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Development of a multi-stage model for intelligent and quantitative appraising of skeletal maturity using cervical vertebras cone-beam CT images of Chinese girls

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Nowadays, the integration of Artificial intelligence algorithms and quantified radiographic imaging-based diagnostic procedures is hailing amplified deliberation particularly in assessment of skeletal maturity. So we intend to formulate a logistic regression model for intelligent and quantitative estimation of Fishman skeletal maturation index (SMI) based on the parameters attained from the cervical vertebrae CBCT images of Chinese girls.

Methods

From 709 hand wrist radiographs and CBCT images, 447 samples were randomly selected (called as G1) to build a logistic regression model. The reliability and reproducibility were assessed by the intraclass correlation coefficient (ICC) and weighted Cohen’s kappa, followed by Spearman’s rank correlation coefficient to identify the parameters significantly associated with the SMI. Two hundred and sixty-two other subjects (named G2) were recruited for external examination of the models by direct visual comparison and the receiver operating characteristic (ROC) curve. In cases of confusion and mispredictions, the model was modified to improve the consistency.

Results

Five significant parameters (Chronological age, C3 height (H3)\()\), C4 upper width (UW4), C4 lower width (LW4), and the ratio of posterior height to lower width of C4 (\(\mathrm{PH}4/\mathrm{LW}4)\)) were administered into logistic regression model. Despite total agreement percentage which was 84% (total AUC = 0.92), unsatisfactory performance was noticed for the 6th and 8th stages which were confused with their neighboring stages. After adjustments of the models, the total agreement percentage and AUC were upgraded to 88% and 0.96, respectively.

Conclusion

Consistency and fitness evaluation of our models demonstrated adequate prediction percentage and reliability for automated classification of skeletal maturation. The presented constructed logistic regression model has the potential to serve as a maturity evaluation index in clinical craniofacial orthopedics in Chinese girls. The proposed model in this study showed promising strength for being expended in the event of other clinical multi-stage conditions.

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Availability of data and material

The data that support the findings of this study are available on request from the corresponding author, [BY]. The data are not publicly available due to being currently used in another ongoing research project.

Code availability

Not applicable.

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Funding

This study is supported by National Natural Science Foundation of China (Grant no. 82071143 and no. 82101079), Key Medical Research Projects of Jiangsu Health Commission (ZDA2020003), Key R&D program of Jiangsu province (BE2018723), Natural Science Foundation of Jiangsu province (BK20180670), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD, 2018-87).

Author information

Author notes

  1. Lizhe Xie and Wen Tang contributed equally as the first author.

Authors and Affiliations

  1. Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China

    Lizhe Xie, Wen Tang, Iman Izadikhah & Bin Yan

  2. Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing Medical University, 136 Hanzhong Street, Gulou District, Nanjing, 210029, China

    Lizhe Xie, Hu Li & Bin Yan

  3. Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University, Gulou District, 136 Hanzhong Street, Nanjing, 210029, China

    Wen Tang, Iman Izadikhah, Hu Li & Bin Yan

  4. Department of Stomatology, The First People’s Hospital of Nantong, Nantong, China

    Zhenqi Zhao

  5. School of Public Health, Department of Biostatistics, Nanjing Medical University, Jiangning District, Nanjing, China

    Yang Zhao

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  1. Lizhe Xie
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  2. Wen Tang
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Contributions

LX and WT designed the study and performed the experiments. Data collection and manuscript writing were done by II and WT. ZZ and YZ carried out statistical analysis and interpretation of the results. HL and BY conceived and supervised the whole project. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Bin Yan.

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Conflicts of interest

The authors declare no potential conflicts of interest with respect to the content, authorship and/or publication of this article.

Ethics approval

This study was approved by the Institutional ethical committee of Nanjing Medical University (No. PJ2017-045-001).

Consent to participate

Written informed consent for utilization of scans in future research projects was obtained from all individuals, their parents or legal tutors prior to taking all the 709 images.

Consent for publication

All the authors certify that human research participants provided informed consent for publication of their data and radiographic images in Figs. 2 and 3.

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Xie, L., Tang, W., Izadikhah, I. et al. Development of a multi-stage model for intelligent and quantitative appraising of skeletal maturity using cervical vertebras cone-beam CT images of Chinese girls. Int J CARS 17, 761–773 (2022). https://doi.org/10.1007/s11548-021-02550-7

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