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2024, Vol. 28 ›› Issue (33): 5370-5374

Feasibility of constructing a diagnostic classification model for cervical instability by magnetic resonance imaging radiomics

Lu Guangqi, Cui Ying, Li Jing, Yu Zhangjingze, Zhu Liguo, Yu Jie, Zhuang Minghui   

  1. Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing 100102, China

  • Received:2023-08-04 Accepted:2023-10-28 Online:2024-11-28 Published:2024-01-30

  • Contact: Yu Jie, Chief physician, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing 100102, China Zhuang Minghui, Attending physician, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing 100102, China

  • About author:Lu Guangqi, Master candidate, Physician, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing 100102, China

  • Supported by:

    Clinical Diagnosis and Treatment Technology Research and Transformation Application Project of Beijing Science and Technology Plan, No. Z211100002921023 (to YJ); National Natural Science Foundation of China, No. 82074455 (to YJ); Key Research Project of Science and Technology Innovation Project of China Academy of Chinese Medical Sciences, No. CI2021A02002 (to YJ)


Abstract: BACKGROUND: Previous studies on cervical instability failed to explain the dynamic and static interaction relationship and pathological characteristics changes in the development of cervical lesions under the traditional imaging examination. In recent years, the emerging nuclear magnetic resonance imaging (MRI) radiomics can provide a new way for in-depth research on cervical instability.
OBJECTIVE: To investigate the application value of MRI radiomics in the study of cervical instability.
METHODS: Through recruitment advertisements and the Second Department of Spine of Wangjing Hospital, China Academy of Chinese Medical Sciences, young cervical vertebra unstable subjects and non-unstable subjects aged 18-45 years were included in the cervical vertebra nuclear magnetic image collection. Five specific regions of interest, including the intervertebral disc region, the facet region, the prevertebral muscle region, the deep region of the posterior cervical muscle group, and the superficial region of the posterior cervical muscle group, were manually segmented to extract and screen the image features. Finally, the cervical instability diagnosis classification model was constructed, and the effectiveness of the model was evaluated using the area under the curve.
RESULTS AND CONCLUSION: (1) A total of 56 subjects with cervical instability and 55 subjects with non-instability were included, and 1 688 imaging features were extracted for each region of interest. After screening, 300 sets of specific image feature combinations were obtained, with 60 sets of regions of interest for each group. (2) Five regions of interest diagnostic classification models for cervical instability were initially established. Among them, the support vector machine model for the articular process region and the support vector machine model for the deep cervical muscle group had certain accuracy for the classification of instability and non-instability, and the average area under the curve of ten-fold cross-validation was 0.719 7 and 0.703 3, respectively. (3) The Logistic model in the intervertebral disc region, the LightGBM model in the prevertebral muscle region, and the Logistic model in the superficial posterior cervical muscle region were generally accurate in the classification of instability and non-instability, and the average area under the curve of ten-fold cross-validation was 0.650 4, 0.620 7, and 0.644 2, respectively. (4) This study proved the feasibility of MRI radiomics in the study of cervical instability, further deepened the understanding of the pathogenesis of cervical instability, and also provided an objective basis for the accurate diagnosis of cervical instability.

Key words: cervical instability, MRI radiomics, diagnostic classification model, region of interest, area under the curve


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