Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach

Age estimation in adults is a complicated task because of various external factors occur concurrently with increasing age. The geometric morphometric method (GMM) is an approach that focuses on shape analysis and is widely recognized for its high reliability and reproducibility. The aim of this stud...

Full description

Bibliographic Details
Published in:Translational Research in Anatomy
Main Author: Mohd Fauad M.F.; Ku Mohd Noor K.M.; Alias A.; Choy K.W.; Ng W.L.; Chung E.; Wu Y.S.; Norman N.H.
Format: Article
Language:English
Published: Elsevier GmbH 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175527486&doi=10.1016%2fj.tria.2023.100269&partnerID=40&md5=46fa896f4033ac88c6ecf01cf576894f
id 2-s2.0-85175527486
spelling 2-s2.0-85175527486
Mohd Fauad M.F.; Ku Mohd Noor K.M.; Alias A.; Choy K.W.; Ng W.L.; Chung E.; Wu Y.S.; Norman N.H.
Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
2023
Translational Research in Anatomy
33

10.1016/j.tria.2023.100269
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175527486&doi=10.1016%2fj.tria.2023.100269&partnerID=40&md5=46fa896f4033ac88c6ecf01cf576894f
Age estimation in adults is a complicated task because of various external factors occur concurrently with increasing age. The geometric morphometric method (GMM) is an approach that focuses on shape analysis and is widely recognized for its high reliability and reproducibility. The aim of this study was to explore the variation of cervical vertebrae among different age groups of the Malaysian population by GMM. Lateral skull radiographs of 432 subjects comprising four adult age groups; young adult age group (20–30 years old), early middle age group (31–40 years old), late middle age group (41–50 years old) and, elder adult age group (51–60 years old) were selected. Fifty-three 2-dimensional (2D) landmarks were applied to the digitalized radiographs by TPSDig2 (Version 2.31) software. Geometric morphometric analysis was performed by MorphoJ software. Results showed that the first three principal components (PC) contributed to 47.71 % of the cervical vertebrae variation and were shown in both lollipop and wireframe graphs. Procrustes ANOVA indicated that the shape was significantly different among different age groups. Canonical variate analysis revealed significant differences of both mahalanobis and procrustes distances among age groups with substantial individual overlap within groups. Discriminant function analysis (DFA) showed a correct classification rate for 61.5 % of cases respective to age groups. In conclusion, this study found significant differences in the shape of cervical vertebrae among different age groups of the Malaysian population using the GMM. © 2023
Elsevier GmbH
2214854X
English
Article
All Open Access; Gold Open Access
author Mohd Fauad M.F.; Ku Mohd Noor K.M.; Alias A.; Choy K.W.; Ng W.L.; Chung E.; Wu Y.S.; Norman N.H.
spellingShingle Mohd Fauad M.F.; Ku Mohd Noor K.M.; Alias A.; Choy K.W.; Ng W.L.; Chung E.; Wu Y.S.; Norman N.H.
Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
author_facet Mohd Fauad M.F.; Ku Mohd Noor K.M.; Alias A.; Choy K.W.; Ng W.L.; Chung E.; Wu Y.S.; Norman N.H.
author_sort Mohd Fauad M.F.; Ku Mohd Noor K.M.; Alias A.; Choy K.W.; Ng W.L.; Chung E.; Wu Y.S.; Norman N.H.
title Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
title_short Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
title_full Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
title_fullStr Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
title_full_unstemmed Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
title_sort Evaluation of age variation changes in cervical vertebrae: 2-Dimensional (2D) geometric morphometrics approach
publishDate 2023
container_title Translational Research in Anatomy
container_volume 33
container_issue
doi_str_mv 10.1016/j.tria.2023.100269
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175527486&doi=10.1016%2fj.tria.2023.100269&partnerID=40&md5=46fa896f4033ac88c6ecf01cf576894f
description Age estimation in adults is a complicated task because of various external factors occur concurrently with increasing age. The geometric morphometric method (GMM) is an approach that focuses on shape analysis and is widely recognized for its high reliability and reproducibility. The aim of this study was to explore the variation of cervical vertebrae among different age groups of the Malaysian population by GMM. Lateral skull radiographs of 432 subjects comprising four adult age groups; young adult age group (20–30 years old), early middle age group (31–40 years old), late middle age group (41–50 years old) and, elder adult age group (51–60 years old) were selected. Fifty-three 2-dimensional (2D) landmarks were applied to the digitalized radiographs by TPSDig2 (Version 2.31) software. Geometric morphometric analysis was performed by MorphoJ software. Results showed that the first three principal components (PC) contributed to 47.71 % of the cervical vertebrae variation and were shown in both lollipop and wireframe graphs. Procrustes ANOVA indicated that the shape was significantly different among different age groups. Canonical variate analysis revealed significant differences of both mahalanobis and procrustes distances among age groups with substantial individual overlap within groups. Discriminant function analysis (DFA) showed a correct classification rate for 61.5 % of cases respective to age groups. In conclusion, this study found significant differences in the shape of cervical vertebrae among different age groups of the Malaysian population using the GMM. © 2023
publisher Elsevier GmbH
issn 2214854X
language English
format Article
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
_version_ 1809677579897012224