Literature DB >> 31322923

Age and sex estimation based on pulp cavity volume using cone beam computed tomography: development and validation of formulas in a Brazilian sample.

Vanessa M Andrade1,2, Rocharles C Fontenele3, Andreia Cb de Souza1,4, Casimiro Ap de Almeida4, Andrea Cd Vieira5, Francisco C Groppo6, Deborah Q Freitas3, Eduardo D Junior2.   

Abstract

OBJECTIVES: To develop and validate formulas for age and sex estimation based on the pulp cavity volume of teeth using cone beam CT.
METHODS: The sample was composed of 116 cone beam CT scans from Brazilian individuals of both sexes, ranging in age from 13 to 70 years. A total of 232 teeth (upper central incisors and canines) were evaluated. Two calibrated examiners determined pulp cavity volumes using the ITK-SNAP software. Pearson's correlation test was used to assess the correlation between chronological age and pulp volume. Linear and logistic regression models were developed for age and sex estimation, respectively, and were validated in another sample of 72 teeth.
RESULTS: Pearson's correlation coefficients between age and pulp volume were negative and significant (p < 0.0001) for both teeth (r = -0.8782 for central incisors and r = -0.8738 for canines). The age estimation formulas showed good determination coefficients (adjusted R² = 0.7614 to 0.8367). For sex estimation, when the age was known, the coefficients were also good (adjusted R² = 0.649 to 0.812). However, when the age was unknown, the coefficients of the sex estimation formulas were low (adjusted R² = 0.047 to 0.393). Validation showed high accuracy of age estimation in individuals older than 35 years, as well as high accuracy of sex estimation when the age was known.
CONCLUSIONS: Our formulas provided excellent results and can be applied to the Brazilian population. The best results were observed for age estimation in females and for sex estimation when the age was known.

Entities:  

Keywords:  age determination by teeth; cone-beam CT; forensic dentistry; secondary dentin; sex characteristics

Mesh:

Year:  2019        PMID: 31322923      PMCID: PMC6775786          DOI: 10.1259/dmfr.20190053

Source DB:  PubMed          Journal:  Dentomaxillofac Radiol        ISSN: 0250-832X            Impact factor:   2.419


  32 in total

1.  Age-related changes in pulp cavity of incisors as a determinant for forensic age identification.

Authors:  Changlian Du; Youjia Zhu; Li Hong
Journal:  J Forensic Sci       Date:  2010-10-06       Impact factor: 1.832

2.  A new age estimation procedure based on the 3D CBCT study of the pulp cavity and hard tissues of the teeth for forensic purposes: A pilot study.

Authors:  Vilma Pinchi; Francesco Pradella; Jacopo Buti; Claudio Baldinotti; Martina Focardi; Gian-Aristide Norelli
Journal:  J Forensic Leg Med       Date:  2015-09-30       Impact factor: 1.614

3.  Age estimation based on three-dimensional measurement of mandibular central incisors in Japanese.

Authors:  H Someda; H Saka; S Matsunaga; Y Ide; K Nakahara; S Hirata; M Hashimoto
Journal:  Forensic Sci Int       Date:  2009-02-07       Impact factor: 2.395

Review 4.  Dental radiographic indicators, a key to age estimation.

Authors:  A S Panchbhai
Journal:  Dentomaxillofac Radiol       Date:  2011-05       Impact factor: 2.419

5.  Accuracy of linear and volumetric measurements of artificial ERR cavities by using CBCT images obtained at 4 different voxel sizes and measured by using 4 different software: an ex vivo research.

Authors:  Gül Sönmez; Cemre Koç; Kıvanç Kamburoğlu
Journal:  Dentomaxillofac Radiol       Date:  2018-06-27       Impact factor: 2.419

6.  Estimation of stature and sex from sacrum and coccyx measurements by multidetector computed tomography in Chinese.

Authors:  Meng-Jun Zhan; Fei Fan; Li-Rong Qiu; Zhao Peng; Kui Zhang; Zhen-Hua Deng
Journal:  Leg Med (Tokyo)       Date:  2018-07-26       Impact factor: 1.376

7.  Age estimation based on pulp chamber volume of first molars from cone-beam computed tomography images.

Authors:  Zhi-pu Ge; Ruo-han Ma; Gang Li; Ji-zong Zhang; Xu-chen Ma
Journal:  Forensic Sci Int       Date:  2015-05-14       Impact factor: 2.395

8.  Applicability of Cameriere's and Drusini's age estimation methods to a sample of Turkish adults.

Authors:  Boyacioglu Dogru Hatice; Avcu Nihal; Akkaya Nursel; Yilanci Humeyra Ozge; Dincer Goksuluk
Journal:  Dentomaxillofac Radiol       Date:  2017-07-14       Impact factor: 2.419

9.  Gender Determination of Adult Individuals by Three-Dimensional Modeling of Canines.

Authors:  Delphine Tardivo; Julien Sastre; Jean-Hugues Catherine; Georges Leonetti; Pascal Adalian; Bruno Foti
Journal:  J Forensic Sci       Date:  2015-08-10       Impact factor: 1.832

10.  Age estimation based on pulp/tooth volume ratio measured on cone-beam CT images.

Authors:  Ayse Gulsahi; Cemal Kivanc Kulah; Batuhan Bakirarar; Orhan Gulen; Kivanc Kamburoglu
Journal:  Dentomaxillofac Radiol       Date:  2017-11-01       Impact factor: 2.419

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  5 in total

1.  Dental age estimation based on pulp chamber/crown volume ratio measured on CBCT images in a Spanish population.

Authors:  Ana Molina; Manuel Bravo; Gabriel M Fonseca; Nicholas Márquez-Grant; Stella Martín-de-Las-Heras
Journal:  Int J Legal Med       Date:  2020-07-17       Impact factor: 2.686

2.  CBCT in dental age estimation: A systematic review and meta analysis.

Authors:  Rizky Merdietio Boedi; Simon Shepherd; Scheila Mânica; Ademir Franco
Journal:  Dentomaxillofac Radiol       Date:  2022-01-07       Impact factor: 3.525

3.  Variations in pulp volume between normotensive and hypertensive individuals on CBCT imaging.

Authors:  Amanda Farias Gomes; Saulo L Sousa Melo; Yuri Nejaim; Francisco Carlos Groppo; Fabrício B Teixeira; Deborah Queiroz Freitas
Journal:  Clin Oral Investig       Date:  2020-04-24       Impact factor: 3.573

4.  Age estimation based on 3D post-mortem computed tomography images of mandible and femur using convolutional neural networks.

Authors:  Cuong Van Pham; Su-Jin Lee; So-Yeon Kim; Sookyoung Lee; Soo-Hyung Kim; Hyung-Seok Kim
Journal:  PLoS One       Date:  2021-05-12       Impact factor: 3.240

5.  Machine Learning Techniques for Human Age and Gender Identification Based on Teeth X-Ray Images.

Authors:  K C Santosh; Nijalingappa Pradeep; Vikas Goel; Raju Ranjan; Ekta Pandey; Piyush Kumar Shukla; Stephen Jeswinde Nuagah
Journal:  J Healthc Eng       Date:  2022-01-04       Impact factor: 2.682

  5 in total

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