European radiology
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There is increasing evidence that thrombotic events occur in patients with coronavirus disease (COVID-19). We evaluated lung and kidney perfusion abnormalities in patients with COVID-19 by dual-energy computed tomography (DECT) and investigated the role of perfusion abnormalities on disease severity as a sign of microvascular obstruction. ⋯ • Pulmonary perfusion abnormalities in COVID-19 patients, associated with disease severity, can be detected by pulmonary DECT. • A cutoff value of 0.485 μg/L for D-dimer plasma levels predicted lung perfusion deficits with 100% specificity and 87% sensitivity (AUROC, 0.957). • Perfusion abnormalities in the kidney are suggestive of a subclinical systemic microvascular obstruction in these patients.
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The aim of this study was to analyse the use of the chest radiograph (CXR) as the first-line investigation in primary care patients with suspected lung cancer. ⋯ • Half of all lung cancer diagnoses in a 1-year period are first investigated with a chest X-ray. • A normal chest X-ray report leads to a significant delay in the diagnosis of lung cancer. • The majority of patients with a normal or abnormal chest X-ray have advanced disease at diagnosis and there is no difference in survival outcomes based on the chest X-ray findings.
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To assess the accuracy of MRI-derived liver surface nodularity (LSN) score for staging of hepatic fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). ⋯ • Liver surface nodularity (LSN) score is a fast retrospective method for precise quantification of nodularity of liver surface. • MR-based LSN score is a promising non-invasive objective tool to accurately detect different stages of fibrosis in patients with non-alcoholic fatty liver disease (NAFLD).
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To identify and prioritize technical procedures for simulation-based training that should be part of the education of residents in radiology. ⋯ • The 26 identified procedures are listed according to priority and should be included as an integral part of simulation-based training curricula of radiologists across Europe. • This needs assessment is only the first step towards developing standardized simulation-based training programs that support the harmonization of education and training across Europe.
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To differentiate combined hepatocellular cholangiocarcinoma (cHCC-CC) from cholangiocarcinoma (CC) and hepatocellular carcinoma (HCC) using machine learning on MRI and CT radiomics features. ⋯ • Retrospective study demonstrated promising predictive performance of MRI radiomics features in the differentiation of cHCC-CC from HCC and CC and of CT radiomics features in the differentiation of HCC from cHCC-CC and CC. • With future validation, radiomics analysis has the potential to inform current clinical practice for the pre-operative diagnosis of cHCC-CC and to enable optimal treatment decisions regards liver resection and transplantation.