Sexual dimorphism of enamel area, coronal dentin area, bicervical diameter and dentinoenamel junction scallop area in longitudinal ground section

How teeth can be used to estimate sexual dimorphism? A scoping review

INTRODUCTION

Teeth are biological structures with a high degree of hardness, density, calcification, and capacity to adapt to extrinsic factors at physical, biological, and physiological levels. Subsequently, they resist for a longer period in deteriorating environmental conditions. With dental analysis, it is possible to acquire biographical data about a person. The aim of this scoping review was to identify publications using human teeth tissues to estimate sexual dimorphism.

METHODS

The scoping review was carried out in the following databases: Jstor, Scielo, Science Direct, PubMed, and Scopus, using ten search strategies in English and guaranteeing completeness and reproducibility of the phases stipulated in the PRISMA guide.

RESULTS

143 studies on sexual dimorphism based on dental tissue traits were included, of which 40.6% (n = 58) were done in Asia and 27.2% (n = 39) in America. 80% of the studies (equivalent to 114 articles) focused their observations and measurements on the dental crown; 4.2% in enamel, dentin, and pulp together; 3.5% in dental pulp; 2.1% in the entire tooth; 2.8% in enamel, root, and the enamel-cementum junction, and only 0.7% in dentin and pulp. In addition, 92.3% of the studies used metric methods, while only 4.9% and 2.8% used biochemical and non-metric method respectively.

CONCLUSION

For sexual dimorphism establishment, enamel has been the most analyzed dental tissue in permanent canines and molars mainly. Likewise, the most widely and accurately used methods for this purpose are the metrics, with the odontometry as the most implemented (intraoral or by using dental plaster models, digital scanning or software) with prediction percentages ranging from 51% to 95.9%. In contrast to biochemical methods, that can achieve the highest precision (up to 100%), the non-metric methods, to a less extent, reported prediction percentages of 58%.

Novel trends, challenges and new perspectives for enamel repair and regeneration to treat dental defects

Dental enamel is the hardest tissue in the human body, providing external protection for the tooth against masticatory forces, temperature changes and chemical stimuli. Once enamel is damaged/altered by genetic defects, dental caries, trauma, and/or dental wear, it cannot repair itself due to the loss of enamel producing cells following the tooth eruption. The current restorative dental materials are unable to replicate physico-mechanical, esthetic features and crystal structures of the native enamel. Thus, development of alternative approaches to repair and regenerate enamel defects is much needed but remains challenging due to the structural and functional complexities involved. This review paper summarizes the clinical aspects to be taken into consideration for the development of optimal therapeutic approaches to tackle dental enamel defects. It also provides a comprehensive overview of the emerging acellular and cellular approaches proposed for enamel remineralization and regeneration. Acellular approaches aim to artificially synthesize or re-mineralize enamel, whereas cell-based strategies aim to mimic the natural process of enamel development given that epithelial cells can be stimulated to produce enamel postnatally during the adult life. The key issues and current challenges are also discussed here, along with new perspectives for future research to advance the field of regenerative dentistry.

A Radio-Odontometric Analysis of Sexual Dimorphism in First Molars Using Cone-Beam Computed Tomography

OBJECTIVE

Different techniques for sex prediction are developed and used in the forensic medicine field. One of these methods is based on the teeth morphometry. The aim of the present study was to evaluate the degree of sex determination of the maxillary and mandibular first molar teeth in cone beam computed tomography images.

METHOD AND MATERIALS

This study was carried out on cone beam computed tomography images of 100 men and 100 women with a mean age of 21.28 ± 2.47 years. The roof, floor and height of pulp chamber, as well as marginal enamel thickness and dentin thickness at the height of contour, tooth width, and crown length were measured. Student t test and discriminant analysis were applied to assess the differences in the measured parameters between men and women.

RESULTS

According to the present study, the maxillary first molar was more dimorphic than the mandibular teeth. The accuracy of sex identification of mandibular and maxillary first molar tooth was 84% and 77%, respectively. The mesiodistal measured variables were more accurate in sexual differentiation than the buccolingual ones. For sex differentiation, the most dominant variables for maxillary and mandibular first molar teeth were crown height and dentin thickness, respectively.

CONCLUSIONS

The first molar tooth showed an acceptable level of sex determination accuracy based on the odontometric measurements.

Sex classification of first molar teeth in cone beam computed tomography images using data mining

OBJECTIVE

The teeth have been used as a supplementary tool for sex differentiation as they are resistant to post-mortem degradation. The present study aimed to develop a new novel informatics framework for predicting sex from linear tooth dimension measurements achieved from cone beam computed tomography (CBCT) images.

METHOD AND MATERIALS

A clinical workflow using different machine learning methods was employed to predict the sex in the present study. The CBCT images of 485 subjects (245 men and 240 women) were evaluated for sex differentiation. Nine parameters were measured in both buccolingual and mesiodistal aspects of the teeth. We applied our dataset to Naïve Bayesian (NB), Random Forest (RF), and Support Vector Machine (SVM) as classifiers for prediction. Genetic feature selection was used to discover real features associated with sex classification.

RESULTS

The 10-fold cross-validation results indicated that NB had higher accuracy than SVM and RF for sex classification. The genetic algorithm (GA) indicated that the model could fit the data without using the enamel thickness and pulp height. The average classification accuracy of our clinical workflow was 92.31 %.

CONCLUSION

The results showed that NB was the best method for sex classification. The application of the first molar teeth in sex prediction indicated an acceptable level of sexual classification. Therefore, these odontometric parameters can be applied as an additional tool for sex determination in forensic anthropology.