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Madhavan, T. S.
- Comparison of Morphological Features of Second Cervical Vertebra between Genders Using Computed Tomography
Authors
1 Department of Medical Imaging Technology, Manipal College of Health Professions , Manipal Academy of Higher Education, IN
Source
Indian Journal of Public Health Research & Development, Vol 11, No 1 (2020), Pagination: 145-150Abstract
Introduction: Gender determination has been the emphasis of many forensic studies and have significance in mass fatality cases where bodies are damaged beyond recognition, as these factors are essential and various method are developed that allows gender determination. Second Cervical vertebra due to its ample degree of sexual dimorphism in its dimension allows sex determination. Forensic investigators can identify the bone by its morphological characteristics, such as the dens, short spinous process and cervical vertebra is known to be the best preserved of all the vertebra in cadavers.
Aim: To compare the morphological features of second cervical vertebra between genders using Computed Tomography.
Materials and Method: This was a retrospective study which included subjects visiting for CT (Computerized Tomography) of cervical spine in Department of Radio-diagnosis and Imaging, Kasturba Medical College, Manipal, Karnataka, India. Sample size was calculated using the formula for estimation of population mean which gave a total sample of 160. A total of 160 patients underwent computed tomography of cervical spine on MDCT Brilliance 64 slice Philips with routine protocol and later post-processed into Multiplanar imaging. In present study nine measurements of the second cervical vertebra were taken. Anthropometric measurements were performed which was calculated using the measurement tools. The data was analyzed using SPSS (V.20.0).
Results: Discriminant function analysis was performed to calculate the mean and standard deviation. Standardized canonical discriminant function was performed to find out the variable dependency and was found that maximum distance measured from the most lateral edges of the superior articular facets (DMFS) contributed much of the separation between genders. Step wise discriminant function test was performed to predict the categorical dependent variable a multivariable model was generated which showed that maximum distance measured from the most lateral edges of the superior articular facets (DMFS) and Maximum sagittal length (AS) reached the accuracy of 77.5% in gender discrimination. The most discriminant variable for the C2 was DMFS followed by AS, with expected accuracies of 73.8% and 71.9%. Among nine variables seven variables (AS, LMA, DMFS, DSD, DTD, WVF and DTMC) showed correct prediction rates approximately 78.8% and two variables (DA, DSMC) yielded no result.
Conclusion: DMFS contributed much separation with high accuracy in comparison to others, affirming that there is considerable sexual dimorphism with respect to the second cervical vertebra which could determine the gender of human based on CT measurements of second cervical vertebra.
