Third molar development: measurements versus scores as age predictor

Effect of impaction on third molar development and age estimation-A study in a Lebanese population

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.

Radiographic dental age estimation applying and comparing Demirjian's seven (1973) and four (1976) teeth methods

To apply Demirjian's seven (1973, D7) and four (1976, D4) teeth methods in a sample of Brazilian children and compare their performances for age estimation. Panoramic radiographs of 1200 children (600 females and 600 males) were collected from Southeast Brazil. The children were equally distributed (n = 60 females and 60 males) between age intervals of 1 year between 6 and 15.9 (mean age = 10.9; standard deviation [SD]: 2.9) years. D7 and D4 dental age estimation methods were applied by two observers and were compared based on their error rates (error = estimated age-chronological age). Both methods overestimated the chronological age (p < 0.0001). D7 led to overestimations of 0.71 (p < 0.0001) in females and 0.83 (p < 0.0001) in males, while the overestimations with D4 were 0.14 (p = 0.0067) and 0.73 (p < 0.0001) for females and males, respectively. The mean age estimated by D7 was 11.7 (SD: 3.1) years, while for D4, it was 11.3 (SD: 3.3) years. Intra- and interobserver agreement was ≥ 0.98. D4 optimized the performance of radiographic dental age estimation compared to D7. Improvements were reflected in the total sample and separately for female and male children from Southeast Brazil.

Diagnostic performance of convolutional neural networks for dental sexual dimorphism

Convolutional neural networks (CNN) led to important solutions in the field of Computer Vision. More recently, forensic sciences benefited from the resources of artificial intelligence, especially in procedures that normally require operator-dependent steps. Forensic tools for sexual dimorphism based on morphological dental traits are available but have limited performance. This study aimed to test the application of a machine learning setup to distinguish females and males using dentomaxillofacial features from a radiographic dataset. The sample consisted of panoramic radiographs (n = 4003) of individuals in the age interval of 6 and 22.9 years. Image annotation was performed with V7 software (V7labs, London, UK). From Scratch (FS) and Transfer Learning (TL) CNN architectures were compared, and diagnostic accuracy tests were used. TL (82%) performed better than FS (71%). The correct classifications of females and males aged ≥ 15 years were 87% and 84%, respectively. For females and males < 15 years, the correct classifications were 80% and 83%, respectively. The Area Under the Curve (AUC) from Receiver-operating Characteristic (ROC) curves showed high classification accuracy between 0.87 and 0.91. The radio-diagnostic use of CNN for sexual dimorphism showed positive outcomes and promising forensic applications to the field of dental human identification.

A large sample-sized study on dental development of children treated at the Central Dental Clinic (OCEx) of the Brazilian Army

OBJECTIVES

To test and compare the performance of two radiographic methods for dental age estimation on a large sample of Brazilian boys and girls.

MATERIAL AND METHODS

The sample consisted of 1.990 panoramic radiographs of Brazilian children (age: 3-15.9 years) equally balanced based on sex. The sample was distributed into ten age categories, each with up to 200 children. Age estimation was performed with Willems' (2001) and Demirjian's (1973) methods. Estimated (EA) and chronological (CA) ages were compared. The performances of the methods were quantified based on sex and age category.

RESULTS

The overall differences between CA and EA for Willems' method in boys and girls were 0.06 and - 0.02, respectively. For Demirjian's method, the differences were 0.60 and 0.74, respectively. The overestimations of Demirjian's method were statistically significant (p < 0.001). Willems' method reached the best outcomes among children between 3 and 12 years, while Demirjian's best performances were between the ages of 7 and 10 years.

CONCLUSION

Willems' method led to differences between CA and AE that were acceptable for clinical and forensic practice.

CLINICAL RELEVANCE

Age estimation may guide clinical decisions based on treatment timing. Validating international tools is necessary to promote evidence-based practice and country-specific application. This study overcame the limitations of previous research to provide a more realistic perspective of the performance of age estimation methods in Brazilian children. Willems' method had a superior performance compared to Demirjian's method and led to outcomes that were better than most studies with the Brazilian population.

Comparison of the third molar maturity index (I3M) between left and right lower third molars to assess the age of majority: a multi-ethnic study sample

The diagnostic accuracy of the I_3M to assess the legal age of 18 years has already been tested in several specific-population samples. The left lower third molar has been extensively used for discriminating between minors and adults. This research aimed to compare the usefulness of lower third molar maturity indexes, from both left and right side (I_3ML and I_3MR), in samples originating from four distinct continents in order to examine possible differences in their accuracy values. For this purpose, a sample of 10,181 orthopantomograms (OPGs), from Europe, Africa, Asia and America, was analysed and previously scored in other studies. The samples included healthy subjects with no systemic disorders with both third molars and clear depicted root apices. Wilcoxon Signed Rank test for left and right asymmetry did not show any significant differences. Data about sensitivity, specificity, predictive values, likelihood ratio and accuracy were pooled together and showed similar results for I_3ML and I_3MR, respectively. In addition, all these quantities were high when only the I_3MR was considered to discriminate between adults and minors. The present referable database was the first to pool third molar measurements using panoramic radiographs of subjects coming from different continents. The results highlighted that both I_3ML and I_3MR are reliable indicators for assessing the legal age of 18 years old in those jurisdictions where this legal threshold has been set as the age of majority.

Comparison of different machine learning approaches to predict dental age using Demirjian's staging approach

CONTEXT

Dental age, one of the indicators of biological age, is inferred by radiological methods. Two of the most commonly used methods are using Demirjian's radiographic stages of permanent teeth excluding the third molar (Demirjian's and Willems' method). The major drawbacks of these methods are that they are based on population-specific conversion tables and may tend to over- or underestimate dental age in other populations. Machine learning (ML) methods make it possible to create complex data schemas more simply while keeping the same annotation system. The objectives of this study are to compare (1) the capacity of ten machine learning algorithms to predict dental age in children using the seven left permanent mandibular teeth compared to reference methods and (2) the capacity of ten machine learning algorithms to predict dental age from childhood to young adulthood using the seven left permanent mandibular teeth and the four third molars.

METHODS

Using a large radiological database of 3605 orthopantomograms (1734 females and 1871 males) of healthy French patients aged between 2 and 24 years, seven left permanent mandibular teeth and the 4 third molars were assessed using Demirjian's stages. Dental age estimation was then performed using Demirjian's reference method and various ML regression methods. Two analyses were performed: with the 7 left mandibular teeth without third molars for the under 16 age group and with the third molars for the entire study population. The different methods were compared using mean error, mean absolute error, root mean square error as metrics, and the Bland-Altman graph.

RESULTS

All ML methods had a mean absolute error (MAE) under 0.811 years. With Demirjian's and Willems' methods, the MAE was 1.107 and 0.927 years, respectively. Except for the Bayesian ridge regression that gives poorer accuracy, there was no statistical difference between all ML tested.

CONCLUSION

Compared to the two reference methods, all the ML methods based on the maturation stages defined by Demirjian were more accurate in estimating dental age. These results support the use of ML algorithms instead of using standard population tables.

Usability of dental pulp visibility and tooth coronal index in digital panoramic radiography in age estimation in the forensic medicine

Age estimation has a great importance due to legal requirements. The aim of our study was to determine the applicability of two different methods in age estimation; one of them based on the calculation of the visibility of the root pulp of mandibular third molar teeth and the other based on the calculation of the tooth coronal index (TCI) in the mandibular first and second molar teeth in the 9059 digital orthopantomogram of people aged between 15 and 40 in Bursa. In the first method in which the visibility of the fully mineralized root pulp of the mandibular third molar teeth was evaluated in 4 stages; the stages 0, 1, 2, and 3 were observed regardless of sex at the earliest 17.2; 19.1; 20.1, and 25.1 years, respectively. In the second method in which TCI was regressed on chronological age using measuring crown and coronal pulp cavity heights, the most accurate age estimation model based on simple linear regression for all cases without any sex difference was found to be with right first molar tooth (SEE ±7304 years) and the most accurate age model based on multiple regression model was found to be with bilateral first molar teeth (SEE ±7413 years). In conclusion, we believe that the root pulp visibility of the third molar teeth can be applied safely for stages 1, 2, and 3 at 16, 17, and 21 years of ages, respectively. A correlation was also found between TCI and age, and our findings have shown that both methods are available for forensic purposes.

Third molar maturity index (I3M) for assessing age of majority: study of a black South African sample

AIMS

The evaluation of the cutoff value of I_3M = 0.08 for discriminating black South African minors from adults, and its relationship with chronological age.

MATERIAL AND METHODS

A sample of 833 panoramic radiographs of healthy black South African subjects (500 females and 333 males), in the age range of 14 to 24 years (mean age 17.67 years in females and 17.42 years in males), was retrospectively evaluated.

RESULTS

ICC values were 99.10% (95% CI 97.70 to 99.70%) and 99.20% (95% CI 98.00 to 99.60%), for the intra- and inter-observer reliability, respectively. I_3M decreased as the real age gradually increased in both sexes. According to the logistic regression model, the variable sex was not significant when the probability that an individual is 18 years or older was calculated. The I_3M = 0.08 was valuable in discriminating between adults and minors. The overall accuracy (ACC = fraction of accurately classified subjects) is 0.90 (95% CI 0.87-0.91); the proportion of correctly classified subjects (Se = sensitivity) is 0.80 (95% CI 0.76-0.84), and specificity (Sp) is 0.95 (95% CI 0.93-0.97). The PPV (predictive positive value) is 0.96 (95% CI 0.95-0.97), and the negative predictive value is 0.76 (95% CI 0.72-0.80).

CONCLUSION

The results show that I_3M is a valuable method to distinguish subjects who are around legal adult age in South Africa.

Accuracy of the third molar maturity index in assessing the legal age of 18 years: a systematic review and meta-analysis

The age estimation is a complex procedure required in the daily practice of legal medicine. The maturity of third molars stands out by the age of 18 because these teeth are still in development. This systematic review aimed to assess the accuracy of the third molar maturity index (I _3M), proposed by Cameriere et al. (2008), in discriminating whether an individual is under or over 18 years. Seven electronic databases were screened: PubMed, Scopus, ISI Web of Science, Cochrane Library, LILACS, SIGLE, and CAPES. Eligible studies included an assessment of I _3M accuracy at the 0.08 cut-off value. The quality assessment was performed by using QUADAS 2. Three meta-analyses (MA) were accomplished: overall, one for males and another for females. From 2397 articles identified, 16 met the eligibility criteria. Of these, two showed high risk of bias, one in the reference standard domain and the other in the flow and timing domain. The percentage of individuals correctly classified ranged from 72.4 to 96.0%. The overall MA showed pooled sensitivity of 0.86 (0.84 to 0.87; p = 0.0000) and pooled specificity of 0.93 (0.92 to 0.94; p = 0.0000). The AUC (area under the summary receiver operator characteristics curve) and DOR (diagnostic odds ratio) values were, respectively, 0.9652 and 104.68, indicating an overall high discrimination effect. Separately, better results of accuracy were found for males. High heterogeneity was achieved for both sensibility (94.6%) and specificity (88.8%). We conclude that the I _3M is a suitable and useful method for estimating adulthood regarding forensic purposes, regardless of gender.

The third molar maturity index in indicating the legal adult age in Kosovar population

The third molar tooth, known as the "wisdom tooth," is the only tooth that can be used to determine legal adult age. This study aimed to test the accuracy of Cameriere's third molar maturity index (I_3M) in assessing the legal adult age of 18 years in the Kosovar population. Orthopantomographs (OPTs) of 1221 healthy living Kosovar individuals, aged between 12 and 23 years and with no congenital or developmental anomalies, were analyzed. Intra-class correlation coefficients were 0.858 (95% CI, 0.786 to 0.906) and 0.852 (95% CI, 0.779 to 0.903) for intra-rater and for inter-rater agreement, respectively. The sample was divided into training dataset (800 OPTs) and test dataset (421 OPTs). The training dataset was used to generate the logistic regression model, while the test dataset was used to study the performance of the model. I_3M and gender as independent variables and adult age (≥ 18 years) or minor age (< 18 years) as the dependent variable were used for logistic regression analysis. The receiver operating curve (ROC) analysis was used to determine the specific cut-off value of I_3M for predicting adult age. The results showed that only I_3M statistically significantly contributed to discriminating adults and minors. ROC analysis showed that the cut-off value of I_3M < 0.08 was the best in discriminating adults and minors. An analysis of the test dataset (421 OPTs) showed that as I_3M decreased the age gradually increased. The performance of the cut-off value of I_3M < 0.08, to discriminate between adults and minors, was analyzed by contingency tables for both sexes. In males, the accurate classification (Acc) was 0.968 (95% CI, 0.926 to 0.985), the sensitivity (Se) was 0.962 (95% CI, 0.925 to 0.978), and the specificity (Sp) was 0.976 (95% CI, 0.929 to 0.995). The Bayes post-test probability (Bayes PTP) was 0.975 (95% CI, 0.905 to 1.00). In females, Acc was 0.909 (95% CI, 0.870 to 0.917), Se and Sp were 0.826 (95% CI, 0.787 to 0.834) and 0.991 (95% CI, 0.953 to 1.00) respectively, while Bayes PTP was 0.989 (95% CI, 0.926 to 1.00). Our data support the usefulness of I_3M < 0.08 to indicate legal adult age in a Kosovar population.

An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study

BACKGROUND

Automated methods to evaluate growth of hand and wrist bones on radiographs and magnetic resonance imaging have been developed. They can be applied to estimate age in children and subadults. Automated methods require the software to (1) recognise the region of interest in the image(s), (2) evaluate the degree of development and (3) correlate this to the age of the subject based on a reference population. For age estimation based on third molars an automated method for step (1) has been presented for 3D magnetic resonance imaging and is currently being optimised (Unterpirker et al. 2015).

AIM

To develop an automated method for step (2) based on lower third molars on panoramic radiographs.

MATERIALS AND METHODS

A modified Demirjian staging technique including ten developmental stages was developed. Twenty panoramic radiographs per stage per gender were retrospectively selected for FDI element 38. Two observers decided in consensus about the stages. When necessary, a third observer acted as a referee to establish the reference stage for the considered third molar. This set of radiographs was used as training data for machine learning algorithms for automated staging. First, image contrast settings were optimised to evaluate the third molar of interest and a rectangular bounding box was placed around it in a standardised way using Adobe Photoshop CC 2017 software. This bounding box indicated the region of interest for the next step. Second, several machine learning algorithms available in MATLAB R2017a software were applied for automated stage recognition. Third, the classification performance was evaluated in a 5-fold cross-validation scenario, using different validation metrics (accuracy, Rank-N recognition rate, mean absolute difference, linear kappa coefficient).

RESULTS

Transfer Learning as a type of Deep Learning Convolutional Neural Network approach outperformed all other tested approaches. Mean accuracy equalled 0.51, mean absolute difference was 0.6 stages and mean linearly weighted kappa was 0.82.

CONCLUSION

The overall performance of the presented automated pilot technique to stage lower third molar development on panoramic radiographs was similar to staging by human observers. It will be further optimised in future research, since it represents a necessary step to achieve a fully automated dental age estimation method, which to date is not available.

Forensic age estimation based on development of third molars: a staging technique for magnetic resonance imaging

BACKGROUND

The development of third molars can be evaluated with medical imaging to estimate age in subadults. The appearance of third molars on magnetic resonance imaging (MRI) differs greatly from that on radiographs. Therefore a specific staging technique is necessary to classify third molar development on MRI and to apply it for age estimation.

AIM

To develop a specific staging technique to register third molar development on MRI and to evaluate its performance for age estimation in subadults.

MATERIALS AND METHODS

Using 3T MRI in three planes, all third molars were evaluated in 309 healthy Caucasian participants from 14 to 26 years old. According to the appearance of the developing third molars on MRI, descriptive criteria and schematic representations were established to define a specific staging technique. Two observers, with different levels of experience, staged all third molars independently with the developed technique. Intra- and inter-observer agreement were calculated. The data were imported in a Bayesian model for age estimation as described by Fieuws et al. (2016). This approach adequately handles correlation between age indicators and missing age indicators. It was used to calculate a point estimate and a prediction interval of the estimated age. Observed age minus predicted age was calculated, reflecting the error of the estimate.

RESULTS

One-hundred and sixty-six third molars were agenetic. Five percent (51/1096) of upper third molars and 7% (70/1044) of lower third molars were not assessable. Kappa for inter-observer agreement ranged from 0.76 to 0.80. For intra-observer agreement kappa ranged from 0.80 to 0.89. However, two stage differences between observers or between staging sessions occurred in up to 2.2% (20/899) of assessments, probably due to a learning effect. Using the Bayesian model for age estimation, a mean absolute error of 2.0 years in females and 1.7 years in males was obtained. Root mean squared error equalled 2.38 years and 2.06 years respectively. The performance to discern minors from adults was better for males than for females, with specificities of 96% and 73% respectively.

CONCLUSION

Age estimations based on the proposed staging method for third molars on MRI showed comparable reproducibility and performance as the established methods based on radiographs.

The iliac crest in forensic age estimation: evaluation of three methods in pelvis X-rays

Age assessment in children and young adults is a relevant forensic issue. It is requested not only in evaluating criminal responsibility in youths without proper identification documents, often in relation to age thresholds, but also for release of a residency permit, and asylum seekers of minors. The analysis of the Risser sign and the iliac crest ossification process has been proposed as a useful tool for forensic age estimation. We evaluated the applicability of three different age estimation methods on a sample of 497 pelvic radiographs of Italian individuals between 10 and 25 years of age. Each method showed high reliability for both reproducibility and repeatability. The staging technique inspired by Kreitner and Kellinghaus methods (KK-MS) is easier than the Risser method in applicability, as it is not affected by the variations of ossification. We observed that all subjects who attained stage 3c of KK-MS and 5 of Risser Fr were >14 years, suggesting the benefits of these methods for that age threshold. The applicability of the area measurement method, inspired by Cameriere's approach, ranged between 12 and 20 years, but the statistical analysis showed only a moderate correlation with age. In order to evaluate the possible use of this approach it is therefore necessary to clarify and exclude external factors influencing the parameter. In conclusion, the iliac crest ossification is of interest in age estimation for forensic purposes. The evaluation of the pelvis X-ray, in addition to the other common dental and skeletal methods, could become a useful supplementary tool in age estimation for the 14 year threshold in order to fulfill forensic-level requirements.

Dental development in patients with agenesis

AIM

Recent research concerning tooth development and dental agenesis suggests that specific genes are associated with agenesis, and that these genetic factors could also cause delayed dental development of the remaining teeth. The objective of this study was to evaluate whether dental development of patients with agenesis is delayed, compared to a control group.

SUBJECTS AND METHOD

Panoramic radiographs of 1145 patients with dental agenesis were collected (452 males, 693 females) aged 6.2 to 24.8 years. The control group included 2032 panoramic radiographs (977 males, 1055 females) aged 6.0 to 24.4 years. A total of 3177 orthopantomograms were staged according to Demirjian. All left permanent teeth present in the mandible (except third molars) were considered. In order to evaluate the difference between patients with and without agenesis, a developmental score (DS) was calculated. The association between the DS and the number of agenetic teeth was evaluated with a Spearman correlation.

RESULTS

Based on the DS, patients with agenesis have a delayed development compared to patients in the control group (p < 0.0001). Within the agenesis group, there is a weak relation between the number of agenetic teeth and the DS: the higher the number of teeth with agenesis, the lower the DS (p < 0.0001 and p = 0.06 for females and males, respectively).

CONCLUSION

The obtained results can be an important factor for treatment planning in patients with dental agenesis. Moreover, the presence of agenesis needs to be taken into account when using age estimation methods based on permanent tooth development.

Dental Age Estimation: A Test of the Reliability of Correctly Identifying a Subject Over 18 Years of Age Using the Gold Standard of Chronological Age as the Comparator

This study was designed to test the reliability of using the third molars to demarcate between child and adult status. A total of 2000 dental panoramic tomographs were used for assessment of the calculated age using the 8-stage system of tooth development and applied to all four third molars. The LL8 was also assessed using this 8-stage system. For each tooth development stage, the Normal distribution and percentile summary data were estimated. The calculated dental age compared with the chronological age was statistically significantly different (p < 0.001) for both females and males giving underestimates of the true age. Comparison of single tooth dental age and chronological age was only slightly different. The most important finding is that the assignment to above or below the 18-year threshold, in the age range 17 years to 19 years, could be wrong on up to 50% of occasions.

Comparison of the diagnostic accuracy, sensitivity and specificity of four odontological methods for age evaluation in Italian children at the age threshold of 14 years using ROC curves

The age threshold of 14 years is relevant in Italy as the minimum age for criminal responsibility. It is of utmost importance to evaluate the diagnostic accuracy of every odontological method for age evaluation considering the sensitivity, or the ability to estimate the true positive cases, and the specificity, or the ability to estimate the true negative cases. The research aims to compare the specificity and sensitivity of four commonly adopted methods of dental age estimation - Demirjian, Haavikko, Willems and Cameriere - in a sample of Italian children aged between 11 and 16 years, with an age threshold of 14 years, using receiver operating characteristic curves and the area under the curve (AUC). In addition, new decision criteria are developed to increase the accuracy of the methods. Among the four odontological methods for age estimation adopted in the research, the Cameriere method showed the highest AUC in both female and male cohorts. The Cameriere method shows a high degree of accuracy at the age threshold of 14 years. To adopt the Cameriere method to estimate the 14-year age threshold more accurately, however, it is suggested - according to the Youden index - that the decision criterion be set at the lower value of 12.928 for females and 13.258 years for males, obtaining a sensitivity of 85% and specificity of 88% in females, and a sensitivity of 77% and specificity of 92% in males. If a specificity level >90% is needed, the cut-off point should be set at 12.959 years (82% sensitivity) for females.

Third molar development by measurements of open apices in an Italian sample of living subjects

The aim of this study is to analyse the age-predicting performance of third molar index (I3M) in dental age estimation. A multiple regression analysis was developed with chronological age as the independent variable. In order to investigate the relationship between the I3M and chronological age, the standard deviation and relative error were examined. Digitalized orthopantomographs (OPTs) of 975 Italian healthy subjects (531 female and 444 male), aged between 9 and 22 years, were studied. Third molar development was determined according to Cameriere et al. (2008). Analysis of covariance (ANCOVA) was applied to study the interaction between I3M and the gender. The difference between age and third molar index (I3M) was tested with Pearson's correlation coefficient. The I3M, the age and the gender of the subjects were used as predictive variable for age estimation. The small F-value for the gender (F = 0.042, p = 0.837) reveals that this factor does not affect the growth of the third molar. Adjusted R(2) (AdjR(2)) was used as parameter to define the best fitting function. All the regression models (linear, exponential, and polynomial) showed a similar AdjR(2). The polynomial (2nd order) fitting explains about the 78% of the total variance and do not add any relevant clinical information to the age estimation process from the third molar. The standard deviation and relative error increase with the age. The I3M has its minimum in the younger group of studied individuals and its maximum in the oldest ones, indicating that its precision and reliability decrease with the age.

Controversies in age estimation from developing teeth

BACKGROUND

Numerous dental reference data exist to estimate age from developing permanent teeth.

AIM

To compare the performance of reference data that provide a point estimate using the developing second molar.

METHODS

Performance of several methods estimating age using mandibular second molar formation was compared using the Maber test sample (age = 3-16) of 946 dental radiographs. Mean difference and mean absolute difference between dental and chronological ages were calculated. The percentage of individuals with mean absolute difference <1 year was counted across age group and tooth stage. Results for the choice of Demirjian or Moorrees tooth staging, pooled-sex, opposite sex reference data, selected stages (initial cusp tips, crown complete, root half and root complete) and statistical approaches were compared.

RESULTS

Tooth reference data conditioning on age, particularly probit mean age (age-at-transition) adapted for age prediction performed best. Results using sex-specific reference data, Moorrees stages and selected Moorrees stages were marginally better than other methods. No method performed well for ages 15 and 16 years.

CONCLUSION

Adapted maturity data L9a and N25a reference data for this tooth performed best across age categories and tooth stages, with a mean absolute difference of 0.8 year.

The Weighted Average Method 'WAM' for dental age estimation: a simpler method for children at the 10 year threshold: "it is vain to do with more when less will suffice" William of Ockham 1288-1358."

The mathematical principle of weighting averages to determine the most appropriate numerical outcome is well established in economic and social studies. It has seen little application in forensic dentistry. This study re-evaluated the data from a previous study of age assessment at the 10 year threshold. A semiautomatic process of weighting averages by n-td, x-tds, sd-tds, se-tds, 1/sd-tds, 1/se-tds was prepared in an Excel worksheet and the different weighted mean values reported. In addition the Fixed Effects and Random Effects models for Meta-Analysis were used and applied to the same data sets. In conclusion it has been shown that the most accurate age estimation method is to use the Random Effects Model for the mathematical procedures.