A systematic review of the agreement between chronological age and skeletal age based on the Greulich and Pyle atlas

Radiological age assessment based on clavicle ossification in CT: enhanced accuracy through deep learning

BACKGROUND

Radiological age assessment using reference studies is inherently limited in accuracy due to a finite number of assignable skeletal maturation stages. To overcome this limitation, we present a deep learning approach for continuous age assessment based on clavicle ossification in computed tomography (CT).

METHODS

Thoracic CT scans were retrospectively collected from the picture archiving and communication system. Individuals aged 15.0 to 30.0 years examined in routine clinical practice were included. All scans were automatically cropped around the medial clavicular epiphyseal cartilages. A deep learning model was trained to predict a person's chronological age based on these scans. Performance was evaluated using mean absolute error (MAE). Model performance was compared to an optimistic human reader performance estimate for an established reference study method.

RESULTS

The deep learning model was trained on 4,400 scans of 1,935 patients (training set: mean age = 24.2 years ± 4.0, 1132 female) and evaluated on 300 scans of 300 patients with a balanced age and sex distribution (test set: mean age = 22.5 years ± 4.4, 150 female). Model MAE was 1.65 years, and the highest absolute error was 6.40 years for females and 7.32 years for males. However, performance could be attributed to norm-variants or pathologic disorders. Human reader estimate MAE was 1.84 years and the highest absolute error was 3.40 years for females and 3.78 years for males.

CONCLUSIONS

We present a deep learning approach for continuous age predictions using CT volumes highlighting the medial clavicular epiphyseal cartilage with performance comparable to the human reader estimate.

Applicability and robustness of an artificial intelligence-based assessment for Greulich and Pyle bone age in a German cohort

PURPOSE

 The determination of bone age (BA) based on the hand and wrist, using the 70-year-old Greulich and Pyle (G&P) atlas, remains a widely employed practice in various institutions today. However, a more recent approach utilizing artificial intelligence (AI) enables automated BA estimation based on the G&P atlas. Nevertheless, AI-based methods encounter limitations when dealing with images that deviate from the standard hand and wrist projections. Generally, the extent to which BA, as determined by the G&P atlas, corresponds to the chronological age (CA) of a contemporary German population remains a subject of continued discourse. This study aims to address two main objectives. Firstly, it seeks to investigate whether the G&P atlas, as applied by the AI software, is still relevant for healthy children in Germany today. Secondly, the study aims to assess the performance of the AI software in handling non-strict posterior-anterior (p. a.) projections of the hand and wrist.

MATERIALS AND METHODS

 The AI software retrospectively estimated the BA in children who had undergone radiographs of a single hand using posterior-anterior and oblique planes. The primary purpose was to rule out any osseous injuries. The prediction error of BA in relation to CA was calculated for each plane and between the two planes.

RESULTS

 A total of 1253 patients (aged 3 to 16 years, median age 10.8 years, 55.7 % male) were included in the study. The average error of BA in posterior-anterior projections compared to CA was 3.0 (± 13.7) months for boys and 1.7 (± 13.7) months for girls. Interestingly, the deviation from CA tended to be even slightly lower in oblique projections than in posterior-anterior projections. The mean error in the posterior-anterior projection plane was 2.5 (± 13.7) months, while in the oblique plane it was 1.8 (± 13.9) months (p = 0.01).

CONCLUSION

 The AI software for BA generally corresponds to the age of the contemporary German population under study, although there is a noticeable prediction error, particularly in younger children. Notably, the software demonstrates robust performance in oblique projections.

KEY POINTS

  · Bone age, as determined by artificial intelligence, aligns with the chronological age of the contemporary German cohort under study.. · As determined by artificial intelligence, bone age is remarkably robust, even when utilizing oblique X-ray projections..

CITATION FORMAT

· Pape J, Hirsch F, Deffaa O et al. Applicability and robustness of an artificial intelligence-based assessment for Greulich and Pyle bone age in a German cohort. Fortschr Röntgenstr 2024; 196: 600 - 606.

Determination of growth and developmental stages in hand-wrist radiographs : Can fractal analysis in combination with artificial intelligence be used?

PURPOSE

The goal of this work was to assess the classification of maturation stage using artificial intelligence (AI) classifiers.

METHODS

Hand-wrist radiographs (HWRs) from 1067 individuals aged between 7 and 18 years were included. Fifteen regions of interest were selected for fractal dimension (FD) analysis. Five predictive models with different inputs were created (model 1: only FD; model 2: FD and Chapman sesamoid stage; model 3: FD, age, and sex; model 4: FD, Chapman sesamoid stage, age, and sex; model 5: Chapman sesamoid stage, age, and sex). The target diagnoses were accelerating growth velocity, very high growth velocity, and decreasing growth velocity. Four AI algorithms were applied: multilayer perceptron (MLP), support vector machine (SVM), gradient boosting machine (GBM) and C 5.0 decision tree classifier.

RESULTS

All AI algorithms except for C 5.0 yielded similar overall predictive accuracies for the five models. In order from lowest to highest, the predictive accuracies of the models were as follows: model 1 < model 3 < model 2 < model 5 < model 4. The highest overall F1 score, which was used instead of accuracy especially for models with unbalanced data, was obtained for models 1, 2, and 3 based on SVM, for model 4 based on MLP, and for model 5 based on C 5.0. Adding Chapman sesamoid stage, chronologic age, and sex as additional inputs to the FD values significantly increased the F1 score.

CONCLUSION

Applying FD analysis to HWRs is not sufficient to predict maturation stage in growing patients but can be considered a growth rate prediction method if combined with the Chapman sesamoid stage, age, and sex.

Skeletal age estimation of living adolescents and young adults: A pilot study on conventional radiography versus magnetic resonance imaging and staging technique versus atlas method

OBJECTIVE

To compare conventional radiography (CR) and magnetic resonance imaging (MRI) of the left hand/wrist and both clavicles for forensic age estimation of adolescents and young adults.

MATERIALS AND METHODS

CR and MRI were prospectively conducted in 108 healthy Caucasian volunteers (52 males, 56 females) aged 16 to 21 years. Skeletal development was assessed by allocating stages (wrist, clavicles) and atlas standards (hand/wrist). Inter- and intra-observer agreements were quantified using linear weighted Cohen's kappa, and descriptive statistics regarding within-stage/standard age distributions were reported.

RESULTS

Inter- and intra-observer agreements for hand/wrist CR (staging technique: 0.840-0.871 and 0.877-0.897, respectively; atlas method: 0.636-0.947 and 0.853-0.987, respectively) and MRI (staging technique: 0.890-0.932 and 0.897-0.952, respectively; atlas method: 0.854-0.941 and 0.775-0.978, respectively) were rather similar. The CR atlas method was less reproducible than the staging technique. Inter- and intra-observer agreements for clavicle CR (0.590-0.643 and 0.656-0.770, respectively) were lower than those for MRI (0.844-0.852 and 0.866-0.931, respectively). Furthermore, although shifted, wrist CR and MRI within-stage age distribution spread were similar, as were those between staging techniques and atlas methods. The possibility to apply (profound) substages to clavicle MRI rendered a more gradual increase of age distributions with increasing stages, compared to CR.

CONCLUSIONS

For age estimation based on the left hand/wrist and both clavicles, reference data should be considered anatomical structure- and imaging modality-specific. Moreover, CR is adequate for hand/wrist evaluation and a wrist staging technique seems to be more useful than an atlas method. By contrast, MRI is of added value for clavicle evaluation.

Precision and Accuracy of Radiological Bone Age Assessment in Children among Different Ethnic Groups: A Systematic Review

AIM

The aim was to identify, evaluate, and summarize the findings of relevant individual studies on the precision and accuracy of radiological BA assessment procedures among children from different ethnic groups.

MATERIALS AND METHODS

A qualitative systematic review was carried out following the MOOSE statement and previously registered in PROSPERO (CRD42023449512). A search was performed in MEDLINE (PubMed) (n = 561), the Cochrane Library (n = 261), CINAHL (n = 103), Web of Science (WOS) (n = 181), and institutional repositories (n = 37) using MeSH and free terms combined with the Booleans "AND" and "OR". NOS and ROBINS-E were used to assess the methodological quality and the risk of bias of the included studies, respectively.

RESULTS

A total of 51 articles (n = 20,100) on radiological BA assessment procedures were precise in terms of intra-observer and inter-observer reliability for all ethnic groups. In Caucasian and Hispanic children, the Greulich-Pyle Atlas (GPA) was accurate at all ages, but in youths, Tanner-Whitehouse radius-ulna-short bones 3 (TW3-RUS) could be an alternative. In Asian and Arab subjects, GPA and Tanner-Whitehouse 3 (TW3) overestimated the BA in adolescents near adulthood. In African youths, GPA overestimated the BA while TW3 was more accurate.

CONCLUSION

GPA and TW3 radiological BA assessment procedures are both precise but their accuracy in estimating CA among children of different ethnic groups can be altered by racial bias.

High performance for bone age estimation with an artificial intelligence solution

PURPOSE

The purpose of this study was to compare the performance of an artificial intelligence (AI) solution to that of a senior general radiologist for bone age assessment.

MATERIAL AND METHODS

Anteroposterior hand radiographs of eight boys and eight girls from each age interval between five and 17 year-old from four different radiology departments were retrospectively collected. Two board-certified pediatric radiologists with knowledge of the sex and chronological age of the patients independently estimated the Greulich and Pyle bone age to determine the standard of reference. A senior general radiologist not specialized in pediatric radiology (further referred to as "the reader") then determined the bone age with knowledge of the sex and chronological age. The results of the reader were then compared to those of the AI solution using mean absolute error (MAE) in age estimation.

RESULTS

The study dataset included a total of 206 patients (102 boys of mean chronological age of 10.9 ± 3.7 [SD] years, 104 girls of mean chronological age of 11 ± 3.7 [SD] years). For both sexes, the AI algorithm showed a significantly lower MAE than the reader (P < 0.007). In boys, the MAE was 0.488 years (95% confidence interval [CI]: 0.28-0.44; r² = 0.978) for the AI algorithm and 0.771 years (95% CI: 0.64-0.90; r² = 0.94) for the reader. In girls, the MAE was 0.494 years (95% CI: 0.41-0.56; r² = 0.973) for the AI algorithm and 0.673 years (95% CI: 0.54-0.81; r² = 0.934) for the reader.

CONCLUSION

The AI solution better estimates the Greulich and Pyle bone age than a general radiologist does.

Prediction of Fishman's skeletal maturity indicators using artificial intelligence

The present study aimed to evaluate the performance of automated skeletal maturation assessment system for Fishman's skeletal maturity indicators (SMI) for the use in dental fields. Skeletal maturity is particularly important in orthodontics for the determination of treatment timing and method. SMI is widely used for this purpose, as it is less time-consuming and practical in clinical use compared to other methods. Thus, the existing automated skeletal age assessment system based on Greulich and Pyle and Tanner-Whitehouse3 methods was further developed to include SMI using artificial intelligence. This hybrid SMI-modified system consists of three major steps: (1) automated detection of region of interest; (2) automated evaluation of skeletal maturity of each region; and (3) SMI stage mapping. The primary validation was carried out using a dataset of 2593 hand-wrist radiographs, and the SMI mapping algorithm was adjusted accordingly. The performance of the final system was evaluated on a test dataset of 711 hand-wrist radiographs from a different institution. The system achieved a prediction accuracy of 0.772 and mean absolute error and root mean square error of 0.27 and 0.604, respectively, indicating a clinically reliable performance. Thus, it can be used to improve clinical efficiency and reproducibility of SMI prediction.

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.

Bone-specific median age of hand-wrist maturation from Sudan

BACKGROUND

Maturation of bones in the hand-wrist region varies among individuals of the same age and among world groups. Although some studies from Africa report differences to other ethnic groups, the lack of detailed bone-specific maturity data prevents meaningful comparisons.

AIM

The aim of this study was to describe bone-specific maturity for developing hand-wrist bones in individuals in Khartoum, Sudan.

SUBJECTS AND METHODS

The sample was selected from healthy patients attending a dental hospital in Khartoum with known age and ancestry (males = 280, females = 330; aged between 3 and 25 years). Bones were assessed from radiographs of the left hand and wrist after the Greulich and Pyle Atlas (1959). Median ages of attainment for bone stages were calculated using probit analysis for each stage in males and females separately.

RESULTS

Maturity data for stages of the phalanges, metacarpals, carpals and radius and ulna in males and females are presented. Median ages in females were earlier compared to males for all stages. These results are largely earlier than previously published findings or where these could be calculated.

CONCLUSION

These results of individual maturity stages of phalanges, metacarpals, carpals and the distal epiphyses of the radius and ulna are useful to assess maturity in growing individuals from Sudan.

The Interrater and Intrarater Reliability of the Humeral Head Ossification System and the Proximal Femur Maturity Index Assessments for Patients with Adolescent Idiopathic Scoliosis

Background

Skeletal maturity can evaluate the growth and development potential of children and provide a guide for the management of adolescent idiopathic scoliosis (AIS). Recent studies have demonstrated the advantages of the Humeral Head Ossification System (HHOS) and the Proximal Femur Maturity Index (PFMI), based on standard scoliosis films, in the management of AIS patients. We further assessed the HHOS and the PFMI method's reliability in the interrater and intrarater.

Methods

The data from 38 patients, including the humeral head and proximal femur on standard scoliosis films, were distributed to the eight raters in the form of a PowerPoint presentation. On 38 independent standard spine radiographs, raters utilized the HHOS and PFMI to assign grades. The PPT sequence was randomly changed and then reevaluated 2 weeks later. For every system, the 95% confidence interval (95% CI) and intraclass correlation coefficient (ICC) were calculated to evaluate the interrater and intrarater reliability.

Results

The HHOS was extremely reliable, with an intraobserver ICC of 0.802. In the first round, the interobserver ICC reliability for the HHOS was 0.955 (0.929-0.974), while in the second round, it was 0.939 (0.905-0.964). The PFMI was extremely reliable, with an intraobserver ICC of 0.888. In the first round, the interobserver ICC reliability for the PFMI was 0.967 (0.948-0.981), while in the second round, it was 0.973 (0.957-0.984).

Conclusions

The HHOS and PFMI classifications had excellent reliability. These two methods are beneficial to reduce additional exposure to radiation and expense for AIS. There are advantages and disadvantages to each classification. Clinicians should choose a personalized and reasonable method to assess skeletal maturity, which will assist in the management of adolescent scoliosis patients.

NMR-based metabolic profiling of children with premature adrenarche

INTRODUCTION

Premature adrenarche (PA) for long time was considered a benign condition but later has been connected to various diseases in childhood and adulthood which remains controversial.

OBJECTIVE

To investigate the effect of premature adrenarche on the metabolic phenotype, and correlate the clinical and biochemical data with the metabolic profile of children with PA.

METHODS

Nuclear magnetic resonance (NMR)-based untargeted and targeted metabolomic approach in combination with multivariate and univariate statistical analysis applied to study the metabolic profiles of children with PA. Plasma, serum, and urine samples were collected from fifty-two children with Idiopathic PA and forty-eight age-matched controls from the division of Pediatric Endocrinology of the University Hospital of Patras were enrolled.

RESULTS

Metabolomic results showed that plasma and serum glucose, myo-inositol, amino acids, a population of unsaturated lipids, and esterified cholesterol were higher and significantly different in PA children. In the metabolic profiles of children with PA and age-matched control group a gradual increase of glucose and myo-inositol levels was observed in serum and plasma, which was positively correlated their body mass index standard deviation score (BMI SDS) values respectively. Urine ¹H NMR metabolic fingerprint of PA children showed positive correlation and a clustering-dependent relationship with their BMI and bone age (BA) respectively.

CONCLUSION

This study provides evidence that PA driven metabolic changes begin during the childhood and PA may has an inductive role in a BMI-driven increase of specific metabolites. Finally, urine may be considered as the best biofluid for identification of the PA metabolism as it reflects more clearly the PA metabolic fingerprint.

Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography

Age estimation in dental radiographs Orthopantomography (OPG) is a medical imaging technique that physicians and pathologists utilize for disease identification and legal matters. For example, for estimating post-mortem interval, detecting child abuse, drug trafficking, and identifying an unknown body. Recent development in automated image processing models improved the age estimation's limited precision to an approximate range of +/- 1 year. While this estimation is often accepted as accurate measurement, age estimation should be as precise as possible in most serious matters, such as homicide. Current age estimation techniques are highly dependent on manual and time-consuming image processing. Age estimation is often a time-sensitive matter in which the image processing time is vital. Recent development in Machine learning-based data processing methods has decreased the imaging time processing; however, the accuracy of these techniques remains to be further improved. We proposed an ensemble method of image classifiers to enhance the accuracy of age estimation using OPGs from 1 year to a couple of months (1-3-6). This hybrid model is based on convolutional neural networks (CNN) and K nearest neighbors (KNN). The hybrid (HCNN-KNN) model was used to investigate 1,922 panoramic dental radiographs of patients aged 15 to 23. These OPGs were obtained from the various teaching institutes and private dental clinics in Malaysia. To minimize the chance of overfitting in our model, we used the principal component analysis (PCA) algorithm and eliminated the features with high correlation. To further enhance the performance of our hybrid model, we performed systematic image pre-processing. We applied a series of classifications to train our model. We have successfully demonstrated that combining these innovative approaches has improved the classification and segmentation and thus the age-estimation outcome of the model. Our findings suggest that our innovative model, for the first time, to the best of our knowledge, successfully estimated the age in classified studies of 1 year old, 6 months, 3 months and 1-month-old cases with accuracies of 99.98, 99.96, 99.87, and 98.78 respectively.

The Application of Magnetic Resonance Imaging in Skeletal Age Assessment

METHOD

The study includes 80 patients identified from an endocrine clinic, two males and two females from each of 5 age groups (<5, 5 to 7, 8 to 10, 11 to 13, and 14 to 16 years). Skeletal age as determined from an open MRI scanner and radiographs performed on the same day was compared for each child. Two observers assess the skeletal age from radiographs and MRI images independently. After a period of at least three weeks, observers determined the skeletal age of all patients independently. All of the images were in different and random orders, on both of the assessment occasions. The agreement was assessed using the interclass correlation coefficient and Bland Altman plots. Problem Statement. The recurrent use of left-hand radiography in children with chronic conditions might result in the patient being exposed to the same image several times throughout the course of their lives. Use of radiation-free methods such as magnetic resonance imaging (MRI) may be able to assist in reducing the risks associated with radiation exposure, if done properly.

RESULTS

Patients' age ranged from 3 to 16 years, in which the mean of the chronological age was 9.3 years (±2.9) and 9.8 years (±2.7) in girls and boys, respectively. The interrater agreement for skeletal age determination was 0.984 for radiographs and 0.976 for MRI scans. Using the G&P technique, for Observer 1, intraobserver agreement for radiographs and DXA was 0.993 and 0.983, respectively, and 0.995 and 0.994, respectively, for Observer 2. Plotting the rater readings against the line of equality shows no significant differences between readings acquired from radiographs and MRI scans.

CONCLUSION

For the study contribution, it is possible to employ open compact MRI to determine the skeletal age of a person. Our results showed that left-hand MRI scans were of better quality than the radiographs.

Forensic age assessment by 3.0 T MRI of the wrist: adaption of the Vieth classification

OBJECTIVES

In order to find a reliable method to correctly assess majority in both sexes by MRI, a study was conducted to evaluate the applicability of the recently presented Vieth classification in wrist MRI, after it had originally been proposed for knee MRI.

METHODS

After receiving a positive vote by the ethics committee, the left-hand wrists of 347 male and 348 female volunteers of German nationality in the age bracket 12-24 years were scanned. Before conducting the prospective, cross-sectional examinations, an informed consent was obtained from each volunteer. A 3.0 T MRI scanner was used, acquiring a T1 turbo spin-echo sequence (TSE) and a T2 TSE sequence with fat suppression by spectral presaturation with inversion recovery (SPIR). The images were assessed by applying the Vieth classification. Minimum, maximum, mean ± standard deviation, and median with lower and upper quartiles were defined. Intra- and interobserver agreements were determined by calculating the kappa coefficients. Differences between the sexes were analyzed using the Mann-Whitney U test.

RESULTS

By applying the unmodified Vieth classification with corresponding schematics, it was possible to assess majority in both sexes via the epiphyseal-diaphyseal fusion of the distal radius and in males also via the epiphyseal-diaphyseal fusion of the distal ulna. The Mann-Whitney U test implied significant sex-related differences for all stages. For both epiphyses, the intra- and interobserver agreement levels were very good (κ > 0.8).

CONCLUSION

If confirmed by further studies, it would be possible to determine the completion of the 18th year of life in both sexes by 3.0 T MRI of the wrist and using the Vieth classification.

KEY POINTS

• The Vieth classification allows determining majority in males and females alike based on the distal radius' epiphysis by 3.0 T MRI of the wrist. • The Vieth classification also allows determining majority in males based on the distal ulna's epiphysis by 3.0 T MRI of the wrist, but not in females. • The presented data can be deemed referential within certain discussed boundaries.

A probability model for assessing age relative to the 18-year old threshold based on magnetic resonance imaging of the knee combined with radiography of third molars in the lower jaw

OBJECTIVE

This study aims to generate a statistical model based on magnetic resonance imaging of the knee and radiography of third molars in the lower jaw, for assessing age relative to the 18-year old threshold.

METHODS

In total, 58 studies correlating knee or tooth development to age were assessed, 5 studies for knee and 7 studies for tooth were included in the statistical model. The relation between the development of the anatomical site, based on a binary system, and age were estimated using logistic regression. Separate meta-populations for knee and tooth were generated from the individual based data for men and women. A weighted estimate of probabilities was made by combining the probability densities for knee and tooth. Margin of errors for males and females in different age groups and knee and tooth maturity were calculated within the larger framework of transition analysis using a logit model as a base. Evidentiary values for combinations of knee and tooth maturity were evaluated with likelihood ratios.

RESULTS

For males, the sensitivity for the method was calculated to 0.78 (probability of correctly classifying adults), the specificity 0.90 (probability of correctly classifying minors), the negative predictive value 0.80 (proportion identified minors are minors) and the positive predictive value 0.89 (proportion identified adults are adults) indicating a model better at identifying minors than adults. The point at which half the female population has reached closed knee lies before the 18-year threshold, adding the knee as an indicator lowers specificity and increases sensitivity. The sensitivity when using tooth as an indicator for females is 0.24 and specificity 0.97, signifying few minors misclassified as adults but also a low probability of identifying adults. The negative predictive value for women when using tooth as the sole indicator is 0.56 and positive predictive value 0.88. Probabilities were calculated for males and females assuming a uniform age distribution between 15 and 21years. The calculated margin of error of minors classified as adults in a population between 15 and 21 years with the model was 11% for males and 12% for females. Further, the evidentiary value as well as margin of error vary for different combinations of knee and tooth maturity.

CONCLUSION

The statistical model based on the combination of MRI knee and radiography of mandibular third molars is a valid method to assess age relative to the 18-year old threshold when applied on males and of limited value in females.

Lower-Extremity Segment-Length Prediction Accuracy of the Sanders Multiplier, Paley Multiplier, and White-Menelaus Formula

BACKGROUND

Several methods are available to estimate leg lengths at maturity to facilitate the determination of timing of epiphysiodesis. We compared the Paley multiplier, Sanders multiplier, and White-Menelaus methods in an epiphysiodesis-aged cohort. We assessed intra- and interrater reliability for Sanders skeletal stages and Greulich and Pyle atlas skeletal age.

METHODS

Actual growth was recorded in healthy, unoperated femoral and tibial segments from an epiphysiodesis database. The predicted and actual lengths were compared with use of the Paley multiplier and White-Menelaus methods, Greulich and Pyle skeletal age, and the Sanders multiplier using Sanders stages. Intra- and interrater reliability were assessed in a separate group of 76 skeletal age films.

RESULTS

The cohort included 148 femora and 195 tibiae in 197 patients. Femoral length at maturity was slightly underestimated by the Sanders multiplier and staging, was overestimated by the Paley multiplier and skeletal age, and was most accurately predicted with use of the White-Menelaus formula and skeletal age. All methods overestimated tibial length at maturity. The whole-leg prediction accuracy of the Sanders multiplier and White-Menelaus formula were comparable and were more accurate than that of the Paley multiplier. For Sanders skeletal staging, the interrater reliability varied from 0.86 to 0.88 and the intrarater reliability varied from 0.87 to 0.96. For Greulich and Pyle skeletal age, the interrater reliability varied from 0.87 to 0.89 and the intrarater reliability varied from 0.91 to 0.95.

CONCLUSIONS

Use of the Sanders multiplier and skeletal stages was more accurate than the Paley multiplier and skeletal age in this cohort. Use of the White-Menelaus formula and skeletal age was slightly more accurate in predicting femoral length and slightly less accurate in predicting tibial length compared with the Sanders multiplier. Intra- and interrater reliability were similar between Sanders skeletal stages and Greulich and Pyle atlas skeletal age. The White-Menelaus formula and skeletal age was the recommended method for predicting lower-extremity segment lengths at maturity and epiphysiodesis effect. Although easier to recall without referencing an atlas and not sex-specific, Sanders skeletal staging does not correspond directly to years of growth remaining, and thus cannot be used with the White-Menelaus formula.

CLINICAL RELEVANCE

The Greulich and Pyle atlas to determine skeletal age and the White-Menelaus formula to determine growth remaining are reliable predictors of epiphysiodesis effect in the lower extremities.

Nomogram for Predicting Bone Development State of Female Children and Adolescents-A Fast Screening Approach Based on Pubes Stages for Growth and Development

Objective: To develop a nomogram for predicting bone development state (BDS) of female children and adolescents in a large scale. Methods: Four hundred forty-seven female students were designated as the training cohort to develop the predictive model, whereas 196 female students were used as the validation cohort to verify the established model. Bone age, height, body mass, body fat percentage, and secondary sexual characteristics were recorded, and BDS was determined with the chronological age and bone age. Multivariate logistic regression was conducted to determine the factors, and nomogram was developed and validated with the training and validation cohorts, respectively. Results: One hundred forty-seven female students were identified as BDS abnormal in the training cohort (32.9%), and 104 were determined in the validation cohort (53.1%). Age, height, weight, and pubes stage were selected for the predictive model. A nomogram was developed and showed a good estimation, with a C-index of 0.78 and a good calibration in the training cohort. Application of the nomogram to the validation cohort showed a similar C-index of 0.75 and a good calibration. Conclusion: A nomogram for predicting bone development was developed, which can provide a relatively good estimation of BDS for female children and adolescents in Chinese metropolis.

Applicability of two commonly used bone age assessment methods to twenty-first century UK children

Objectives

To assess the effect of secular change on skeletal maturation and thus on the applicability of the Greulich and Pyle (G&P) and Tanner and Whitehouse (TW3) methods.

Methods

BoneXpert was used to assess bone age from 392 hand trauma radiographs (206 males, 257 left). The paired sample t test was performed to assess the difference between mean bone age (BA) and mean chronological age (CA). ANOVA was used to assess the differences between groups based on socioeconomic status (taken from the Index of Multiple Deprivation).

Results

CA ranged from 2 to 15 years for females and 2.5 to 15 years for males. Numbers of children living in low, average and high socioeconomic areas were 216 (55%), 74 (19%) and 102 (26%) respectively. We found no statistically significant difference between BA and CA when using G&P. However, using TW3, CA was underestimated in females beyond the age of 3 years, with significant differences between BA and CA (− 0.43 years, SD 1.05, p = < 0.001) but not in males (0.01 years, SD 0.97, p = 0.76). Of the difference in females, 17.8% was accounted for by socioeconomic status.

Conclusion

No significant difference exists between BoneXpert-derived BA and CA when using the G&P atlas in our study population. There was a statistically significant underestimation of BoneXpert-derived BA compared with CA in females when using TW3, particularly in those from low and average socioeconomic backgrounds. Secular change has not led to significant advancement in skeletal maturation within our study population.

Key Points

• The Greulich and Pyle method can be applied to the present-day United Kingdom (UK) population.

• The Tanner and Whitehouse (TW3) method consistently underestimates the age of twenty-first century UK females by an average of 5 months.

• Secular change has not advanced skeletal maturity of present-day UK children compared with those of the mid-twentieth century.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06300-x) contains supplementary material, which is available to authorized users.

Bone age for chronological age determination - statement of the European Society of Paediatric Radiology musculoskeletal task force group

Radiologists are sometimes requested to determine a person's age based on skeletal radiographs. Critical reviews demonstrate that this cannot be done with sufficient accuracy with existing methods.

Age assessment by Demirjian's development stages of the third molar: a systematic review

OBJECTIVES

Radiographic evaluation of the wisdom teeth (third molar) formation is a widely used age assessment method for adolescents and young adults. This systematic review examines evidence on the agreement between Demirjian's development stages of the third molar and chronological age.

METHODS

We searched four databases up until May 2016 for studies reporting Demirjian's stages of third molar and confirmed chronological age of healthy individuals aged 10-25 years. Heterogeneity test of the included studies was performed.

RESULTS

We included 21 studies from all continents except Australia, all published after 2005. The mean chronological age for Demirjian's stages varied considerably between studies. The results from most studies were affected by age mimicry bias. Only a few of the studies based their results on an unbiased age structure, which we argue as important to provide an adequate description of the method's ability to estimate age.

CONCLUSION

Observed study variation in the timing of Demirjian's development stages for third molars has often been interpreted as differences between populations and ethnicities. However, we consider age mimicry to be a dominant bias in these studies. Hence, the scientific evidence is insufficient to conclude whether such differences exist.

KEY POINTS

• There is significant heterogeneity between studies evaluating age assessment by Demirjian's third molar development. • Most of the studies were subject to the selection bias age mimicry which can be a source of heterogeneity. • Presence of age mimicry bias makes it impossible to compare and combine results. These biased studies should not be applied as reference studies for age assessment.