Sexual dimorphism of foramen magnum and occipital condyles using cone beam computed tomography: A morphometric study

Comparison of different methods of analysis of maxillary sinus volume and validation of a new proposal using cone beam computed tomography

PURPOSE

develop and validate a formula, through a discriminant analysis of sex estimation, evaluating maxillary sinus in cone beam computed tomography scans in a Brazilian population, comparing this formula with two other existing ones.

METHODS

190 cone beam CT scans of Brazilian adults were retrospectively evaluated by an independent examiner. Measurements were performed in the right and left MS region: height, width, length, distance between the breasts, distance between infraorbital foramina, and volume in the ITK software. The sample was divided into female and male. T test, ANOVA, Tukey test and the ROC Curve was performed (p > 0,05).

RESULTS

statistically significant differences were found in relation to the maximum height of the MS both right (p = 0,001) and left (p = 0,026) between sexes and the maximum length in the right MS (p = 0,01). Regarding the comparison of MS volume according to the different analysis methods, statistically significant differences were found between sexes for the right MS when using the method by Bangi et al. (p = 0,012) and the volume of the left MS in females (p < 0,001). Comparing the three classification models, statistically significant differences were found between the proposed method and the classification by Bangi et al. (p < 0.007). The ROC curve showed greater accuracy in the classification proposed in this work.

CONCLUSION

the new proposed formula obtained better predictions of sexual dimorphism, when compared to classifications already described in the literature.

Sex estimation using foramen magnum measurements, discriminant analyses and artificial neural networks on an eastern Turkish population sample

BACKGROUND

Although many studies have been conducted using the foramen magnum for sex estimation, recent findings have indicated that the discriminant and regression models obtained from the foramen magnum may not be reliable. Artificial Neural Networks, was used as a classification technique in sex estimation studies on some other bones, did not used in sex estimation studies on the foramen magnum until now. The aim of this study was sex estimation on an Eastern Turkish population sample using foramen magnum measurements, discriminant analyses and Artificial Neural Networks.

METHODOLOGY

The study was performed on the CT images of a total of 720 cases, comprising 360 males and 360 females. For sex estimation, discriminant analysis and Artificial Neural Networks were used.

RESULTS

The accuracy rate was 86.7% with discriminant analysis and when sex estimation accuracy was determined according to cases with posterior probabilities above 95%, the accuracy ranged from 0% to 33.3%. With the use of the discriminant formulas of 2 other studies, obtained from different Turkish samples, sex could be determined at a rate of 84.6%. Some formulas were found to be unsuccessful in sex estimation. Sex estimation accuracy of 88.2% was achieved with Artificial Neural Networks.

CONCLUSION

In this study, it was found that sex could be determined to some extent with discriminant formulas from other samples from the same population, although some formulas were unsuccessful. With the use of image processing techniques and machine learning algorithms, better results can be obtained in sex estimation.