.description.abstract | <p>Purpose: This study aimed to apply a newly developed semi-automatic phantom-less QCT (PL-QCT) to measure proximal humerus trabecular bone density based on chest CT and verify its accuracy and precision. Methods: Subcutaneous fat of the shoulder joint and trapezius muscle were used as calibration references for PL-QCT BMD measurement. A self-developed algorithm based on a convolution map was utilized in PL-QCT for semi-automatic BMD measurements. CT values of ROIs used in PL-QCT measurements were directly used for phantom-based quantitative computed tomography (PB-QCT) BMD assessment. The study included 376 proximal humerus for comparison between PB-QCT and PL-QCT. Two sports medicine doctors measured the proximal humerus with PB-QCT and PL-QCT without knowing each other’s results. Among them, 100 proximal humerus were included in the inter-operative and intra-operative BMD measurements for evaluating the repeatability and reproducibility of PL-QCT and PB-QCT. Results: A total of 188 patients with 376 shoulders were involved in this study. The consistency analysis indicated that the average bias between proximal humerus BMDs measured by PB-QCT and PL-QCT was 1.0 mg/cc (agreement range – 9.4 to 11.4; P > 0.05, no significant difference). Regression analysis between PB-QCT and PL-QCT indicated a good correlation (R-square is 0.9723). Short-term repeatability and reproducibility of proximal humerus BMDs measured by PB-QCT (CV: 5.10% and 3.41%) were slightly better than those of PL-QCT (CV: 6.17% and 5.64%). Conclusions: We evaluated the bone quality of the proximal humeral using chest CT through the semi-automatic PL-QCT system for the first time. Comparison between it and PB-QCT indicated that it could be a reliable shoulder BMD assessment tool with acceptable accuracy and precision. Summary: This study developed and verify a semi-automatic PL-QCT for assessment of proximal humeral bone density based on CT to assist in the assessment of proximal humeral osteoporosis and development of individualized treatment plans for shoulders.</p> | - |
dc.language | eng | - |
dc.publisher | Springer | - |
dc.relation.ispartof | Osteoporosis International | - |
dc.subject | Bone mineral density | - |
dc.subject | Humeral proximal | - |
dc.subject | Phantom-less QCT | - |
dc.title | Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/s00198-024-07047-y | - |
dc.identifier.pmid | 38459138 | - |
dc.identifier.scopus | eid_2-s2.0-85186851112 | - |
dc.identifier.volume | 35 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 1049 | - |
dc.identifier.epage | 1059 | - |
dc.identifier.eissn | 1433-2965 | - |
dc.identifier.issnl | 0937-941X | - |