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open access eISSN 2093-3673

Journal
Impact Factor

1.1

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Original Article

Anat Cell Biol 2023; 56(4): 474-481

Published online December 31, 2023

https://doi.org/10.5115/acb.23.140

Copyright © Korean Association of ANATOMISTS.

Dental characteristics on panoramic radiographs as parameters for non-invasive age estimation: a pilot study

Harin Cheong1 , Akiko Kumagai2 , Sehyun Oh3 , Sang-Seob Lee3,4

1Department of Forensic Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea, 2Division of Forensic Odontology and Disaster Oral Medicine, Department of Forensic Science, Iwate Medical University, Iwate, Japan, 3Department of Anatomy, College of Medicine, The Catholic University of Korea, Seoul, 4Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, Korea

Correspondence to:Sang-Seob Lee
Department of Anatomy, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
E-mail: sslee1418@gmail.com

Received: May 16, 2023; Revised: July 14, 2023; Accepted: July 25, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.

Keywords: Age determination by teeth, Dental characteristics, Non-invasive, Panoramic radiography

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