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Image Rendering Techniques in Postmortem Computed Tomography: Evaluation of Biological Health and Profile in Stranded Cetaceans
Published on: September 27, 2020
Volumetric assessment of canines using post-mortem computed tomography (PMCT) for sexual dimorphism in a Malaysian
Mohd Hafizal Harudin1, Ademir Franco2, Norhayati Jaffar1
1Unit of Forensic Odontology, Department of Oral and Maxillofacial Surgery, Kuala Lumpur Hospital, Ministry of Health Malaysia, Kuala Lumpur, Malaysia.
Background:
Recent research has explored volumetric assessment in three-dimensional (3D) imaging procedures for sexual dimorphism. The 3D techniques have enabled a more realistic, accurate, and non-invasive visualization of sex-related anatomical parameters, such as the size and shape of human teeth.
Aim:
To perform sexual dimorphism based on dental tissue volumes of permanent left maxillary and mandibular canines in a Malaysian population.
Methods:
A cross-sectional study was carried out on 220 post-mortem computed tomography (PMCT) scans of Malaysian subjects (114 males and 106 females) aged between 18 and 40 years old. The permanent left maxillary and mandibular canines were analysed based on the volume of their (I) enamel cap, (II) coronal dentine, and (III) root, as well as the combination between the three dental tissue volumes (DTV). 3D Slicer version 4.10.2 computer software was used to perform a semi-automated segmentation of the anatomic regions of interest of each tooth.
Results:
The DTV of the permanent left maxillary and mandibular canines showed sexual dimorphism as the males presented larger DTV than females (p < 0.05). After binary logistic regression, the DTV revealed an overall sex classification rate of 60 to 74.1%. The DTV of the permanent left mandibular canine had more discriminant power to correctly classify males and females compared to the left maxillary canine.
Conclusions:
The volumetric assessment of the dental tissues of the permanent left maxillary and mandibular canines could discriminate sex in the Malaysian population. Given the limited classification rate, this approach could act solely as a supplementary tool to existing sex estimation methods.

