Gender Estimation Using Dental Measurements in CBCT: Focusing on the Mandibular Canine Index.

Abstract

Background: Gender determination is one of the most important stages in forensic science. Radiological techniques provide objective data in gender determination.

Aim: The present study aimed to assess the potential of the mandibular canine index (MCI) as a predictor of gender in cone beam computed tomography (CBCT) scans.

Methods: This study employed a retrospective analysis of oral and maxillofacial radiology department archives, encompassing a total of 503 patients. MCI was calculated on CBCT sections. The mesiodistal widths of the right (43) and left (33) canines, as well as the arch width of these canines, were measured and proportioned. The obtained results were subjected to statistical analysis.

Results: To determine the sensitivity and specificity of the dental parameters examined for predicting sex, ROC Curve analysis was performed. In ROC analysis, the area under the curve (Area Under Curve, AUC) indicates that the closer the value is to 1, the higher the likelihood of it being a valid marker. The sensitivity of the marker predicts one sex, while its specificity predicts the other. According to the ROC analysis, the dental parameters with the closest and highest sensitivity and specificity for determining sex (male) are selected, along with their cutoff points. The most consistent results and values were obtained from the measurements of the mesiodistal diameter of the right mandibular canine. Consequently, the cut-off point for the mesiodistal width of the right mandibular canine, at 5.65 mm or above, indicates a 72.8% probability of male sex. The results obtained from the left canine were then analyzed. The remaining results were less consistent. The obtained data represents reliable results that can be used as an auxiliary method in forensic sciences.

Conclusion: It has been determined that the mesiodistal diameter measurements of teeth 43 and 33 can be utilized to corroborate forensic findings about gender estimation.