Estimation Of Chronological Age Research Articles

Epigenetic age-predictor for mice based on three CpG sites.

Epigenetic clocks for mice were generated based on deep-sequencing analysis of the methylome. Here, we demonstrate that site-specific analysis of DNA methylation levels by pyrosequencing at only three CG dinucleotides (CpGs) in the genes Prima1, Hsf4, and Kcns1 facilitates precise estimation of chronological age in murine blood samples, too. DBA/2 mice revealed accelerated epigenetic aging as compared to C57BL6 mice, which is in line with their shorter life-expectancy. The three-CpG-predictor provides a simple and cost-effective biomarker to determine biological age in large intervention studies with mice.

Predicting Age From Brain EEG Signals-A Machine Learning Approach.

Objective: The brain age gap estimate (BrainAGE) is the difference between the estimated age and the individual chronological age. BrainAGE was studied primarily using MRI techniques. EEG signals in combination with machine learning (ML) approaches were not commonly used for the human age prediction, and BrainAGE. We investigated whether age-related changes are affecting brain EEG signals, and whether we can predict the chronological age and obtain BrainAGE estimates using a rigorous ML framework with a novel and extensive EEG features extraction.Methods: EEG data were obtained from 468 healthy, mood/anxiety, eating and substance use disorder participants (297 females) from the Tulsa-1000, a naturalistic longitudinal study based on Research Domain Criteria framework. Five sets of preprocessed EEG features across channels and frequency bands were used with different ML methods to predict age. Using a nested-cross-validation (NCV) approach and stack-ensemble learning from EEG features, the predicted age was estimated. The important features and their spatial distributions were deduced.Results: The stack-ensemble age prediction model achieved R2 = 0.37 (0.06), Mean Absolute Error (MAE) = 6.87(0.69) and RMSE = 8.46(0.59) in years. The age and predicted age correlation was r = 0.6. The feature importance revealed that age predictors are spread out across different feature types. The NCV approach produced a reliable age estimation, with features consistent behavior across different folds.Conclusion: Our rigorous ML framework and extensive EEG signal features allow a reliable estimation of chronological age, and BrainAGE. This general framework can be extended to test EEG association with and to predict/study other physiological relevant responses.

Evaluation of massively parallel sequencing for forensic DNA methylation profiling

Epigenetics is an emerging area of interest in forensic science. DNA methylation, a type of epigenetic modification, can be applied to chronological age estimation, identical twin differentiation and body fluid identification. However, there is not yet an agreed, established methodology for targeted detection and analysis of DNA methylation markers in forensic research. Recently, a massively parallel sequencing-based approach has been suggested. The use of massively parallel sequencing is well established in clinical epigenetics and is emerging as a new technology in the forensic field. This review investigates the potential benefits, limitations, and considerations of this technique for the analysis of DNA methylation in a forensic context. The importance of a robust protocol, regardless of the methodology used, which minimizes potential sources of bias is highlighted.

Advancing estimation of chronological age by utilizing available evidence based on two radiographical methods.

This paper describes a strategy for estimating chronological age of individuals based on age indicators of X-ray of the hand and the third molar tooth. The great majority of studies in the field provide group-wise data of different formats, which makes them difficult to compare and utilize in a model. In this paper, we have provided a framework to utilize different types of data formats to build a common model for estimating chronological age. We used transition analysis to describe the relationship between the age indicators and chronological age. Further, likelihood ratio weight of evidence and posterior distribution of chronological age were used to model the distribution of chronological age given the observed age indicators. Being able to utilize such a large amount of data, with different data formats, from different studies, as presented in this paper improves previous age estimation methods.

P.4.001 - Accelerated biological aging in major depressive disorder: capturing aging patterns in DNA methylation with machine learning methods

Introduction Patients with major depressive disorder (MDD) are likely to experience stress and have a higher risk of developing aging-related diseases [1]. Globally, an estimated 350 million people of all ages suffer from a depression. At the same time, we are facing an aging society, in which manifestations of depression and aging are linked to decreased health, decreased quality of life, and increased healthcare costs. This underlines the importance of developing targeted therapeutic interventions in pursuance of a more healthy and happy society. More evidence is emerging showing that chronological age and biological age may be two different processes that can even diverge. MDD patients seem to feel older and age faster than healthy people of the same age. Current machine learning methods can accurately predict chronological age with correlations of 0.8-0.95 from epigenetics, transcriptomics, proteomics, metabolomics, brain, and other biological data [2]. By calculating the difference between one’s estimated biology-based age and chronological age, one can translate a complex multidimensional aging pattern across biology into one outcome [3]: “the age gap”. A positive age gap represents accelerated aging, whereas a negative brain age gap represents decelerated aging. Previous studies have shown biological age gap associations with physical and cognitive fitness, psychiatric and somatic diseases, health and lifestyle variables, and mortality [4], providing biologically meaningful support. Methods Within the Netherlands Study of Depression and Anxiety (NESDA) [5] we also developed such a biology-based age, specifically one based on DNA methylation patterns (DNAmAge). We selected DNA methylation levels of all 28 million CpG sites in blood as features to predict chronological age in N=1130 subjects (n=811 MDD), using ridge regression. The predictive power was estimated using 10-fold cross-validation. The correlation between chronological age and DNA methylation age estimates were 0.95. MDD diagnosis and clinical characteristics (childhood trauma, symptom duration and severity, age of onset, comorbid anxiety or alcohol dependence disorder, antidepressant use) were assessed with questionnaires and psychiatric interviews. Analyses were adjusted for sociodemographics, lifestyle, and health status. A pathway enrichment analysis was conducted using ConsensusPathDB to gain insight in the biological processes underlying DNAmAge. Results Higher DNAmAge was observed in MDD patients compared to controls (P=0.008), with a dose-effect with increasing symptom severity in the overall sample (P=0.001). Within MDD patients, DNAm age residuals were positively associated with childhood trauma scores (P=0.02). Top significantly enriched Gene Ontology terms included neuronal processes such as neurogenesis and neuron differentiation. Conclusion Our findings show that the DNAmAge for MDD patients is higher than their corresponding chronological age, as well as compared to controls. This potentially suggests an explanation for their increased risk of mortality and aging related diseases. This is an important finding as it may potentially be a therapeutic target to monitor within subjects with regards to illness progression and effectiveness of treatment. More research is needed to investigate the longitudinal dynamics and causal relationships between age-associated alterations in DNA methylation, and depression.

New Approaches to Juvenile Age Estimation in Forensics: Application of Transition Analysis via the Shackelford et al. Method to a Diverse Modern Subadult Sample

Dental development is one of the most widely utilized and accurate methods available for estimating age in subadult skeletal remains. The timing of tooth growth and development is regulated by genetics and less affected by external factors, allowing reliable estimates of chronological age. Traditional methodology focuses on comparing tooth developmental scores to corresponding age charts. Using the Moorrees, Fanning, and Hunt (MFH) developmental scores, Shackelford and colleagues embed the dental development method in a statistical framework based on transition analysis. They generated numerical parameters underlining each "stage" and age-at-death distribution and applied them to fossil hominins and Neanderthals with limited application to modern humans. We use this same method on a subadult test sample (n = 201), representing modern individuals that may become part of the forensic record. We assess the probability coverage of the Shackelford et al. method derived from MFH standards as it applies to all available dentition. Results indicate promise: the age range at 90% and 95% confidence levels includes the chronological age of almost every individual tested. The maximum likelihood age estimates underestimate age by 0.5-2.5 years for individuals 0-15 years of age and by >2.5 years for individuals 16-18 years of age, as previously shown. In an attempt to refine the method, we adjusted the numerical parameters underlying the stages for developing teeth based on a combined modern reference sample (n = 1,964) and tested these revised parameters using the same test sample. The estimated ages from the modified method differ from the original Shackelford et al. methodology by underestimating age to a lesser degree. The modified method does include mean age-at-attainment values for earlier stages of several teeth, allowing for the calculation of narrower confidence intervals. While this study highlights areas of future research in refining dental developmental aging by transition analysis, it also demonstrates that the Shackelford et al. method is applicable and accurate when aging modern subadults in forensic work.

Radiological Development of Mandibular third Molar as An Indicator of Chronological Age itn south Indian Population

Background: Forensic age estimation and its medicolegal implications are gaining lot of importance mainly to determine the age of undocumented youths and to differentiate juvenile from adults. Radiographic evaluation of third molars in terms of its stages of development, its position and extent of mineralization provides an important tool for age estimation, especially in middle teens and early twenties. Hence, this study was designed to assess the reliability of lower third molar development as an indicator for chronological age estimation in young adults of South Indian Population. Material and methods: The study sample comprised of OPG’s (orthopantamographs) of 188 subjects from a restricted geographic area and known chronological age and gender. Radiographs were evaluated using Demerjian’s method to assess the various stages of mandibular right and left third molar development. Data obtained were subjected to statistical analysis. Regression analysis was performed to obtain formula for dental age calculation. Results: Study revealed strong correlation between Demirjians third molar developmental stages and chronological age. Our study also showed that accuracy of age estimation is enhanced when bilateral third molar is evaluated and used for age estimation. The probability of an individual being adult at developmental stage G is still remains uncertain, however at developmental stage H it is almost assured. Conclusion: Several research groups have evaluated the reliability of third molars in age estimation but consensus on the usefulness of these teeth in forensic view has not been reached. The present study has discussed the utility of 3rd molar calcification stage in differentiating between juvenile and adolescent. Demirjian’s stage H can be used as cut off point for determining the majority/minority status of the individual.

Reliability of the Greulich and Pyle method for chronological age estimation and age majority prediction in a Spanish sample.

Estimating the forensic age of living individuals is ever more important in forensic practice, due to the ongoing increase of migratory flows, amongst other causes. Using the Greulich and Pyle method on a sample of 1150 individuals of the Spanish population (n = 560, 0-18years for girls, and n = 590, 0-19years for boys), the mean difference between the bone and chronological ages was obtained: 0.01years (- 0.81, + 0.92) for girls and 0.33years (- 1.15, + 0.34) for boys. For a same class of age and sex, the inherent variability was also evaluated: [Formula: see text] (0.41-1.25) for girls and [Formula: see text]years (0.36-1.76) for boys. To minimise systematic errors with regard to the reference population, adjustment factors are proposed for each age and sex. A sequential classification criterion based on decision trees is postulated to improve reliability in the prediction of maturity. Implementation of the decision criterion in three categories enables the doubtful individuals to be separated into the category of "undetermined" and to satisfactorily classify in the categories of "mature" and "under age": 0.96 (0.86-0.99) specificity; 1.00 (0.92-1.00) specificity; and 1.00 (0.92-1.00) predictive value.

A longitudinal study of DNA methylation as a potential mediator of age-related diabetes risk.

DNA methylation (DNAm) has been found to show robust and widespread age-related changes across the genome. DNAm profiles from whole blood can be used to predict human aging rates with great accuracy. We sought to test whether DNAm-based predictions of age are related to phenotypes associated with type 2 diabetes (T2D), with the goal of identifying risk factors potentially mediated by DNAm. Our participants were 43 women enrolled in the Women's Health Initiative. We obtained methylation data via the Illumina 450K Methylation array on whole blood samples from participants at three timepoints, covering on average 16years per participant. We employed the method and software of Horvath, which uses DNAm at 353 CpGs to form a DNAm-based estimate of chronological age. We then calculated the epigenetic age acceleration, or Δage, at each timepoint. We fit linear mixed models to characterize how Δage contributed to a longitudinal model of aging and diabetes-related phenotypes and risk factors. For most participants, Δage remained constant, indicating that age acceleration is generally stable over time. We found that Δage associated with body mass index (p=0.0012), waist circumference (p=0.033), and fasting glucose (p=0.0073), with the relationship with BMI maintaining significance after correction for multiple testing. Replication in a larger cohort of 157 WHI participants spanning 3years was unsuccessful, possibly due to the shorter time frame covered. Our results suggest that DNAm has the potential to act as a mediator between aging and diabetes-related phenotypes, or alternatively, may serve as a biomarker of these phenotypes.

Age of majority assessment in Dutch individuals based on Cameriere’s third molar maturity index

Radiological examination of the third molar is done in living individuals for estimation of chronological age, especially in the late adolescence. The aim of this study was to assess the application of Cameriere’s third molar maturity index (I3M) to determine whether an individual is 18 years or older (adult) or younger than 18 years (minor) in a sample of Dutch individuals. The sample consisted of panoramic images of 360 individuals aged between 14 and 22 years old. Three observers performed the measurements. Gender was not statistically significant in discriminating adults and minors. The highest value of the Youden index of the receiver operating curve analysis was for the value of I3M<0.08 in discriminating individuals as minor or adult. The specificity (Sp) and sensitivity (Se) results for females were 96.3% and 72.7% respectively. The Sp and Se for males were 95.0% and 84.0% respectively. The probabilities of correctly classified individuals were 83.3% and 88.9%, and Bayes post-test probability was 96.3% and 95.7% in females and males respectively. Obtained results showed that the specific cut-off point of I3M<0.08 may be a useful and reliable method for adult age assessment in a Dutch population.

The Demirjian versus the Willems method for dental age estimation in different populations: A meta-analysis of published studies.

BackgroundThe accuracy of radiographic methods for dental age estimation is important for biological growth research and forensic applications. Accuracy of the two most commonly used systems (Demirjian and Willems) has been evaluated with conflicting results. This study investigates the accuracies of these methods for dental age estimation in different populations.MethodsA search of PubMed, Scopus, Ovid, Database of Open Access Journals and Google Scholar was undertaken. Eligible studies published before December 28, 2016 were reviewed and analyzed. Meta-analysis was performed on 28 published articles using the Demirjian and/or Willems methods to estimate chronological age in 14,109 children (6,581 males, 7,528 females) age 3–18 years in studies using Demirjian’s method and 10,832 children (5,176 males, 5,656 females) age 4–18 years in studies using Willems’ method. The weighted mean difference at 95% confidence interval was used to assess accuracies of the two methods in predicting the chronological age.ResultsThe Demirjian method significantly overestimated chronological age (p<0.05) in males age 3–15 and females age 4–16 when studies were pooled by age cohorts and sex. The majority of studies using Willems’ method did not report significant overestimation of ages in either sex. Overall, Demirjian’s method significantly overestimated chronological age compared to the Willems method (p<0.05). The weighted mean difference for the Demirjian method was 0.62 for males and 0.72 for females, while that of the Willems method was 0.26 for males and 0.29 for females.ConclusionThe Willems method provides more accurate estimation of chronological age in different populations, while Demirjian’s method has a broad application in terms of determining maturity scores. However, accuracy of Demirjian age estimations is confounded by population variation when converting maturity scores to dental ages. For highest accuracy of age estimation, population-specific standards, rather than a universal standard or methods developed on other populations, need to be employed.

Effectiveness of three age estimation methods based on dental and skeletal development in a sample of young Brazilians

ObjectiveThis study compared three methods designed for age estimation. MethodsA sample of 468 radiographs (234 panoramic and 234 carpal radiographs) collected from patients ranging from 5 to 14 years old (mean age: 11.27years old±2.27years) was used. Three age estimation methods: were applied: one founded on dental development, one founded on hand and wrist development, and a method combining both measurements. For each method, the mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and mean percentage of absolute error (MPAE) were quantified. The methods: were compared based on their effectiveness for estimating age in relation to sex and age range. ResultsThe data show that the method exclusively using the development of the hand and wrist had the highest error rates (ME: 1.28M, 1.85F; MAE: 1.64M, 1.96F; RMSE: 1.94M, 2.32F) for both males (M) and females (F). In males, the method combining dental and skeletal development obtained outcomes that were slightly better than the method founded on only dental development (MPAE: 6.99% and 7.47%, respectively). In females, the opposite result was observed (MPAE: 8.48% and 6.59%, respectively). The method founded exclusively on skeletal development significantly overestimated (p=0.001) the age (mean chronological and estimated ages: 11.27 and 12.88, respectively). ConclusionThe methods involving dental development provided more accurate age estimates of chronological age. The method exclusively based on hand and wrist development resulted in outcomes that were highly discrepant from the chronological age.

Listener estimates of talker age in a single-talker, 50-year longitudinal sample

PurposeWhile many studies have shown that listeners make relatively accurate age judgments from hearing talkers’ voices, most have used just one age per talker. The present study evaluated listeners’ age estimation abilities for a longitudinal sample: a single talker recorded over nearly five decades. MethodWe extracted 60 samples from addresses given by a male talker over 48 years. For each sample, listeners gave a direct estimate of his age. We also asked listeners if they could identify the talker, who was known locally, from the recordings. ResultsWhile correlations between the talker’s chronological age and direct estimates of age were generally strong, the relationship was particularly strong when the talker was older than 68 years, although listeners underestimated chronological age by approximately 5 years. When the talker was between 49 and 68 years, direct age estimates were less accurate and less strongly correlated with chronological age. Additionally, direct age estimates were more accurate when listeners recognized the talker. ConclusionsCorroborating cross-sectional studies, our listeners overestimated the talker’s age when he was younger and underestimated it when he was older. However, the crossover between overestimation and underestimation, the point where estimated and chronological ages were equal, occurred at a later talker age for this longitudinal study than in previous cross-sectional studies. Additionally, listeners who recognized the talker made more accurate age estimates when the talker’s chronological age was near the age where they would have known him. We propose future studies explore the relationship between familiarity and estimated age.

Age estimation in Portuguese population: The application of the London atlas of tooth development and eruption

Chronological age estimation from the dental parameters is becoming increasingly important. The London atlas of tooth development is the most recent developed method and represents a modification of the previous older methods.The aim of this study was to evaluate the accuracy of the London atlas for the dental age estimation in the Portuguese population.The study sample included 736 radiographic images (498 females and 238 males) of Portuguese origin, patients of Dental Clinic of Superior Institute of Health Sciences Egas Moniz and Dental Medicine Faculty, University of Lisbon. The age range of the individuals was between 3 and 24 years. Estimated age was compared with the chronological age using the paired t-test.The results showed that there was no statistically significant difference between left and right side of the jaw (p>0.05). Both sides showed an average overestimation of age by one month approximately. Moreover, the significant difference between chronological and estimated age was not observed in the females. However, the significant difference was observed in a sample coming from males (right: p=0.008; left: p=0.003).Our results showed that the London atlas can be potentially used as a tool for age estimation. However, the difference between sexes clearly suggests that separate charts should be made for each sex. Further studies, which will have as a final goal the development of a new method for age estimation using dental parameters, are needed.

Chronological Age Estimation Based on Mandibular Third Molar Development from Digital Panoramic Radiograph in a South Kerala Population

Introduction: Tooth development is the best method in estimating the chronological age of young adults. Demirjan’s method has high value of correlation and observer agreement between chronological age and estimated age. Aim of the study: To assess the chronological age based on developmental stages of mandibular third molar using Demirjian’s method. Materials and methods: A retrospective study of 160 radiographs, among subjects in the age group of 9-25 years who underwent digital panoramic radiographic examination during the last 6 months in the Department of Oral Medicine and Radiology, Pushpagiri College of Dental Sciences, Thiruvalla, Kerala, South India. TenmaIes and ten females were selected for each stage of third molar development (n=160). Developmental stage of the mandibular third molar was assessed using Demirjian’s method. Results: The root formation of mandibular third molars is completed (stage H) at the mean age of 21.4 ± 2.5 years and 21.2 ± 3.2years in females and males respectively. At the mean age of 14.6 ± 1.5 and 13.6 ± 1.9years, the formation of inter-radicular bifurcation (Stage E) had started in males and in females. The data showed that males reached the stages at indicated ages earlier than females. Conclusion: Radiological development of the third molar may be a useful biological variable for estimating the age of a person between teens and early 20s.

Assessing the variability of telomere length measures by means of Telomeric Restriction Fragments (TRF) in different tissues of cod Gadus morhua

The chronological age estimation is still an elusive parameter in many wild animals. Telomeres are nucleoprotein on the ends of chromosomes that shorten throughout the life of many animals. In this study, Telomeric Restriction Fragments length was measured in four different tissues (brain, liver, muscle and skin) of aquaculture cods (Gadus morhua) of different age: larvae (0–110dph); fry (111–180dph), juvenile (181–420dph) and adults (>421dph). Telomeres shortened with increasing age and body length, with differences in telomere rate of shortening depending on the tissue and the developmental stage. The shortening of telomeres with age was significant in brain and liver but it was observed inter-individual variability among individuals of the same age class. Skin and muscle showed no significant shortening pattern with age even tending to elongate in the case of muscle.

Comparison of accuracy between dental and skeletal age in the estimation of chronological age of Down syndrome individuals

This study aimed to evaluate the accuracy of dental age (DA) and skeletal age (SA) methods in order to estimate chronological age (CA) in individuals with Down syndrome (DS), contributing to the Forensic Dentistry and making the identification of these individuals age possible. For this, 278 images of individuals were selected and divided in 2 groups: 216 non-DS patients and 62 with DS. At first, DA was evaluated by Nolla method, on panoramic radiographs, followed by SA, evaluated by Greulich and Pyle method. The linear correlation coefficient of Pearson was used for the analysis of concordance between the methods. Paired t-test with confidence interval was used to evaluate the accuracy and Bland and Altman method was applied to estimate limits of concordance. Complementary to this first analysis, descriptive statistics and ANOVA test were applied for comparison among chronological age (CA), dental age (DA) and skeletal age (SA), with a significance level of 95% (p≥0.05), ordering to observe the differences among them. DA, estimated by Nolla, is underestimated in both, DS and non-DS individuals, and it is more notable in DS individuals. SA estimated by Greulich and Pyle method is overestimated, except for non-DS males. The range of variance is greater in SA and DS than DA and non-DS individuals, respectively. A greater accordance was found for DA×CA if compared to SA×CA, indicating that DA, estimated by Nolla method, is more accurate than SA, evaluated by Greulich and Pyle method, for estimating CA of both, DS and non-DS individuals. However, neither method seems to be precise and more caution is required for age estimation in DS individuals.

Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures.

Aging is reflected by highly reproducible DNA methylation (DNAm) changes that open new perspectives for estimation of chronological age in legal medicine. DNA can be harvested non-invasively from cells at the inside of a person's cheek using buccal swabs – but these specimens resemble heterogeneous mixtures of buccal epithelial cells and leukocytes with different epigenetic makeup. In this study, we have trained an age predictor based on three age-associated CpG sites (associated with the genes PDE4C, ASPA, and ITGA2B) for swab samples to reach a mean absolute deviation (MAD) between predicted and chronological age of 4.3 years in a training set and of 7.03 years in a validation set. Subsequently, the composition of buccal epithelial cells versus leukocytes was estimated by two additional CpGs (associated with the genes CD6 and SERPINB5). Results of this “Buccal-Cell-Signature” correlated with cell counts in cytological stains (R2 = 0.94). Combination of cell type-specific and age-associated CpGs into one multivariate model enabled age predictions with MADs of 5.09 years and 5.12 years in two independent validation sets. Our results demonstrate that the cellular composition in buccal swab samples can be determined by DNAm at two cell type-specific CpGs to improve epigenetic age predictions.

Determining the effectiveness of adult measures of standardised age estimation on juveniles in a Western Australian population

The estimation of chronological age through assessment of dental radiographs is well-established and a useful method to assist in the identification of persons in forensic and anthropological scenarios. The objective of our investigation was twofold: (i) to validate the Kvaal et al. age-estimation method on a sample of Western Australian subjects, and (ii) to increase the range of chronological ages to which the Kvaal et al. method can be applied. Our sample size included panoramic radiographs from 74 subjects (aged 12–28 years). A set of ratios were calculated and then used to apply different statistical models of linear regression, in order to generate a final formula to estimate age. The most accurate estimations were obtained from the models generated by the mandibular canine measurement (SEE ± 3.708 years), and for the three mandibular teeth (SEE ± 3.388 years). The results indicate that inclusion of juveniles did not affect final results, and the method still produced estimates acceptable in a forensic framework.

Radiological assessment of age from epiphyseal fusion at the knee joint

Objectives: Age determination is needed in administration of justice, employment, marriage, forensic investigation and identification. This cross-sectional study aimed to investigate the relationship between stages of epiphyseal union at the knee joint and chronological age. Methods: Anterior posterior and lateral knee radiographs of 100 males and 110 females aged 9–19 years were examined. Epiphyseal union was divided into five specific stages in the femur, tibia and fibula. Fusion was scored as stage 0: non-union,stage 1: beginning union, stage 2: active union, stage 3: recent union, and stage 4: complete union. Results: Mean age gradually increased with each stage of union and varied between males and females. A statistically significant difference in mean age was recorded between stages for the three epiphyses. Epiphyseal union occurred earlier in females than in males. A statistically significant difference was observed between the mean age of union for males and females for stages 1 and 2 for the femur, and stages 0, 1, 2 and 3 for the tibia and fibula. Conclusion: The results of this study indicate that radiographic analysis of the knee is a valuable alternative for estimation of chronological age. Keywords: age estimation; epiphysis; fusion; knee joint; radiograph; skeletal maturation