Literature DB >> 26650061

Age estimation in children by measurement of open apices in teeth with Bayesian calibration approach.

R Cameriere1, A Pacifici2, L Pacifici3, A Polimeni3, F Federici3, M Cingolani4, L Ferrante5.   

Abstract

Age estimation from teeth by radiological analysis, in both children and adolescents, has wide applications in several scientific and forensic fields. In 2006, Cameriere et al. proposed a regression method to estimate chronological age in children, according to measurements of open apices of permanent teeth. Although several regression models are used to analyze the relationship between age and dental development, one serious limitation is the unavoidable bias in age estimation when regression models are used. The aim of this paper is to develop a full Bayesian calibration method for age estimation in children according to the sum of open apices, S, of the seven left permanent mandibular teeth. This cross-sectional study included 2630 orthopantomographs (OPGs) from healthy living Italian subjects, aged between 4 and 17 years and with no obvious developmental abnormalities. All radiographs were in digital format and were processed by the ImageJ computer-aided drawing program. The distance between the inner side of the open apex was measured for each tooth. Dental maturity was then evaluated according to the sum of normalized open apices (S). Intra- and inter-observer agreement was satisfactory, according to an intra-class correlation coefficient of S on 50 randomly selected OPGs. Mean absolute errors were 0.72 years (standard deviation 0.60) and 0.73 years (standard deviation 0.61) in boys and girls, respectively. The mean interquartile range (MIQR) of the calibrating distribution was 1.37 years (standard deviation 0.46) and 1.51 years (standard deviation 0.52) in boys and girls, respectively. Estimate bias was βERR=-0.005 and 0.003 for boys and girls, corresponding to a bias of a few days for all individuals in the sample. Neither of the βERR values was significantly different from 0 (p>0.682). In conclusion, the Bayesian calibration method overcomes problems of bias in age estimation when regression models are used, and appears to be suitable for assessing both age and age distribution in children according to tooth maturity.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Age estimation; Bayesian calibration; Cameriere's method; Open apices

Mesh:

Year:  2015        PMID: 26650061     DOI: 10.1016/j.forsciint.2015.11.005

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  9 in total

1.  Chronology of mineralization of the permanent mandibular second molar teeth and forensic age estimation.

Authors:  Pedro Fins; Maria Lurdes Pereira; Américo Afonso; Daniel Pérez-Mongiovi; Inês Morais Caldas
Journal:  Forensic Sci Med Pathol       Date:  2017-06-03       Impact factor: 2.007

2.  Age estimation by measuring open apices in teeth: a new formula for two samples of South African black and white children.

Authors:  N Angelakopoulos; S De Luca; L A Velandia Palacio; E Coccia; L Ferrante; V Pinchi; R Cameriere
Journal:  Int J Legal Med       Date:  2019-06-14       Impact factor: 2.686

3.  Proposal of new regression formulae for the estimation of age in infant skeletal remains from the metric study of the pars basilaris.

Authors:  Javier Irurita Olivares; Inmaculada Alemán Aguilera
Journal:  Int J Legal Med       Date:  2016-10-27       Impact factor: 2.686

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

Authors:  Zedeng Yang; Dan Wen; Jiao Xiao; Qianying Liu; Shule Sun; Aliye Kureshi; Yunfeng Chang; Lagabaiyila Zha
Journal:  Forensic Sci Res       Date:  2021-01-04

5.  Comparison between Two Radiological Methods for Assessment of Tooth Root Resorption: An In Vitro Study.

Authors:  Sabina Saccomanno; Pier Carmine Passarelli; Bruno Oliva; Cristina Grippaudo
Journal:  Biomed Res Int       Date:  2018-03-04       Impact factor: 3.411

6.  Age-group determination of living individuals using first molar images based on artificial intelligence.

Authors:  Seunghyeon Kim; Yeon-Hee Lee; Yung-Kyun Noh; Frank C Park; Q-Schick Auh
Journal:  Sci Rep       Date:  2021-01-13       Impact factor: 4.379

7.  The Application of the Cameriere's Methodologies for Dental Age Estimation in a Select KwaZulu-Natal Population of South Africa.

Authors:  Sundika Ishwarkumar; Pamela Pillay; Manogari Chetty; Kapil Sewsaran Satyapal
Journal:  Dent J (Basel)       Date:  2022-07-08

8.  Comparative assessment of the Willems dental age estimation methods: a Chinese population-based radiographic study.

Authors:  Jian Wang; Linfeng Fan; Shihui Shen; Meizhi Sui; Jiaxin Zhou; Xiaoyan Yuan; Yiwen Wu; Pingping Zhong; Fang Ji; Jiang Tao
Journal:  BMC Oral Health       Date:  2022-09-03       Impact factor: 3.747

9.  Deep Learning Neural Modelling as a Precise Method in the Assessment of the Chronological Age of Children and Adolescents Using Tooth and Bone Parameters.

Authors:  Maciej Zaborowicz; Katarzyna Zaborowicz; Barbara Biedziak; Tomasz Garbowski
Journal:  Sensors (Basel)       Date:  2022-01-14       Impact factor: 3.576

  9 in total

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