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When a disaster occurs, the authority must prioritise two things. First, the search and rescue of lives, and second, the identification and management of deceased individuals. However, with thousands of dead bodies to be individually identified in mass disasters, forensic teams face challenges such as long working hours resulting in a delayed identification process and a public health concern caused by the decomposition of the body. Using dental panoramic imaging, teeth have been used in forensics as a physical marker to estimate the age of an individual. Traditionally, dental age estimation has been performed manually by experts. Although the procedure is fairly simple, the large number of victims and the limited amount of time available to complete the assessment during large-scale disasters make forensic work even more challenging. The emergence of artificial intelligence (AI) in the fields of medicine and dentistry has led to the suggestion of automating the current process as an alternative to the conventional method. This study aims to test the accuracy and performance of the developed deep convolutional neural network system for age estimation in large, out-of-sample Malaysian children dataset using digital dental panoramic imaging. Forensic Dental Estimation Lab (F-DentEst Lab) is a computer application developed to perform the dental age estimation digitally. The introduction of this system is to improve the conventional method of age estimation that significantly increase the efficiency of the age estimation process based on the AI approach. A total number of one-thousand-eight-hundred-and-ninety-two digital dental panoramic images were retrospectively collected to test the F-DentEst Lab. Data training, validation, and testing have been conducted in the early stage of the development of F-DentEst Lab, where the allocation involved 80 % training and the remaining 20 % for testing. The methodology was comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental imaging, segmentation, and classification of mandibular premolars using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. The suggested DCNN approach underestimated chronological age with a small ME of 0.03 and 0.05 for females and males, respectively.

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Background The study highlights the gonial angle as a key craniofacial landmark for age and gender determination in forensic cases. It emphasizes population-specific analysis, enhancing precision by recognizing variations between populations. By clarifying the gonial angle's forensic use, the study offers clear guidelines, improving forensic practices. Moreover, the gonial angle and age and gender correlations are thoroughly examined, offering important information on their forensic relevance. The results highlight how crucial population-specific research is to improving the precision and dependability of forensic age and gender estimation techniques, which advances forensic anthropology and supports forensic investigations around the globe. Aim and objective The purpose of this study is to assess the accuracy of age and gender estimates using gonial angles. The objectives of this research are to evaluate the precision of age and gender estimates utilizing the gonial angle. Materials and methods This present study comprises two groups based on age groups: Group I belongs to 51 to 60 years of age, and Group II belongs to 61 to 70 years of age. Making use of G-Power software (version 3.1.9.4, Düsseldorf, Germany), the sample size was determined. The calculation ensured 95% statistical power at a significance level (alpha error probability) of 0.05. To achieve sufficient statistical power, a total of 1000 samples were included, with a projected required sample size of 92. A total of 1000 samples, consisting of 500 male and 500 female panoramic radiographs, were meticulously selected for the study. The samples picked were within the age range of 51 to 70 years. Orthopantomograms were determined using Planmeca software (Planmeca Romexis®, Version 6.0, USA Inc.). Descriptive statistics, including prediction classification analysis of age and gender, were conducted using SPSS Statistics version 16.0 (SPSS Inc., Released 2007, SPSS for Windows, Version 16.0, Chicago, SPSS Inc.). Results According to this study, the mean gonial angle of males aged 51 to 60 years is larger (124.7370 degrees) than that of females (119.6371 degrees). The female group's mean estimates are more accurate, as seen by the smaller standard error (0.20844) compared to the male group's (0.60998). A statistically significant difference in mean gonial angles between the genders is evident, with males having a larger gonial angle (p-value <0.001). In the age range of 61 to 70 years, the mean gonial angle of females is higher (128.4322 degrees) than that of males (124.0529 degrees). In this instance, the male group's standard error is smaller (0.14968) than the female group's (0.30028), indicating more accurate mean estimates. Once more, a statistically significant difference is indicated by a p-value of less than 0.001, with females having a larger gonial angle than males. Conclusion Our study revealed that the gonial angle of the mandible can be considered a reliable parameter for gender identification. The study's limitation is its inability to reliably identify gender in the subadult population and in cases of edentulousness. An orthopantomogram is a trustworthy and accurate method for taking the different measurements needed to identify the gender of a particular mandible.

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Cameriere developed a method on orthopantomograms (OPG) to assess adult age of 18 years based on the relationship between age and the third molar maturity index I3M. The aim of this study was to evaluate whether Cameriere's method could be applied to computed-tomography scans (CT-scans) from a population of French juveniles and young adults and compare the results obtained from OPG of the same individuals. Our sample comprised 200 examinations that had been performed at the radiological department of a French University hospital between 2007 and 2020. Each patient had received an OPG and a cranial CT scan for medical purposes, and we used a similar adaptation of I3M based on OPG to determine the I3M based on CT scans. Due to exclusion criteria, our final sample comprised 71 OPGs and 63 CT scans. Based on the 71 OPGs, there was concordance between chronological age and estimated age, with a sensitivity of 78.57%, a specificity of 89.47%, and a misclassified rate of 18.03% based on tooth 38, and a sensitivity of 78.79%, a specificity of 91.67%, and a misclassified rate of 17.78% based on tooth 48. Our results based on CT scans presented concordance between chronological age and estimated age for tooth 38 described by a sensitivity of 77.78%, a specificity of 94.12%, and a misclassified rate of 16.98%. The concordance between chronological age and estimated age based on 48 had a sensitivity of 75.00%, a specificity of 93.75%, and a misclassified rate of 19.23%. The > 90% ICC indicate an excellent similarity between measurements of teeth 38 and 48 based on OPGs and CT scans. This study has revealed the applicability of the Cameriere's method to calculate the I3M based on CT scans from a French population. The results based on CT scans are similar to results based on OPGs from the same individuals.

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In forensic practice, medicolegal physicians are often tasked with estimating age using dental evidence. This calls for an uncomplicated, reliable, and reproducible method for dental age estimation, enabling physicians to proceed without specific odontological expertise. Among various dental methods, third molar eruption analyses are less complicated and easier to perform. In our study, we explored the effectiveness of Gambier et al.'s scoring system, which examines the eruption of all third molars. We retrospectively analysed 1032 orthopantomograms (528 males and 504 females) of individuals aged between 15 and 24 years. The mean chronological age increased with the progression of stages (1 to 3) and phases (A to D) of the third molar eruption for both sexes. In terms of stages, none showed significant discrimination between minors (<18 years) and adults (>18 years), especially for males. However, Gambier's phase D displayed a relatively high likelihood of being 18 years or older, with an overall 85.9 % of males and 95.7 % of females having all third molars in stage 3 being 18 years or older. While the tested method could be helpful in indicating the completion of the 18th year of life, caution is advised (due to a high percentage of false positives), and it should be used alongside other age assessment methods by experts.

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This work aimed to assess the pulp/tooth area ratio's utility in the upper central incisors using orthopantomograms. A convenience sample of 801 adult patient orthopantomograms was studied. Image J® software was used to measure the pulp/tooth area ratio, and a regression model was developed. Our results conclude that the methodology assessing upper incisors' pulp/tooth area ratio using orthopantomograms can lead to age overestimation and statistically significant differences between chronological and estimated age. For those over 50, no correlation between pulp/tooth area ratio and chronological age was found, suggesting that this may be the upper limit of this technique in this population. This methodology may not be suitable for age estimation, particularly in older adults.

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Dental age estimation, a cornerstone in forensic age assessment, has been extensively tried and tested, yet manual methods are impeded by tedium and interobserver variability. Automated approaches using deep transfer learning encounter challenges like data scarcity, suboptimal training, and fine-tuning complexities, necessitating robust training methods. This study explores the impact of convolutional neural network hyperparameters, model complexity, training batch size, and sample quantity on age estimation. EfficientNet-B4, DenseNet-201, and MobileNet V3 models underwent cross-validation on a dataset of 3896 orthopantomograms (OPGs) with batch sizes escalating from 10 to 160 in a doubling progression, as well as random subsets of this training dataset. Results demonstrate the EfficientNet-B4 model, trained on the complete dataset with a batch size of 160, as the top performer with a mean absolute error of 0.562 years on the test set, notably surpassing the MAE of 1.01 at a batch size of 10. Increasing batch size consistently improved performance for EfficientNet-B4 and DenseNet-201, whereas MobileNet V3 performance peaked at batch size 40. Similar trends emerged in training with reduced sample sizes, though they were outperformed by the complete models. This underscores the critical role of hyperparameter optimization in adopting deep learning for age estimation from complete OPGs. The findings not only highlight the nuanced interplay of hyperparameters and performance but also underscore the potential for accurate age estimation models through optimization. This study contributes to advancing the application of deep learning in forensic age estimation, emphasizing the significance of tailored training methodologies for optimal outcomes.

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Forensic odontologists use biological patterns to estimate chronological age for the judicial system. The age of majority is a legally significant period with a limited set of reliable oral landmarks. Currently, experts rely on the questionable development of third molars to assess whether litigants can be prosecuted as legal adults. Identification of new and novel patterns may illuminate features more dependably indicative of chronological age, which have, until now, remained unseen. Unfortunately, biased perceptions and limited cognitive capacity compromise the ability of researchers to notice new patterns. The present study demonstrates how artificial intelligence can break through identification barriers and generate new estimation modalities. A convolutional neural network was trained with 4003 panoramic-radiographs to sort subjects into 'under-18' and 'over-18' age categories. The resultant architecture identified legal adults with a high predictive accuracy equally balanced between precision, specificity and recall. Moving forward, AI-based methods could improve courtroom efficiency, stand as automated assessment methods and contribute to our understanding of biological ageing.

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Different studies have established that the mineralization stages of the second mandibular molar can be used in forensic age estimation. Nowadays, the estimate's accuracy is an ethical concern, producing as few false positives (individuals incorrectly classified as older than a determined threshold) and false negatives (individuals incorrectly classified as younger than a determined threshold) as possible. Some have hypothesized that changes in teeth number may influence tooth mineralization, altering the age estimate process. This paper analyzes whether third molar agenesis affects the second mandibular molar mineralization time frame. To do so, 355 orthopantomograms were evaluated for third molar agenesis, and the second mandibular molar mineralization stage was assessed using the Demirjian stages. Student's t-test was used to compare the difference in the mean age at which the various stages of 37 mineralization were reached in the groups with and without third molar agenesis. The level of statistical significance was set at 5%. The results pointed to a delay in second mandibular molar mineralization in the case of agenesis, suggesting the need to consider this when estimating age using dental techniques.

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This study aimed to systematically review the correlational accuracy between width ratios and length ratios based on the Kvaal methodology with chronological age. This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The search strategy included ProQuest, PubMed, Science Direct, and Taylor and Francis and Willey online without time or language restriction using Kvaal method of age estimation as key words for the search up to December 2021. A team of two researchers independently selected the studies and extracted the data. The Covidence platform was used to systematically organize all titles. The full texts of eligible studies were analyzed. Risk of bias (RoB) was assessed using a modified (to the specific characteristics of this systematic review) checklist based on Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement checklist for observational studies. A total of 658 articles were initially reviewed, but 22 were selected for inclusion. The risk of bias was estimated to be unclear to low overall. Among the length ratios, ratio R showed a strong association with chronological age, followed by ratio P. For the width ratios, ratio B demonstrated a close association with chronological age, followed by ratio C. The results suggest that width ratios correlate better with chronological age than length ratios. This systematic review suggests the width ratios are more strongly associated with chronological age than the length ratios. Using a width ratio could serve as a convenient and rapid way to estimate dental age. Our results apply equally to all types of ethnic groups.

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There are many dental age estimation methods, but all the methods do not correspond, especially for aging methods for adults and mature individuals, to the reality of the forensic field, which favors simple, effective, and easy-to-use methods. Ruquet (2015) developed a method based on alveolar bone loss that predicts age for individuals between 25 and 60 years old and is even more accurate for those 25-40 years old. This study re-evaluated Ruquet's alveolar bone loss method using three-dimensional imaging of individuals whose age and sex were known, without taking into account their medical conditions. Digital measurements, from the cemento-enamel junction (CEJ) to the alveolar bone crest (ABC), were performed on the mesial and distal surfaces of teeth on 243 patients, independent of the tridimensional imaging test. With these measurements, two alveolar bone loss averages (ABL) were calculated, one with all the teeth present on the arches and another with only Ramfjörd's teeth. Bone loss showed a significant correlation with age (p < 0.001). The age estimation with all teeth and with only Ramfjörd's teeth showed a statistically significant difference, and age estimation was more accurate when all teeth were used. The assessment of alveolar resorption appears to be an interesting tool for age estimation in adult individuals. However, the method still lacks precision, and the mean absolute errors (MAEs) obtained by age group were all greater than 5 years, except for the age group 35-39 years old, for the age estimation with all teeth. Further studies should explore this existing correlation between alveolar bone loss and age and refine this method to make it more accurate.

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The purpose of this study is to establish and test a reference data set of dental development of Qatari subjects aged between 5 and 25 years. Radiographs of individuals aged between 5 and 25 years were re-used to establish a reference data set (RDS). A scheme comprising 8 tooth development stages (TDS) was used to assess all the teeth on the left side of the maxilla and mandible. The accuracy of dental age estimation (DAE) was tested with a separate sample of radiographs - the validation sample (VS) comprised 50 females and 50 males of known chronological age (CA). Dental panoramic tomographs (DPT) of 1,597 Qataris were assessed. The summary data for the individual TDS comprising the number (n-tds), mean ( x ¯ -tds), standard deviation (sd-tds), 0th%-ile (the minimum), 25th%-ile, 50th%-ile (the median), 75th%-ile, and 100th%-ile (the maximum) were used to estimate the age of the VS subjects using the simple average method (SAM). There is a significant difference in dental age of 4.8 months in the female group when compared to the CA. The difference in the male group is 4.5 months. This shows similar differences to assessments of other ancestral or ethnic groups.

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Introduction: Age estimation using regressive alterations such as root dentin translucency, PDL attachment, and attrition are easy and reliable way of predicting the age. However, extensive and population-specific formula has not been generated. This attempt was to assess the correlation of these alterations with age and to generate a Linear regressive formula, specific to this population. Methods and Material: Three alterations were assessed such as dental attrition, root dentin translucency, and periodontal attachment level from the extracted teeth. Dental attrition was measured using Johanson's and Li and Ji criteria. PDL attachment level and root dentin translucency was measured using the Johanson method and the Lamendin method. Statistical Analysis: SPSS software (Version 27), Pearson correlation test, and Linear regressive analysis were used. Results: Our results showed all three factors/parameters such as attrition, periodontal ligament, and translucency having a very good correlation with age and correlation coefficient r value ranging from 0.6 to 0.8. All the parameters were having statistically significant correlation with P value <0.005. Among them, root dentin translucency with Johanson G method showed excellent correlation with r = 0.83 followed by PDL attachment by Johanson G method with r = 0.702. Conclusions: Regressive changes such as Dentin translucency, PDL attachment and attrition on Coastal Karnataka showed a very good correlation with age. Among them, Dentin translucency by Johanson G method had the best correlation with the a standard error of estimate (SEE). Results of our study indicates that all these parameters [Translucency, PDL attachment, and attrition] can be utilized in age estimation.

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BACKGROUND: The effect of impaction on third molar development is disputable as the scientific literature is not uniform. In parallel, population-specific studies have been encouraged in dental age estimation. This study aimed to investigate the effect of impaction on third molar formation in a sample of Lebanese individuals. MATERIALS AND METHODS: The sample consisted of 518 panoramic radiographs of females (n=229) and males (n=289) between 15 and 23.9 years. Mandibular third molars were classified based on their position as non-impacted and impacted (with horizontal, vertical, mesioangular, and distoangular impaction). Dental development was classified according to Demirjian's 8-level staging system. RESULTS: Most teeth presented mesioangular impaction (#38=29.7%, #48=33%). Developing third molars were predominantly distributed between stages D and G. The mean age of most developmental stages was higher among impacted teeth, meaning that third molar mineralization could be slower in the presence of impaction. In general, the delayed dental development did not have statistically significant effects (P<0.05). However, descriptive data pointed out differences between (impacted and non-impacted) mean ages of >12 months-suggesting a potential clinical significance (despite the lack of a statistical one). Furthermore, differences changed based on sex and side (#38/#48). CONCLUSION: Therefore, dental age estimation from third molars in the selected Lebanese population should preferably be performed in non-impacted third molars whenever available.

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THE AIM OF THE STUDY: Was to conduct the comparative analysis of the age groups' separation accuracy (<18 years old; ≥18 years old) by orthopantomogram depending on the examination's side in Russian population sample. The number of orthopantomograms equal 600 (190 of male and 410 of female) aged from 14 to 23 were investigated. Index value of third molar (Im3) was calculated by the R. Cameriere method, in female and male, on the right and left sides. Index of third molar on the right and left sides shows a high correlation. In the male sample the result specificity was 0.97 on the left and 1.0 on the right, the sensitivity was 0.96 on the left and 0.94 on the right. In the female sample the values were as follows: the specificity was 0.96 on the left and 0.98 on the right, the sensitivity was 0.92 on the left and 0.94 on the right. The results showed the possibility of Im3 (0.08) use to determine the target age group for Russian citizens of both sexes regardless of examination side.

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This paper presents a retrospective analysis of postmortem computed tomography (PMCT) scans of secondary ossification centers in the medial clavicular epiphysis, iliac crest apophysis, proximal humeral epiphysis, distal femoral epiphysis, proximal tibial epiphysis, and distal tibial epiphysis. At the same time, we analyzed PMCT scans of the maxillary and mandibular incisors, canines, premolars, and molars. We assessed 203 corpses, whose age ranged from 2 to 30 years, including 156 males and 47 females. The purpose of our study was to compare the processes of secondary ossification center fusion and permanent tooth maturation. Our research hypothesis was that certain stages of skeletal and dental maturation occur along consistent timelines that can be related to the chronological age. Secondary ossification center fusion was evaluated based on Kreitner and also McKern and Steward's classifications. The process of permanent tooth maturation was evaluated with Demirjian's method. Spearman's correlation coefficients (Rho) were positive in all analyses, which indicates that epiphyseal fusion progresses with age. The strongest relationship between the age and the stages of ossification was observed in the proximal tibial epiphysis (p < 0.001; Rho = 0.93) in females and in the medial clavicular epiphysis (p < 0.001; Rho = 0.77) in males. Studies show the importance of concomitant analysis of skeletal and dental maturation with a subsequent comparison of the results to achieve a greater precision in age estimation. A comparison of the results obtained in the study population of Polish children, adolescents, and young adults with the results of other studies in populations of similar ages showed a number of similarities in the time windows of dental and skeletal maturation. These similarities may help in age estimation.

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Objectives: The objective of this study was to evaluate the accuracy of forensic age estimation in a German population by combining clavicle and wisdom teeth assessments based on cone beam computed tomography (CT) data. The study aimed to determine the reliability of this approach in predicting biological age. Material and Methods: A total of 161 CT data sets from 120 males and 41 females with known exact ages were evaluated by three raters. The clavicle was assessed according to stages 1-5 (including substages 2a-c and 3a-c), and the Demirjian stage's classification method was used for the wisdom teeth. Inter-class correlation (ICC) was calculated to assess the agreement among the three raters. Additionally, ordinary least square regressions were performed to predict chronological age using the clavicle or one of the four teeth. Finally, age prediction models using multiple indicators were developed. Results: The ICCs ranged from 0.82 for the clavicle to 0.86 and 0.88 for the wisdom teeth. Linear estimation tended to overestimate chronological age, especially in subjects over 18 years old. The clavicle showed the strongest overestimation. Combining age estimation from the clavicle with the upper and lower wisdom teeth improved the predictive power, resulting in a 14% and 15% increase in R² for the upper and lower wisdom teeth, respectively. Adding more than one tooth to the prediction did not improve the predictive power (all ΔR² < 1%). Conclusions: Age estimation using CT can be significantly improved by combining information from the analysis of wisdom teeth with age estimation based on the clavicle.

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OBJECTIVES: Validation studies in juvenile dental age estimation primarily focus on point estimates while interval performance for reference samples of different ancestry group compositions has received minimal attention. We tested the effect of reference sample size and composition by sex and ancestry group on age interval estimates. MATERIALS AND METHODS: The dataset consisted of Moorrees et al. dental scores from panoramic radiographs of 3334 London children of Bangladeshi and European ancestry and 2-23 years of age. Model stability was assessed using standard error of mean age-at-transition for univariate cumulative probit and sample size, group mixing (sex or ancestry), and staging system as factors. Age estimation performance was tested using molar reference samples of four sizes, stratified by year of age, sex, and ancestry. Age estimates were performed using Bayesian multivariate cumulative probit with 5-fold cross-validation. RESULTS: Standard error increased with decreasing sample size but showed no effect from mixing by sex or ancestry. Estimating ages using a reference and target sample of different sex reduced success rate significantly. The same test by ancestry groups had a lesser effect. Small sample size (n < 20/year of age) negatively affected most performance metrics. DISCUSSION: We found that reference sample size, followed by sex, primarily drove age estimation performance. Combining reference samples by ancestry produced equivalent or better estimates of age by all metrics than using a single-demographic reference of smaller size. We further proposed that population specificity is an alternative hypothesis of intergroup difference that has been erroneously treated as a null.

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Background: Age estimation is integral to science of forensic odontology and plays an important role in human identification. Pulp volume estimation using cone-beam computed tomography (CBCT) to derive age can be very useful as it is noninvasive and can be applied on individuals of all ages. Aims and Objectives: The study aimed to estimate the chronological age-based pulp and tooth volume (PTV) ratios in adults from Uttar Pradesh, India, using CBCT and voxel counting dental software. Materials and Methods: Thirty-six CBCT scans were allocated into three Groups, I, II, and III (12 in each group) randomly to study the pulp volume of lateral incisor, canine, and first premolar, respectively. PTV was calculated by image segmentation method using Xelis Dental software. A correlation between chronological age with PTV was established using derived regression equations. Statistical Analysis: All the data were subjected to statistical analysis using Statistical Package for Social Sciences version 16.0. Results: Estimated age and standard error were determined. Standard errors of estimates were 11.24 years (LI), 7.78 years (C), 9.89 years (PM) group, lowest being for canines. The estimated age was compared with the chronological age. The difference between the chronological age and the estimated age by the derived equation for the present study was statistically nonsignificant (P = 1.00). Conclusions: The results of the study show the feasibility of calculation of PTV ratios on CBCT to estimate the age for the set population with canine as the best predictor of age for the present study population.

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This article is a retrospective analysis of postmortem computed tomography scans of ossification stages of the anterior and posterior intra-occipital sutures, the anterior arch of the atlas, and the neurocentral junction of the axis. We also analyzed the development of secondary ossification centers in the proximal humeral, femoral, and tibial epiphyses, and the distal femoral and tibial epiphyses. Additionally, the development of primary ossification centers in the wrist and metacarpals, and maxillary and mandibular deciduous tooth maturation. A total of 58 cadavers (35 males, 23 females), whose age ranged from 3rd month of pregnancy to 14 years, were analyzed. The results of this study show that analysis of synchondrosis closure, primary, and secondary ossification center development and deciduous tooth changes are a good tool for age estimation in subadults group (fetuses, newborns, infants, and children). The results of the study in a Polish population are consistent with those reported by other authors.

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Dental age estimation (DAE) is key to establishing an individual's identity, and this is relevant in minors. A widely used method for DAE in children is Cameriere's open apices (CAM). Despite its wide dissemination, there are no clear reports of its use in Latin American populations. A scoping review was conducted using a search strategy in the PubMed/MEDLINE database, Web of Science, and a complementary manual search. Only papers using CAM or its regression equation models for evaluating Latin American populations were included. Ten studies published between 2007 and 2020 responded to the search objective. Brazil was the country with the most studies using CAM (7/10), and the University of Macerata (Italy) was the most declared affiliation (6/10). Seven studies used the original CAM formula in populations from Brazil and Peru, while the European formula (EuCAM) was applied in Mexico, Colombia, and Brazil. Although the method underestimated the age values with acceptable error margins, the correction factor substantially improved the predictive power of the method. Some limitations of the method are highlighted. CAM and its variants can be useful for validation in Latin American settings, but attention to population structures and terminologies is suggested for future research.