Anatomy and Cell Biology

Korean Association of Anatomists (대한해부학회)
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Dental characteristics on panoramic radiographs as parameters for non-invasive age estimation: a pilot study

  • Harin Cheong (Department of Forensic Medicine, College of Medicine, The Catholic University of Korea) ;
  • Akiko Kumagai (Division of Forensic Odontology and Disaster Oral Medicine, Department of Forensic Science, Iwate Medical University) ;
  • Sehyun Oh (Department of Anatomy, College of Medicine, The Catholic University of Korea) ;
  • Sang-Seob Lee (Department of Anatomy, College of Medicine, The Catholic University of Korea)
  • Received : 2023.05.16
  • Accepted : 2023.07.25
  • Published : 2023.12.31
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Abstract

The dental characteristics created by acquired dental treatments can be used as age estimators. This pilot study aimed to analyze the correlation between the number of teeth observed for dental characteristics and chronological age and to develop new non-invasive age estimation models. Dental features on panoramic radiographs (420 radiographs of subjects aged 20-89 years) were classified and coded. The correlation between the number of teeth for each selected code (codes V, X, T, F, P, and L) and age was observed, and multiple regression was performed to analyze the relationship between them. Eleven regression models with various combinations of dental sextants were presented. The model with the data from both sides of the posterior teeth on both jaws showed the best performance (root mean square error of 14.78 years and an adjusted R2 of 0.461). The model with all teeth was the second-best. Based on these results, we confirmed statistically significant correlations between certain dental features and chronological age. We also observed that some regression models performed sufficiently well to be used as adjunctive methods in forensic practice. These results provide valuable information for the design and performance of future full-scale studies.

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Acknowledgement

This study was supported by a National Research Foundation of Korea (NRF) grant (No. 2022R1F1A1063719).

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