Automated determination of bone age and bone mineral density in patients with juvenile idiopathic arthritis: a feasibility study

Introduction

Chronic inflammation combined with glucocorticoid treatment and immobilization puts juvenile idiopathic arthritis (JIA) patients at risk of impaired growth and reduced bone mineral density (BMD). Conventional methods for evaluating bone age and BMD are time-consuming or come with additional costs and radiation exposure. In addition, an automated measurement of bone age and BMD is likely to be more consistent than visual evaluation. In this study, we aimed to evaluate the feasibility of an automated method for determination of bone age and (cortical) bone mineral density (cBMD) in severely affected JIA patients. A secondary objective was to describe bone age and cBMD in this specific JIA population eligible for biologic treatment.

Methods

In total, 69 patients with standard hand radiographs at the start of etanercept treatment and of calendar age within the reliability ranges (2.5 to 17 years for boys and 2 to 15 years for girls) were extracted from the Dutch Arthritis and Biologicals in Children register. Radiographs were analyzed using the BoneXpert method, thus automatically determining bone age and cBMD expressed as bone health index (BHI). Agreement between measurements of the left- and right-hand radiographs and a repeated measurement of the left hand were assessed with the intraclass correlation coefficient (ICC). Regression analysis was used to identify variables associated with Z-scores of bone age and BHI.

Results

The BoneXpert method was reliable in the evaluation of radiographs of 67 patients (radiographs of 2 patients were rejected because of poor image quality). Agreement between left- and right-hand radiographs (ICC = 0.838 to 0.996) and repeated measurements (ICC = 0.999 to 1.000) was good. Mean Z-scores of bone age (−0.36, P = 0.051) and BHI (−0.85, P < 0.001) were lower compared to the healthy population. Glucocorticoid use was associated with delayed bone age (0.79 standard deviation (SD), P = 0.028), and male gender was associated with a lower Z-score of BHI (0.65 SD, P = 0.021).

Conclusions

BoneXpert is an easy-to-use method for assessing bone age and cBMD in patients with JIA, provided that radiographs are of reasonable quality and patients’ bone age lies within the age ranges of the program. The population investigated had delayed bone maturation and lower cBMD than healthy children.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-014-0424-1) contains supplementary material, which is available to authorized users.     

Genome size evolution of the extant lycophytes and ferns

Ferns and lycophytes have remarkably large genomes. However, little is known about how their genome size evolved in fern lineages. To explore the origins and evolution of chromosome numbers and genome size in ferns, we used flow cytometry to measure the genomes of 240 species (255 samples) of extant ferns and lycophytes comprising 27 families and 72 genera, of which 228 species (242 samples) represent new reports. We analyzed correlations among genome size, spore size, chromosomal features, phylogeny, and habitat type preference within a phylogenetic framework. We also applied ANOVA and multinomial logistic regression analysis to preference of habitat type and genome size. Using the phylogeny, we conducted ancestral character reconstruction for habitat types and tested whether genome size changes simultaneously with shifts in habitat preference. We found that 2C values had weak phylogenetic signal, whereas the base number of chromosomes (x) had a strong phylogenetic signal. Furthermore, our analyses revealed a positive correlation between genome size and chromosome traits, indicating that the base number of chromosomes (x), chromosome size, and polyploidization may be primary contributors to genome expansion in ferns and lycophytes. Genome sizes in different habitat types varied significantly and were significantly correlated with habitat types; specifically, multinomial logistic regression indicated that species with larger 2C values were more likely to be epiphytes. Terrestrial habitat is inferred to be ancestral for both extant ferns and lycophytes, whereas transitions to other habitat types occurred as the major clades emerged. Shifts in habitat types appear be followed by periods of genomic stability. Based on these results, we inferred that habitat type changes and multiple whole-genome duplications have contributed to the formation of large genomes of ferns and their allies during their evolutionary history.