New regression models for dental age estimation in children using third molar maturity index: A preliminary analysis testing its usefulness as reliable age marker

Use of third molar eruption based on Gambier's criteria in assessing dental age

The biological aspects of determining the dental age of subadults represent an important interdisciplinary scientific link with applications in criminal law and in forensic anthropology and dentistry. In criminal procedural law, it is necessary to determine the exact age of an undocumented person in view of the application of the provisions on juvenile offenders and minor victims. Chronological age can be estimated from the development of the third molars, as these are the only teeth that develop at the age of 18. The aim of this study was to verify the applicability of the Gambier method based on the eruption of the third permanent molars in the mandible and maxilla, to contribute to forensic age assessment. The analyzed group that met the criteria consisted of 811 orthopantomograms (OPGs) (339 females and 472 males) between the ages of 13 and 25 years. The OPGs were retrospectively analyzed according to the method of Gambier et al. (Int J Legal Med 133:625-632, 29), which refers to the eruption stages of the third molar. Differences between eruption stages of maxillary and mandibular third molars were statistically significant in both biological sexes. Intersexual differences in mean age were significant only at stage 3 for any M3 tooth and at stage 1 for mandibular M3. There were no statistically significant differences between the left and right mandibular and maxillary third molars, respectively. Differences between mandibular and maxillary M3 were significant only for stage 1 in males on the left side and for stage 2 in both sexes and sides. The method used allowed the best classification of individuals into minor and adult groups (based on phase D-90.41% of individuals, based on the third stage of the mandibular left third molar-86.29%). Based on the results obtained, we can assume that the method cannot be used alone in the initial examination of living individuals, since all four third molars must be assessed and there are no additional findings from practice.

Correlation of chronological age with dental age estimated using modified Cameriere’s method and UT-age estimation software — a cross-sectional study

Background

Estimating age is essential in both the analysis of human skeletal remains and assessing live persons. The third molar develops over a longer period and is hence used in age estimation for subadults. Since dental age correlates with chronological age better than other growth markers, this study aims to assess the reliability of dental age assessed using the University of Texas (UT) age estimation method and modified Cameriere’s method.

Methods

It is a retrospective cross-sectional study in which the development and maturation of mandibular third molars were examined in 600 orthopantomograms (264 males and 336 females) of South Indian individuals (16–23 years). Dental age was estimated by using an Indian-specific formula based on maturity index value and the UT-age estimation  software program. The results were evaluated using the Student’s t-test for both methods and Pearson’s correlation test to compare chronological age with estimated dental age.

Results

Positive correlation was noted between chronological age and estimated dental age for males, females, and the total sample with highly statistically significant differences (p = 0.000). Modified Cameriere’s method underestimated dental age in samples ranging from less than 1 year to more than 2 years. UT-age estimation method underestimated age in samples above 20 years and overestimated age in samples below 20 years. The predictive classification of utilizing the maturity index was 79.17% accurate.

Conclusions

Dental age was negligibly over and underestimated in UT software method whereas it was overestimated in the modified Cameriere's method. To evaluate the reliability of these two methods, studies with larger sample sizes and population-specific data sets should be performed.

Graphical Abstract

Evaluation of the effect of impaction on the mineralization of mandibular third molars and forensic age estimation in a sample of south Indian children

Assessment of third molar mineralization is a basic forensic odontological method available for age estimation in children and adolescents. Due to their protracted development into the late adolescence, their development has become the subject of interest and acquired great forensic importance. It is clearly evident in the literature that impaction factor has an influence on the rate of maturation of the third molars. In this regard, the present study was undertaken to test the relationship between impaction and its concomitant effect on the mineralization of the third molar and forensic age estimation. A total of 520 digital orthopantomograms (OPG) of 260 males and 260 females of south Indian origin were assessed retrospectively. Maturation of the third molars (I3M) was assessed using the method of Cameriere et al. (Int J Leg Med 122 (6):493-497, 2008). Impaction status was determined according to the position of lower right and left third molars in relation to the long axis of the second molars. Out of the total sample, 68.1% of lower left third molars and 71.2% of lower right molars were impacted. Statistical measures for I3M were calculated in the males and females for both impacted and non-impacted third molars. It was ascertained that the mean age and I3M values were higher in impacted third molars, indicating the slower rate of maturation than non-impacted ones. The sensitivity and specificity of the test (I3M < 0.08) was 96.2% and 72.4% for non-impacted third molars and 46.2% and 87% for impacted third molars, respectively. Our findings indicate that the cut-off value of I3M < 0.08 resulted in greater number of age misclassifications (false negatives) for impacted molars, highlighting the need for new cut-off value of I3M to meet the legal standards. It was concluded that the mineralization of impacted third molars was slower compared to non-impacted ones in south Indian males and females. Further studies are warranted to validate these findings among a larger and more diverse sample.

Age estimation using third molar maturation based on Demirjian's criteria

Dental age estimation is routinely used in human identification, in both the living and the dead. Teeth follow a predictable pattern of eruption and maturation that can be assessed radiographically in the living, allowing experts to estimate an individual's age. Third molars develop much later than the other permanent teeth, and can be used to estimate age of individuals nearing the age of maturity. Ability of third molar maturation when graded using Demirjian's method in ascertaining whether an individual has attained the medicolegal ages of 16 and 18 years has not yet been verified. The present study involved assessing the third molar maturation of 220 individuals of a training set using Demirjian's scoring system, generating regression models to estimate age using the third molar maturity scores, applying these models on a test set of 40 individuals, and calculating the mean difference (MD) and the mean absolute error (MAE) between the chronological and estimated ages of the test set participants. It was observed that the lowest mean difference and mean absolute error was observed for the maturation of the left mandibular third molar (MD = 1.05 years, MAE = 2.09 years). Boxplots generated in the study report that the third molar maturation stages given by Demirjian can identify whether an individual has attained the medicolegally significant ages of 16 and 18 years of age.

Age Estimation Using the Cameriere Methods of Open Apices: A Meta-Analysis

Purpose: To evaluate the actual variability of the mean difference between chronological and dental age using the Cameriere method of open apices and to test its accuracy in variable age groups. Method: We selected studies that contained data about the mean, standard deviation, and number of cases for chronological age, dental age and gender. We used a random-effects model. Statistical significance was estimated, at a p < 0.05, using prediction intervals. For the analysis of publication bias we used the funnel plot and Egger’s regression test for plot asymmetry. I² was used to test the presence of heterogeneity between studies. The Z test was used to test for statistical differences between subgroups, with p < 0.05 being considered statistically significant. We also used 95% for confidence intervals and prediction intervals. Results: In boys, the average difference between chronological and dental age was 0.44 (0.26–0.63) years, while in girls the average difference between chronological and dental age was 0.34 (0.19–0.49) years. In the 6–7 years age group and in the 14–15 years age group, there was a statistically significant difference between dental and chronological age. Our study shows that the Cameriere method is useful for estimating the chronological age, with errors of less than one year. Conclusions: The Cameriere method of evaluating dental age using open apices is sufficiently accurate for forensic practice, at least in the 7–14 age-interval.

Application and performance of artificial intelligence technology in forensic odontology - A systematic review

Forensic odontology (FO) mainly deals with the identification of the individual through the remains, which mainly includes teeth and jawbones. Artificial intelligence (AI) technology has proven to be a breakthrough in providing reliable information in decision making in forensic sciences. This systematic review aimed to report on the application and performance of AI technology in FO. The data was gathered through searching for the articles in the renowned search engines, which have been published between January 2000 - June 2020. QUADAS-2 was adopted for the risk of bias analysis of the included studies. AI technology has been widely applied in FO for identifying bite-marks, predicting mandibular morphology, gender determination, and age estimation. Most of these AI models are based on either artificial neural networks (ANNs) or convolutional neural networks (CNNs). The results of the studies are promising. Studies have reported that these models display accuracy and precision equivalent to that of the trained examiners. These models can be promising tools when identifying victims of mass disasters and as an additive aid in medico-legal situations.