Notes

Dendritic tissue perform simply no significant role inside the laser-induced choroidal neovascularization design.
© 2020 IOP Publishing Ltd.Epicardial adipose tissue (EAT) is a visceral fat deposit, that's known for its association with factors, such as obesity, diabetes mellitus, age, and hypertension. Segmentation of the EAT in a fast and reproducible way is important for the interpretation of its role as an independent risk marker intricate. However, EAT has a variable distribution, and various diseases may affect the volume of the EAT, which can increase the complexity of the already time-consuming manual segmentation work. We propose a 3D deep attention U-Net method to automatically segment the EAT from coronary computed tomography angiography (CCTA). Five-fold cross-validation and hold-out experiments were used to evaluate the proposed method through a retrospective investigation of 200 patients. The automatically segmented EAT volume was compared with physician-approved clinical contours. Quantitative metrics used were the Dice similarity coefficient (DSC), sensitivity, specificity, Jaccard index (JAC), Hausdorff distance (HD), mean surface distance (MSD), residual mean square distance (RMSD), and the center of mass distance (CMD). For cross-validation, the median DSC, sensitivity, and specificity were 92.7%, 91.1%, and 95.1%, respectively, with JAC, HD, CMD, MSD, and RMSD are 82.9% ± 8.8%, 3.77 ± 1.86mm, 1.98 ± 1.50mm, 0.37 ± 0.24mm, and 0.65 ± 0.37mm, respectively. For the hold-out test, the accuracy of the proposed method remained high. We developed a novel deep learning-based approach for the automated segmentation of the EAT on CCTA images. We demonstrated the high accuracy of the proposed learning-based segmentation method through comparison with ground truth contour of 200 clinical patient cases using 8 quantitative metrics, Pearson correlation, and Bland-Altman analysis. EstradiolBenzoate Our automatic EAT segmentation results show the potential of the proposed method to be used in computer-aided diagnosis of coronary artery diseases (CADs) in clinical settings. © 2020 Institute of Physics and Engineering in Medicine.OBJECTIVE Instrumental identification of proximal scleroderma, which is necessary for the early diagnosis of systemic sclerosis (SSD), has not yet been developed. The aim of this study was to assess the potential diagnostic value of the imaging photoplethysmography (IPPG) method in patients with SSD. APPROACH The study enrolled 19 patients with SSD and 21 healthy subjects matched by age and sex with the patients. Spatial distribution of capillary-blood-flow parameters and their dynamics was estimated in the facial area of patients and subjects. In the IPPG system, a 40-s video of the subject's face illuminated by green polarized light was recorded with a monochrome digital camera in synchronization with the electrocardiogram. Experimental data were processed by using custom software allowing assessment of an arrival time of the blood pressure wave (PAT), an amplitude of pulsatile component (APC) of the photoplethysmographic waveform, and their variability. MAIN RESULTS Our study has revealed significant increase of PAT variability in patients with SSD compared to the control group 52±47 ms vs 24±13 ms (P = 0.01). Similarly, the variability of PPG-pulse shape was larger in patients with SSD 0.13±0.07 % vs 0.09±0.02 % (P less then 0.001). In addition, patients with scleroderma showed significantly greater degree of asymmetry of APC parameter than the control group 17.7±9.7 vs 7.9±5.0 (P less then 0.001). At the same time, no correlation was found between the photoplethysmographic waveform parameters and either the form or duration of the disease. No relationship between the characteristics of the PPG waveform and the modified Rodnan skin score was found, as well. SIGNIFICANCE Novel instrumental markers found in our pilot study showed that the IPPG method can be used for diagnosing the systemic sclerosis in the early stages of the disease. © 2020 Institute of Physics and Engineering in Medicine.3D bioprinting may revolutionize the field of tissue engineering by allowing fabrication of bio-structures with high degree of complexity, fine architecture and heterogeneous composition. The printing substances in these processes are mostly based on biomaterials and living cells. As such, they generally possess weak mechanical properties and thus must be supported during fabrication in order to prevent the collapse of large, volumetric multi-layered printouts. In this work, we characterize a uniquely formulated media used to support printing of extracellular matrix-based biomaterials. We show that a hybrid material, comprised of calcium-alginate nanoparticles and xanthan gum, presents superb qualities that enable printing at high resolution of down to 10 microns, allowing fabrication of complex constructs and cellular structures. This hybrid also presents an exclusive combination of desirable properties such as biocompatibility, high transparency, stability at a wide range of temperatures and amenability to delicate extraction procedures. Moreover, as fabrication of large, volumetric biological structures may require hours and even days to accomplish, we have demonstrated that the hybrid medium can support prolonged, precise printing for at least 18 hours. All these qualities make it a promising support medium for 3D printing of tissues and organs. © 2020 IOP Publishing Ltd.INTRODUCTION The lack of rigorous quality standards in pre-clinical radiation dosimetry has renewed interest in the development of anthropomorphic phantoms. Using 3D printing customisable phantoms can be created to assess all parts of pre-clinical radiation research planning, image guidance and treatment delivery. We present the full methodology, including material development and printing designs, for the production of a high spatial resolution, anatomically realistic heterogeneous small animal phantom. METHODS A methodology for creating and validating tissue equivalent materials is presented. The technique is demonstrated through the development of a bone-equivalent material. This material is used together with a soft-tissue mimicking ABS plastic filament to reproduce the corresponding structure geometries captured from a CT scan of a nude mouse. Air gaps are used to represent the lungs. Phantom validation was performed through comparison of the geometry and X-ray attenuation of CT images of the phantom and animal images.
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