Age Estimation by Kvaal’s Method Using CBCT Scans of Mandibular Canine Teeth in an Iranian Population

Abstract

Introduction: Age estimation of individuals older than 21 years remains a challenge in forensic medicine. This study sought to assess the accuracy of age estimation by Kvaal’s method using cone beam computed tomography (CBCT) scans of mandibular canine teeth in an Iranian population. Materials and Methods: In this cross-validation study, information of 150 test subjects and 30 controls was collected from the files of patients presenting to Shahid Beheshti University of Medical Sciences, School of Dentistry from 2014 to 2015. The parameters used in the Kvaal’s method were measured in mandibular canine teeth on CBCT scans of patients. First, the regression formula suggested by Kvaal et al, was used for age estimation. Then we designed our own formula for age estimation according to Kvaal’s method in our Iranian population and the fitness of statistical model was assessed. Results: Use of multiple linear regression model for assessment of the correlation of parameters in Kvaal’s method according to CBCT images of mandibular canines and age in a step by step fashion showed that all variables namely pulp length/root length, pulp length/tooth length, pulp width/root width at the cementoenamel junction (CEJ) and pulp width/root width at the mid-point of CEJ and mid-root were significant in age estimation (P<0.005 for all four). In this model, R2 was found to be 0.567, which indicated appropriate fitness of the regression model this should be revised "optimal". In this model, no significant linear correlation was noted between independent variables such that the variance inflation factor was maximally 1.4. Conclusions: Although most of the variables mentioned by Kvaal were effective in age estimation, some errors were seen in age estimation in the modeling and cross-validation phase. Thus, some other variables need to be included in the model to increase the accuracy of Kvaal’s formula in the Iranian population

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