Controversies in age estimation from developing teeth

Dental age estimation in adults using the Lamendin criteria: Validation of a bayesian model in the Brazilian population

Age estimation provides information for biological profile, which is used as an important data during the process of to aid in the identification of bodies of deceased persons. Lamendin et al. proposed a simplified dental age estimation technique for adults based on the analysis of periodontal recession height, root height, and root translucency height. These characteristics were used to build a multi-population database that served in the development of a Bayesian model, known as the Forensic International Dental Database (FIDB). However, before this research, this model did not incorporate dental information from the Brazilian population. The aim of this article was to validate the application of the FIDB Bayesian statistical model for estimating dental age in samples from the Brazilian population and compare it to Lamendin's technique. A cross-sectional study was conducted using 230 dental elements extracted for therapeutic reasons and stored in a biobank. Two independent and calibrated examiners collected the data, considering the randomization of dental samples. Intra- and inter-examiner reliability analysis included the re-evaluation of 20 % (n = 40) of the sample. For statistical analyses, the data were organized in Microsoft© Excel© 365 version 2204 (Microsoft Corp., Redmond, WA, USA) spreadsheets, and R version 4.0.2 (R Foundation, Vienna, Austria) and IBM® SPSS® version 23.0 (SPSS Inc., IBM, Chicago, IL, USA) software were used. After applying inclusion and exclusion criteria, the final sample comprised 200 intact dental elements from 84 male and 116 female individuals. According to the Kolmogorov-Smirnov test, the data did not show a normal distribution, and the Intraclass Correlation Coefficient indicated that intra- and inter-examiner agreements were adequate. Through the Mann-Whitney U test, statistically significant differences between sexes were not observed. In terms of overall accuracy, the Bayesian model and the original Lamendin´s technique showed a mean absolute error of 9.39 years and 9.95, respectively. Regarding bias, it was generally 0.15 years for the Bayesian model and 5.62 years for the original Lamendin´s technique. The Wilcoxon classification test revealed no statistically significant difference between chronological and estimated ages, but only for the Bayesian model. It can be concluded that the developed Bayesian statistical model was able to estimate the age of Brazilian adults satisfactorily, and overall, the error rates were acceptable.

Development of a deep-learning algorithm for age estimation on CT images of the vertebral column

PURPOSE

The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on CT images of the vertebral column and checked its accuracy.

METHOD

For the development of our deep learning algorithm, we included 1,120 CT data of the vertebral column of 140 patients for each of 8 age decades. The deep learning model of regression analysis based on Visual Geometry Group-16 (VGG16) was improved in its estimation accuracy by bagging. To verify its accuracy, we applied our deep learning algorithm to estimate the age of 219 cadavers who had undergone postmortem CT (PMCT). The mean difference and the mean absolute error (MAE), the standard error of the estimate (SEE) between the known- and the estimated age, were calculated. Correlation analysis using the intraclass correlation coefficient (ICC) and Bland-Altman analysis were performed to assess differences between the known- and the estimated age.

RESULTS

For the 219 cadavers, the mean difference between the known- and the estimated age was 0.30 years; it was 4.36 years for the MAE, and 5.48 years for the SEE. The ICC (2,1) was 0.96 (95 % confidence interval: 0.95-0.97, p < 0.001). Bland-Altman analysis showed that there were no proportional or fixed errors (p = 0.08 and 0.41).

CONCLUSIONS

Our deep learning algorithm for estimating the age of 219 cadavers on CT images of the vertebral column was more accurate than conventional methods and highly useful.

Information fusion for infant age estimation from deciduous teeth using machine learning

OBJECTIVES

Over the past few years, several methods have been proposed to improve the accuracy of age estimation in infants with a focus on dental development as a reliable marker. However, traditional approaches have limitations in efficiently combining information from different teeth and features. In order to address these challenges, this article presents a study on age estimation in infants with Machine Learning (ML) techniques, using deciduous teeth.

MATERIALS AND METHODS

The involved dataset comprises 114 infant skeletons from the Granada osteological collection of identified infants, aged between 5 months of gestation and 3 years of age. The samples consist of features such as the maximum length and mineralization and alveolar stages of teeth. For the purpose of designing a method capable of combining all the information available from each individual, a Multilayer Perceptron model is proposed, one of the most popular artificial neural networks. This model has been validated using the leave-one-out experimental validation protocol. Through different groups of experiments, the study examines the informativeness of the aforementioned features, individually and in combination.

RESULTS

The results indicate that the fusion of different variables allows for more accurate age estimates (RMSE = 66 days) than when variables are analyzed separately (RMSE = 101 days). Additionally, the study demonstrates the benefits of involving multiple teeth, which significantly reduces the RMSE compared to a single tooth.

DISCUSSION

This article underlines the clear advantages of ML-based methods, emphasizing their potential to improve the accuracy and robustness when estimating the age of infants.

MRI segmentation of tooth tissue in age prediction of sub-adults - a new method for combining data from the 1st, 2nd, and 3rd molars

PURPOSE

We aimed to establish a model combining MRI volume measurements from the 1st, 2nd and 3rd molars for age prediction in sub-adults and compare the age prediction performance of different combinations of all three molars, internally in the study cohort.

MATERIAL AND METHOD

We examined 99 volunteers using a 1.5 T MR scanner with a customized high-resolution single T2 sequence. Segmentation was performed using SliceOmatic (Tomovision©). Age prediction was based on the tooth tissue ratio (high signal soft tissue + low signal soft tissue)/total. The model included three correlation parameters to account for statistical dependence between the molars. Age prediction performance of different combinations of teeth for the three molars was assessed using interquartile range (IQR).

RESULTS

We included data from the 1st molars from 87 participants (F/M 59/28), 2nd molars from 93 (F/M 60/33) and 3rd molars from 67 (F/M 45/22). The age range was 14-24 years with a median age of 18 years. The model with the best age prediction performance (smallest IQR) was 46-47-18 (lower right 1st and 2nd and upper right 3rd molar) in males. The estimated correlation between the different molars was 0.620 (46 vs. 47), 0.430 (46 vs. 18), and 0.598 (47 vs. 18). IQR was the smallest in tooth combinations including a 3rd molar.

CONCLUSION

We have established a model for combining tissue volume measurements from the 1st, 2nd and 3rd molars for age prediction in sub-adults. The prediction performance was mostly driven by the 3rd molars. All combinations involving the 3rd molar performed well.

Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

PURPOSE

To investigate prediction of age older than 18 years in sub-adults using tooth tissue volumes from MRI segmentation of the entire 1st and 2nd molars, and to establish a model for combining information from two different molars.

MATERIALS AND METHODS

We acquired T2 weighted MRIs of 99 volunteers with a 1.5-T scanner. Segmentation was performed using SliceOmatic (Tomovision©). Linear regression was used to analyse the association between mathematical transformation outcomes of tissue volumes, age, and sex. Performance of different outcomes and tooth combinations were assessed based on the p-value of the age variable, common, or separate for each sex, depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach using information from the 1st and 2nd molars both separately and combined.

RESULTS

1st molars from 87 participants, and 2nd molars from 93 participants were included. The age range was 14-24 years with a median age of 18 years. The transformation outcome (high signal soft tissue + low signal soft tissue)/total had the strongest statistical association with age for the lower right 1st (p= 7.1*10-4 for males) and 2nd molar (p=9.44×10-7 for males and p=7.4×10-10 for females). Combining the lower right 1st and 2nd molar in males did not increase the prediction performance compared to using the best tooth alone.

CONCLUSION

MRI segmentation of the lower right 1st and 2nd molar might prove useful in the prediction of age older than 18 years in sub-adults. We provided a statistical framework to combine the information from two molars.

Evaluation of four criteria in assessing third molar maturity for age estimation in Koreans

Third molar maturity is one of the major criteria for estimating human age. This study aimed to determine the most suitable third molar maturity criteria for age estimation in Koreans. The correlation between chronological age and the Demirjian, Köhler, Liversidge, and Thevissen criteria was evaluated using 900 panoramic radiographs of patients aged 15-23 years. The four criteria were applied separately to measure third molar maturity on the same radiograph. The concordance rates between third molars within the same jaw and between jaws were calculated and tested using a paired t-test. Regression was performed to observe the relationship between age and the evaluated stages for each tested criterion. The Demirjian standard showed the lowest root mean square error (1.29 years for males, 1.30 years for females) and highest adjusted R ² (0.753 for males, 0.739 for females) values; however, the differences of the values derived from other criteria were minute. In addition, the symmetry (within the same jaw) and asymmetry (between the upper and lower jaws) of third molar development, which was confirmed in previous Korean studies, was observed only in the Demirjian and Liversidge criteria. Based on the results, we can conclude that all four tested criteria are suitable for age estimation in Koreans. However, the Demirjian and Liversidge criteria can be recommended from the perspective of accurate reflection of the developmental patterns. Further research is necessary to determine whether the results of this study are consistently observed in other populations.

Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes

PURPOSE

Our aim was to investigate tissue volumes measured by MRI segmentation of the entire 3rd molar for prediction of a sub-adult being older than 18 years.

MATERIAL AND METHOD

We used a 1.5-T MR scanner with a customized high-resolution single T2 sequence acquisition with 0.37 mm iso-voxels. Two dental cotton rolls drawn with water stabilized the bite and delineated teeth from oral air. Segmentation of the different tooth tissue volumes was performed using SliceOmatic (Tomovision^©). Linear regression was used to analyze the association between mathematical transformation outcomes of the tissue volumes, age, and sex. Performance of different transformation outcomes and tooth combinations were assessed based on the p value of the age variable, combined or separated for each sex depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach.

RESULTS

We included 67 volunteers (F/M: 45/22), range 14-24 years, median age 18 years. The transformation outcome (pulp + predentine)/total volume for upper 3rd molars had the strongest association with age (p = 3.4 × 10^-9).

CONCLUSION

MRI segmentation of tooth tissue volumes might prove useful in the prediction of age older than 18 years in sub-adults.

[Radiological methods for age diagnostics : Clinical and forensic aspects]

Age diagnostics play an increasing role in radiology. Medical and forensic questions are indications for the application of age diagnostics. In addition to X‑rays of the hand in childhood, panoramic tomography and computed tomography are currently the standard procedures. Alternative modalities without ionizing radiation (sonography, magnetic resonance imaging) have not (yet) been established. The purpose of this article is to present the indications and methods of age diagnostics in the clinical and forensic contexts and to familiarize you with their advantages and disadvantages as well as the possibility of determining the final length.

Analysis of the performance of machine learning and deep learning methods for sex estimation of infant individuals from the analysis of 2D images of the ilium

Reducing the subjectivity of the methods used for biological profile estimation is, at present, a priority research line in forensic anthropology. To achieve this, artificial intelligence (AI) techniques can be a valuable tool yet to be exploited in this discipline. The goal of this study is to compare the effectiveness of different machine learning (ML) methods with the visual assessment of an expert to estimate the sex of infant skeletons from images of the ilium. Photographs of the ilium of 135 individuals, age between 5 months of gestation and 6 years, from the collection of identified infant skeletons of the University of Granada have been used, and classic ML and deep learning (DL) techniques have been applied to develop prediction algorithms. To assess their effectiveness, the results have been compared with those obtained by a forensic expert, who has estimated the sex from each photograph through direct observation and subjective assessment following the criteria described by Schutkowsky in 1993. The results show that the algorithms obtained using DL techniques offer an accuracy of 59%, very close to the 61% obtained by the expert, and 10 percentual points better than classic ML techniques. This study offers promising results and represents the first AI-based approach for estimating sex in infant individuals using photographs of the ilium.

Lack of biological mortality bias in the timing of dental formation in contemporary children: Implications for the study of past populations

OBJECTIVES

Biological mortality bias is the idea that individuals who perish (non-survivors) are biologically distinct from those who survive (survivors). If biological mortality bias is large enough, bioarchaeological studies of nonsurvivors (skeletal samples) cannot accurately represent the experiences of the survivors of that population. This effect is particularly problematic for the study of juvenile individuals, as growth is particularly sensitive to environmental insults. In this study, we test whether biological mortality bias exists in one dimension of growth, namely dental development.

MATERIALS AND METHODS

Postmortem computed tomography scans of 206 children aged 12 years and younger at death were collected from two institutions in the United States and Australia. The sample was separated into children dying from natural causes as proxies for non-survivors and from accidental causes as proxies for survivors. Differences in the timing of dental development were assessed using sequential logistic regressions between dental formation stages and residual analysis of dental minus chronological age.

RESULTS

No consistent delay in age of attainment of dental stages was documented between survivors and non-survivors. Delays between survivors and non-survivors in dental relative to chronological age were greatest for infants, and were greater for females than for males.

DISCUSSION

Lack of biological mortality bias in dental development reinforces confidence in juvenile age estimates and therefore in skeletal growth profiles and growth studies. As dental development is known to be less environmentally sensitive than skeletal growth and development, further studies should examine biological mortality bias in long bone length.

Measurement of the open apices of mandibular first and second premolars to test the chronological age over 14 years: Study on a sample of south Indian children

Age estimation is an integral part of forensic medical and dental practice. In many countries, the age threshold of 14 years is set to determine the minimum age for criminal responsibility. In the present study, the authors studied the final maturation of the first (IPM₁) and second mandibular premolars (IPM₂) by Cameriere maturity index and determined cut-offs at the age threshold of 14 years, and validate on the test sample. Orthopantomograms of 960 healthy south Indian children and sub-adults (480 boys and 480 girls) aged between 10 and 18 were analysed, 640 as training sample and 320 as a test sample. The results of logistic regression analysis with age (</≥14 years) as a dependent variable and IPM₁, IPM_2, and sex as predictor variables on training sample showed that both IPM₁ and IPM₂ significantly related to the legal age of 14 years but not the sex (p = 0.052). A receiver operating characteristic (ROC) curve analysis was performed to evaluate the specific cut-off values of IPM₁ and IPM₂ for predicting 14 years. A cut- off value of IPM₁ < 0.01 and IPM₂ < 0.02 were obtained using the highest Youden index value. Our results on test sample showed that the combined predictor, IPM₁ + IPM₂ < 0.02, showed the highest specificity (97.5% in boys and 92.5% for girls), better post-test probability, 97.2% in boys and 91.9% for girls, and a smaller number of false positives (6.8%). In conclusion, the combination of IPM₁ and IPM₂ could be useful in determining the age of over 14 years in south Indian children.

Age estimation in forensic anthropology: methodological considerations about the validation studies of prediction models

There is currently no clear consensus on how to calculate, express, and interpret the error when validating methods for age estimation in forensic anthropology. For this reason, it is likely that researchers are commonly drawing erroneous or confusing conclusions about the existence of population differences or the need to design new and increasingly complex estimation methods. In recent years, many researchers have highlighted these limitations. They propose new lines of research focused on the use of rigorous statistics and new technologies for the development of methods for estimating age. Our main objective in this study is to contribute to the strengthening of these novel ideas, for which we show the existing empirical evidence about the inadequacy of some age estimation methods in calculating, expressing, and interpreting the errors obtained. With this aim, a total of 500 simulations have been performed, in which hypothetical research teams develop and validate methods for age estimation. The data employed in this study was obtained from the "Centers for Disease Control and Prevention (CDC) Growth Charts: United States" released in 2000. The charts relate age with height, weight, and head circumference of US male children. Five learning algorithms have been employed as age estimators. We have performed three experiments in which the following aspects have been analyzed: frequency with which "negative" results can be obtained in the validation studies; which are the most appropriate criteria to compare and select the age estimation methods; and what analysis should be employed to carry out the validation studies. The results show possible errors in the interpretation of validation studies as a consequence of the confusion of statistical concepts. To conclude, we made a proposal of "good practices" for the correct calculation, expression, and interpretation of the error when validating age estimation methods in forensic anthropology.

CT and MR imaging used in age estimation: a systematic review

Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) may be useful tools in assessment of age of an individual. This article presents a review of published studies using CT or MRI in dental age estimation. They were published between July 2004 and September 2017 investigating different types of teeth, methods and formulae for age estimation. Twenty-seven articles were included. The different studies show good results, and it seems that a combination of different types of teeth, methods (depending on the degree of root formation) and cooperation between different disciplines in the same study gives a higher accuracy.

The growth pattern of Neandertals, reconstructed from a juvenile skeleton from El Sidrón (Spain)

Ontogenetic studies help us understand the processes of evolutionary change. Previous studies on Neandertals have focused mainly on dental development and inferred an accelerated pace of general growth. We report on a juvenile partial skeleton (El Sidrón J1) preserving cranio-dental and postcranial remains. We used dental histology to estimate the age at death to be 7.7 years. Maturation of most elements fell within the expected range of modern humans at this age. The exceptions were the atlas and mid-thoracic vertebrae, which remained at the 5- to 6-year stage of development. Furthermore, endocranial features suggest that brain growth was not yet completed. The vertebral maturation pattern and extended brain growth most likely reflect Neandertal physiology and ontogenetic energy constraints rather than any fundamental difference in the overall pace of growth in this extinct human.

A radiographic study of the mandibular third molar root development in different ethnic groups

BACKGROUND

The nature of differences in the timing of tooth formation between ethnic groups is important when estimating age.

AIM

To calculate age of transition of the mandibular third (M3) molar tooth stages from archived dental radiographs from sub-Saharan Africa, Malaysia, Japan and two groups from London UK (Whites and Bangladeshi).

MATERIALS AND METHODS

The number of radiographs was 4555 (2028 males, 2527 females) with an age range 10-25 years. The left M3 was staged into Moorrees stages. A probit model was fitted to calculate mean ages for transitions between stages for males and females and each ethnic group separately. The estimated age distributions given each M3 stage was calculated. To assess differences in timing of M3 between ethnic groups, three models were proposed: a separate model for each ethnic group, a joint model and a third model combining some aspects across groups. The best model fit was tested using Bayesian and Akaikes information criteria (BIC and AIC) and log likelihood ratio test.

RESULTS

Differences in mean ages of M3 root stages were found between ethnic groups, however all groups showed large standard deviation values. The AIC and log likelihood ratio test indicated that a separate model for each ethnic group was best. Small differences were also noted between timing of M3 between males and females, with the exception of the Malaysian group. These findings suggests that features of a reference data set (wide age range and uniform age distribution) and a Bayesian statistical approach are more important than population specific convenience samples to estimate age of an individual using M3.

CONCLUSION

Some group differences were evident in M3 timing, however, this has some impact on the confidence interval of estimated age in females and little impact in males because of the large variation in age.

Proposal of new regression formulae for the estimation of age in infant skeletal remains from the metric study of the pars basilaris

In the context of physical and forensic anthropology, when a child's skeleton is damaged or in poor condition, which is common, many of the metric methods for the estimation of skeletal age cannot be used. In these circumstances, those more resistant bones, such as the pars basilaris, will be most useful. The aims of this study were to test existing methods for estimating skeletal age from the metric study of the pars basilaris and to propose new regression formulae. One hundred fourteen individuals aged between 5 months of gestation and 6 years were analyzed; seven measures were taken from each pars basilaris using a digital caliper. The chronological age was compared with the estimated age using the methods published by Fazekas and Kósa in 1978 and by Scheuer and MacLaughlin in 1994. New regression formulae are proposed, obtained by classical calibration, which include confidence intervals at 50 and 97.5 % to express the error. With both methods, significant differences were observed; the method of Fazekas and Kósa shows a tendency to underestimate the age, and the method of Scheuer and MacLaughlin tends to overestimate it. The proposed formulae represent a good tool for estimating age in many different contexts because they are relatively easy to apply, although other analysis systems, such as Bayesian approach or geometric morphometry, offer more robust and effective results.

Measures of maturation in early fossil hominins: events at the first transition from australopiths to early Homo

An important question in palaeoanthropology is whether, among the australopiths and the first fossil hominins attributed to early Homo, there was a shift towards a more prolonged period of growth that can be distinguished from that of the living great apes and whether between the end of weaning and the beginning of puberty there was a slow period of growth as there is in modern humans. Evidence for the pace of growth in early fossil hominins comes from preserved tooth microstructure. A record of incremental growth in enamel and dentine persists, which allows us to reconstruct tooth growth and compare key measures of dental maturation with modern humans and living great apes. Despite their diverse diets and way of life, it is currently difficult to identify any clear differences in the timing of dental development among living great apes, australopiths and the earliest hominins attributed to the genus Homo There is, however, limited evidence that some early hominins may have attained a greater proportion of their body mass and stature relatively earlier in the growth period than is typical of modern humans today.This article is part of the themed issue 'Major transitions in human evolution'.

An overview of age estimation in forensic anthropology: perspectives and practical considerations

CONTEXT

Information on methods of age estimation in physical anthropology, in particular with regard to age-at-death from human skeletal remains, is widely available in the literature. However, the practicalities and real challenges faced in forensic casework are not always highlighted.

OBJECTIVES

To provide a practitioner's perspective, regarding age estimation in forensic anthropology (both in the living as well as the dead), with an emphasis on the types of cases, the value of such work and its challenges and limitations.

METHODS

The paper reviews the current literature on age estimation with a focus on forensic anthropology, but it also brings the author's personal perspective derived from a number of forensic cases.

RESULTS AND CONCLUSIONS

Although much is known about what methods to use, but not always how to apply them, little attention has been given in the literature to the real practicalities faced by forensic anthropologists, for example: the challenges in different types of scenarios; how to report age estimations; responsibilities; and ethical concerns. This paper gathers some of these aspects into one overview which includes the value of such work and the practical challenges, not necessarily with the methods themselves, but also with regard to how these are applied in the different cases where age estimation is required.