Association between serum uric acid level and bone mineral density at multiple skeletal sites in middle-aged and elderly men: a cross-sectional study of a healthy population in Taiwan.

This study revealed that serum uric acid (sUA) levels were not associated with bone mineral density (BMD) at different skeletal sites in middle-aged and elderly men, even adjusting for confounding variables. Nevertheless, a positive association was only found between sUA levels and BMD at all skeletal sites in the normal BMI group. INTRODUCTION: Previous studies have reported an association between serum uric acid (sUA) levels and bone mineral density (BMD). However, their findings are controversial and limited to adult men in the general population. This study was aimed at examining the association between sUA levels and BMD at multiple skeletal sites in middle-aged and elderly men. METHODS: A cross-sectional analysis of BMD at different skeletal sites and sUA levels was conducted on 918 men (age: 50.83 ± 7.95) using data from the Ditmanson Research Database. The participants were categorized into four groups based on quartiles of the sUA level, and BMD were assessed using dual-energy X-ray absorptiometry. Multivariate linear regression models were utilized to investigate the association between sUA levels and BMD. Further, subgroup analyses were performed. RESULTS: After adjusting for potential confounding factors, sUA as a continuous variable was significantly associated with BMD at the femoral neck only (ß, 95% confidence interval: 0.007 [0.001-0.013]). However, in the categorical analysis, no significant differences were detected in terms of BMD at different skeletal sites across the different sUA quartile groups. Moreover, if the body mass index (BMI) was < 24 kg/m2 for each unit increase in sUA level, the spine, femoral neck, and total hip BMD increased by 0.014, 0.013, and 0.015 g/cm2, respectively. CONCLUSION: The sUA level was not associated with BMD at different skeletal sites in middle-aged and elderly men. Nevertheless, a positive association was only found between sUA levels and BMD at all skeletal sites in the normal weight group.

Accurate Measurement of Cross-Sectional Area of Femoral Artery on MRI Sequences of Transcontinental Ultramarathon Runners Using Optimal Parameters Selection.

In clinics an accurate vessel segmentation method is important to quantize the vessel volume change with respect to time for artery elasticity measurement. This study proposes a modified version on 3D-expanded dynamic programming to find an optimal surface in a 3D matrix. The aim of this study is to discover the robustness against noises in measuring the cross-sectional area of the femoral artery on MRI datasets of ultra-endurance runners as accurately as possible. To do this, we use phantom images with different added noises and different image contrasts to find out the optimal parameters using grid search. The contrast between the vessel lumen and its background in phantom study is changed to simulate the real MRI dataset. We also add a plaque in phantom images to test the accuracy of the proposed algorithm in dealing pathologic cases. The phantom studies and grid search on selecting optimal parameters can offer an alternative way on parameter selection. In application to MRI, the accuracy is performed via comparisons between the manual tracings of experts and automated results. The mean relative error is 2.1 % ± 2.1 % on testing 11 MRI datasets (total 550 images). The phantom studies and grid search on selecting optimal parameters can offer an alternative way on parameter selection.