Dental age estimation in children with chromosomal syndromes.
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ABSTRACT:
SUBMITTER: Pinchi V
PROVIDER: S-EPMC6195943 | biostudies-other | 2018 May
REPOSITORIES: biostudies-other
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Project description:Dental root calcification has proven to be a reliable biological evidence to estimate chronological age of children. The development of structures usually examined in the age estimation forensic practice (e.g. skeleton, teeth) is supposed to be influenced by diseases and nutritional, environmental, ethnic, and ultimately even socioeconomic factors. This research aims to study the age estimation in children affected by juvenile rheumatoid arthritis (JRA) with and without steroids treatment and compared with healthy subjects. MATERIAL AND METHODS: Dental age estimations based on 752 OPGs, 420 girls and 332 boys, aged from 3.3 to 15.99 years, were provided by applying Demirjian and Willems' original methods. Of the whole sample, 103 individuals were affected by JRA and 40 received a continuous corticosteroid therapy, over 1 year long. CONCLUSIONS: Willems' and Demirjian's original methods, as methods commonly applied to estimate age for sub-adults with unremarkable medical history, can be used for medico-legal purposes to children affected by JRA. Willems' method tended to underestimate age while Demirjian's method resulted to be prone to overestimation for both healthy and JRA-affected children. JRA showed to have no influence on root calcification process even in children that received steroid treatment for 1 year or longer.
| S-EPMC7870602 | biostudies-literature
Project description:AimsThe aims of this study were to evaluate the applicability of Demirjian's method for dental age assessment in a group of Egyptian children in Minia city and to develop an age predictive equation suitable for the studied group.Subjects and methodsIn this retrospective, blind, cross-sectional study, 160 dental panoramic radiographs (DPTs) were selected from 420 DPTs from healthy children aged between three and 10 years old from the archived medical files of patients attending Minia University Dental Hospital (MUDH) and evaluated to estimate dental ages.ResultsAge was overestimated for almost all of the studied subjects with an accuracy range from 0.18 to 1.19 years for males and from 0.08 to 0.87 years for females, with the exception of two age subgroups (9-10-year-old males and 10-11-year-old females, for which the mean difference values were -0.06 and -0.008 years, respectively). A Logistic regression was used to generate a suggested formula for dental age estimation.ConclusionsDemirjian's method may be unsuitable for Egyptian children living in Minia city. Development of a predication equation and the introduction of adaptable conversion tables to transform the maturity score into a dental age for Egyptian children may be suitable alternatives. The validity of the newly developed prediction equation must be tested among all Egyptian children.
| S-EPMC6430778 | biostudies-literature
Project description:ObjectivesTo review the scientific literature of studies on dental age estimation methods applied to Brazilian children.MethodsA systematic literature review was designed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered in PROSPERO (CRD42020136170). Six scientific databases were used as primary search sources (PubMed, Scopus, LILACS, SciELO, Embase and Web of Science) and two databases (Open Grey and Open Thesis) were searched to partially select the "grey literature." Only cross-sectional studies were included. The risk of bias was assessed by means of Joanna Briggs Institute Critical Appraisal Tools for Systematic Reviews. The standardized mean difference (SMD) between the estimated dental and chronological ages was meta-analysed via random effects model.ResultsThe search resulted in 2,527 studies, from which 13 met the eligibility criteria. Out of the eligible studies, 76.92% had low risk of bias and high methodological quality. Ten studies provided proper information to be included in the meta-analysis.The methods and their SMD between estimated and chronological ages were: Willems'=0.05, Lilequist and Lundberg's = -0.11, Nolla's = 0.22, Mornstad's = 0.27, Cameriere's = -0.31, Demirjian's = 0.74 and Haavikko's = -0.87.ConclusionAlthough originally trained in populations worldwide, most of the international methods for radiographical dental age estimation had optimal performance in Brazilian children.
| S-EPMC7860950 | biostudies-literature
Project description:BackgroundRecently, the dental age estimation method developed by Cameriere has been widely recognized and accepted. Although machine learning (ML) methods can improve the accuracy of dental age estimation, no machine learning research exists on the use of the Cameriere dental age estimation method, making this research innovative and meaningful.AimThe purpose of this research is to use 7 lower left permanent teeth and three models [random forest (RF), support vector machine (SVM), and linear regression (LR)] based on the Cameriere method to predict children's dental age, and compare with the Cameriere age estimation.Subjects and methodsThis was a retrospective study that collected and analyzed orthopantomograms of 748 children (356 females and 392 males) aged 5-13 years. Data were randomly divided into training and test datasets in an 80-20% proportion for the ML algorithms. The procedure, starting with randomly creating new training and test datasets, was repeated 20 times. 7 permanent developing teeth on the left mandible (except wisdom teeth) were recorded using the Cameriere method. Then, the traditional Cameriere formula and three models (RF, SVM, and LR) were used to estimate the dental age. The age prediction accuracy was measured by five indicators: the coefficient of determination (R2), mean error (ME), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE).ResultsThe research showed that the ML models have better accuracy than the traditional Cameriere formula. The ME, MAE, MSE, and RMSE values of the SVM model (0.004, 0.489, 0.392, and 0.625, respectively) and the RF model (- 0.004, 0.495, 0.389, and 0.623, respectively) were lower with the highest accuracy. In contrast, the ME, MAE, MSE and RMSE of the European Cameriere formula were 0.592, 0.846, 0.755, and 0.869, respectively, and those of the Chinese Cameriere formula were 0.748, 0.812, 0.890 and 0.943, respectively.ConclusionsCompared to the Cameriere formula, ML methods based on the Cameriere's maturation stages were more accurate in estimating dental age. These results support the use of ML algorithms instead of the traditional Cameriere formula.
| S-EPMC8672533 | biostudies-literature
Project description:Although DNA methylation variation of autosomal CpGs provides robust age predictive biomarkers, no male-specific age predictor exists based on Y-CpGs yet. Since sex chromosomes play an important role in aging, a Y-chromosome-based age predictor would allow studying male-specific aging effects and would also be useful in forensics. Here, we used blood-based DNA methylation microarray data of 1,057 males from six cohorts aged 15-87 and identified 75 Y-CpGs with an interquartile range of ≥0.1. Of these, 22 and six were significantly hyper- and hypomethylated with age (p(cor)<0.05, Bonferroni), respectively. Amongst several machine learning algorithms, a model based on support vector machines with radial kernel performed best in male-specific age prediction. We achieved a mean absolute deviation (MAD) between true and predicted age of 7.54 years (cor=0.81, validation) when using all 75 Y-CpGs, and a MAD of 8.46 years (cor=0.73, validation) based on the most predictive 19 Y-CpGs. The accuracies of both age predictors did not worsen with increased age, in contrast to autosomal CpG-based age predictors that are known to predict age with reduced accuracy in the elderly. Overall, we introduce the first-of-its-kind male-specific epigenetic age predictor for future applications in aging research and forensics.
| S-EPMC7993701 | biostudies-literature
Project description:BackgroundNumerous dental age estimation methods have been devised and practised for decades. Among these, the London Atlas and Willems methods were two of the most frequently adopted, however dependent on atlantes or tables. A new estimation method less reliant on external measurement could be efficient and economical.AimThis study aimed to evaluate the utility and applicability of the dental age estimation methods of London Atlas, Willems, and a new quick method that subtracts the number of developing teeth from the universal root mature age of 16 years in one of the lower quadrants reported in this work among Chinese Uyghur children.MethodsA comparative cross-sectional study was conducted. Subjects enrolled in the study were screened according to preset inclusion and exclusion criteria. The observer then obtained the dental age from the subjects' panoramic radiographs based on the estimated rules of the London Atlas, Willems, and a new quick method. Paired t-test was used to compare the accuracy and precision of the above three estimation methods. Independent-sample t-test was used to find the difference between gender.ResultsTotally, 831 radiographs entered the analyses of this study. Among the three methods evaluated, the Willems method, in particular, showed a distinct underestimated tendency. The mean error of the dental age predicted by the London Atlas, the Willems method, and the quick method was 0.06 ± 1.13 years, 0.44 ± 1.14 years, and 0.30 ± 0.63 years, respectively. The mean absolute error was 0.86 ± 0.75 years according to the London Atlas, 1.17 ± 0.89 years under the Willems method, and 0.70 ± 0.54 years under our quick method. No significant difference was found between the chronological age and dental age using the London Atlas, generally for the 10 to 15 years group (p > 0.05), but our quick method for the 15-16 years children (p < 0.05) and Willems method (p < 0.001).ConclusionThe London Atlas outperformed the Willems method with better accuracy and precision among 10-15 years Chinese Uyghur children. Our new quick method may be comparable to the London Atlas for children aged 10-14 and potentially become a more straightforward dental age prediction instrument.
| S-EPMC9773604 | biostudies-literature
Project description:Background:Forensic estimation of chronological age has played an increasingly important role as part of cadaver identification, and also in living individuals due to the phenomenon of immigration and sexual abuse of undocumented trafficked children. Objective:This research aimed to validate the already used dental mineralization and eruption atlas in normal children and adolescent population in estimating chronological age in a young population, particularly those with special needs, majority of them with systemic diseases. Participants and Setting:A sample of 163 orthopantomograms from two independent medical institutions was collected from 133 patients aged between 4 and 23 years. Method:The orthopantomograms were divided into two groups, 95 from patients with systemic pathologies that have repercussions on dental development and 68 with systemic pathologies without dental repercussions. Dental ages were estimated by the London Atlas using the left side and then independently the right side of the maxilla. The intraobserver and interobserver agreements were evaluated. The difference between dental age estimates and the chronological age and its absolute value were calculated and analyzed. Results:Statistically significant differences were found between estimates and chronological age, revealing a general prevalence for underestimation; except for those under the age of 12. Nevertheless, the underestimation in individuals under the age of 16 was not significant (with an average of less than one month), while the underestimation was significant for persons who were at least 16 years old (with an average over 26 months). Furthermore, for those persons with systemic diseases with dental repercussions a greater error in underestimation was obtained, which indicates that the midpoint values should be reassessed in persons with Down's syndrome, chromosomal alterations, syndromes and central nervous system disorders. Conclusions:This atlas can be potentially used as a tool for age estimation in a population with special needs and, also, in a population with systemic diseases, but we suggest further studies with larger international samples to create adequate atlases for all the required scenarios, mainly, diagrams for people with systemic diseases who are over the age of 16.
| S-EPMC6993474 | biostudies-literature
Project description:Background Dental age (DA) estimation using two convolutional neural networks (CNNs), VGG16 and ResNet101, remains unexplored. In this study, we aimed to investigate the possibility of using artificial intelligence-based methods in an eastern Chinese population. Methods A total of 9586 orthopantomograms (OPGs) (4054 boys and 5532 girls) of the Chinese Han population aged from 6 to 20 years were collected. DAs were automatically calculated using the two CNN model strategies. Accuracy, recall, precision, and F1 score of the models were used to evaluate VGG16 and ResNet101 for age estimation. An age threshold was also employed to evaluate the two CNN models. Results The VGG16 network outperformed the ResNet101 network in terms of prediction performance. However, the model effect of VGG16 was less favorable than that in other age ranges in the 15–17 age group. The VGG16 network model prediction results for the younger age groups were acceptable. In the 6-to 8-year-old group, the accuracy of the VGG16 model can reach up to 93.63%, which was higher than the 88.73% accuracy of the ResNet101 network. The age threshold also implies that VGG16 has a smaller age-difference error. Conclusions This study demonstrated that VGG16 performed better when dealing with DA estimation via OPGs than the ResNet101 network on a wholescale. CNNs such as VGG16 hold great promise for future use in clinical practice and forensic sciences. Supplementary Information The online version contains supplementary material available at 10.1186/s12903-023-02817-2.
| S-EPMC9938587 | biostudies-literature
Project description:Several approaches have been developed to estimate age, an important aspect of forensics and orthodontics, using different measures and radiological examinations. Here, through meta-analysis, we determined the validity of age estimation methods and reproducibility of bone/dental maturity indices used for age estimation. The PubMed and Google Scholar databases were searched to December 31, 2021 for human cross-sectional studies meeting pre-defined PICOS criteria that simultaneously assessed the reproducibility and validity. Meta-estimates of validity (mean error: estimated age-chronological age) and intra- and inter-observer reproducibility (Cohen's kappa, intraclass correlation coefficient) and their predictive intervals (PI) were calculated using mixed-effect models when heterogeneity was high (I2 > 50%). The literature search identified 433 studies, and 23 met the inclusion criteria. The mean error meta-estimate (mixed effects model) was 0.08 years (95% CI - 0.12; 0.29) in males and 0.09 (95% CI - 0.12; 0.30) in females. The PI of each method spanned zero; of nine reported estimation methods, Cameriere's had the smallest (- 0.82; 0.47) and Haavikko's the largest (- 7.24; 4.57) PI. The reproducibility meta-estimate (fixed effects model) was 0.98 (95% CI 0.97; 1.00) for intra- and 0.99 (95% CI 0.98; 1.00) for inter-observer agreement. All methods were valid but with different levels of precision. The intra- and inter-observer reproducibility was high and homogeneous across studies.
| S-EPMC9481543 | biostudies-literature
Project description:Age-at-death estimation constitutes one of the key parameters for identification of human remains in forensic investigations. However, for applications in forensic anthropology, many current methods are not sufficiently accurate for adult individuals, leading to chronological age estimates erring by ±10 years. Based on recent trends in aging studies, DNA methylation has great potential as a solution to this problem. However, there are only a few studies that have been published utilizing DNA methylation to determine age from human remains. The aim of the present study was to expand the range of this work by analyzing DNA methylation in dental pulp from adult individuals. Healthy erupted third molars were extracted from individuals aged 22-70. DNA from pulp was isolated and bisulfite converted. Pyrosequencing was the chosen technique to assess DNA methylation. As noted in previous studies, we found that ELOVL2 and FHL2 CpGs played a role in age estimation. In addition, three new markers were evaluated-NPTX2, KLF14, and SCGN. A set of CpGs from these five loci was used in four different multivariate regression models, providing a Mean Absolute Error (MAE) between predicted and chronological age of 1.5-2.13 years. The findings from this research can improve age estimation, increasing the accuracy of identification in forensic anthropology.
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