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Age Estimation from Mandibles in Malay: A 2d Geometric Morphometric Analysis
Journal
Journal of Taibah University Medical Sciences
Date Issued
2023
Author(s)
Nur Ariessa Farhana Zulkifli
Nur Aliya Syuhada Mohd Saaid
Aspalilah Alias
Nurjehan Mohamed Ibrahim
Choy Ker Woon
Arofi Kurniawan
Beshlina Fitri Widayanti Roosyanto Prakoeswa
DOI
10.1016/j.jtumed.2023.05.020
Abstract
Objectives
In this study, the sizes and forms of mandibles in various age groups of the Malay population were measured and compared.
Methods
Geometric morphometric (GM) analysis of mandibles from 400 dental panoramic tomography (DPT) specimens was conducted. The MorphoJ program was used to perform generalized Procrustes analysis (GPA), Procrustes ANOVA, principal component analysis (PCA), discriminant function analysis (DFA), and canonical variate analysis (CVA). In the tpsDig2 program, the 27 landmarks were applied to the DPT radiographs. Variations in mandibular size and form were categorized into four age groups: group 1 (15–24 years), group 2 (25–34 years), group 3 (35–44 years), and group 4 (45–54 years).
Results
The diversity in mandibular shape among the first eight principal components was 81%. Procrustes ANOVA revealed significant shape differences (P < 0.001) among age groups. Mahalanobis distances indicated substantial differences among all age groups; group 1 and group 4 scored highest, at 2.114. The ranges for the cross-validation and discriminant function tests were 90–72% and 81–49%, respectively.
Conclusion
GM analysis through radiography is a simple, non-invasive, and non-destructive method of estimating age by using the mandible. GM analysis is unique because it can visualize the changes in mandible shape among age groups. This method should aid in age identification in forensic odontology investigations.
In this study, the sizes and forms of mandibles in various age groups of the Malay population were measured and compared.
Methods
Geometric morphometric (GM) analysis of mandibles from 400 dental panoramic tomography (DPT) specimens was conducted. The MorphoJ program was used to perform generalized Procrustes analysis (GPA), Procrustes ANOVA, principal component analysis (PCA), discriminant function analysis (DFA), and canonical variate analysis (CVA). In the tpsDig2 program, the 27 landmarks were applied to the DPT radiographs. Variations in mandibular size and form were categorized into four age groups: group 1 (15–24 years), group 2 (25–34 years), group 3 (35–44 years), and group 4 (45–54 years).
Results
The diversity in mandibular shape among the first eight principal components was 81%. Procrustes ANOVA revealed significant shape differences (P < 0.001) among age groups. Mahalanobis distances indicated substantial differences among all age groups; group 1 and group 4 scored highest, at 2.114. The ranges for the cross-validation and discriminant function tests were 90–72% and 81–49%, respectively.
Conclusion
GM analysis through radiography is a simple, non-invasive, and non-destructive method of estimating age by using the mandible. GM analysis is unique because it can visualize the changes in mandible shape among age groups. This method should aid in age identification in forensic odontology investigations.
Subjects
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Age estimation from mandibles in Malay_ A 2D geometric morphometric analysis.pdf
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