대한치과교정학회지 (The korean journal of orthodontics)

  • 제52권4호
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  • Pages.287-297
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  • 2022
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  • 2234-7518(pISSN)
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  • 2005-372X(eISSN)
대한치과교정학회 (The Korean Association Of Orthodontists)
권호 표지
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Accuracy of artificial intelligence-assisted landmark identification in serial lateral cephalograms of Class III patients who underwent orthodontic treatment and two-jaw orthognathic surgery

  • Hong, Mihee (Department of Orthodontics, School of Dentistry, Dental Research Institute, Seoul National University) ;
  • Kim, Inhwan (Department of Convergence Medicine, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Cho, Jin-Hyoung (Department of Orthodontics, Chonnam National University School of Dentistry) ;
  • Kang, Kyung-Hwa (Department of Orthodontics, School of Dentistry, Wonkwang University) ;
  • Kim, Minji (Department of Orthodontics, College of Medicine, Ewha Womans University) ;
  • Kim, Su-Jung (Department of Orthodontics, Kyung Hee University School of Dentistry) ;
  • Kim, Yoon-Ji (Department of Orthodontics, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Sung, Sang-Jin (Department of Orthodontics, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Kim, Young Ho (Department of Orthodontics, Institute of Oral Health Science, Ajou University School of Medicine) ;
  • Lim, Sung-Hoon (Department of Orthodontics, College of Dentistry, Chosun University) ;
  • Kim, Namkug (Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine) ;
  • Baek, Seung-Hak (Department of Orthodontics, School of Dentistry, Dental Research Institute, Seoul National University)
  • 투고 : 2021.09.24
  • 심사 : 2022.03.11
  • 발행 : 2022.07.25
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초록

Objective: To investigate the pattern of accuracy change in artificial intelligence-assisted landmark identification (LI) using a convolutional neural network (CNN) algorithm in serial lateral cephalograms (Lat-cephs) of Class III (C-III) patients who underwent two-jaw orthognathic surgery. Methods: A total of 3,188 Lat-cephs of C-III patients were allocated into the training and validation sets (3,004 Lat-cephs of 751 patients) and test set (184 Lat-cephs of 46 patients; subdivided into the genioplasty and non-genioplasty groups, n = 23 per group) for LI. Each C-III patient in the test set had four Lat-cephs: initial (T0), pre-surgery (T1, presence of orthodontic brackets [OBs]), post-surgery (T2, presence of OBs and surgical plates and screws [S-PS]), and debonding (T3, presence of S-PS and fixed retainers [FR]). After mean errors of 20 landmarks between human gold standard and the CNN model were calculated, statistical analysis was performed. Results: The total mean error was 1.17 mm without significant difference among the four time-points (T0, 1.20 mm; T1, 1.14 mm; T2, 1.18 mm; T3, 1.15 mm). In comparison of two time-points ([T0, T1] vs. [T2, T3]), ANS, A point, and B point showed an increase in error (p < 0.01, 0.05, 0.01, respectively), while Mx6D and Md6D showeda decrease in error (all p < 0.01). No difference in errors existed at B point, Pogonion, Menton, Md1C, and Md1R between the genioplasty and non-genioplasty groups. Conclusions: The CNN model can be used for LI in serial Lat-cephs despite the presence of OB, S-PS, FR, genioplasty, and bone remodeling.

키워드

과제정보

This research was supported by grants from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute and funded by the Ministry of Health &Welfare (HI18C1638) and the Technology Innovation Program (20006105) funded by the Ministry of Trade, Industry & Energy, Republic of Korea.

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