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...
Published in: | Translational Research in Anatomy |
---|---|
Main Author: | |
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 |