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Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan

Human identification is the main goal in anthropological and forensic investigations such as examination of ancient skeletons, investigations at criminal related scenes, or due to mass disasters. The primary focus is to determine the biological profile of unknown individuals by estimating their sex...

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Main Author: Sharifah Nabilah , Syed Mohd Hamdan
Format: Thesis
Published: 2024
Subjects:
RK Dentistry
Online Access:http://studentsrepo.um.edu.my/15429/1/Sharifah_Nabilah.pdf
http://studentsrepo.um.edu.my/15429/2/Sharifah_Nabilah.pdf
http://studentsrepo.um.edu.my/15429/
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spelling my.um.stud.154292024-10-05T03:31:57Z Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan Sharifah Nabilah , Syed Mohd Hamdan RK Dentistry Human identification is the main goal in anthropological and forensic investigations such as examination of ancient skeletons, investigations at criminal related scenes, or due to mass disasters. The primary focus is to determine the biological profile of unknown individuals by estimating their sex and ethnicity. Sex and ethnicity estimation methods utilised in adult are less effective in sub-adults due to varied cranium patterns during growth. Therefore, this study aimed to develop three-dimensional (3D) craniometric models in Malaysian sub-adults for sex and ethnicity estimation, and to establish a cephalic index (CI) classification for Malaysian sub-adults. A total of 521 cranial multi-slice computed tomography (MSCT) dataset of sub-adult Malaysians aged 0 to 20 with Malay, Chinese, and Indian ethnicities were obtained. MIMICS software version 21.0 (Materialise, Leuven, Belgium) was used to construct 3D models and plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. Additionally, CI was calculated according to the following equation: cephalic width/cephalic length×100. This present study demonstrated a minimal degree of sexual dimorphism in the cranium of individuals below the age of six, and the level was then increased with age. All the age groups, except for 0–2 years and 3–6 years, exhibited reliable sex estimation with a high accuracy percentage (≥75%) when tested using DFA and BLR. As for the ethnicity estimation models, a high similarity of craniometric measurements between Chinese and Malays (as compared to Indians and Malays, and Chinese and Indians) was demonstrated. This resulted in the highest classification accuracy obtained by Indians, followed by Chinese and Malays in the age groups of 10–12 years and 16–20 years. Moreover, ML methods obtained slightly higher accuracy rates than classical methods for sex (RF: 73% vs BLR: 66.9% and DFA: 61.6%) and ethnicity estimation (LDA: 58% vs DFA: 57.5%) using sub-adults’ crania. In addition, the modified CI of Malaysian sub-adults were found to be as follows: dolichocephalic, 78.8 or less; mesocephalic, 78.9–89.0; brachycephalic, 89.1–94.0; and hyperbrachycephalic, 94.1 or higher. Hence, the proposed CI index indicated that the dominating type of head for Malaysian sub-adults was mesocephalic (66.4%), followed by dolichocephalic (18.4%), brachycephalic (12.3%), and hyperbrachycephalic (2.9%). The present study has demonstrated that sex and ethnicity estimation of sub-adults can be effectively performed by assessing the cranium via 3D virtual anthropometry. To the best of our knowledge, this was the preliminary study that described craniometric variations of multi-ethnic groups in Malaysian sub-adult population using MSCT data. Ultimately, this present study has bridged the gap of population-specific cranial data in Malaysian sub-adults. 2024-07 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/15429/1/Sharifah_Nabilah.pdf application/pdf http://studentsrepo.um.edu.my/15429/2/Sharifah_Nabilah.pdf Sharifah Nabilah , Syed Mohd Hamdan (2024) Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan. PhD thesis, Universiti Malaya. http://studentsrepo.um.edu.my/15429/
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Student Repository
url_provider http://studentsrepo.um.edu.my/
topic RK Dentistry
spellingShingle RK Dentistry
Sharifah Nabilah , Syed Mohd Hamdan
Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan
description Human identification is the main goal in anthropological and forensic investigations such as examination of ancient skeletons, investigations at criminal related scenes, or due to mass disasters. The primary focus is to determine the biological profile of unknown individuals by estimating their sex and ethnicity. Sex and ethnicity estimation methods utilised in adult are less effective in sub-adults due to varied cranium patterns during growth. Therefore, this study aimed to develop three-dimensional (3D) craniometric models in Malaysian sub-adults for sex and ethnicity estimation, and to establish a cephalic index (CI) classification for Malaysian sub-adults. A total of 521 cranial multi-slice computed tomography (MSCT) dataset of sub-adult Malaysians aged 0 to 20 with Malay, Chinese, and Indian ethnicities were obtained. MIMICS software version 21.0 (Materialise, Leuven, Belgium) was used to construct 3D models and plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. Additionally, CI was calculated according to the following equation: cephalic width/cephalic length×100. This present study demonstrated a minimal degree of sexual dimorphism in the cranium of individuals below the age of six, and the level was then increased with age. All the age groups, except for 0–2 years and 3–6 years, exhibited reliable sex estimation with a high accuracy percentage (≥75%) when tested using DFA and BLR. As for the ethnicity estimation models, a high similarity of craniometric measurements between Chinese and Malays (as compared to Indians and Malays, and Chinese and Indians) was demonstrated. This resulted in the highest classification accuracy obtained by Indians, followed by Chinese and Malays in the age groups of 10–12 years and 16–20 years. Moreover, ML methods obtained slightly higher accuracy rates than classical methods for sex (RF: 73% vs BLR: 66.9% and DFA: 61.6%) and ethnicity estimation (LDA: 58% vs DFA: 57.5%) using sub-adults’ crania. In addition, the modified CI of Malaysian sub-adults were found to be as follows: dolichocephalic, 78.8 or less; mesocephalic, 78.9–89.0; brachycephalic, 89.1–94.0; and hyperbrachycephalic, 94.1 or higher. Hence, the proposed CI index indicated that the dominating type of head for Malaysian sub-adults was mesocephalic (66.4%), followed by dolichocephalic (18.4%), brachycephalic (12.3%), and hyperbrachycephalic (2.9%). The present study has demonstrated that sex and ethnicity estimation of sub-adults can be effectively performed by assessing the cranium via 3D virtual anthropometry. To the best of our knowledge, this was the preliminary study that described craniometric variations of multi-ethnic groups in Malaysian sub-adult population using MSCT data. Ultimately, this present study has bridged the gap of population-specific cranial data in Malaysian sub-adults.
format Thesis
author Sharifah Nabilah , Syed Mohd Hamdan
author_facet Sharifah Nabilah , Syed Mohd Hamdan
author_sort Sharifah Nabilah , Syed Mohd Hamdan
title Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan
title_short Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan
title_full Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan
title_fullStr Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan
title_full_unstemmed Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan
title_sort three-dimensional craniometrics identification model and cephalic index classification of malaysian sub-adults: a multi-slice computed tomography study / sharifah nabilah syed mohd hamdan
publishDate 2024
url http://studentsrepo.um.edu.my/15429/1/Sharifah_Nabilah.pdf
http://studentsrepo.um.edu.my/15429/2/Sharifah_Nabilah.pdf
http://studentsrepo.um.edu.my/15429/
_version_ 1814047817042231296
score 13.211869

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