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Accuracy of virtual 3-dimensional cephalometric images constructed with 2-dimensional cephalograms using the biplanar radiography principle

  • Lee, Jae-Seo (Department of Oral and Maxillofacial Radiology, School of Dentistry, Chonnam National University) ;
  • Kim, Sang-Rok (Department of Orthodontics, School of Dentistry, Chonnam National University) ;
  • Hwang, Hyeon-Shik (Department of Orthodontics, School of Dentistry, Chonnam National University) ;
  • Lee, Kyungmin Clara (Department of Orthodontics, School of Dentistry, Chonnam National University)
  • Received : 2021.04.13
  • Accepted : 2021.06.23
  • Published : 2021.12.31

Abstract

Purpose: The purpose of this study was to evaluate the accuracy of virtual 3-dimensional (3D) cephalograms constructed using the principle of biplanar radiography by comparing them with cone-beam computed tomography (CBCT) images. Materials and Methods: Thirty orthodontic patients were enrolled in this study. Frontal and lateral cephalograms were obtained with the use of a head posture aligner and reconstructed into 3D cephalograms using biplanar radiography software. Thirty-four measurements representing the height, width, depth, and oblique distance were computed in 3 dimensions, and compared with the measurements from the 3D images obtained by CBCT, using the paired t-test and Bland-Altman analysis. Results: Comparison of height, width, depth, and oblique measurements showed no statistically significant differences between the measurements obtained from 3D cephalograms and those from CBCT images (P>0.05). Bland-Altman plots also showed high agreement between the 3D cephalograms and CBCT images. Conclusion: Accurate 3D cephalograms can be constructed using the principle of biplanar radiography if frontal and lateral cephalograms can be obtained with a head posture aligner. Three-dimensional cephalograms generated using biplanar radiography can replace CBCT images taken for diagnostic purposes.

Keywords

Acknowledgement

This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and ICT) (No. 2020R1F1A 1070617 and NRF-2017R1D1A1B03032132).

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