European journal of radiology
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To investigate the success of different quantitative lung assessment (QLA) methods on high-resolution CT (HRCT) to assess the severity of Sjogren's syndrome (SjS) related interstitial lung disease (ILD). ⋯ The QLA methods are a promising alternative to the Goh score in the objective evaluation of SjS-related ILD. The QLA methods are capable of distinguishing extensive (which is responsible for poor prognosis in SjS patients) from limited ILD.
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Multicenter Study
Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study.
To develop a deep learning-based method to assist radiologists to fast and accurately identify patients with COVID-19 by CT images. ⋯ Based on deep learning method, the proposed diagnosis model trained on multi-view images of chest CT images showed great potential to improve the efficacy of diagnosis and mitigate the heavy workload of radiologists for the initial screening of COVID-19 pneumonia.
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Multicenter Study
Radiomics nomogram for preoperative differentiation of lung tuberculoma from adenocarcinoma in solitary pulmonary solid nodule.
To investigate the preoperative differential diagnostic performance of a radiomics nomogram in tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) appearing as solitary pulmonary solid nodules (SPSNs). ⋯ The radiomics nomogram we developed can preoperatively distinguish between LAC and TBG in patient with a SPSN.
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To establish and validate a radiomics nomogram for predicting bone metastasis (BM) in patients with newly diagnosed prostate cancer (PCa). ⋯ The radiomics nomogram, which incorporates the multiparametric MRI-based radiomics signature and clinical risk factors, can be conveniently used to promote individualized prediction of BM in patients with newly diagnosed PCa.
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The purpose of this study was to explore the usefulness of diffusion kurtosis imaging (DKI) and molecular markers in predicting the prognosis of glioma patients. ⋯ Molecular markers and DKI parameters, especially MK values, can be used to effectively evaluate the prognosis of glioma patients.