Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation

De-Ming Guo; Yuan-Zhi Weng; Ze-Hao Yu; Shi-Huai Li; Wen-Rui Qu; Xiao-Ning Liu; Huan Qi; Chi Ma; Xiong-Feng Tang; Rui-Yan Li; Qinghe Han; Hao Xu; Weijia William Lu; Yan-Guo Qin

doi:10.1007/s00198-024-07047-y

Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation

Osteoporos Int. 2024 Mar 9. doi: 10.1007/s00198-024-07047-y. Online ahead of print.

Authors

De-Ming Guo^#^{1

2

3}, Yuan-Zhi Weng^#⁴, Ze-Hao Yu^{1

2

3}, Shi-Huai Li^{1

2

3}, Wen-Rui Qu^{2

3

5}, Xiao-Ning Liu^{1

2}, Huan Qi⁶, Chi Ma⁴, Xiong-Feng Tang^{1

2

3}, Rui-Yan Li^{1

2

3}, Qinghe Han⁷, Hao Xu^{3

8}, Weijia William Lu⁹, Yan-Guo Qin^{10

11

12}

Affiliations

¹ Orthopaedic Medical Center, The Second Norman Bethune Hospital of Jilin University, Changchun, People's Republic of China.
² Jilin Provincial Key Laboratory of Orthopaedics, Changchun, People's Republic of China.
³ Joint International Research Laboratory of Ageing Active Strategy and Bionic Health in Northeast Asia of Ministry of Education, Jilin University, Changchun, 130041, Jilin Province, China.
⁴ Orthopaedic and Traumatology, The University of Hong Kong, Hong Kong, People's Republic of China.
⁵ Department of Hand Surgery, The Second Norman Bethune Hospital of Jilin University, Changchun, People's Republic of China.
⁶ Bone's Technology Limited, Shenzhen, Hong Kong, People's Republic of China.
⁷ Radiology Department, The Second Norman Bethune Hospital of Jilin University, Changchun, People's Republic of China.
⁸ College of Computer Science and Technology, Jilin University, Changchun, People's Republic of China.
⁹ Orthopaedic and Traumatology, The University of Hong Kong, Hong Kong, People's Republic of China. wwlu@hku.hk.
¹⁰ Orthopaedic Medical Center, The Second Norman Bethune Hospital of Jilin University, Changchun, People's Republic of China. qinyg@jlu.edu.cn.
¹¹ Jilin Provincial Key Laboratory of Orthopaedics, Changchun, People's Republic of China. qinyg@jlu.edu.cn.
¹² Joint International Research Laboratory of Ageing Active Strategy and Bionic Health in Northeast Asia of Ministry of Education, Jilin University, Changchun, 130041, Jilin Province, China. qinyg@jlu.edu.cn.

^# Contributed equally.

PMID: 38459138
DOI: 10.1007/s00198-024-07047-y

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. 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.

Keywords: Bone mineral density; Humeral proximal; Phantom-less QCT.

Abstract

Grants and funding