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Huang X, Luo M, Liu L, Wu D, You X, Deng Z, Xiu P, Yang X, Zhou C, Feng G, Wang L, Zhou Z, Fan J, He M, Gao Z, Pu L, Wu Z, Zhou Z, Song Y, Huang S. The Comparison of Convolutional Neural Networks and the Manual Measurement of Cobb Angle in Adolescent Idiopathic Scoliosis. Global Spine J 2024; 14:159-168. [PMID: 35622711 PMCID: PMC10676172 DOI: 10.1177/21925682221098672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
STUDY DESIGN Comparative study. OBJECTIVE To compare manual and deep learning-based automated measurement of Cobb angle in adolescent idiopathic scoliosis. METHODS We proposed a fully automated framework to measure the Cobb angle of AIS patients. Whole-spine images of 500 AIS individuals were collected. 200 digital radiographic (DR) images were labeled manually as training set, and the remaining 300 images were used to validate by mean absolute error (MAE), Pearson or spearman correlation coefficients, and intra/interclass correlation coefficients (ICCs). The relationship between accuracy of vertebral boundary identification and the subjective image quality score was evaluated. RESULTS The PT, MT, and TL/L Cobb angles were measured by the automated framework within 300 milliseconds. Remarkable 2.92° MAE, .967 ICC, and high correlation coefficient (r = .972) were obtained for the major curve. The MAEs of PT, MT, and TL/L were 3.04°, 2.72°, and 2.53°, respectively. The ICCs of these 3 curves were .936, .977, and .964, respectively. 88.7% (266/300) of cases had a difference range of ±5°, with 84.3% (253/300) for PT, 89.7% (269/300) for MT, and 93.0% (279/300) for TL/L. The decreased bone/soft tissue contrast (2.94 vs 3.26; P=.039) and bone sharpness (2.97 vs 3.35; P=.029) were identified in the images with MAE exceeding 5°. CONCLUSION The fully automated framework not only identifies the vertebral boundaries, vertebral sequences, the upper/lower end vertebras and apical vertebra, but also calculates the Cobb angle of PT, MT, and TL/L curves sequentially. The framework would shed new light on the assessment of AIS curvature.
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Affiliation(s)
- Xianming Huang
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Ming Luo
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Department of Spine Surgery and Musculoskeletal Tumor, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China
- Key Laboratory of Big Data for Spinal Deformities, Chinese Academy of Medical Sciences, Beijing, China
| | - Limin Liu
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Diwei Wu
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Xuanhe You
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Zhipeng Deng
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Peng Xiu
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Xi Yang
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Chunguang Zhou
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Ganjun Feng
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Lei Wang
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Zhongjie Zhou
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Jipeng Fan
- Chengdu Chengdian Goldisc Health Data Technology Co., Ltd, Chengdu, China
| | - Mingjie He
- Chengdu Chengdian Goldisc Health Data Technology Co., Ltd, Chengdu, China
| | - Zhongjun Gao
- Chengdu Chengdian Goldisc Health Data Technology Co., Ltd, Chengdu, China
| | - Lixin Pu
- Chengdu Chengdian Goldisc Health Data Technology Co., Ltd, Chengdu, China
- School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhihong Wu
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
- Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Beijing, China
| | - Zongke Zhou
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Yueming Song
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Shishu Huang
- Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
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