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https://www.selleckchem.com/products/baf312-siponimod.html To evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR). The study cohort of 59 consecutive patients (mean age, 67.2 years) who underwent whole-body LD CT and a prior standard-dose (SD) CT reconstructed with hybrid iterative reconstruction (SD-IR) within one year for surveillance of malignancy were assessed. The LD CT images were reconstructed with hybrid iterative reconstruction of 40% (LD-IR) and DLIR (LD-DLIR). The radiologists independently evaluated image quality (5-point scale) and lesion detection. Attenuation values in Hounsfield units (HU) of the liver, pancreas, spleen, abdominal aorta, and portal vein; the background noise and signal-to-noise ratio (SNR) of the liver, pancreas, and spleen were calculated. Qualitative and quantitative parameters were compared between the SD-IR, LD-IR, and LD-DLIR images. The CT dose-index volumes (CTDI ) and dose-length product (DLP) wereg image reconstruction algorithm enables around 80% reduction in radiation dose while maintaining the image quality and lesion detection compared to standard-dose whole-body CT.The novel coronavirus disease 2019 (COVID-19) predisposes patients to venous thromboembolism (VTE) due to risk factors, severe infection, and severe inflammatory responses. The objective is to determine the risk of developing VTE after corticosteroid administration during COVID-19 treatment. Using PRISMA reporting guidelines, a review was conducted from inception until 20 September 2020 with MESH terms including "venous thromboembolism" and "covid-19," using MEDLINE, Scopus, CINAHL Plus, and WHO Global Database. The inclusion criteria included studies with COVID-19 patients aged 18 years and older with VTE diagnosed by duplex ultrasonography or computed tomography pulmonary angiography (CTPA). Exclusion criteria were studies with non C

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