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

Estimation of Age implementing pulp tooth volume ratio in maxillary canines of an Indian population by means of CBCT scans

BACKGROUND

Forensic odontology is a subfield of forensics that can assist in determining age, gender, and other demographic factors.

OBJECTIVE

The focus of this research is to ascertain age by tooth volume ratio of permanent maxillary canines using a CBCT scan.

METHODS

In this retrospective investigation, 1000 CBCT images were gathered and focused on only fully developed maxillary canines. For each of the maxillary canines, the researchers measured and calculated the volume of the pulp chamber, root canal, and entire tooth using the ITK Snap programme. The pulp volume to tooth volume ratio was computed. The equation AGE = 59.208 - (583.652 x pulp volume/tooth volume) was then used to compute age. The samples were divided into 5 age groups; 13-20, 21-30, 31-40, 41-50, and 51-60. The age was calculated for samples in each group and it was compared to the actual age.

RESULTS

Between individuals' actual age and computed age, the study discovered a statistically significant positive association. While groups 3, 4, and 5 demonstrated positive but weaker correlations (r= 0.854, r= 0.658, and r= 0.612, respectively), groups 1 and 2 displayed statistically significant strong positive correlations (r= 0.987 and r= 0.923, respectively). The average total discrepancy between the age that was computed and the actual age was 2.45 1.344.

CONCLUSION

The study found a statistically significant positive correlation between computed age and actual age, with the younger age groups 1 (13-20) and 2 (21-30) showing the strongest relationships. This underlines its potential success in court, particularly when dealing with young criminals.

Dental age estimation in Indonesian adults: An investigation of the maxillary canine pulp-to-tooth volume ratio using cone-beam computed tomography

Purpose

This study was performed to develop a linear regression model using the pulp-to-tooth volume ratio (PTVR) ratio of the maxillary canine, assessed through cone-beam computed tomography (CBCT) images, to predict chronological age (CA) in Indonesian adults.

Materials and Methods

A sample of 99 maxillary canines was collected from patients between 20 and 49.99 years old. These samples were obtained from CBCT scans taken at the Universitas Padjadjaran Dental Hospital in Indonesia between 2018 and 2022. Pulp volume (PV) and tooth volume (TV) were measured using ITK-SNAP, while PTVR was calculated from the PV/TV ratio. Using RStudio, a linear regression was performed to predict CA using PTVR. Additionally, correlation and observer agreement were assessed.

Results

The PTVR method demonstrated excellent reproducibility, and a significant correlation was found between the PTVR of the maxillary canine and CA (r=-0.74, P<0.01). The linear regression analysis showed an R2 of 0.58, a root mean square error of 5.85, and a mean absolute error of 4.31.

Conclusion

Linear regression using the PTVR can be effectively applied to predict CA in Indonesian adults between 20 and 49.99 years of age. As models of this type can be population-specific, recalibration for each population is encouraged. Additionally, future research should explore the use of other teeth, such as molars.

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.

Age Estimation Using Maxillary Central Incisor Analysis on Cone Beam Computed Tomography Human Images

Forensic dentistry plays an important role in human identification, and dental age estimation is an important part of the process. Secondary dentin deposition throughout an individual's lifetime and consequent modification in teeth anatomy is an important parameter for age estimation procedures. The aim of the present study was to develop regression equations to determine age in adults by means of linear measurements and ratios on sagittal, coronal and axial slices of maxillary central incisors using cone bean computed tomography (CBCT). Multiplanar measurements of upper central incisors were taken for a sample of 373 CBCTs. Subsequently, one-way analysis of variance (ANOVA) and multivariate linear regressions were performed for age estimation. The equations obtained from axial linear measurements and ratios presented a standard error of the estimate (SEE) of ±10.9 years (R² = 0.49), and a SEE of ±10.8 years (R² = 0.50), respectively. The equation obtained for multiplanar linear measurements presented a SEE of ±10.9 years (R² = 0.52), while the equation for multiplanar ratios presented a SEE of ±10.7 years (R² = 0.51). Thus, CBCT measurements on upper central incisors were found to be an acceptable method for age estimation. Horizontal measurements, especially pulp measurements, improve the accuracy of age estimate equations.

CBCT in dental age estimation: A systematic review and meta analysis

OBJECTIVES

This study aimed to investigate the reproducibility of dental age estimation methods in cone beam computed tomography (CBCT) and the correlation between dental (DA) and chronological (CA) ages.

METHODS

The scientific literature was searched in six databases (PubMed, Scopus, LILACS, Web of Science, SciELO, and OATD). Only observational studies were selected. Within each study, the outcomes of interest were (I) the quantified reproducibility of the method (κ statistics and Intraclass correlation coefficient); and (II) the correlation (r) between the dental and chronological ages. A random-effect three-level meta-analysis was conducted alongside moderator analysis based on methods, arch (maxillary/mandibular), population, and number of roots.

RESULTS

From 671 studies, 39 fulfilled the inclusion criteria, with one study reporting two different methods. The methods used in the studies were divided into metric (n = 17), volumetric (n = 20), staging (n = 2), and atlas (n = 1). All studies reported high examiner reproducibility. Group 1 (metric and volumetric) provided a high inverse weighted r ([Formula: see text] = -0.71, CI [-0.79,-0.61]), and Group 2 (staging) provided a medium-weighted r ([Formula: see text] = 0.49, CI [0.44, 0.53]). Moderator analysis on Group one did not show statistically significant differences between methods, tooth position, arch, and number of roots. An exception was detected in the analysis based on population (Southeast Asia, [Formula: see text] = -0.89, CI [-0.94,-0.81]).

CONCLUSION

There is high evidence that CBCT methods are reproducible and reliable in dental age estimation. Quantitative metric and volumetric analysis demonstrated better performance in predicting chronological age than staging. Future studies exploring population-specific variability for age estimation with metric and volumetric CBCT analysis may prove beneficial.