Coronal pulp cavity index as noble modality for age estimation: a digital image analysis

Three-dimensional surface area analyses of developing maxillary second premolar root apices for age estimation using CBCT images

Three-dimensional surface area analyses of developing root apices for age estimation in children and young adults have shown promising results. The current study aimed to apply this three-dimensional method to develop a regression model for estimating age in Malaysian children aged 7 to 14 using developing maxillary second premolars. A training sample of 155 cone-beam computed tomography scans (83 Malays and 72 Chinese) was analysed, and the formula was subsequently validated on an independent sample of 92 cone-beam computed tomography scans (45 Malays and 47 Chinese). The results showed a strong correlation (r = 94 %) between the chronological age as a dependent variable and the predictor variables, including root surface area of the apex, sex, ethnicity, and root development status (open/closed apices). For this model, the predictor variables accounted for 88.4 % of the variation in age except sex and ethnicity. A mean absolute error value of 0.42 indicated that this model can be reliably used for Malaysian children. In conclusion, this study recognises the method of three-dimensional surface area analyses as a valuable tool for age estimation in forensic and clinical practice. Further studies are highly recommended to assess its effectiveness across different demographic groups.

A systematic overview of dental methods for age assessment in living individuals: from traditional to artificial intelligence-based approaches

Dental radiographies have been used for many decades for estimating the chronological age, with a view to forensic identification, migration flow control, or assessment of dental development, among others. This study aims to analyse the current application of chronological age estimation methods from dental X-ray images in the last 6 years, involving a search for works in the Scopus and PubMed databases. Exclusion criteria were applied to discard off-topic studies and experiments which are not compliant with a minimum quality standard. The studies were grouped according to the applied methodology, the estimation target, and the age cohort used to evaluate the estimation performance. A set of performance metrics was used to ensure good comparability between the different proposed methodologies. A total of 613 unique studies were retrieved, of which 286 were selected according to the inclusion criteria. Notable tendencies to overestimation and underestimation were observed in some manual approaches for numeric age estimation, being especially notable in the case of Demirjian (overestimation) and Cameriere (underestimation). On the other hand, the automatic approaches based on deep learning techniques are scarcer, with only 17 studies published in this regard, but they showed a more balanced behaviour, with no tendency to overestimation or underestimation. From the analysis of the results, it can be concluded that traditional methods have been evaluated in a wide variety of population samples, ensuring good applicability in different ethnicities. On the other hand, fully automated methods were a turning point in terms of performance, cost, and adaptability to new populations.

Coronal pulp: An age biomarker - A cross-sectional radiographic study in children

Background:

Age plays an important role in personal identification, treatment planning, forensic dentistry, and legal issues. It is one of the key identification tools for distinguishing one person from another and one population from another. An intraoral radiographic technique for age estimation is an easier approach. The widely accepted age estimation method in children is the Demirjian system. Tooth coronal index is another method that gained popularity for adult age estimation.

Aim:

This study aims to estimate the tooth coronal index (TCI) of mandibular right and left second deciduous molar and its correlation with chronological age to derive a regression equation.

Settings and Design:

The present study is a cross-sectional radiographical study which is conducted in AME's Dental College and Hospital, Raichur, Karnataka, India.

Materials and Methods:

A total of 100 children aged 5–10 years were selected. Digital intraoral periapical radiographs were taken for right and left deciduous mandibular second molar. The length of the tooth crown and the coronal pulp cavity were measured. Statistical Analysis: Further, the data are subjected to student's unpaired t-test and ANOVA test for the statistical analysis and simple linear regression to derive the regression equation.

Results:

TCI showed a statistically significant reduction with increasing age in both right and left mandibular deciduous second molar (P ≤ 0.05), and the strength of the correlation is moderate (r = −0.59) if age is correlated with TCI using simple linear regression.

Conclusion:

The tooth coronal index method is found as a simple, noninvasive, nondestructive and cost-effective method for age assessment in children.

The accuracy of age estimation from pulp chamber/crown volume ratio of canines obtained by cone beam computed tomography images: an Egyptian study

Background

Globally, the need for an accurate and valid method for age estimation in adults still exists. The aging process is associated with secondary dentine deposition that reduces the volume of teeth pulp. Therefore, dental age could be recognized from the volume of pulp cavity. The aim of this study was to assess the accuracy and validity of pulp chamber/crown volume ratio of maxillary and mandibular canines in estimating age using cone beam computed tomography (CBCT) images in a sample of the Egyptian population.

Results

There were significant strong negative correlations between age and each of the maxillary pulp chamber volume (PCV), mandibular PCV, maxillary pulp chamber/crown volume (PCV/CV) ratio, and mandibular PCV/CV ratio (p < 0.001). Furthermore, no significant differences were detected between both sexes regarding the mean maxillary and mandibular PCV and PCV/CV ratios (p > 0.05). The best fit regression model for age prediction was as follows: age (years) = 70.21 − 784.0x maxillary PCV/CV ratio − 1.66x maxillary PCV. The proposed model showed good power of prediction (R2 adjusted = 0.951). Additionally, the model was validated on an independent sample of 100 CBCT images with a root mean squared error (RMSE) of 2.86 years.

Conclusion

The obtained valid regression formula in this study can serve as a reliable tool for age estimation in Egyptians. This formula should be further validated on a larger sample size of the Egyptian population that considers more steady age distribution.