Application of Cameriere's method for dental age estimation in children in South China.

Cameriere’s method Forensic sciences South China dental age estimation linear regression

Journal

Forensic sciences research
ISSN: 2471-1411
Titre abrégé: Forensic Sci Res
Pays: England
ID NLM: 101724928

Informations de publication

Date de publication:
2022
Historique:
entrez: 5 7 2022
pubmed: 4 1 2021
medline: 4 1 2021
Statut: epublish

Résumé

The aim of this study was to evaluate the applicability of Cameriere's European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children. Moreover, the performance of dental age estimation based on Cameriere's method combining the developmental information of permanent teeth (PT) and third molar (TM) was also analysed. Orthopantomographs of 720 healthy children in Group A, and orthopantomographs of 320 children and 280 subadults in Group B were assessed. The samples of Group A were divided into training dataset 1 and test dataset 1, and the samples of Group B were also divided into training dataset 2 and test dataset 2. A South China-specific formula was established based on the training dataset 1, and the comparison of accuracy between the Cameriere's European formula and the South China-specific formula was conducted with the test dataset 1. Additionally, a PT regression model, a TM regression model, and a combined regression model (PT + TM) were established based on the training dataset 2, and the performance of these three models were validated on the test dataset 2. The Cameriere's European formula underestimated chronological age with a mean difference (ME) of -0.47 ± 1.11 years in males and -0.69 ± 1.19 years in females. However, the South China-specific formula underestimated chronological age, with a mean difference (ME) of -0.02 ± 0.71 years in males and -0.14 ± 0.73 years in females. Compared with PT model and TM model, the PT and TM combined model obtained the smallest root mean square error (RMSE) of 1.29 years in males and 0.93 years in females. In conclusion, the South China-specific formula was more suitable for assessing the dental age of children in South China, and the PT and TM combined model can improve the accuracy of dental age estimation in children.Key pointsOrthopantomographs of 720 healthy children in Group A, and orthopantomographs of 320 children and 280 subadults in Group B were assessed.A South China-specific formula was established based on the training dataset 1, and the comparison of accuracy between the Cameriere's European formula and the South China-specific formula was conducted with the test dataset 1.A PT regression model, a TM regression model, and a combined regression model (PT + TM) were established based on the training dataset 2, and the performance of these three models were validated on the test dataset 2.The South China-specific formula was more suitable for assessing the dental age of children in South China, and the PT and TM combined model can improve the accuracy of dental age estimation in children.

Identifiants

pubmed: 35784412
doi: 10.1080/20961790.2020.1830515
pii: 1830515
pmc: PMC9246020
doi:

Types de publication

Journal Article

Langues

eng

Pagination

106-114

Informations de copyright

© 2021 The Author(s). Published by Taylor & Francis Group on behalf of the Academy of Forensic Science.

Déclaration de conflit d'intérêts

No potential conflict of interest was reported by the authors.

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Auteurs

Zedeng Yang (Z)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.

Dan Wen (D)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.

Jiao Xiao (J)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.

Qianying Liu (Q)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.

Shule Sun (S)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.

Aliye Kureshi (A)

Xinjiang Medical University, Urumqi, China.

Yunfeng Chang (Y)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.

Lagabaiyila Zha (L)

Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.
Xinjiang Medical University, Urumqi, China.

Classifications MeSH