European radiology
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Observational Study
Effects of sirolimus in lymphangioleiomyomatosis patients on lung cysts and pulmonary function: long-term follow-up observational study.
To determine whether sirolimus has beneficial effects on lymphangioleiomyomatosis (LAM) lung cysts in CT with long-term follow-up (FU) and to investigate whether CT is an appropriate imaging biomarker to monitor and evaluate LAM progression. ⋯ • Qualitative analysis showed a total of 15.8% to 21.1% of patients had a reduced lung cyst volume after sirolimus treatment, and in quantitative analysis, there was no significant difference in lung cyst volume between CT at the start of sirolimus therapy and the last CT. • Pulmonary function was also improved or maintained after sirolimus treatment. • Chest CT could be a useful imaging biomarker for evaluating and monitoring lung cysts in patients with lymphangioleiomyomatosis.
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To develop and validate a radiomics nomogram for preoperative differentiating renal angiomyolipoma without visible fat (AML.wovf) from homogeneous clear cell renal cell carcinoma (hm-ccRCC). ⋯ • Differential diagnosis between AML.wovf and hm-ccRCC is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of AML.wovf from hm-ccRCC with improved diagnostic efficacy. • The CT-based radiomics nomogram might spare unnecessary surgery for AML.wovf.
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To evaluate gender differences in the authorship of articles published in two major European radiology journals, European Radiology (EurRad) and CardioVascular and Interventional Radiology (CVIR). ⋯ • There was a significant increase in female authorship in original diagnostic but not interventional imaging research articles between 2002 and 2016. • There is a strong influence of the radiological subspecialty on the percentage of female authors. • Women are significantly more frequently first authors when the last author is a woman.
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This study aims to evaluate ultrafast DCE-MRI-derived kinetic parameters that reflect contrast agent inflow effects in differentiating between subcentimeter BI-RADS 4-5 breast carcinomas and benign lesions. ⋯ • Ultrafast DCE-MRI can generate kinetic parameters, effectively differentiating breast carcinomas from benign lesions. • Subcentimeter carcinomas demonstrated significantly larger maximum slope and shorter bolus arrival time than benign lesions. • Maximum slope and bolus arrival time contribute to better management of suspicious subcentimeter breast lesions.
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To present a deep learning-based approach for semi-automatic prostate cancer classification based on multi-parametric magnetic resonance (MR) imaging using a 3D convolutional neural network (CNN). ⋯ • Prostate cancer classification using a deep learning model is feasible and it allows direct processing of MR sequences without prior lesion segmentation. • Prostate cancer classification performance as measured by AUC is comparable to that of an experienced radiologist. • Perfusion MR images (K-trans), followed by DWI and ADC, have the highest effect on the overall performance; whereas T2w images show hardly any improvement.