Studies on the radiographic visibility of the periodontal ligament in lower third molars: can the Olze method be used in the Chinese population?

Radiological assessment of periodontal ligament space visibility on third molars for forensic age assessment - a comparison study of three different staging scales

Various staging scales have been proposed for the assessment of the visibility of the periodontal ligament space of mandibular third molars on dental panoramic radiographs (PANs) for forensic age assessment in living individuals. However, up to now, there has been no systematic comparison between these staging scales available. We directly compared the 2010 staging scale proposed by Olze et al. with the 2017 staging by Lucas et al. and the 2020 staging by Guo et al. in a German study population. We evaluated 233 PANs from 115 females and 118 males aged 20.0 to 40.9 years using three independent examiners, with one examiner conducting two assessments. We examined the correlation between age and stage, as well as the inter- and intra-rater reliabilities. While the point estimates for the correlation coefficient and the reliability measures were lowest for the Guo scale and highest for the Olze scale, confidence intervals showed a large overlap, particularly for the scales of Olze et al. and Lucas et al. The correlation coefficients between stage and age were consistently lower in females than in males across all methods. In summary, we showed that the staging scales of Olze et al. and Lucas et al. were very similar. The Olze method showed higher point estimates across all analyses, and because there are more reference data available for this method, we argue that it should be preferred as the method of choice for further studies in the field. However, Guo method could be considered for instances, in which the inter-radicular periodontal ligament is not evaluable.

The relevance of taurodontism in forensic dental age estimation

Taurodontism is a dental morphological anomaly characterized by enlarged pulp cavities repositioned towards the apical region of the tooth, coupled with shortened root structures. Molars are commonly affected by this alteration. Certain populations exhibit up to 48% prevalences for this dental alteration, underscoring its significance in dental age estimation (DAE). In the field of DAE, an individual's chronological age is inferred from specific dental features, frequently employed within the forensic context. The effect of taurodontism on the features of DAE is an unanswered issue. The influence of taurodontism on eruption, mineralization, radiographic visibility of root canals, and radiographic visibility of the periodontal ligament space in mandibular third molars- some of the established criteria for DAE as examples-is currently not systematically examined. Some common staging scales for the dental features of DAE cannot technically be applied to taurodontic teeth. Additionally, given the association of taurodontism with syndromes affecting tooth development, caution is warranted in age assessment procedures. Notably, taurodontic teeth may serve as indicators of syndromes influencing skeletal development, further emphasizing the relevance of taurodontism in forensic age assessment. Presumably taurodontic teeth were included in reference data to some extent due to their partially high prevalence in the past, whereby the influence of taurodontism has been statistically absorbed within the overall spread of the features. Future studies should compare the temporal course of these tooth characteristics in affected and unaffected teeth. Subsequent initiatives should focus on raising awareness among forensic dentists regarding taurodontism, necessitating in-depth exploration of the subject.

Predicting chronological age of 14 or 18 in adolescents: integrating dental assessments with machine learning

AIM

Age estimation plays a critical role in personal identification, especially when determining compliance with the age of consent for adolescents. The age of consent refers to the minimum age at which an individual is legally considered capable of providing informed consent for sexual activities. The purpose of this study is to determine whether adolescents meet the age of 14 or 18 by using dental development combined with machine learning.

METHODS

This study combines dental assessment and machine learning techniques to predict whether adolescents have reached the consent age of 14 or 18. Factors such as the staging of the third molar, the third molar index, and the visibility of the periodontal ligament of the second molar are evaluated.

RESULTS

Differences in performance metrics indicate that the posterior probabilities achieved by machine learning exceed 93% for the age of 14 and slightly lower for the age of 18.

CONCLUSION

This study provides valuable insights for forensic identification for adolescents in personal identification, emphasizing the potential to improve the accuracy of age determination within this population by combining traditional methods with machine learning. It underscores the importance of protecting and respecting the dignity of all individuals involved.

Accurate age classification using manual method and deep convolutional neural network based on orthopantomogram images

Age estimation is an important challenge in many fields, including immigrant identification, legal requirements, and clinical treatments. Deep learning techniques have been applied for age estimation recently but lacking performance comparison between manual and machine learning methods based on a large sample of dental orthopantomograms (OPGs). In total, we collected 10,257 orthopantomograms for the study. We derived logistic regression linear models for each legal age threshold (14, 16, and 18 years old) for manual method and developed the end-to-end convolutional neural network (CNN) which classified the dental age directly to compare with the manual method. Both methods are based on left mandibular eight permanent teeth or the third molar separately. Our results show that compared with the manual methods (92.5%, 91.3%, and 91.8% for age thresholds of 14, 16, and 18, respectively), the end-to-end CNN models perform better (95.9%, 95.4%, and 92.3% for age thresholds of 14, 16, and 18, respectively). This work proves that CNN models can surpass humans in age classification, and the features extracted by machines may be different from that defined by human.

Usability of dental pulp visibility and tooth coronal index in digital panoramic radiography in age estimation in the forensic medicine

Age estimation has a great importance due to legal requirements. The aim of our study was to determine the applicability of two different methods in age estimation; one of them based on the calculation of the visibility of the root pulp of mandibular third molar teeth and the other based on the calculation of the tooth coronal index (TCI) in the mandibular first and second molar teeth in the 9059 digital orthopantomogram of people aged between 15 and 40 in Bursa. In the first method in which the visibility of the fully mineralized root pulp of the mandibular third molar teeth was evaluated in 4 stages; the stages 0, 1, 2, and 3 were observed regardless of sex at the earliest 17.2; 19.1; 20.1, and 25.1 years, respectively. In the second method in which TCI was regressed on chronological age using measuring crown and coronal pulp cavity heights, the most accurate age estimation model based on simple linear regression for all cases without any sex difference was found to be with right first molar tooth (SEE ±7304 years) and the most accurate age model based on multiple regression model was found to be with bilateral first molar teeth (SEE ±7413 years). In conclusion, we believe that the root pulp visibility of the third molar teeth can be applied safely for stages 1, 2, and 3 at 16, 17, and 21 years of ages, respectively. A correlation was also found between TCI and age, and our findings have shown that both methods are available for forensic purposes.

Dental age estimation based on the radiographic visibility of the periodontal ligament in the lower third molars: application of a new stage classification

The purpose of the present study was to test whether a new stage classification based on radiographic visibility of the periodontal ligament in lower third molars in a Chinese population can be used for the 18- and 21-year thresholds. A total of 1300 orthopantomograms, including equal numbers of northern Chinese males and females evenly distributed between the ages of 15 and 40 years, were analyzed. The stages were defined according to the visibility of periodontal ligament for the outer parts of lower third molar roots because the visibility status of the periodontal ligament between the roots of lower third molars is none valuable in many Chinese individuals. Stage 0 was first achieved at the age of 17.05 years in males and 17.46 years in females. The earliest appearance of stage 1 was 17.47 years in males and 17.86 years in females. Stage 2 was first observed in males at the age of 21.43 years and in females at the age of 21.96 years. The onset of stage 3 was first observed at the age of 25.83 years in males and 23.14 years in females. Compared with the stage classification of Olze et al., which also considers the mesial parts of the roots, the number of assessable cases could be significantly increased. Therefore, our novel approach is effective for age estimation in the Chinese population.

Age assessment in the living using modified Gustafson's criteria in a northern Chinese population

Regressive dental changes appear to be suitable for age assessment in living adults. In 2012, Olze et al. showed that several criteria presented by Gustafson for extracted teeth can also be applied to orthopantomograms. The objective of this study was to test the applicability and reliability of this method in a Chinese population. For this purpose, 1300 orthopantomograms of 650 female and 650 male Chinese aged between 15 and 40 years were evaluated. The characteristics of secondary dentin formation, periodontal recession, attrition, and cementum apposition were reviewed in all the mandibular premolars. The sample was split into a training and test dataset. Based on the training set, the correlation of the individual characteristics with chronological age was studied with a stepwise multiple regression analysis, in which individual characteristics formed the independent variable. According to the results, the R values amounted to 0.80 to 0.83; the standard error of estimate was 4.29 to 4.75 years. By analyzing the test dataset, the accuracy of the present study, Olze's and Timme's formulas were determined by the difference between the estimated dental age (DA) and chronological age (CA). Taking both mean differences and mean absolute differences into account, the Chinese age estimation formula did not always perform better compared with Olze's and Timme's formulas for both males and females. It was concluded that this method can be used in Chinese individuals for age assessment. However, the applicability of the method is limited by the quality of the X-ray images, and the method should only be applied by experienced forensic odontologists.