The Foramen Magnum: A Morphometric Study on Ct Images of Adults

Garapati, Supriya; Santhi, Ch.; Pentyala, Suneetha; K.V, Krishna Sahith Reddy.

doi:10.16965/ijar.2018.144

Cited by 1 publication

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“…Forensic experts find it difficult to achieve that especially when some few skeletal elements are the only available evidence found in the scenes 21 . Therefore several researchers have used the direct metric measurements of the different parts of skull bones [22][23][24] and the radiologic metric measurements [13][14][15][16][25][26][27][28][29][30] to test the accuracy and reliability of individual parts of the skull in identifying the sex when only such parts are available for investigations.…”

Section: Discussionmentioning

confidence: 99%

Kraniyofasiyal boyutlar kullanarak cinsiyet tahmini: Kaduna Eyaleti, Nijerya'da BT tarama görüntüleri çalışması

JAAFAR,

MURDAKAİ,

TERSOO

et al. 2023

Cukurova Medical Journal

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Purpose: The aim of this study is to evaluate the potential of craniofacial dimensions in estimating sex in a sample population in Kaduna State, Nigeria. Materials and Methods: This is a retrospective study of normal CT scan images of 399 Crania (comprising 236 males and 163 females) of age range 18–95 years that came for CT scans for the diagnostic purpose at the National Ear Care Centre, Kaduna between the years of 2017–2019. The images were randomly taken at the archives of the Radiology Department of the institute on an axial plane. The five craniofacial dimensions were measured directly from the computer screen using Vitrea CT Software. Results: Maximum cranial width (13.49±0.57 cm), maximum cranial length (18.11±0.74 cm), and bizygomatic length (12.64±0.58 cm) of males were significantly greater than in females (13.35±0.49 cm), (17.82±0.66 cm) and (12.22±0.59 cm) respectively. The bizygomatic length on the receiver operating characteristic curve (Area under the curve = 0.711), logistic regression (odd ratio = 1.254), and discriminant function analysis (percentage accuracy after cross validation = 67.4 %.) was the best single variable for estimating sex. Bizygomatic and maximum cranial length were selected as the significant estimators of sex by multivariate logistic regression with Adjusted Odd Ratios of 1.412 and 3.984 respectively, as well as discriminant function analysis (percentage accuracy after cross validation = 66.9%). Conclusion: Among the sample population in Kaduna State, Nigeria, there is sexual dimorphism in some of the craniofacial variable found in CT scan images. Multivariate logistic regression may be the best model to utilize for predicting sex among the Kaduna State sample group.

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