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Ahead of Print
ORIGINAL ARTICLES
Published online: 2018-09-25
Submitted: 2018-07-11
Accepted: 2018-09-12
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Assessment of paranasal sinus parameters according to ancient skulls’ gender and age by using cone beam computed tomography

Kemal Demiralp, Sebnem Kursun Cakmak, Secil Aksoy, Seval Bayrak, Kaan Orhan, Pervin Demir
DOI: 10.5603/FM.a2018.0089
·
Pubmed: 30280374

open access

Ahead of Print
ORIGINAL ARTICLES
Published online: 2018-09-25
Submitted: 2018-07-11
Accepted: 2018-09-12

Abstract

Background: The aim of this study was to determine whether paranasal sinus dimensions and volume can be useful to identify gender and age estimation for ancient skulls using cone beam computed tomography (CBCT) images.

Materials and methods: CBCT scans of 32 ancient skulls from app. 1000 years of age were included in this retrospective study. The gender and age estimation of the skulls were made by an independent anthropologist which was served as the gold standard. Paranasal sinuses dimensions (width and height) and volumes of each sinus were measured from the CBCT data set that were linked to the 3D rendering software (Anatomage, Invivo 5.2). All measurements were performed by an independent observer. Intra-observer analysis was made. Mann-Whitney test and Kruskal-Wallis tests were used to compare paranasal sinus parameters in terms of age estimation and gender (p<0.05).

Results: The results demonstrated no statistically significant difference between measurements (p<0.05). The measurements were found to be high reproducibility. The mean volumes for frontal and sphenoid sinus were found to be higher in males. The distance from anterior-posterior wall of sphenoid sinus in axial sections is larger in males (p>0.05).  The frontal sinus width and volume increased statistically with age above 60 yrs. of age (p>0.05). 

Conclusions: The paranasal volume and dimensions measurements from CBCT data can be a promising technique to determine gender and age estimation from ancient skulls because of its lower voxel sizes and higher resolution.

Abstract

Background: The aim of this study was to determine whether paranasal sinus dimensions and volume can be useful to identify gender and age estimation for ancient skulls using cone beam computed tomography (CBCT) images.

Materials and methods: CBCT scans of 32 ancient skulls from app. 1000 years of age were included in this retrospective study. The gender and age estimation of the skulls were made by an independent anthropologist which was served as the gold standard. Paranasal sinuses dimensions (width and height) and volumes of each sinus were measured from the CBCT data set that were linked to the 3D rendering software (Anatomage, Invivo 5.2). All measurements were performed by an independent observer. Intra-observer analysis was made. Mann-Whitney test and Kruskal-Wallis tests were used to compare paranasal sinus parameters in terms of age estimation and gender (p<0.05).

Results: The results demonstrated no statistically significant difference between measurements (p<0.05). The measurements were found to be high reproducibility. The mean volumes for frontal and sphenoid sinus were found to be higher in males. The distance from anterior-posterior wall of sphenoid sinus in axial sections is larger in males (p>0.05).  The frontal sinus width and volume increased statistically with age above 60 yrs. of age (p>0.05). 

Conclusions: The paranasal volume and dimensions measurements from CBCT data can be a promising technique to determine gender and age estimation from ancient skulls because of its lower voxel sizes and higher resolution.

Get Citation

Keywords

age estimation, anthropology, CBCT, gender, paranasal sinus

About this article
Title

Assessment of paranasal sinus parameters according to ancient skulls’ gender and age by using cone beam computed tomography

Journal

Folia Morphologica

Issue

Ahead of Print

Published online

2018-09-25

DOI

10.5603/FM.a2018.0089

Pubmed

30280374

Keywords

age estimation
anthropology
CBCT
gender
paranasal sinus

Authors

Kemal Demiralp
Sebnem Kursun Cakmak
Secil Aksoy
Seval Bayrak
Kaan Orhan
Pervin Demir

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