Quantitative analysis and clinical determinants of orthodontically induced root resorption using automated tooth segmentation from CBCT imaging.

Journal: BMC oral health
Published Date: May 8, 2025

Abstract

BACKGROUND: Orthodontically induced root resorption (OIRR) is difficult to assess accurately using traditional 2D imaging due to distortion and low sensitivity. While CBCT offers more precise 3D evaluation, manual segmentation remains labor-intensive and prone to variability. Recent advances in deep learning enable automatic, accurate tooth segmentation from CBCT images. This study applies deep learning and CBCT technology to quantify OIRR and analyze its risk factors, aiming to improve assessment accuracy, efficiency, and clinical decision-making.

Authors

  • Jiaqi Lin
    Department of Chemical Engineering and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Qianhan Zheng
    Department of Orthodontics, Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Hangzhou, PR China.
  • Yongjia Wu
    Department of Orthodontics, Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Hangzhou, PR China. Electronic address: yogurtwu@zju.edu.cn.
  • Mengqi Zhou
    School of Stomatology, Clinical Research Center for Oral Diseases of Zhejiang Province, Stomatology HospitalZhejiang University School of MedicineKey Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  • Jiahao Chen
    The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310006, China.
  • Xiaozhe Wang
    School of Stomatology, Clinical Research Center for Oral Diseases of Zhejiang Province, Stomatology HospitalZhejiang University School of MedicineKey Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
  • Ting Kang
    Department of Oncology, Affiliated Hospital of Yan'an University, Yan'an 716000, Shaanxi, China.
  • Weifang Zhang
    Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, Zhejiang, China; Social Medicine and Health Affairs Administration, Zhejiang University, Hangzhou, Zhejiang, China. Electronic address: chzwf@zju.edu.cn.
  • Xuepeng Chen
    Department of Orthodontics, Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Hangzhou, PR China. Electronic address: cxp1979@zju.edu.cn.

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