Bone age assessment by dual-energy X-ray absorptiometry in children: an alternative for X-ray?

Fat-free mass predictive equation using bioelectrical impedance and maturity offset in adolescent athletes: Development and cross-validation

OBJECTIVES

This is a cross-sectional study, aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using single-frequency bioelectrical impedance (BIA), considering the predicted age at peak height velocity (PHV) as a variable. Additionally, the study aims to test the FFM-BIA obtained using a previous predictive equation that used skeletal maturity as a variable.

METHOD

The participants (n = 169 male adolescent athletes) were randomly divided into two groups: development of a new predictive equation (n = 113), and cross-validation (n = 56). The concordance test between the FFM values obtained by Koury et al. predictive equation and DXA data was determined (n = 169). Bioelectrical data was obtained using a single-frequency analyzer.

RESULTS

Among the models tested, the new predictive equation has resistance index (height2/resistance) and predictive age at PHV as variables and presented R2 = 0.918. The frequency of maturity status using skeletal maturity and PHV diagnosis was inadequate (Kappa = 0.4257; 95%CI = 0.298-0.553). Bland-Altman plots and concordance correlation coefficient showed substantial concordance between the FFM-DXA values (48.8 ± 11.2 kg) and the new predictive equation (CCC = 0.960). The results showed that the new equation performed better than the equation developed by Koury et al. (CCC = 0.901).

CONCLUSIONS

Our results show that it is feasible to predict FFM in male adolescent athletes using predictive age at PHV, with moderate concordance. The calculation of FFM using more economical and less complex variables is viable and should be further explored.

Bone health index in the assessment of bone health: The Generation R Study

Bone Health Index (BHI) has been proposed as a useful instrument for assessing bone health in children. However, its relationship with fracture risk remains unknown. We aimed to investigate whether BHI is associated with bone mineral density (BMD) and prevalent fracture odds in children from the Generation R Study. We also implemented genome-wide association study (GWAS) and polygenic score (PGS) approaches to improve our understanding of BHI and its potential. In total, 4150 children (49.4 % boys; aged 9.8 years) with genotyped data and bone assessments were included in this study. BMD was measured across the total body (less head following ISCD guidelines) using a GE-Lunar iDXA densitometer; and BHI was determined from the hand DXA scans using BoneXpert®. Fractures were self-reported collected with home questionnaires. The association of BHI with BMD and fractures was evaluated using linear models corrected for age, sex, ethnicity, height, and weight. We observed a positive correlation between BHI and BMD (ρ = 0.32, p-value<0.0001). Further, every SD decrease in BHI was associated with an 11 % increased risk of prevalent fractures (OR:1.11, 95 % CI 1.00-1.24, p-value = 0.05). Our BHI GWAS identified variants (lead SNP rs1404264-A, p-value = 2.61 × 10-14) mapping to the ING3/CPED1/WNT16 locus. Children in the extreme tails of the BMD PGS presented a difference in BHI values of -0.10 standard deviations (95% CI -0.14 to -0.07; p-value<0.0001). On top of the demonstrated epidemiological association of BHI with both BMD and fracture risk, our results reveal a partially shared biological background between BHI and BMD. These findings highlight the potential value of using BHI to screen children at risk of fracture.

Bone Age Reading by DXA Images should not Replace Bone Age Reading by X-ray Images

X-ray image of the hand is the most used technique to estimate bone age in children. For the analysis of bone mineral density using DXA in children, bone age may help to adjust such measurement in some cases. During image acquisition in DXA, an anteroposterior image of the hand may be acquired and used to evaluate bone age but few studies have evaluated the agreement between conventional X-ray and DXA images. The aim of the study was to determine bone age estimation agreement between conventional X-ray images and DXA in children and adolescents aged 5 to 16 years of age. We performed an analytical cross-sectional study of 711 healthy subjects. Subject´s bone age, both in conventional X-ray, and DXA images were read independently by two expert evaluators blinded for chronological age. Intraobserver and inter-observer reproducibility were evaluated using Intraclass Correlation Coefficient (ICC), and the agreement between bone age estimations made by both evaluators was analyzed using ICC and Bland-Altman analysis. General agreement between techniques measured through ICC was 0.99 with a mean difference of 6 months between techniques being older the ages obtained by DXA. The agreement limits were around ±2 years, which means that 95% of all differences between techniques were covered within this range. We found a high level of ICC agreement in bone age readings from X-ray and DXA images although we observed overestimation of bone age measurements in DXA. Differences between techniques were greater in women than in men, especially at the ages corresponding to puberty. Bone age measurement in DXA images appears not to be reliable; hence it should be suggested to perform conventional radiography of the hand to assess bone age taking into account that X-ray images have better resolution.

Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks

Age prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this study, we used low-resolution, dual-energy, full-body X-ray absorptiometry images to train deep learning models to predict age. In particular, we proposed a preprocessing framework and adapted many partially pretrained convolutional neural network (CNN) models to predict the age of children and young adults. We used a new dataset of 910 multispectral images that were weakly annotated by specialists. The experimental results showed that the proposed preprocessing techniques and the adapted approach to the CNN model achieved a discrepancy between chronological age and predicted age of around 15.56 months for low-resolution whole-body X-rays. Furthermore, we found that the main factor that influenced age prediction scores was spatial features, not multispectral features.

CYP11B1 variants influence skeletal maturation via alternative splicing

We performed genome-wide association study meta-analysis to identify genetic determinants of skeletal age (SA) deviating in multiple growth disorders. The joint meta-analysis (N = 4557) in two multiethnic cohorts of school-aged children identified one locus, CYP11B1 (expression confined to the adrenal gland), robustly associated with SA (rs6471570-A; β = 0.14; P = 6.2 × 10^-12). rs6410 (a synonymous variant in the first exon of CYP11B1 in high LD with rs6471570), was prioritized for functional follow-up being second most significant and the one closest to the first intron-exon boundary. In 208 adrenal RNA-seq samples from GTEx, C-allele of rs6410 was associated with intron 3 retention (P = 8.11 × 10^-40), exon 4 inclusion (P = 4.29 × 10^-34), and decreased exon 3 and 5 splicing (P = 7.85 × 10^-43), replicated using RT-PCR in 15 adrenal samples. As CYP11B1 encodes 11-β-hydroxylase, involved in adrenal glucocorticoid and mineralocorticoid biosynthesis, our findings highlight the role of adrenal steroidogenesis in SA in healthy children, suggesting alternative splicing as a likely underlying mechanism.

A Novel Shorthand Approach to Knee Bone Age Using MRI: A Validation and Reliability Study

Background:

Bone-age determination remains a difficult process. An atlas for bone age has been created from knee-ossification patterns on magnetic resonance imaging (MRI), thereby avoiding the need for radiographs and associated costs, radiation exposure, and clinical inefficiency. Shorthand methods for bone age can be less time-consuming and require less extensive training as compared with conventional methods.

Purpose:

To create and validate a novel shorthand algorithm for bone age based on knee MRIs that could correlate with conventional hand bone age and demonstrate reliability across medical trainees.

Study Design:

Cohort study (diagnosis); Level of evidence, 2.

Methods:

Included in this study were adolescent patients who underwent both knee MRI and hand bone age radiographs within 90 days between 2009 and 2018. A stepwise algorithm for predicting bone age using knee MRI was developed separately for male and female patients, and 7 raters at varying levels of training used the algorithm to determine the bone age for each MRI. The shorthand algorithm was validated using Spearman rho (r_S) to correlate each rater’s predicted MRI bone age with the recorded Greulich and Pyle (G&P) hand bone age. Interrater and intrarater reliability were also calculated using intraclass correlation coefficients (ICCs).

Results:

A total of 38 patients (44.7% female) underwent imaging at a mean age of 12.8 years (range, 9.3-15.7 years). Shorthand knee MRI bone age scores were strongly correlated with G&P hand bone age (r_S = 0.83; P < .001). The shorthand algorithm was a valid predictor of G&P hand bone age regardless of level of training, as medical students (r_S = 0.75), residents (r_S = 0.81), and attending physicians (r_S = 0.84) performed similarly. The interrater reliability of our shorthand algorithm was 0.81 (95% CI, 0.73-0.88), indicating good to excellent interobserver agreement. Respondents also demonstrated consistency, with 6 of 7 raters demonstrating excellent intrarater reliability (median ICC, 0.86 [range, 0.68-0.96]).

Conclusion:

This shorthand algorithm is a consistent, reliable, and valid way to determine skeletal maturity using knee MRI in patients aged 9 to 16 years and can be utilized across different levels of orthopaedic and radiographic expertise. This method is readily applicable in a clinical setting and may reduce the need for routine hand bone age radiographs.

Reproducibility of bone age assessment from DXA hand scans: expert versus novice

Dual-energy x-ray absorptiometry (DXA) scans are frequently used in human biological research to study bone health and body composition. Hand-wrist scans for the assessment of skeletal maturity can also be easily obtained in immature research participants who are being scanned to assess bone health. Whilst assessment by an expert is the desired arrangement such expertise may not be available, and thus knowledge of the relative reproducibility of a trained novice and an acknowledged expert is pertinent. Here we compare the relative reproducibility of an expert and a trained novice on 41 DXA left-hand scans of adolescent males using the Tanner-Whitehouse 3 (TW3) RUS method. The trained novice showed almost perfect reproducibility when evaluating bone age from DXA hand scans compared to an expert in skeletal maturity assessment. Both observers demonstrated reproducibility good enough to suggest that the TW3 method is appropriate to use with DXA hand scans by a trained researcher.

The skeletal maturity of Australian children aged 10-13 years in 2016

Skeletal maturity can be used as a biological indicator of the tempo of growth in children and adolescents. We present a description of skeletal maturity from a cohort of white Australian children and describe variation in skeletal maturity based on child age. Participants (n = 71; age 10.5-13.9 years) were recruited from the 'Healthy, Active Preschool & Primary Years (HAPPY)' study. Left hand-wrist radiographs were used to determine skeletal maturity using the Tanner-Whitehouse III (TW3) RUS technique. In boys, the mean skeletal maturity offset (bone age - chronological age) was -0.12 ± 0.19 years and 57.9% had delayed skeletal maturity compared to chronological age. Among those with delayed skeletal maturity, the average delay was 0.99 years (range 0.02-2.54 years). In girls, skeletal age was advanced, on average, compared to chronological age by 0.32 ± 0.20 years. Among the 39.4% of girls with delayed skeletal maturity, the average delay was 0.48 years (range: 0.01-2.28). Four children in the sample exhibited a delay in skeletal maturity greater than 2 years. In the context of secular trends towards advanced skeletal maturity observed globally, delayed skeletal maturation in this white, economically privileged cohort are surprising and warrant further exploration.

Fat-free mass in adolescent athletes: Accuracy of bioimpedance equations and identification of new predictive equations

OBJECTIVES

The aims of this study were to evaluate the effect of biological maturity on body composition in Brazilian adolescent athletes, to verify the accuracy of previous bioimpedance predictive equations for estimating fat-free mass (FFM), and to develop new predictive equations, considering sexual and skeletal maturity.

METHODS

There were 318 Brazilian adolescent athletes (52% male) involved in this study. FFM was determined using single-frequency (50 kHz) bioelectrical impedance analysis (BIA) and dual-energy x-ray absorptiometry (DXA), which was used as the reference method. The adolescents were classified into skeletally mature using bone age (both sexes), and sexually mature using menarche occurrence (female). The effect of maturity on bioelectrical values was tested using bioelectrical impedance vector analysis. Three predictive BIA equations to estimate FFM were selected from the reviewed literature. Lin's concordance correlation coefficient and Bland-Altman test were used to test the concordance and accuracy of BIA equations. Stepwise multiple regression was used to develop new predictive equations, considering BIA vectors, age, skeletal, and sexual maturity.

RESULTS

DXA and BIA results showed wide limits of disagreement for FFM for all the three equations. Two new equation models were developed, including age and skeletal maturity for both sexes and menarche status for females. Both models showed high R² (males = 0.92 and females = 0.84).

CONCLUSIONS

The assessment of body composition in adolescent athletes should consider sexual (female) or skeletal (male) maturity. The newly proposed equations showed promising results in Brazilian adolescent athletes. A test in different groups and populations is necessary to evaluate the general suitability of the equations in adolescents.

Comparison of DXA Scans and Conventional X-rays for Spine Morphometry and Bone Age Determination in Children

Conventional lateral spine and hand radiographs are the standard tools to evaluate vertebral morphometry and bone age in children. Beside bone mineral density analyses, dual-energy X-ray absorptiometry (DXA) measurements with lower radiation exposure provide high-resolution scans which are not approved for diagnostic purposes. Data about the comparability of conventional radiographs and DXA in children are missing yet. The purpose of the trial was to evaluate whether conventional hand and spine radiographs can be replaced by DXA scans to diminish radiation exposure. Thirty-eight children with osteogenesis imperfecta or secondary osteoporosis or short stature (male, n=20; age, 5.0-17.0 yr) were included and assessed once by additional DXA (GE iDXA) of the spine or the left hand. Intraclass correlation coefficients (ICCs) were used to express agreement between X-ray and iDXA assessment. Evaluation of the spine morphometry showed reasonable agreement between iDXA and radiography (ICC for fish-shape, 0.75; for wedge-shape, 0.65; and for compression fractures, 0.70). Bone age determination showed excellent agreement between iDXA and radiography (ICC, 0.97). IDXA-scans of the spine in a pediatric population should be used not only to assess bone mineral density but also to evaluate anatomic structures and vertebral morphometry. Therefore, iDXA can replace some radiographs in children with skeletal diseases.