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Morphometric evaluation of the orbital region for sex determination in a Saudi Arabian population using 3DCT images.

Vasanthakumar PackiriswamyKhaled AljarrahSatheesha B Nayak
Published in: Anatomical science international (2023)
In forensic anthropology, the analysis of variations in the orbitometric features plays a crucial role in identifying the sex of a skull detached from its skeleton. Therefore, it is essential to create population-specific values to maximize the accuracy rate of sex estimation. The objective of this study was to evaluate the orbital region morphometrically for sex determination in a Saudi Arabian population using CT scan images. This study included 456 CT images (228 males and 228 females; age range, 18-58 years). Six orbital measurements and the orbital index of both sides were evaluated to determine sexual dimorphism and laterality using an independent t-test. Sex was estimated using discriminant function analysis. Based on the orbital index, the orbit was classified into megasemes, mesosemes, and microsemes. All the measurements were significantly greater in males than females, but the orbital index showed no significant sexual dimorphism. No significant asymmetry was found in all orbital dimensions. The univariate discriminant function of the orbital measurements showed an accuracy rate between 83.8 and 70%. The multivariate analysis classified the orbital dimensions into male (93%) and female (92.1%) to the highest level of accuracy. In Saudis, the megaseme category was the most prevalent form of orbit. The right orbit height (83.8%), left orbit height (80.7%), right orbit width (79.4%), and left orbit height (79.4%) were the most reliable variables that could be used in sex determination. According to multivariate analysis, the overall accuracy rate for determining sex was 92.1%. While the present study data may not be used alone for sexing a complete skull, there must be various occasions in which this new standard will contribute to determining sex in forensic contexts.
Keyphrases
  • computed tomography
  • body mass index
  • deep learning
  • convolutional neural network
  • optical coherence tomography
  • high resolution
  • data analysis
  • magnetic resonance
  • molecularly imprinted
  • big data