Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
Background: The anterior chest wall (ACW) involvement is characteristic of synovitis, acne, pustulosis, hyperostosis,\nand osteitis (SAPHO) syndrome, yet little research has focused on its magnetic resonance imaging (MRI) findings.\nPurpose: To characterize the MRI features of the ACW in patients with SAPHO syndrome.\nMethods: Seventy-one patients with SAPHO syndrome and ACW involvement evidenced by bone scintigraphy\nwere recruited in this cross-sectional study. The ACW region was scanned using sagittal, axial, and oblique coronal\nDixon T2-weighted sequences and axial Dixon T1-weighted sequences. The characteristics of both active\ninflammatory and chronic structural lesions were evaluated.................................
Background: To compare the glycosaminoglycan (GAG) content of lumbar intervertebral disks (IVDs) of patients\nwith ankylosing spondylitis (AS) and healthy volunteers and to investigate the association of GAG depletion and\ndisease-related clinical and imaging features........................
Background: Introducing deep learning approach to medical images has rendered a\nlarge amount of un-decoded information into usage in clinical research. But mostly,\nit has been focusing on the performance of the prediction modeling for diseaserelated\nentity, but not on the clinical implication of the feature itself. Here we\nanalyzed liver imaging features of abdominal CT images collected from 2019 patients\nwith stage I â?? III colorectal cancer (CRC) using convolutional neural network (CNN) to\nelucidate its clinical implication in oncological perspectives......................
Background: Chest CT is used for the assessment of the severity of patients infected\nwith novel coronavirus 2019 (COVID-19). We collected chest CT scans of 202 patients\ndiagnosed with the COVID-19, and try to develop a rapid, accurate and automatic tool\nfor severity screening follow-up therapeutic treatment.\nMethods: A total of 729 2D axial plan slices with 246 severe cases and 483 non-severe\ncases were employed in this study. By taking the advantages of the pre-trained deep\nneural network, four pre-trained off-the-shelf deep models (Inception-V3, ResNet-50,\nResNet-101, DenseNet-201) were exploited to extract the features from these CT scans.\nThese features are then fed to multiple classifiers (linear discriminant, linear SVM, cubic\nSVM, KNN and Adaboost decision tree) to identify the severe and non-severe COVID-\n19 cases. Three validation strategies (holdout validation, tenfold cross-validation and\nleave-one-out) are employed to validate the feasibility of proposed pipelines.....................
Background: Measuring optic nerve sheath diameter (ONSD), a relatively\nrecent technique, allows an indirect and non-invasive diagnosis of intracranial\nhypertension. The ONSD ratio to eyeball transverse diameter (ETD) increases\nthis reliability of the technique. The objective of this study was to determine\nthe normal ONSD and its ratio with ETD in black African adults in\nBenin. Methods: A descriptive cross-sectional study was conducted between\nMay 2019 and August 2019. Ultrasound ONSD and ONSD/ETD ratio were\nmeasured in 210 healthy adults received in the medical imaging department\nof the Borgou and Alibori University Hospital Center in Benin. The ONSD\ncorresponded to the average of 12 measurements (03 horizontal and 03 vertical\nfor each eye) taken 3 mm behind the papilla. The transverse ETD corresponded\nto the average of 03 measurements......................
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