THE IMPACT OF TYPE 1 DIABETES MELLITUS ON BONE HEALTH IN CHILDREN

This paper gives an overview of the impact of type 1 diabetes on bone health in children and adolescents. First, we analyse studies using DXA (dual x-ray absorptiometry) to assess BMC (bone mineral content) and BMD (bone mineral density). Then, we discuss modern, non-invasive techniques including pQCT (peripheral quantitative computer tomography) and HRpQCT (high-resolution peripheral quantitative computer tomography) for the detailed assessment of bone health aspects including bone mass, bone geometry, bone microarchitecture and bone strength. Thereafter, we explore some of the mechanisms that are responsible for diabetic bone disease in children, like low bone turnover and high sclerostin levels. Finally, we summarise some of the evidence for the importance of microvascular disease in the pathophysiology of diabetic bone disease.

The role of imaging in predicting the development of rheumatoid arthritis

Rheumatoid arthritis (RA) remains a chronic debilitating disease with a significant negative societal impact, despite the expanding landscape of treatment options. This condition is often preceded by a phase of systemic autoimmunity with circulating autoantibodies, elevated pro-inflammatory cytokines, or subtle structural changes. The capability of identifying individuals in the preclinical phase of RA disease makes a “preventive window of opportunity” possible. Much recent work has focused on the role of imaging modalities including ultrasound (US), magnetic resonance imaging (MRI), and high-resolution peripheral quantitative computer tomography (HR-pQCT) in identifying at-risk individuals with or without early joint symptoms for the development of inflammatory arthritis. This article will review the evidence and discuss the challenges as well as opportunities of proactive risk assessment by imaging in RA.

Development and first biomechanical validation of a score to predict bone implant interface stability based on clinical qCT scans

Sufficient implant anchoring in osteoporotic bone is one major challenge in trauma and orthopedic surgery. In these cases, preoperative planning of osteosynthesis is becoming increasingly important. This study presents the development and first biomechanical validation of a bone-implant-anchorage score based on clinical routine quantitative computer tomography (qCT) scans. 10 pairs of fresh frozen femora (mean age 77.4 years) underwent clinical qCT scans after placing 3 referential screws (for matching with the second scan). Afterwards, three 4.5 mm cortical screws (DePuy Synthes, Zuchwil, Switzerland) were placed in each distal femur in the dia-metaphyseal transition followed by the second CT scan. The femur was segmented using thresholding and its outer shape was visualized as a surface model. A 3D model of the cortex screw in STL format was used to model the screw surface precisely. For each femur, the 3 cortex screw models were exactly positioned at the locations previously determined using the second CT scan. The BMD value was calculated at the center of each triangle as an interpolation from the measured values at the three vertices (triangle corners) in the CT. Scores are based on the sum of all the triangles’ areas multiplied by their BMD values. Four different scores were calculated. A screw pull-out test was performed until loss of resistance. A quadratic model adequately describes the relation between all the scores and pull-out values. The square of the best score explains just fewer than 70% of the total variance of the pull-out values and the standardized residual which were approximately normally distributed. In addition, there was a significant correlation between this score and the peak pull-out force (p < 0.001). The coefficient of determination was 0.82. The presented score has the potential to improve preoperative planning by adding the mechanical to the anatomical dimension when planning screw placement.

Bioelectrical Impedance Analysis Versus Quantitative Computer Tomography and Anthropometry for The Assessment of Body Composition Parameters in China

Objectives: The study evaluated the bioelectrical impedance analysis (BIA) device against the body composition parameters measured by anthropometry and quantitative computer tomography (QCT) to assess its reliability and accuracy among Chinese adults.Methods: Body composition parameters (waist circumstance [WC], body weight, body mass index [BMI] and visceral fat area [VFA]) were measured in 1,379 subjects (20-81 years old), both manually and by BIA, and in 1,317 of 1,379 subjects by QCT. The correlation coefficients were calculated between these measurements. Linear regression models were used to estimate each parameter based on the BIA measurements. Multivariate linear regression models were applied to calculate the correlation among VFA, WC and BMI. The concordance correlation coefficient from the Bland-Altman plots were calculated for VFA between QCT and BIA. Results: High correlation was observed for WC, weight and BMI (adjusted R2=0.78, 0.99 and 0.99) between BIA and anthropometry, and for VFA between BIA and QCT in both sex (adjusted R2=0.549 and 0.462). The multivariate regression models were established for the accurate prediction of QCT-VFA using WC and BMI (adjusted R2=0.603). In addition, a strong consistency of VFA measurement was found between BIA and QCT.Conclusion: Body composition parameters could be accurately determined in clinic using simple measurements of BIA. WC is more reliable as a predictor of visceral fat in the metabolic syndrome. Being non-invasive, accurate and free of radiation, BIA can be used as a safe and convenient tool in scientific research and clinical practice for the quick measurement of anthropometric parameters.

Effect of ovariectomy on proximal tibia metaphysis and lumbar vertebral body in common marmoset monkeys

This study aimed to investigate the effect of estrogen withdrawal on bone tissue in adult female marmoset monkeys. In a 1-year follow-up study we used quantitative computer tomography to measure total bone mineral density (BMD) of the proximal tibia and the second-last lumbar vertebral body (L5/L6) before and 1, 3, 6, and 12 months after ovariectomy. Body mass did not significantly change during the 1-year observation period. However, a significant decline of total BMD after ovariectomy was observed in the proximal tibia but not in L5/L6. In addition, regression analysis showed a significant positive relationship between BMD and body mass in both tibia and L5/L6. The results of our study support the idea that ovariectomized marmoset monkeys may serve as a model to investigate bone loss related to decline of estrogen production.