European radiology
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To investigate the clinical utility of the Vesical Imaging-Reporting and Data System (VI-RADS) by comparing its diagnostic performance for muscle-invasive bladder cancer (MIBC) between radiologists and urologists based on multiparametric MRI, including three-dimensional (3D) fast spin-echo (FSE) T2-weighted acquisitions. ⋯ • VI-RADS (using multiparametric MRI including 3D FSE T2-weighted acquisitions) achieves good to excellent interobserver agreement and has similar diagnostic performance for detecting muscle invasion by both radiologists and urologists. • The diagnostic performance of the overall VI-RADS score is high for both radiologists and urologists, particularly due to the dominant effect of diffusion-weighted imaging on the overall VI-RADS score. • The sensitivity and specificity values of the T2WI VI-RADS scores for four readers in our study (using 3D FSE T2-weighted acquisitions) were similar (with slightly higher specificity values) to previously published results (using 2D FSE T2-weighted acquisitions).
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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.