Norwood Kvist (humorstew5)

Volumetric high-resolution computed tomography (HRCT) of the chest has recently replaced incremental CT in the diagnostic workup of idiopathic pulmonary fibrosis (IPF). Concomitantly, visual and quantitative scores have been proposed for disease extent assessment to ameliorate disease management. To compare the performance of density histograms (mean lung attenuation, skewness, and kurtosis) and visual scores, along with lung function correlations, in IPF patients submitted to incremental or volumetric thorax HRCT. Clinical data and CT scans of 89 newly diagnosed and therapy-naive IPF patients were retrospectively evaluated. Forty-six incremental and 43 volumetric CT scans were reviewed. No differences of density histograms and visual scores estimates were found by comparing two HRCT techniques, with an optimal inter-operator agreement (concordance correlation coefficient >0.90 in all instances). Single-breath diffusing lung capacity for carbon monoxide (DLCO ) was inversely related with the Best al scoring as more strongly correlated with lung function. Time-efficient and accurate whole volume thigh muscle segmentation is a major challenge in moving from qualitative assessment of thigh muscle MRI to more quantitative methods. This study developed an automated whole thigh muscle segmentation method using deep learning for reproducible fat fraction quantification on fat-water decomposition MRI. This study was performed using a public reference database (Dataset 1, 25 scans) and a local clinical dataset (Dataset 2, 21 scans). A U-net was trained using 23 scans (16 from Dataset 1, seven from Dataset 2) to automatically segment four functional muscle groups quadriceps femoris, sartorius, gracilis and hamstring. The segmentation accuracy was evaluated on an independent testing set (3 × 3 repeated scans in Dataset 1 and four scans in Dataset 2). The average Dice coefficients between manual and automated segmentation were > 0.85. The average percent difference (absolute) in volume was 7.57%, and the average difference (absolute) in mean fat fraction (meanFF) was 0.17%. The reproducibility in meanFF was calculated using intraclasscorrelationcoefficients (ICCs) for the repeated scans, and automated segmentation produced overall higher ICCs than manual segmentation (0.921 vs. 0.902). A preliminary quantitative analysis was performed using two-sample t test to detect possible differences in meanFF between 14 normal and 14 abnormal (with fat infiltration) thighs in Dataset 2 using automated segmentation, and significantly higher meanFF was detected in abnormal thighs. OTX008 solubility dmso automated thigh muscle segmentation exhibits excellent accuracy and higher reproducibility in fat fraction estimation compared to manual segmentation, which can be further used for quantifying fat infiltration in thigh muscles. This automated thigh muscle segmentation exhibits excellent accuracy and higher reproducibility in fat fraction estimation compared to manual segmentation, which can be further used for quantifying fat infiltration in thigh muscles.In this paper, we created a dynamic adhesive environment (DAE) for adipose tissue-derived mesenchymal stem cells (ADMSCs) cultured on smart thermo-responsive substrates, i.e., poly (N-isopropyl acrylamide) (PNIPAM), via introducing periodic changes in the culture temperature. We further explored the particular role of adsorbed fibronectin (FN), an important cell adhesive protein that was recently attributed to the recruitment of stem cells in the niche. The engineered FN/PNIPAM DAE system significantly increased the symmetric renewal of ADMSCs, particularly between passages 7 and 9 (p7-p9), before it dropped down to the level of the control (FN-coated TC polystyrene). This decline in the growth curve was consistent with the increased number of senescent cells, the augmented average cell size and the suppressed FN ma