Bone Age: A Handy Tool for Pediatric Providers

Automated bone age assessment in a German pediatric cohort: agreement between an artificial intelligence software and the manual Greulich and Pyle method

OBJECTIVES

This study aimed to evaluate the performance of artificial intelligence (AI) software in bone age (BA) assessment, according to the Greulich and Pyle (G&P) method in a German pediatric cohort.

MATERIALS AND METHODS

Hand radiographs of 306 pediatric patients aged 1-18 years (153 boys, 153 girls, 18 patients per year of life)-including a subgroup of patients in the age group for which the software is declared (243 patients)-were analyzed retrospectively. Two pediatric radiologists and one endocrinologist made independent blinded BA reads. Subsequently, AI software estimated BA from the same images. Both agreements, accuracy, and interchangeability between AI and expert readers were assessed.

RESULTS

The mean difference between the average of three expert readers and AI software was 0.39 months with a mean absolute difference (MAD) of 6.8 months (1.73 months for the mean difference and 6.0 months for MAD in the intended use subgroup). Performance in boys was slightly worse than in girls (MAD 6.3 months vs. 5.6 months). Regression analyses showed constant bias (slope of 1.01 with a 95% CI 0.99-1.02). The estimated equivalence index for interchangeability was - 14.3 (95% CI -27.6 to - 1.1).

CONCLUSION

In terms of BA assessment, the new AI software was interchangeable with expert readers using the G&P method.

CLINICAL RELEVANCE STATEMENT

The use of AI software enables every physician to provide expert reader quality in bone age assessment.

KEY POINTS

• A novel artificial intelligence-based software for bone age estimation has not yet been clinically validated. • Artificial intelligence showed a good agreement and high accuracy with expert radiologists performing bone age assessment. • Artificial intelligence showed to be interchangeable with expert readers.

Unsupervised Learning-Based Measurement of Ultrasonic Axial Transmission Velocity in Neonatal Bone

OBJECTIVES

To develop a robust algorithm for estimating ultrasonic axial transmission velocity from neonatal tibial bone, and to investigate the relationships between ultrasound velocity and neonatal anthropometric measurements as well as clinical biochemical markers of skeletal health.

METHODS

This study presents an unsupervised learning approach for the automatic detection of first arrival time and estimation of ultrasonic velocity from axial transmission waveforms, which potentially indicates bone quality. The proposed method combines the ReliefF algorithm and fuzzy C-means clustering. It was first validated using an in vitro dataset measured from a Sawbones phantom. It was subsequently applied on in vivo signals collected from 40 infants, comprising 21 males and 19 females. The extracted neonatal ultrasonic velocity was subjected to statistical analysis to explore correlations with the infants' anthropometric features and biochemical indicators.

RESULTS

The results of in vivo data analysis revealed significant correlations between the extracted ultrasonic velocity and the neonatal anthropometric measurements and biochemical markers. The velocity of first arrival signals showed good associations with body weight (ρ = 0.583, P value <.001), body length (ρ = 0.583, P value <.001), and gestational age (ρ = 0.557, P value <.001).

CONCLUSION

These findings suggest that fuzzy C-means clustering is highly effective in extracting ultrasonic propagating velocity in bone and reliably applicable in in vivo measurement. This work is a preliminary study that holds promise in advancing the development of a standardized ultrasonic tool for assessing neonatal bone health. Such advancements are crucial in the accurate diagnosis of bone growth disorders.

Artificial intelligence model system for bone age assessment of preschool children

BACKGROUD

Our study aimed to assess the impact of inter- and intra-observer variations when utilizing an artificial intelligence (AI) system for bone age assessment (BAA) of preschool children.

METHODS

A retrospective study was conducted involving a total sample of 53 female individuals and 41 male individuals aged 3-6 years in China. Radiographs were assessed by four mid-level radiology reviewers using the TW3 and RUS-CHN methods. Bone age (BA) was analyzed in two separate situations, with/without the assistance of AI. Following a 4-week wash-out period, radiographs were reevaluated in the same manner. Accuracy metrics, the correlation coefficient (ICC)and Bland-Altman plots were employed.

RESULTS

The accuracy of BAA by the reviewers was significantly improved with AI. The results of RMSE and MAE decreased in both methods (p < 0.001). When comparing inter-observer agreement in both methods and intra-observer reproducibility in two interpretations, the ICC results were improved with AI. The ICC values increased in both two interpretations for both methods and exceeded 0.99 with AI.

CONCLUSION

In the assessment of BA for preschool children, AI was found to be capable of reducing inter-observer variability and enhancing intra-observer reproducibility, which can be considered an important tool for clinical work by radiologists.

IMPACT

The RUS-CHN method is a special bone age method devised to be suitable for Chinese children. The preschool stage is a critical phase for children, marked by a high degree of variability that renders BA prediction challenging. The accuracy of BAA by the reviewers can be significantly improved with the aid of an AI model system. This study is the first to assess the impact of inter- and intra-observer variations when utilizing an AI model system for BAA of preschool children using both the TW3 and RUS-CHN methods.

Olecranon bone age assessment in puberty using a lateral elbow radiograph and a deep-learning model

OBJECTIVES

To improve pubertal bone age (BA) evaluation by developing a precise and practical elbow BA classification using the olecranon, and a deep-learning AI model.

MATERIALS AND METHODS

Lateral elbow radiographs taken for BA evaluation in children under 18 years were collected from January 2020 to June 2022, retrospectively. A novel classification and the olecranon BA were established based on the morphological changes in the olecranon ossification process during puberty. The olecranon BA was compared with other elbow and hand BA methods, using intraclass correlation coefficients (ICCs), and a deep-learning AI model was developed.

RESULTS

A total of 3508 lateral elbow radiographs (mean age 9.8 ± 1.8 years) were collected. The olecranon BA showed the highest applicability (100%) and interobserver agreement (ICC 0.993) among elbow BA methods. It showed excellent reliability with Sauvegrain (0.967 in girls, 0.969 in boys) and Dimeglio (0.978 in girls, 0.978 in boys) elbow BA methods, as well as Korean standard (KS) hand BA in boys (0.917), and good reliability with KS in girls (0.896) and Greulich-Pyle (GP)/Tanner-Whitehouse (TW)3 (0.835 in girls, 0.895 in boys) hand BA methods. The AI model for olecranon BA showed an accuracy of 0.96 and a specificity of 0.98 with EfficientDet-b4. External validation showed an accuracy of 0.86 and a specificity of 0.91.

CONCLUSION

The olecranon BA evaluation for puberty, requiring only a lateral elbow radiograph, showed the highest applicability and interobserver agreement, and excellent reliability with other BA evaluation methods, along with a high performance of the AI model.

CLINICAL RELEVANCE STATEMENT

This AI model uses a single lateral elbow radiograph to determine bone age for puberty from the olecranon ossification center and can improve pubertal bone age assessment with the highest applicability and excellent reliability compared to previous methods.

KEY POINTS

Elbow bone age is valuable for pubertal bone age assessment, but conventional methods have limitations. Olecranon bone age and its AI model showed high performances for pubertal bone age assessment. Olecranon bone age system is practical and accurate while requiring only a single lateral elbow radiograph.

An artificial intelligence-based bone age assessment model for Han and Tibetan children

Background: Manual bone age assessment (BAA) is associated with longer interpretation time and higher cost and variability, thus posing challenges in areas with restricted medical facilities, such as the high-altitude Tibetan Plateau. The application of artificial intelligence (AI) for automating BAA could facilitate resolving this issue. This study aimed to develop an AI-based BAA model for Han and Tibetan children. Methods: A model named "EVG-BANet" was trained using three datasets, including the Radiology Society of North America (RSNA) dataset (training set n = 12611, validation set n = 1425, and test set n = 200), the Radiological Hand Pose Estimation (RHPE) dataset (training set n = 5491, validation set n = 713, and test set n = 79), and a self-established local dataset [training set n = 825 and test set n = 351 (Han n = 216 and Tibetan n = 135)]. An open-access state-of-the-art model BoNet was used for comparison. The accuracy and generalizability of the two models were evaluated using the abovementioned three test sets and an external test set (n = 256, all were Tibetan). Mean absolute difference (MAD) and accuracy within 1 year were used as indicators. Bias was evaluated by comparing the MAD between the demographic groups. Results: EVG-BANet outperformed BoNet in the MAD on the RHPE test set (0.52 vs. 0.63 years, p < 0.001), the local test set (0.47 vs. 0.62 years, p < 0.001), and the external test set (0.53 vs. 0.66 years, p < 0.001) and exhibited a comparable MAD on the RSNA test set (0.34 vs. 0.35 years, p = 0.934). EVG-BANet achieved accuracy within 1 year of 97.7% on the local test set (BoNet 90%, p < 0.001) and 89.5% on the external test set (BoNet 85.5%, p = 0.066). EVG-BANet showed no bias in the local test set but exhibited a bias related to chronological age in the external test set. Conclusion: EVG-BANet can accurately predict the bone age (BA) for both Han children and Tibetan children living in the Tibetan Plateau with limited healthcare facilities.

Deeplasia: deep learning for bone age assessment validated on skeletal dysplasias

BACKGROUND

Skeletal dysplasias collectively affect a large number of patients worldwide. Most of these disorders cause growth anomalies. Hence, evaluating skeletal maturity via the determination of bone age (BA) is a useful tool. Moreover, consecutive BA measurements are crucial for monitoring the growth of patients with such disorders, especially for timing hormonal treatment or orthopedic interventions. However, manual BA assessment is time-consuming and suffers from high intra- and inter-rater variability. This is further exacerbated by genetic disorders causing severe skeletal malformations. While numerous approaches to automate BA assessment have been proposed, few are validated for BA assessment on children with skeletal dysplasias.

OBJECTIVE

We present Deeplasia, an open-source prior-free deep-learning approach designed for BA assessment specifically validated on patients with skeletal dysplasias.

MATERIALS AND METHODS

We trained multiple convolutional neural network models under various conditions and selected three to build a precise model ensemble. We utilized the public BA dataset from the Radiological Society of North America (RSNA) consisting of training, validation, and test subsets containing 12,611, 1,425, and 200 hand and wrist radiographs, respectively. For testing the performance of our model ensemble on dysplastic hands, we retrospectively collected 568 radiographs from 189 patients with molecularly confirmed diagnoses of seven different genetic bone disorders including achondroplasia and hypochondroplasia. A subset of the dysplastic cohort (149 images) was used to estimate the test-retest precision of our model ensemble on longitudinal data.

RESULTS

The mean absolute difference of Deeplasia for the RSNA test set (based on the average of six different reference ratings) and dysplastic set (based on the average of two different reference ratings) were 3.87 and 5.84 months, respectively. The test-retest precision of Deeplasia on longitudinal data (2.74 months) is estimated to be similar to a human expert.

CONCLUSION

We demonstrated that Deeplasia is competent in assessing the age and monitoring the development of both normal and dysplastic bones.

Correlations Between Eight Comprehensive Skeletal Maturity Systems in a Modern Peripubertal Pediatric Population

BACKGROUND

Several skeletal maturity systems allow for accurate skeletal age assessment from a wide variety of joints. However, discrepancies in estimates have been noted when applying systems concurrently. The aims of our study were to (1) compare the agreement among 8 different skeletal maturity systems in modern pediatric patients and (2) compare these discrepancy trends qbetween modern and historic children.

METHODS

We performed a retrospective (January 2000 to May 2022) query of our picture archiving and communication systems and included peripubertal patients who had at least two radiographs of different anatomic regions obtained ≤3 months apart for 8 systems: (1) proximal humerus ossification system (PHOS), (2) olecranon apophysis ossification staging system (OAOSS), (3) lateral elbow system, (4) modified Fels wrist system, (5) Sanders Hand Classification, (6) optimized oxford hip system, (7) modified Fels knee system, and (8) calcaneal apophysis ossification staging system (CAOSS). Any abnormal (ie, evidence of fracture or congenital deformity) or low-quality radiographs were excluded. These were compared with a cohort from a historic longitudinal study. SEM skeletal age, representing the variance of skeletal age estimates, was calculated for each system and used to compare system precision.

RESULTS

A total of 700 radiographs from 350 modern patients and 954 radiographs from 66 historic patients were evaluated. In the modern cohort, the greatest variance was seen in PHOS (SEM: 0.28 y), Sanders Hand (0.26 y), and CAOSS (0.25 y). The modified Fels knee system demonstrated the smallest variance (0.20 y). For historic children, the PHOS, OAOSS, and CAOSS were the least precise (0.20 y for all). All other systems performed similarly in historic children with lower SEMs (range: 0.18 to 0.19 y). The lateral elbow system was more precise than the OAOSS in both cohorts.

CONCLUSIONS

The precision of skeletal maturity systems varies across anatomic regions. Staged, single-parameter systems (eg, PHOS, Sanders Hand, OAOSS, and CAOSS) may correlate less with other systems than those with more parameters.

LEVEL OF EVIDENCE

Level III-retrospective study.

Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels

OBJECTIVE

To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model.

MATERIALS AND METHODS

A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model).

RESULTS

Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2.

CONCLUSION

The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.

Magnetic resonance imaging of knees: a novel approach to predict recombinant human growth hormone therapy response in short-stature children in late puberty

BACKGROUND

There is no appropriate tool to predict recombinant human growth hormone (rhGH) response before therapy initiation in short-stature children in late puberty. The current study aimed to explore the associations between magnetic resonance imaging (MRI) stages of the knee growth plates and rhGH response in short-stature children in late puberty.

METHODS

In this prospective cohort study, short-stature children in late puberty were treated with rhGH and followed up for 6 months. We proposed a novel knee MRI staging system according to the growth plate states of distal femurs or proximal tibias and divided the participants into three groups: unclosed growth plate group, marginally closed growth plate group, and nearly closed growth plate group. The primary outcomes were height gain and growth velocity (GV), which were assessed three months later.

RESULTS

Fifty participants were enrolled, including 23 boys and 27 girls. GV and height gain after 6 months of rhGH therapy decreased successively in the three groups with an increased degree of growth plate fusion, especially when grouped by proximal tibias (GV1-3 mon from 9.38 to 6.08 to 4.56 cm/year, GV4-6 mon from 6.75 to 4.92 to 3.25 cm/year, and height gain from 4.03 to 2.75 to 1.95 cm, all P < 0.001). Moreover, the MRI stages of growth plates independently served as a significant variable for GV and height gain after therapy, especially when grouped by proximal tibias (all P < 0.01).

CONCLUSION

The MRI staging method is expected to be an effective tool for predicting rhGH response before therapy initiation in short-stature children in late puberty.

Altered Emotion Perception Linked to Structural Brain Differences in Youth With Congenital Adrenal Hyperplasia

CONTEXT

Congenital adrenal hyperplasia (CAH) is a genetic disorder that results in hormonal imbalances and decreased brain volumes in regions important for emotional processing.

OBJECTIVE

To examine whether emotion perception differs between youth with CAH and control youth, and if these differences relate to brain volumes.

METHODS

In this cross-sectional study of 27 youths with CAH (mean age = 12.63 years, 16 female) and 35 age- and sex-matched controls (mean age = 13.03 years, 20 female), each participant rated picture stimuli and completed a 3T structural brain scan. Valence and arousal ratings and reaction times of 61 affective images were assessed. Gray matter volumes were measured by MRI.

RESULTS

Youth with CAH had lower valence ratings for negative (P = .007) and neutral (P = .019) images. Controls showed differences in reaction times and arousal ratings across stimuli conditions, but youth with CAH did not. Brain volumes of the right amygdala (P = .025) and left hippocampus (P = .002) were associated with valence ratings. Left rostral middle frontal (P < .001) and right medial orbitofrontal cortex (P = .002) volumes were negatively related to valence scores only in youth with CAH, whereas left medial orbitofrontal cortex (P < .001) volumes were associated with valence scores positively in youth with CAH and negatively in controls.

CONCLUSION

Findings suggest that youth with CAH perceive emotive stimuli as more unpleasant. Decreased brain volumes in the amygdala, hippocampus, and prefrontal cortex are associated with these measures of altered emotion perception in youth with CAH.

Applicability of Shoulder, Olecranon, and Wrist-based Skeletal Maturity Estimation Systems to the Modern Pediatric Population

BACKGROUND

The proximal humerus ossification system (PHOS), olecranon apophyseal ossification system (OAOS), and modified Fels wrist skeletal maturity system (mFWS) were recently developed or updated using a historical, mostly White, pediatric population. These upper extremity skeletal maturity systems have demonstrated skeletal age estimation performance superior or equivalent to Greulich and Pyle in historical patients. Their applicability to modern pediatric populations has not yet been evaluated.

METHODS

We reviewed anteroposterior shoulder, lateral elbow, and anteroposterior hand and wrist x-rays of 4 pediatric cohorts: White males, Black males, White females, and Black females. Peripubertal x-rays were evaluated: males 9 to17 years and females 7 to 15 years. Five nonpathologic radiographs for each age and joint were randomly selected from each group. Skeletal age estimates made by each of the 3 skeletal maturity systems were plotted against the chronological age associated with each radiograph and compared between cohorts, and with the historical patients.

RESULTS

Five hundred forty modern radiographs were evaluated (180 shoulders, 180 elbows, and 180 wrists). All radiographic parameters had inter- and intra-rater reliability coefficients at or above 0.79, indicating very good reliability. For PHOS, White males had delayed skeletal age compared with Black males (Δ-0.12 y, P=0.02) and historical males (Δ-0.17 y, P<0.001). Black females were skeletally advanced compared with historical females (Δ0.11 y, P=0.01). For OAOS, White males (Δ-0.31 y, P<0.001) and Black males (Δ-0.24 y, P<0.001) had delayed skeletal age compared with historical males. For mFWS, White males (Δ0.29 y, P=0.024), Black males (Δ0.58 y, P<0.001), and Black females (Δ0.44 y, P<0.001) had advanced skeletal age compared with historical counterparts of the same sex. All other comparisons were not significant (P>0.05).

CONCLUSIONS

The PHOS, OAOS, and mFWS have mild discrepancies in skeletal age estimates when applied to modern pediatric populations depending on the race and sex of the patient.

LEVEL OF EVIDENCE

Level III - retrospective chart review.

The uncovered biases and errors in clinical determination of bone age by using deep learning models

OBJECTIVES

To evaluate AI biases and errors in estimating bone age (BA) by comparing AI and radiologists' clinical determinations of BA.

METHODS

We established three deep learning models from a Chinese private dataset (CHNm), an American public dataset (USAm), and a joint dataset combining the above two datasets (JOIm). The test data CHNt (n = 1246) were labeled by ten senior pediatric radiologists. The effects of data site differences, interpretation bias, and interobserver variability on BA assessment were evaluated. The differences between the AI models' and radiologists' clinical determinations of BA (normal, advanced, and delayed BA groups by using the Brush data) were evaluated by the chi-square test and Kappa values. The heatmaps of CHNm-CHNt were generated by using Grad-CAM.

RESULTS

We obtained an MAD value of 0.42 years on CHNm-CHNt; this result indicated an appropriate accuracy for the whole group but did not indicate an accurate estimation of individual BA because with a kappa value of 0.714, the agreement between AI and human clinical determinations of BA was significantly different. The features of the heatmaps were not fully consistent with the human vision on the X-ray films. Variable performance in BA estimation by different AI models and the disagreement between AI and radiologists' clinical determinations of BA may be caused by data biases, including patients' sex and age, institutions, and radiologists.

CONCLUSIONS

The deep learning models outperform external validation in predicting BA on both internal and joint datasets. However, the biases and errors in the models' clinical determinations of child development should be carefully considered.

KEY POINTS

• With a kappa value of 0.714, clinical determinations of bone age by using AI did not accord well with clinical determinations by radiologists. • Several biases, including patients' sex and age, institutions, and radiologists, may cause variable performance by AI bone age models and disagreement between AI and radiologists' clinical determinations of bone age. • AI heatmaps of bone age were not fully consistent with human vision on X-ray films.

Tanner-Whitehouse skeletal maturity score derived from ultrasound images to evaluate bone age

OBJECTIVE

The complexity of radiographic Tanner-Whitehouse method makes it less acceptable by radiologists and endocrinologists to assess bone age. Conventional ultrasound could be used to measure the ratio of the height of the ossification center to the epiphysis of the bone to evaluate maturity of bone. The purpose of this study is to obtain radiographic TW3 skeletal maturity score with ultrasound images.

METHODS

In this prospective diagnostic study, participants aged between 1 and 18 years undergoing radiography for bone age evaluation were evaluated from April 2019 to November 2021. Ultrasonic skeletal maturity scores of participants were transformed into radiographic skeletal maturity scores with the fitted formulas established in this study. Diagnostic performances of the transformed scores to diagnose advanced or delayed bone age were confirmed. Ultrasound images of 50 participants in the validation group were re-evaluated to confirm inter-rater reliability.

RESULTS

A total of 442 participants (median age, 9.5 years [interquartile range, 7.8-11.1 years]; 185 boys) were enrolled. Ultrasound determination of bone age had a sensitivity of 97% (34/35, 95% CI: 83, 99) and a specificity of 98% (106/108, 95% CI: 93, 99) to diagnose advanced or delayed bone age. The intra-class correlation coefficient for inter-rater reliability was 0.993 [95% CI: 0.988, 0.996], p < 0.0001.

CONCLUSIONS

Radiographic Tanner-Whitehouse skeletal maturity score could be obtained from ultrasound images in a simple, fast, accurate, and radiation-free manner.

KEY POINTS

• The fitting formulas between radiographic TW3 skeletal maturity score and ultrasonic skeletal maturity score were developed. • Through measurement of ossification ratios of bones with ultrasound, TW3 skeletal maturity score was obtained in a simple, fast, and radiation-free manner.

Applicability of the Modified Fels and Optimized Oxford Skeletal Maturity Estimation Systems to the Modern Pediatric Population

BACKGROUND

The recently developed modified Fels knee and optimized Oxford hip skeletal maturity systems (SMS) have demonstrated impressive performance compared with the Greulich and Pyle skeletal age atlas when applied to the same historical, mostly white, pediatric population. We sought to determine whether these 2 systems require modification before being used in modern children.

METHODS

We collected knee and hip radiographs between January 2015 and September 2020 from our electronic medical record from 4 groups of children: (1) white males, (2) black males, (3) white females, and (4) black females. Males between 9 and 17 years and females between 7 and 15 years were included. After reliability analyses, 5 nonpathologic radiographs for each age and joint were randomly selected from each group and evaluated with the appropriate SMS. The mean discrepancy between each group's chronological age at the time of radiograph and estimated skeletal age was compared between our modern cohort and the historical Bolton-Brush children. After normality testing, paired t tests or Wilcoxon signed-rank tests were performed, as appropriate. A Bonferroni correction was applied to address multiple testing.

RESULTS

Three hundred sixty modern radiographs were evaluated (180 knees and 180 hips). All 7 modified Fels knee parameters and all 5 optimized Oxford hip parameters had inter and intrarater reliability coefficients ≥0.7, indicating good to very good reliability. For the modified Fels knee SMS, white males (Δ0.74 y, P <0.001), black males (Δ0.69 y, P <0.001), and black females (Δ0.4 y, P =0.04) had advanced skeletal age compared with their historical counterparts of the same sex. No differences were found between historical and modern patients for the optimized Oxford hip SMS. No differences were found for either SMS comparing modern patients along racial lines ( P >0.05 for all).

CONCLUSIONS

Discrepancies in skeletal age estimates made by the modified Fels knee SMS exist between modern pediatric white males, black males, and black females and their historic counterparts. No differences were found when using optimized Oxford hip SMS. Future studies should evaluate how these translate to clinical decision-making.

LEVEL OF EVIDENCE

Level III; retrospective chart review.

Bone age assessment: Large-scale comparison of Greulich-Pyle method and Tanner-Whitehouse 3 method for Taiwanese children

BACKGROUND

The Greulich-Pyle (GP) and Tanner-Whitehouse 3 (TW3) methods are two common methods for assessing bone age (BA). The applicability of these methods for populations other than those in the United States and Europe has been questioned. Thus, this study tested the applicability of these methods for Taiwanese children.

METHODS

In total, 1476 radiographs (654 boys, 822 girls) were analyzed. A subset of 200 radiographs was evaluated to determine intrarater and interrater reliability and the time required to yield a BA assessment. BA was determined by two reviewers using the GP method and two of the TW3 methods (the Radial-Ulnar-Short bones [RUS] method and the carpals method [Carpal]). The GP and TW3 methods were directly compared using statistical techniques. A subgroup analysis by age was performed to compare BA and chronological age using a paired t test for each age group.

RESULTS

The average times required to yield an assessment using the GP and TW3-RUS methods were 0.79 ± 0.14 and 3.01 ± 0.84 min (p < 0.001), respectively. Both the intrarater and interrater correlation coefficients were higher for the GP method (0.993, 0.992) than the TW3-RUS (0.985, 0.984) and TW3-Carpal (0.981, 0.973) methods. The correlation coefficient for the GP and TW3-RUS methods was highest in the pubertal stage (0.898 for boys and 0.909 for girls). The mean absolute deviations for the GP and TW3-RUS methods in the pubertal stage were 0.468 years (boys) and 0.496 years (girls). Both the GP and TW3-Carpal methods underestimated BA for boys in the prepubertal stage. Both the GP and TW3-RUS methods overestimated BA for girls in the pubertal and postpubertal stages.

CONCLUSION

The GP and TW3-RUS methods exhibit strong agreement in the pubertal and postpubertal stages for both sexes. With appropriate adjustments based on Taiwanese data, both methods are applicable to our children.

A novel approach to radiographic detection of growth development period with hand-wrist radiographs: A preliminary study with ImageJ imaging software

OBJECTIVE

The purpose of this study is to determine whether or not the ImageJ program can be used to automatically determine the growth period of the hand and wrist which have different growth-development periods according to the density values in the phalanges in radiographs.

SETTING AND SAMPLE POPULATION

Our study included hands-wrist radiographs of 270 individuals aged 8-17 years.

MATERIAL AND METHODS

The study's participants were classified into 7 groups according to their skeletal maturation stage (PP2=, MP3=, MP3cap, DP3u, PP3u, MP3u, and Ru) which included pre-peak, peak, and post-peak periods. The total density values (TDV) and pure density values (PDV) in the distal, medial, and proximal phalanges were calculated using each radiograph in the ImageJ program. Analysis of variance (ANOVA) was used to evaluate the density values and chronological age, and pairwise comparisons were made using the post-hoc LSD test.

RESULTS

The total density value was graphically zigzagged in the mesial, distal, and proximal phalanges. However, the pure density value increased continuously until the post-peak period and decreased after the DP3u period until the Ru period. While no significant difference in total density values was observed between the growth periods for all three phalanges, a significant difference in pure density values was observed.

CONCLUSION

It has been demonstrated in the ImageJ program that the peak growth period can be distinguished using the pure density values obtained from all phalanges of the third finger and that this method can be used as an alternative to the growth period detection through artificial intelligence.

Height benefit of GnRH agonists after age 8 in a Portuguese cohort of central precocious puberty

OBJECTIVE

Idiopathic central precocious puberty (iCPP) is common in paediatric endocrinology. Gonadotropin-releasing hormone agonists (GnRHa) are safe, but the effect on final height and the ideal timing for treatment remains controversial. This study aims to assess the effectiveness of GnRHa on growth outcomes in girls with iCPP treated before and after the age of 8 years old.

DESIGN AND PATIENTS

This retrospective longitudinal study evaluated data from Portuguese girls with iCPP who completed treatment between 2010 and 2021.

MEASUREMENTS

Auxological and clinical characteristics were compared according to age at treatment onset.

RESULTS

A cohort of 134 girls with iCPP, was divided into early treatment (ET) (<8 years, n = 48) and later treatment (LT) groups (≥8 years, n = 86). In both groups, most children presented with Tanner II and III. Tanner IV was more frequent in LT group (p = .003). At the end of treatment, predicted adult height increased in both groups (ET p = .032; LT p = .04) and bone age significantly slowed down in all participants (p = .008, p = .034). The height gain was greater in the ET group, but without significant differences (p = .065).

CONCLUSIONS

Treatment with GnRHa improved final height in all girls with iCPP, even when initiated after 8 years. To achieve better outcomes, treatment should be provided promptly after diagnosis.

A real-time automated bone age assessment system based on the RUS-CHN method

BACKGROUND

Bone age is the age of skeletal development and is a direct indicator of physical growth and development in children. Most bone age assessment (BAA) systems use direct regression with the entire hand bone map or first segmenting the region of interest (ROI) using the clinical a priori method and then deriving the bone age based on the characteristics of the ROI, which takes more time and requires more computation.

MATERIALS AND METHODS

Key bone grades and locations were determined using three real-time target detection models and Key Bone Search (KBS) post-processing using the RUS-CHN approach, and then the age of the bones was predicted using a Lightgbm regression model. Intersection over Union (IOU) was used to evaluate the precision of the key bone locations, while the mean absolute error (MAE), the root mean square error (RMSE), and the root mean squared percentage error (RMSPE) were used to evaluate the discrepancy between predicted and true bone age. The model was finally transformed into an Open Neural Network Exchange (ONNX) model and tested for inference speed on the GPU (RTX 3060).

RESULTS

The three real-time models achieved good results with an average (IOU) of no less than 0.9 in all key bones. The most accurate outcomes for the inference results utilizing KBS were a MAE of 0.35 years, a RMSE of 0.46 years, and a RMSPE of 0.11. Using the GPU RTX3060 for inference, the critical bone level and position inference time was 26 ms. The bone age inference time was 2 ms.

CONCLUSIONS

We developed an automated end-to-end BAA system that is based on real-time target detection, obtaining key bone developmental grade and location in a single pass with the aid of KBS, and using Lightgbm to obtain bone age, capable of outputting results in real-time with good accuracy and stability, and able to be used without hand-shaped segmentation. The BAA system automatically implements the entire process of the RUS-CHN method and outputs information on the location and developmental grade of the 13 key bones of the RUS-CHN method along with the bone age to assist the physician in making judgments, making full use of clinical a priori knowledge.

Long-Term Organ Function After HCT for SCD: A Report From the Sickle Cell Transplant Advocacy and Research Alliance

Hematopoietic cell transplantation (HCT) is an established cure for sickle cell disease (SCD) supported by long-term survival, but long-term organ function data are lacking. We sought to describe organ function and assess predictors for dysfunction in a retrospective cohort (n = 247) through the Sickle cell Transplant Advocacy and Research alliance. Patients with <1-year follow-up or graft rejection/second HCT were excluded. Organ function data were collected from last follow-up. Primary measures were organ function, comparing pre- and post-HCT. Bivariable and multivariable analyses were performed for predictors of dysfunction. Median age at HCT was 9.4 years; the majority had HbSS (88.2%) and severe clinical phenotype (65.4%). Most received matched related (76.9%) bone marrow (83.3%) with myeloablative conditioning (MAC; 57.1%). Acute and chronic graft-versus-host disease (GVHD) developed in 24.0% and 24.8%. Thirteen patients (5.3%) died ≥1 year after HCT, primarily from GVHD or infection. More post-HCT patients had low ejection or shortening fractions than pre-HCT (0.6% → 6.0%, P = .007 and 0% → 4.6%, P = .003). The proportion with lung disease remained stable. Eight patients (3.2%) had overt stroke; most had normal (28.3%) or stable (50.3%) brain magnetic resonance imaging. On multivariable analysis, cardiac dysfunction was associated with MAC (odds ratio [OR] = 2.71; 95% confidence interval [CI], 1.09-6.77; P = .033) and severe acute GVHD (OR = 2.41; 95% CI, 1.04-5.62; P = .041). Neurologic events were associated with central nervous system indication (OR = 2.88; 95% CI, 2.00-4.12; P < .001). Overall organ dysfunction was associated with age ≥16 years (OR = 2.26; 95% CI, 1.35-3.78; P = .002) and clinically severe disease (OR = 1.64; 95% CI, 1.02-2.63; P = .043). In conclusion, our results support consideration of HCT at younger age and use of less intense conditioning.

Combined assisted bone age assessment and adult height prediction methods in Chinese girls with early puberty: analysis of three artificial intelligence systems

BACKGROUND

The applicability and accuracy of artificial intelligence (AI)-assisted bone age assessment and adult height prediction methods in girls with early puberty are unknown.

OBJECTIVE

To analyze the performance of AI-assisted bone age assessment methods by comparing the corresponding methods for predicted adult height with actual adult height.

MATERIALS AND METHODS

This retrospective review included 726 girls with early puberty, 87 of whom had reached adult height at last follow-up. Bone age was evaluated using the Greulich-Pyle (GP), Tanner-Whitehouse (TW3-RUS) and China 05 RUS-CHN (RUS-CHN) methods. Predicted adult height was calculated using the China 05 (CH05), TW3 and Bayley-Pinneau (BP) methods.

RESULTS

We analyzed 1,663 left-hand radiographs, including 155 from girls who had reached adult height. In the 6-8- and 9-11-years age groups, bone age differences were smaller than those in the 12-14-years group; however, the differences between predicted adult height and actual adult height were larger than those in the 12-14-years group. TW3 overestimated adult height by 0.4±2.8 cm, while CH05 and BP significantly underestimated adult height by 2.9±3.6 cm and 1.3±3.8 cm, respectively. TW3 yielded the highest proportion of predicted adult height within ±5 cm of actual adult height (92.9%), with the highest correlation between predicted and actual adult heights.

CONCLUSION

The differences in measured bone ages increased with increasing bone age. However, the corresponding method for predicting adult height was more accurate when the bone age was older. TW3 might be more suitable than CH05 and BP for predicting adult height in girls with early puberty. Methods for predicting adult height should be optimized for populations of the same ethnicity and disease.

The diverse pleiotropic effects of spliceosomal protein PUF60: A case series of Verheij syndrome

Verheij syndrome (VRJS) is a rare craniofacial spliceosomopathy presenting with craniofacial dysmorphism, multiple congenital anomalies and variable neurodevelopmental delay. It is caused by single nucleotide variants (SNVs) in PUF60 or interstitial deletions of the 8q24.3 region. PUF60 encodes a splicing factor which forms part of the spliceosome. To date, 36 patients with a sole diagnosis of VRJS due to disease-causing PUF60 SNVs have been reported in peer-reviewed publications. Although the depth of their phenotyping has varied greatly, they exhibit marked phenotypic heterogeneity. We report 10 additional unrelated patients, including the first described patients of Khmer, Indian, and Vietnamese ethnicities, and the eldest patient to date, with 10 heterozygous PUF60 variants identified through exome sequencing, 8 previously unreported. All patients underwent deep phenotyping identifying variable dysmorphism, growth delay, neurodevelopmental delay, and multiple congenital anomalies, including several unique features. The eldest patient is the only reported individual with a germline variant and neither neurodevelopmental delay nor intellectual disability. In combining these detailed phenotypic data with that of previously reported patients (n = 46), we further refine the known frequencies of features associated with VRJS. These include neurodevelopmental delay/intellectual disability (98%), axial skeletal anomalies (74%), appendicular skeletal anomalies (73%), oral anomalies (68%), short stature (66%), cardiac anomalies (63%), brain malformations (48%), hearing loss (46%), microcephaly (41%), colobomata (38%), and other ocular anomalies (65%). This case series, incorporating three patients from previously unreported ethnic backgrounds, further delineates the broad pleiotropy and mutational spectrum of PUF60 pathogenic variants.

Association between phthalate exposure and accelerated bone maturation in Chinese girls with early puberty onset: a propensity score-matched case-control analysis

Estrogen can promote the acceleration of bone maturation and phthalate esters (PAEs) have estrogen-mimicking effects. We investigated whether PAEs are associated with the acceleration of bone age (BA) in girls with early onset of puberty (EOP). This case–control study enrolled 254 girls with EOP from the Endocrinology Department at Shenzhen Children’s Hospital between December 2018 and August 2019. Ultra-performance liquid chromatography and tandem mass spectrometry were used to analyze the 10 metabolites of PAEs (mPAEs) in urine samples. BA was measured using an artificial intelligence system. BA exceeding the chronological age (CA) by > 2 years (BA-CA ≥ 2 years) was referred to as significant BA advancement. Participants were divided into groups A (BA-CA ≥ 2 years; case group) and B (BA-CA < 2 years; control group). Propensity score matching (PSM) was performed for both groups in a 1:2 ratio with a caliper of 0.25. To identify potential dose–response relationships between PAEs exposure and BA advancement, we grouped the participants after PSM according to the tertiles of the mPAE concentrations. After PSM, 31 and 62 girls in groups A and B were selected. The concentration of Mono-ethyl phthalate (MEP) in group A was significantly higher than in group B (11.83 μg/g vs. 7.11 μg/g, P < 0.05); there was no significant difference in the levels of other mPAEs between the groups. The degree of BA advancement and proportion of significantly advanced BA in the lowest, middle, and highest tertiles of the MEP sequentially increased, as well as in the lowest, middle, and highest tertiles of Mono-(2-ethyl-5-carboxypentyl) phthalate; however, these were only statistically different between the highest and lowest MEP tertiles (both P < 0.05). For the remaining mPAEs, differences in the degree of BA advancement among the lowest, middle, and highest tertiles, as well as differences in the proportion of significantly advanced BA among the lowest, middle, and highest tertiles, were not significant (all P > 0.05). Our findings suggested that MEP was positively associated with BA advancement in girls with EOP. Exposure to PAEs may promote accelerated bone maturation.

Using Skeletal Maturity in Pediatric Orthopaedics: A Primer

This article provides researchers with the background and guidance necessary to practically incorporate skeletal maturity estimation into any study of adolescents with imaging of the shoulder, elbow, hand, hip, knee, or foot. It also provides clinicians with a comprehensive, concise synopsis of systems that can be used to estimate skeletal maturity in clinical practice. In the article, we provide a relatively brief overview of each currently available skeletal maturity system that has been validated on a longitudinal dataset. The supplementary files include 2 PowerPoint files for each skeletal maturity system. The first PowerPoint file offers examples and instructions for using each radiographic system. The second PowerPoint file includes 20 graded radiographs that can be used for reliability analyses in the research setting. We have also developed a free mobile application available on the iOS and Android platforms named "What's the Skeletal Maturity?" that allows clinicians to rapidly estimate skeletal maturity on any patient using any commonly obtained orthopaedic radiograph.

Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method

PURPOSE

To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean children using manual and deep learning-based methods.

MATERIALS AND METHODS

We collected 485 hand radiographs of healthy children aged 2-17 years (262 boys) between 2008 and 2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA assessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs. Estimated BA was compared to chronological age (CA) using intraclass correlation (ICC), Bland-Altman analysis, linear regression, mean absolute error, and root mean square error. The proportion of children showing a difference >12 months between the estimated BA and CA was calculated.

RESULTS

CA and all estimated BA showed excellent agreement (ICC ≥0.978, p<0.001) and significant positive linear correlations (R²≥0.935, p<0.001). The estimated BA of all methods showed systematic bias and tended to be lower than CA in younger patients, and higher than CA in older patients (regression slopes ≤-0.11, p<0.001). The mean absolute error of radiologist 1, radiologist 2, original, and modified DLBAA models were 13.09, 13.12, 11.52, and 11.31 months, respectively. The difference between estimated BA and CA was >12 months in 44.3%, 44.5%, 39.2%, and 36.1% for radiologist 1, radiologist 2, original, and modified DLBAA models, respectively.

CONCLUSION

Contemporary healthy Korean children showed different rates of skeletal development than GP standard-BA, and systemic bias should be considered when determining children's skeletal maturation.

Can forensic radiological skeletal age estimation be performed by examining ischiopubic-ilioischial-iliopubic synchondrosis in computed tomography images?

Introduction

In this study, we evaluated whether it is possible to perform forensic radiological skeletal age estimation via radiological examination of the ilioischial, ischiopubic, and iliopubic synchondrosis regions of the pelvis.

Methods

This study was conducted by retrospectively examining the abdominopelvic images of individuals aged 8–16 who had applied to the hospital for any reason without having a chronic disorder and who had undergone computed tomography. Two radiologists retrospectively reviewed the images. The BT images of the pelvis ilioischial, ischiopubic, and iliopubic synchondrosis regions were evaluated as follows: 0: open, 1: semiclosed, and 2: closed. The data were evaluated using the SPSS 17 program.

Results

Two hundred sixty-three children (118 girls and 145 boys) between the ages of 8 and 16 years without any health problems participated. There was a significant difference between the groups for all the evaluated synchondrosis joints in girls and boys (p<0.001 for each group comparison). We observed that ilioischial, ischiopubic, and iliopubic synchondrosis closed earlier in girls than boys. In addition, we found that the joints were closed at the age of 15 and over in boys and at 14 and over in girls.

Discussion

Some studies have previously evaluated synchondrosis by using computed tomography. We showed that forensic radiological skeletal age estimation could be performed by examining ischiopubic-ilioischial-iliopubic synchondrosis in pelvis computed tomography images. The pelvis is more resistant to decay than other parts of the body. Furthermore, pelvis bones can withst and the effects of postmortem animal attacks for a longer period. Therefore, we believe that forensic age estimation can be made on corpses with no extremity, a damaged chest, or whose only pelvic bones are assessable through the method we use.

Conclusion

In our study, the ischiopubic-ilioischial-iliopubic joints were open in those aged nine and under and closed in those aged 15 and above. Ilioischial, ischiopubic, and iliopubic synchondrosis were observed to close earlier in girls than in boys. We consider that our study will be beneficial in the 8-16-year-old age group if used. In addition, our study can be used to determine the radiological bone age in cases with wrist bone abnormalities or wrist amputation.

The Optimized Oxford Hip Skeletal Maturity System Proves Resilient to Rotational Variation

BACKGROUND

The recently described optimized Oxford skeletal maturity system utilizes anteroposterior (AP) hip radiographs to accurately, rapidly, and reliably estimate skeletal maturity. However, in the real-world setting, significant positional variation in AP hip radiographs may influence the accuracy of optimized Oxford skeletal age estimates. We sought to evaluate the consistency of skeletal age estimations using the optimized Oxford system between differently rotated radiographs.

METHODS

Thirty normal computerized tomography scans of males (15 children, 9 to 15 y) and females (15 children, 8 to 14 y) were obtained retrospectively, converted into 3D reconstructions, and then used to produce simulated hip radiographs in five different rotational positions. The optimized Oxford system was applied to the 150 simulated AP hip radiographs (5 differently rotated views of 30 hips) to produce a skeletal age estimate for each.

RESULTS

Rotational position did not have a statistically significant effect on the skeletal age (P=0.84) using 1-way repeated measures analysis of variance. Of the 5 radiographic parameters in the optimized Oxford system, only greater trochanter height showed significant rotational variation after Greenhouse-Geisser correction (F2.58, 74.68=5.98, P<0.001). However, post hoc analyses showed that the greater trochanter height obtained at the most centered position was not different from the other 4 rotational positions (P>0.05 for all).

CONCLUSION

The optimized Oxford skeletal maturity system is resilient to rotational variation. Mildly to moderately rotated radiographs obtained in the modern clinical setting can be used for skeletal age estimation by this method, broadening the clinical usage of this system.

LEVEL OF EVIDENCE

Level III-diagnostic study.

Ultrasonic bone age fractionates cognitive abilities in adolescence

Adolescent development is not only shaped by the mere passing of time and accumulating experience, but it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities. Comparing cognitive performance of female participants with different skeletal maturity we uncover the impact of biological age on both IQ and specific abilities. We find that biological age has a selective effect on abilities: more mature individuals within the same age group have higher working memory capacity and processing speed, while those with higher chronological age have better verbal abilities, independently of their maturity. Based on our findings, bone age is a promising biomarker of adolescent maturity.

Classification of Distal Growth Plate Ossification States of the Radius Bone Using a Dedicated Ultrasound Device and Machine Learning Techniques for Bone Age Assessments

X-ray imaging, based on ionizing radiation, can be used to determine bone age by examining distal growth plate fusion in the ulna and radius bones. Legal age determination approaches based on ultrasound signals exist but are unsuitable to reliably determine bone age. We present a low-cost, mobile system that uses one-dimensional ultrasound radio frequency signals to obtain a robust binary classifier enabling the determination of bone age from data of girls and women aged 9 to 24 years. These data were acquired as part of a clinical study conducted with 148 subjects. Our system detects the presence or absence of the epiphyseal plate by moving ultrasound array transducers along the forearm, measuring reflection and transmission signals. Even though classical digital signal processing methods did not achieve a robust classifier, we achieved an F1 score of approximately 87% for binary classification of completed bone growth with machine learning approaches, such as the gradient boosting machine method CatBoost. We demonstrate that our ultrasound system can classify the fusion of the distal growth plate of the radius bone and the completion of bone growth with high accuracy. We propose a non-ionizing alternative to established X-ray imaging methods for this purpose.

Systematic Isolation of Key Parameters for Estimating Skeletal Maturity on Anteroposterior Wrist Radiographs

BACKGROUND

The ability to make a continuous skeletal maturity estimate from a wrist radiograph would be useful in the treatment of adolescent forearm fractures, scoliosis, and other conditions. We attempted to create a reliable, rapid, and accurate method to do this.

METHODS

Many anteroposterior wrist radiographic parameters from 3 skeletal maturity systems were simplified to 23 based on relevance to the peripubertal age range, univariate correlation with skeletal maturity, and reliability. These 23 parameters were evaluated on serial peripubertal anteroposterior hand-wrist radiographs. We determined the Greulich and Pyle (GP) skeletal age and Sanders hand system (SHS) stage. We used stepwise linear regression and generalized estimating equation (GEE) procedures to identify important radiographic and demographic parameters for estimating skeletal maturity, creating the "Modified Fels wrist skeletal maturity system." Its accuracy predicting skeletal maturity was evaluated and compared with that of 4 other systems: (1) GP system, (2) SHS, (3) GP parameters along with age and sex, and (4) SHS parameters along with age and sex.

RESULTS

Three hundred and seventy-two radiographs of 42 girls (age range, 7 to 15 years) and 38 boys (age range, 9 to 16 years) were included. Fifteen radiographic parameters were excluded from the Modified Fels wrist system by stepwise regression and GEE analyses, leaving age, sex, and 8 radiographic parameters in the final model. Use of the Modified Fels wrist system resulted in more accurate skeletal maturity estimations (0.34-year mean discrepancy with actual skeletal maturity) than all other systems (p < 0.001 for all). The Modified Fels wrist system had a similar rate of outlier skeletal maturity estimations as the age, sex, and SHS model (1.9% versus 3.5%, p = 0.11) and fewer outliers than all other systems (p < 0.05 for all).

CONCLUSIONS

A system that included demographic factors and 8 anteroposterior wrist radiographic parameters estimates skeletal maturity more accurately than the 2 most-used skeletal maturity systems in the United States.

CLINICAL RELEVANCE

The Modified Fels wrist skeletal maturity system may allow for more accurate, reliable, and rapid skeletal maturity estimation than current systems, and also may be used when treating adolescent forearm fractures as it does not require imaging past the metacarpals.

LEVEL OF EVIDENCE

Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Forensic bone age estimation of adolescent pelvis X-rays based on two-stage convolutional neural network

In the forensic estimation of bone age, the pelvis is important for identifying the bone age of teenagers. However, studies on this topic remain insufficient as a result of lower accuracy due to the overlapping of pelvic organs in X-ray images. Segmentation networks have been used to automate the location of key pelvic areas and minimize restrictions like doubling images of pelvic organs to increase the accuracy of estimation. This study conducted a retrospective analysis of 2164 pelvis X-ray images of Chinese Han teenagers ranging from 11 to 21 years old. Key areas of the pelvis were detected with a U-Net segmentation network, and the findings were combined with the original X-ray image for regional augmentation. Bone age estimation was conducted with the enhanced and not enhanced pelvis X-ray images by separately using three convolutional neural networks (CNNs). The root mean square errors (RMSE) of the Inception-V3, Inception-ResNet-V2, and VGG19 convolutional neural networks were 0.93 years, 1.12 years, and 1.14 years, respectively, and the mean absolute errors (MAE) of these networks were 0.67 years, 0.77 years, and 0.88 years, respectively. For comparison, a network without segmentation was employed to conduct the estimation, and it was found that the RMSE of the three CNNs above became 1.22 years, 1.25 years, and 1.63 years, respectively, and the MAE became 0.93 years, 0.96 years, and 1.23 years. Bland-Altman plots and attention maps were also generated to provide a visual comparison. The proposed segmentation network can be used to reduce the influence of restrictions like image overlapping of organs and can thus increase the accuracy of pelvic bone age estimation.

Difference between bone age at the hand and elbow at the onset of puberty

In the pubertal period, bone age advances rapidly in conjunction with growth spurts. Precise bone-age assessments in this period are important, but results from the hand and elbow can be different. We aimed to compare the bone age between the hand and elbow around puberty onset and to elucidate the chronological age confirming puberty onset according to elbow-based bone age.A total of 211 peripubertal subjects (127 boys and 84 girls) who underwent hand and elbow radiographs within 2 months was enrolled. Two radiologists and a pediatric orthopedic surgeon assessed bone age. Hand bone age was graded using the Greulich-Pyle (GP) method, and elbow bone age was determined using the Sauvegrain method. The correlation of 2 methods was evaluated by Demining regression analysis, and the mean absolute difference (MAD) with chronological age was compared between pre-pubertal and pubertal subjects. Receiver-operating characteristic curve analysis was performed to determine the chronological age confirming puberty onset.There was a statistically significant difference in bone age revealed by the GP and Sauvegrain methods in the pubertal group. In the pubertal group, the MAD was 1.26 ± 0.90 years with the GP method and 0.61 ± 0.47 years with the Sauvegrain method in boys (P < .001), while in girls, the MAD was 0.84 ± 0.60 years and 0.53 ± 0.36 years with the same 2 methods (P = .033). The chronological age for confirming puberty onset using the elbow was 12.2 years in boys and 10.3 years in girls.The bone ages of hand and elbow were different at puberty, and the elbow was a more reliable location for bone-age assessment at puberty. Puberty onset according to elbow occurred slightly earlier than expected.

Clinical application of artificial intelligence in longitudinal image analysis of bone age among GHD patients

OBJECTIVE

This study aims to explore the clinical value of artificial intelligence (AI)-assisted bone age assessment (BAA) among children with growth hormone deficiency (GHD).

METHODS

A total of 290 bone age (BA) radiographs were collected from 52 children who participated in the study at Sun Yat-sen Memorial Hospital between January 2016 and August 2017. Senior pediatric endocrinologists independently evaluated BA according to the China 05 (CH05) method, and their consistent results were regarded as the gold standard (GS). Meanwhile, two junior pediatric endocrinologists were asked to assessed BA both with and without assistance from the AI-based BA evaluation system. Six months later, around 20% of the images assessed by the junior pediatric endocrinologists were randomly selected to be re-evaluated with the same procedure half a year later. Root mean square error (RMSE), mean absolute error (MAE), accuracy, and Bland-Altman plots were used to compare differences in BA. The intra-class correlation coefficient (ICC) and one-way repeated ANOVA were used to assess inter- and intra-observer variabilities in BAA. A boxplot of BA evaluated by different raters during the course of treatment and a mixed linear model were used to illustrate inter-rater effect over time.

RESULTS

A total of 52 children with GHD were included, with mean chronological age and BA by GS of 6.64 ± 2.49 and 5.85 ± 2.30 years at baseline, respectively. After incorporating AI assistance, the performance of the junior pediatric endocrinologists improved (P < 0.001), with MAE and RMSE both decreased by more than 1.65 years (Rater 1: ΔMAE = 1.780, ΔRMSE = 1.655; Rater 2: ΔMAE = 1.794, ΔRMSE = 1.719), and accuracy increasing from approximately 10% to over 91%. The ICC also increased from 0.951 to 0.990. During GHD treatment (at baseline, 6-, 12-, 18-, and 24-months), the difference decreased sharply when AI was applied. Furthermore, a significant inter-rater effect (P = 0.002) also vanished upon AI involvement.

CONCLUSION

AI-assisted interpretation of BA can improve accuracy and decrease variability in results among junior pediatric endocrinologists in longitudinal cohort studies, which shows potential for further clinical application.

A comparative study of three bone age assessment methods on Chinese preschool-aged children

BACKGROUND

Bone age assessment (BAA) is an essential tool utilized in outpatient pediatric clinics. Three major BAA methods, Greulich-Pyle (GP), Tanner-Whitehouse 3 (TW3), and China 05 RUS-CHN (RUS-CHN), were applied to comprehensively compare bone age (BA) and chronological age (CA) in a Chinese sample of preschool children. This study was designed to determine the most reliable method.

METHODS

The BAA sample consisted of 207 females and 183 males aged 3-6 years from the Zhejiang Province in China. The radiographs were estimated according to the GP, TW3, and RUS-CHN methods by two pediatric radiologists. The data was analyzed statistically using boxplots, the Wilcoxon rank test, and Student's t-test to explore the difference (D) between BA and CA.

RESULTS

According to the distributions of D, the boxplots showed that the median D of the TW3 method was close to zero for both male and female subjects. The TW3 and RUS-CHN methods overestimated the age of both genders. The TW3 method had the highest correct classification rate for males but a similar rate for females. The GP method did not show any significant difference between the BA and CA when applied to 3-year-old males and 4-year-old females while the TW3 method showed similar results when applied to 6-year-old females. The RUS-CHN method showed the least consistent results among the three methods.

CONCLUSION

The TW3 method was superior to the GP and RUS-CHN methods but not reliable on its own. It should be noted that a precise age diagnosis for preschool children cannot be easily made if only one of the methods is utilized. Therefore, it is advantageous to combine multiple methods when assessing bone age.

Case report: 11-ketotestosterone may potentiate advanced bone age as seen in some cases of Wiedemann-Steiner Syndrome

CONTEXT

Wiedemann-Steiner Syndrome (WSS) is a genetic disorder associated with an array of clinical phenotypes, including advanced bone age and short stature. 11-ketotestosterone (11KT) is a member of the group known as 11-oxygenated C19 androgens that are implicated in premature adrenarche.

CASE DESCRIPTION

Case 1: The patient is a 3 year and 11-month-old female diagnosed with WSS due to deletion of KMT2A detected on CGH microarray. At two years and 11 months, imaging revealed an advanced bone age. We obtained an 11KT level on this patient. 11KT in case 1 was elevated at 26.3 ng/dL, while the normal reference range is 7.3-10.9 ng/dL and the reference interval for premature adrenarche is 12.3-22.9 ng/dL, The repeat 11KT at follow up (chronological age 4 years and 6 months) was still elevated at 33.8 ng/dL Case 2: A second child with WSS and a 5kb intragenic KMT2A deletion was evaluated at 11 months of age; his 11KT was 4.5 ng/dL.

CONCLUSIONS

The elevated 11KT may indicate maturational changes related to increasing adrenal gland androgenic activation and may explain the advanced bone age seen in some patients with WSS. To our knowledge, this is the first case report that describes 11KT as a bioactive androgen potentially causing bone age advancement in WSS. Lack of elevation of 11KT in the second child who is an infant suggests increasing androgenic precursors and metabolites related to premature adrenarche may need to be longitudinally followed.

Artificial Intelligence-Assisted Bone Age Assessment to Improve the Accuracy and Consistency of Physicians With Different Levels of Experience

BACKGROUND

The accuracy and consistency of bone age assessments (BAA) using standard methods can vary with physicians' level of experience.

METHODS

To assess the impact of information from an artificial intelligence (AI) deep learning convolutional neural network (CNN) model on BAA, specialists with different levels of experience (junior, mid-level, and senior) assessed radiographs from 316 children aged 4-18 years that had been randomly divided into two equal sets-group A and group B. Bone age (BA) was assessed independently by each specialist without additional information (group A) and with information from the model (group B). With the mean assessment of four experts as the reference standard, mean absolute error (MAE), and intraclass correlation coefficient (ICC) were calculated to evaluate accuracy and consistency. Individual assessments of 13 bones (radius, ulna, and short bones) were also compared between group A and group B with the rank-sum test.

RESULTS

The accuracies of senior, mid-level, and junior physicians were significantly better (all P < 0.001) with AI assistance (MAEs 0.325, 0.344, and 0.370, respectively) than without AI assistance (MAEs 0.403, 0.469, and 0.755, respectively). Moreover, for senior, mid-level, and junior physicians, consistency was significantly higher (all P < 0.001) with AI assistance (ICCs 0.996, 0.996, and 0.992, respectively) than without AI assistance (ICCs 0.987, 0.989, and 0.941, respectively). For all levels of experience, accuracy with AI assistance was significantly better than accuracy without AI assistance for assessments of the first and fifth proximal phalanges.

CONCLUSIONS

Information from an AI model improves both the accuracy and the consistency of bone age assessments for physicians of all levels of experience. The first and fifth proximal phalanges are difficult to assess, and they should be paid more attention.

White Matter Microstructural Differences in Youth With Classical Congenital Adrenal Hyperplasia

CONTEXT

Gray matter morphology in the prefrontal cortex and subcortical regions, including the hippocampus and amygdala, are affected in youth with classical congenital adrenal hyperplasia (CAH). It remains unclear if white matter connecting these aforementioned brain regions is compromised in youth with CAH.

OBJECTIVE

To examine brain white matter microstructure in youth with CAH compared to controls.

DESIGN

A cross-sectional sample of 23 youths with CAH due to 21-hydroxylase deficiency (12.9 ± 3.5 year; 61% female) and 33 healthy controls (13.1 ± 2.8 year; 61% female) with 3T multishell diffusion-weighted magnetic resonance brain scans.

MAIN OUTCOME MEASURES

Complementary modeling approaches, including diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), to examine in vivo white matter microstructure in six white matter tracts that innervate the prefrontal and subcortical regions.

RESULTS

DTI showed CAH youth had lower fractional anisotropy in both the fornix and stria terminalis and higher mean diffusivity in the fornix compared to controls. NODDI modeling revealed that CAH youth have a significantly higher orientation dispersion index in the stria terminalis compared to controls. White matter microstructural integrity was associated with smaller hippocampal and amygdala volumes in CAH youth.

CONCLUSIONS

These patterns of microstructure reflect less restricted water diffusion likely due to less coherency in oriented microstructure. These results suggest that white matter microstructural integrity in the fornix and stria terminalis is compromised and may be an additional related brain phenotype alongside affected hippocampus and amygdala neurocircuitry in individuals with CAH.

Skeletal Maturity Using Knee X-rays: Understanding the Resilience of 7 Radiographic Parameters to Rotational Position

BACKGROUND

Recently, a skeletal maturity system using knee radiographs, named the modified Roche-Wainer-Thissen (RWT) system, has been developed using 7 discrete radiographic parameters. While the system has been shown to significantly outperform the Greulich and Pyle atlas, the effect of rotational variation of the knee radiograph on skeletal maturity determinations has not been studied.

METHODS

Normal knee computed tomography scans of 12 male children ages 10 to 16 years and 8 female children ages 8 to 14 years were obtained retrospectively, converted into 3-dimensional reconstructions, and then used to simulate knee radiographs in 5 different rotational positions. Images were graded using the modified RWT system, and 1-way repeated measures analysis of variance was used to compare skeletal age in the patella centered view versus the other positions. We next retrospectively found 85 pediatric patients with both bilateral standing anteroposterior hip to ankles and separate knee radiograph within 6 months of each other. The skeletal maturity values from the 2 different radiographs were compared in 39 males between the ages of 10 and 16 years and 46 females between 8 and 14 years of age using paired t test and Wilcoxon-signed rank test.

RESULTS

On the computed tomography scan-based images, there was no statistically significant effect of rotational position on the modified RWT score using repeat measures analysis of variance (P=0.210). Only the width ratio of the tibial epiphysis and metaphysis and the width ratio of the fibular epiphysis and metaphysis were statistically different between rotational positions (P<0.05). Comparing clinical full length versus knee radiographs, we found a small difference of 0.069 years which trended towards a statistically significant difference (P=0.009).

CONCLUSIONS

This retrospective study supports the resilience of the RWT model to rotational variation, reassuring clinicians that bone age estimation can be performed in a slightly rotated knee x-ray within a reasonable margin of error. These results can minimize the number of radiographs needed to assess skeletal maturity limiting radiation exposure and expedite clinical flow.

LEVEL OF EVIDENCE

Level-III-diagnostic study.

Estimating Skeletal Maturity Using Knee Radiographs During Preadolescence: The Epiphyseal:Metaphyseal Ratio

BACKGROUND

Though skeletal maturity is most relevant during adolescence, it has utility in treatment of younger patients in some circumstances. Accurate estimation of skeletal maturity using knee radiographs would be useful when treating limb length discrepancy and other general medical conditions in preadolescent patients. Currently, a quick, accurate, and reproducible method of estimating skeletal maturity in preadolescents is lacking.

METHODS

Serial anteroposterior knee radiographs taken at historical growth study visits leading up to the chronological age associated with 90% of final height (an enhanced skeletal maturity standard as compared with peak height velocity) were analyzed in 75 children. Epiphyseal and metaphyseal widths of the distal femur, proximal tibia, and proximal fibula were measured and the epiphyseal:metaphyseal ratio was calculated. Greulich and Pyle (GP) bone ages were also assigned by an experienced pediatric endocrinologist using left hand radiographs. Stepwise linear regression and generalized estimating equation analyses were used to make a skeletal maturity model incorporating demographics (age+sex) and knee epiphyseal:metaphyseal ratios.

RESULTS

A total of 258 left knee radiographs from 39 girls (mean age 8.6 y, range: 2.9 to 13 y) and 36 boys (mean age 10.6 y, range: 3.8 to 15 y) were included. The demographics+ratios model had similar prediction accuracy (0.49 vs. 0.48 y, P=0.84) and rate of outliers (11% vs. 9%, P=0.11) as the demographics+GP model. The demographics+ratios model outperformed all other models evaluated, including a demographics-only model (P<0.001 for all).

CONCLUSIONS

When combined with chronological age and sex, epiphyseal:metaphyseal ratio measurement in the knee allows for skeletal maturity estimation comparable to using the GP technique.

CLINICAL RELEVANCE

We have defined a knee skeletal maturity system that could be applied in treatment of orthopaedic conditions in preadolescents where a knee radiograph is already obtained, avoiding the need for an additional hand radiograph.

A Polygenic Risk Score to Predict Future Adult Short Stature Among Children

CONTEXT

Adult height is highly heritable, yet no genetic predictor has demonstrated clinical utility compared to mid-parental height.

OBJECTIVE

To develop a polygenic risk score for adult height and evaluate its clinical utility.

DESIGN

A polygenic risk score was constructed based on meta-analysis of genomewide association studies and evaluated on the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.

SUBJECTS

Participants included 442 599 genotyped White British individuals in the UK Biobank and 941 genotyped child-parent trios of European ancestry in the ALSPAC cohort.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Standing height was measured using stadiometer; Standing height 2 SDs below the sex-specific population average was considered as short stature.

RESULTS

Combined with sex, a polygenic risk score captured 71.1% of the total variance in adult height in the UK Biobank. In the ALSPAC cohort, the polygenic risk score was able to identify children who developed adulthood short stature with an area under the receiver operating characteristic curve (AUROC) of 0.84, which is close to that of mid-parental height. Combining this polygenic risk score with mid-parental height or only one of the child's parent's height could improve the AUROC to at most 0.90. The polygenic risk score could also substitute mid-parental height in age-specific Khamis-Roche height predictors and achieve an equally strong discriminative power in identifying children with a short stature in adulthood.

CONCLUSIONS

A polygenic risk score could be considered as an alternative or adjunct to mid-parental height to improve screening for children at risk of developing short stature in adulthood in European ancestry populations.

Statistical Confirmation of a Method of US Determination of Bone Age

Background There is limited literature on conventional US to assess bone age. Purpose To determine the diagnostic performance of US in the assessment of abnormal bone age in Chinese children. Materials and Methods In this prospective study, children and young adults aged between birth and 19 years from a large provincial teaching hospital were enrolled from January to November 2020. Children without clinical diseases potentially affecting skeletal growth were included in the normal-value group. Children with clinically suspected growth disturbances who were undergoing bone age evaluation were included in the validation group. Ossification ratios (ie, the ratio of the height of the epiphyseal ossification center to the entire epiphysis, including the cartilaginous component) of the radius, ulna, and femur from all the children were measured using US. Ultrasonic skeletal maturity scores (ie, the summation of ossification ratios of the radius, ulna, and femur multiplied by 100) collected from children in the normal-value group were used for score-for-age curve fitting through Box-Cox power exponential distribution. Test performance characteristics for the ability of US to help diagnose abnormal bone age were determined using radiographic bone age as a reference standard. Statistically significant difference between groups was determined by using a paired-sample t test. Results A total of 1089 children (median age, 9 years [interquartile range, 3-14 years]; 578 boys) were enrolled, including 929 children (mean age, 8 years [interquartile range, 4-12 years]; 515 boys) in the normal-value group and 160 children (mean age, 9 years [interquartile range, 7-11 years]; 63 boys) in the validation group. Ultrasonic bone ages in the validation group were evaluated with use of the lists of normal score-for-age values. With radiographic bone age as a reference standard, US could help diagnose abnormal bone age with high sensitivity (93% [14 of 15 participants; 95% CI: 66, 100] for boys, 100% [14 of 14 participants; 95% CI: 73, 100] for girls) and specificity (98% [47 of 48 participants; 95% CI: 88, 100] for boys, 98% [81 of 83 participants; 95% CI: 91, 100] for girls). Conclusion The US scoring system established can be used to evaluate bone age with high sensitivity and specificity. Clinical trial registration no. ChiCTR1900027917 © RSNA, 2021 Online supplemental material is available for this article.

The NIMH Intramural Longitudinal Study of the Endocrine and Neurobiological Events Accompanying Puberty: Protocol and rationale for methods and measures

Delineating the relationship between human neurodevelopment and the maturation of the hypothalamic-pituitary-gonadal (HPG) axis during puberty is critical for investigating the increase in vulnerability to neuropsychiatric disorders that is well documented during this period. Preclinical research demonstrates a clear association between gonadal production of sex steroids and neurodevelopment; however, identifying similar associations in humans has been complicated by confounding variables (such as age) and the coactivation of two additional endocrine systems (the adrenal androgenic system and the somatotropic growth axis) and requires further elucidation. In this paper, we present the design of, and preliminary observations from, the ongoing NIMH Intramural Longitudinal Study of the Endocrine and Neurobiological Events Accompanying Puberty. The aim of this study is to directly examine how the increase in sex steroid hormone production following activation of the HPG-axis (i.e., gonadarche) impacts neurodevelopment, and, additionally, to determine how gonadal development and maturation is associated with longitudinal changes in brain structure and function in boys and girls. To disentangle the effects of sex steroids from those of age and other endocrine events on brain development, our study design includes 1) selection criteria that establish a well-characterized baseline cohort of healthy 8-year-old children prior to the onset of puberty (e.g., prior to puberty-related sex steroid hormone production); 2) temporally dense longitudinal, repeated-measures sampling of typically developing children at 8-10 month intervals over a 10-year period between the ages of eight and 18; 3) contemporaneous collection of endocrine and other measures of gonadal, adrenal, and growth axis function at each timepoint; and 4) collection of multimodal neuroimaging measures at these same timepoints, including brain structure (gray and white matter volume, cortical thickness and area, white matter integrity, myelination) and function (reward processing, emotional processing, inhibition/impulsivity, working memory, resting-state network connectivity, regional cerebral blood flow). This report of our ongoing longitudinal study 1) provides a comprehensive review of the endocrine events of puberty; 2) details our overall study design; 3) presents our selection criteria for study entry (e.g., well-characterized prepubertal baseline) along with the endocrinological considerations and guiding principles that underlie these criteria; 4) describes our longitudinal outcome measures and how they specifically relate to investigating the effects of gonadal development on brain development; and 5) documents patterns of fMRI activation and resting-state networks from an early, representative subsample of our cohort of prepubertal 8-year-old children.

Assessment of skeletal age in youth female soccer players: Agreement between Greulich-Pyle and Fels protocols

OBJECTIVE

The purpose of the study was to evaluate the agreement between the Fels and Greulich-Pyle methods for the assessment of skeletal age (SA) in female youth soccer players.

METHODS

The sample included 441 Portuguese players 10.08-16.73 years of age who regularly participated in organized and competitive soccer. Standardized radiographs of the left hand-wrist were obtained and analyzed by an experienced examiner. SA was estimated with the Fels and Greulich-Pyle (GP) methods. Differences between SA and chronological age (CA) were used to define skeletal maturity groups: late, average and early maturing. In addition to descriptive statistics, Cohen's kappa and Lin concordance correlation coefficients were used to evaluate agreement between methods.

RESULTS

Intraindividual differences in SA based on the two methods varied between 0.10 to 1.47 years among age groups with larger mean differences at older ages. Agreement of maturity classifications between methods was 74% at younger ages (under-13: kappa = 0.48; under-14: kappa = 0.39; Lin CCC = 0.68) and declined with increasing CA (under-17: 19% agreement; kappa = 0.001; Lin CCC = 0.11). About 19% of the total sample was skeletally mature with the Fels method and an SA was not assigned; in contrast, no players were skeletally mature with the GP method.

CONCLUSIONS

GP SAs were systematically lower than Fels SAs among female soccer players. Intraindividual variability in SAs between methods was considerable. The findings highlight the impact of method on estimates of maturity status.

Bone age is not just for kids

More informed discussions between physicians and older adults about the consequences of an initial osteoporotic fracture could encourage more patients to consider treatments that protect against future fracture.

The epiphyseal secondary ossification center: Evolution, development and function

Bone age is used widely by pediatricians to assess the skeletal maturity of a child and predict growth potential. This entails measuring the size of secondary ossification centers (SOCs), which develop with age in the ends of long bones, which are initially cartilaginous. However, little is presently known about the developmental biology, evolution and functional role of these skeletal elements. Here, we summarize the knowledge currently available in this area and discuss potential primary functions of the SOC.

Carpal Bone Segmentation Using Fully Convolutional Neural Network

BACKGROUND

Bone Age Assessment (BAA) refers to a clinical procedure that aims to identify a discrepancy between biological and chronological age of an individual by assessing the bone age growth. Currently, there are two main methods of executing BAA which are known as Greulich-Pyle and Tanner-Whitehouse techniques. Both techniques involve a manual and qualitative assessment of hand and wrist radiographs, resulting in intra and inter-operator variability accuracy and time-consuming. An automatic segmentation can be applied to the radiographs, providing the physician with more accurate delineation of the carpal bone and accurate quantitative analysis.

METHODS

In this study, we proposed an image feature extraction technique based on image segmentation with the fully convolutional neural network with eight stride pixel (FCN-8). A total of 290 radiographic images including both female and the male subject of age ranging from 0 to 18 were manually segmented and trained using FCN-8.

RESULTS AND CONCLUSION

The results exhibit a high training accuracy value of 99.68% and a loss rate of 0.008619 for 50 epochs of training. The experiments compared 58 images against the gold standard ground truth images. The accuracy of our fully automated segmentation technique is 0.78 ± 0.06, 1.56 ±0.30 mm and 98.02% in terms of Dice Coefficient, Hausdorff Distance, and overall qualitative carpal recognition accuracy, respectively.

Accelerated skeletal maturation is associated with overweight and obesity as early as preschool age: a cross-sectional study

Background

Body mass index (BMI) and skeletal age (SA) are important indicators of individual growth and maturation. Although the results have not been unified, most studies indicated that accelerated skeletal maturation is associated with overweight/obesity. However, there have so far been insufficient studies about the association between accelerated skeletal maturation and overweight/obesity in preschoolers, particularly Asian children. A cross-sectional study was conducted on Chinese children to verify the association between accelerated skeletal maturation and overweight/obesity at preschool age.

Methods

The study involved 1330 participants aged 3.1–6.6 years old (730 males and 600 females) in Shanghai, China. The skeletal age was determined according to the method of TW3-C RUS. Accelerated skeletal maturation was defined as relative SA (SA minus chronological age [CA]) ≥1.0 years. BMI was classified as thinness, normal weight, overweight, and obesity according to the International Obesity Task Force (IOTF) BMI cut-offs. The Chi-square was performed to determine the statistically significant difference in the frequency of accelerated skeletal maturation in BMI and age categories. The logistic regression model analyzed the association between accelerated skeletal maturation and overweight/obesity.

Results

The percentage of accelerated skeletal maturation increased with BMI (7.8% of children in thinness group had accelerated skeletal maturation; the percentage increased to 30.8% in obese group. x² = 89.442, df = 3, P < 0.01) and age group (at age 3.5, 3.5% of participants had accelerated skeletal maturation; at age 6.0 years, this increased to 27.8%. x² = 43.417, df = 5, P < 0.01). Logistic regression analysis showed that children with overweight and obesity are more likely to have accelerated skeletal maturation than children with normal weight after adjusting for gender and age (Overweight, odds ratio [OR] = 3.27, 95% confidence interval [CI]: 2.20–4.87; Obese, OR = 4.73, 95% CI: 2.99–7.48).

Conclusions

There is an association between accelerated skeletal maturation and overweight/obesity among preschool children. This study suggests that accelerated skeletal maturation might coexist with overweight/obesity in preschool children, and interventions, such as dietary modifications and increasing levels of physical activity, should be employed to prevent both accelerated skeletal maturation and overweight/obesity as early as preschool age.