European radiology
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• Novel coronavirus (COVID-19)-infected pneumonia usually manifests as bilateral ground-glass opacities in the lung periphery on chest CT scans. • Role of radiologists includes not only early detection of lung abnormality, but also suggestion of disease severity, potential progression to acute respiratory distress syndrome, and possible bacterial co-infection in hospitalized patients.
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The diagnostic reading of follow-up low-dose whole-body computed tomography (WBCT) examinations in patients with multiple myeloma (MM) is a demanding process. This study aimed to evaluate the diagnostic accuracy and benefit of a novel software program providing rapid-subtraction maps for bone lesion change detection. ⋯ • A novel algorithm has been successfully applied to generate motion-corrected bone subtraction maps of whole-body low-dose CT scans in less than 2 min. • Motion-corrected bone subtraction maps significantly facilitate the reading of follow-up whole-body low-dose CT scans in multiple myeloma by reducing reading time and increasing sensitivity.
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To evaluate the agreement among readers with different expertise in detecting suspicious lesions at prostate multiparametric MRI using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. ⋯ • Agreement on index lesion detection among radiologists of various experiences is substantial to excellent using PI-RADS v2.1. • Concordance between experienced readers is higher than between less-experienced readers. • Concordance on absence of lesions is excellent across readers' experience.
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The purpose of this study was to observe the imaging characteristics of the novel coronavirus pneumonia. ⋯ • High-resolution CT (HRCT) of the chest is critical for early detection, evaluation of disease severity and follow-up of patients with the novel coronavirus pneumonia. • The manifestations of the novel coronavirus pneumonia are diverse and change rapidly. • Radiologists should be aware of the various features of the disease and temporal changes.
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Artificial intelligence (AI) has the potential to significantly disrupt the way radiology will be practiced in the near future, but several issues need to be resolved before AI can be widely implemented in daily practice. These include the role of the different stakeholders in the development of AI for imaging, the ethical development and use of AI in healthcare, the appropriate validation of each developed AI algorithm, the development of effective data sharing mechanisms, regulatory hurdles for the clearance of AI algorithms, and the development of AI educational resources for both practicing radiologists and radiology trainees. This paper details these issues and presents possible solutions based on discussions held at the 2019 meeting of the International Society for Strategic Studies in Radiology. KEY POINTS: • Radiologists should be aware of the different types of bias commonly encountered in AI studies, and understand their possible effects. • Methods for effective data sharing to train, validate, and test AI algorithms need to be developed. • It is essential for all radiologists to gain an understanding of the basic principles, potentials, and limits of AI.