Key Points:1. It is important for all radiologists to be aware of the imaging spectrum of the disease and contribute to effective surveillance and response measures.2. Ground-glass opacities and consolidation can demonstrate an organizing pneumonia pattern. Cavitation can also occur in areas of airspace disease.This copy is for personal use only. To order printed copies, contact reprints@rsna.org I n P r e s s Abstract:COVID-19 (previously known as novel coronavirus [2019-nCoV]), first reported in China, has now been declared a global health emergency by World Health Organization. As confirmed I n P r e s s Case 1:A 59-year-old female from Sichuan Provincial People's Hospital presented with fever and chills.She had no history of sick contacts in the family, but she referred a plane ride 5 days prior to onset of symptoms from London, U.K., to Chengdu, China. Chest radiograph (Fig 1a) and chest CT (Fig 1b,c) at presentation showed patchy right lower lobe ground-glass opacities. Follow-up chest CT images (Fig 1d, e) obtained 2 days later showed improvement of the ground-glass opacities, with development of subpleural curvilinear lines. Case 2:A 62-year-old female from Sichuan Provincial People's Hospital presented 7 days after contact with relative who had recently traveled from Wuhan, China. Symptoms at presentation included paroxysmal cough, productive sputum, and fever. Chest CT showed a small solitary nodular ground-glass opacity in the left upper lobe (Fig 2a), which progressed in 3 days to multifocal nodular and peripheral ground-glass opacities involving both upper lobes (Fig 2 b,c). Another follow-up CT done 5 days from presentation showed a new tiny cavity (Fig 2d) and increasing component of consolidation (Fig 2e) admixed with ground-glass opacities and crazy-paving pattern. Case 3:A 45-year-old female from Sichuan Provincial People's Hospital presented with fever, cough, and chest pain after recent travel to Japan. Her CT at presentation showed extensive peripheral

Objectives Asymptomatic infection of SARS-CoV-2 has become a concern worldwide. This study aims to compare the epidemiology and the clinical characteristics of SARS-CoV-2 infection in asymptomatic and symptomatic individuals. Methods A total of 511 confirmed SARS-CoV-2 infection cases, including 100 asymptomatic (by the time of the pathogenic tests) and 411 symptomatic individuals were consecutively enrolled from January 25 to February 20, 2020 from hospitals in 21 cities and 47 counties or districts in Sichuan Province. Epidemiological and clinical characteristics were compared. Results Compared to the symptomatic patients, the asymptomatic cases were younger (P < 0.001), had similar co-morbidity percentages (P = 0.609), and came from higher altitude areas with lower population mobility (P < 0.001) with better defined epidemiological history (P < 0.001). 27.4% of well-documented asymptomatic cases developed delayed symptoms after the pathogenic diagnosis. 60% of asymptomatic cases demonstrated findings of pneumonia on the initial chest CT, including well-recognized features of coronavirus disease-19. None of the asymptomatic individuals died. Two elderly individuals with initially asymptomatic infection developed severe symptoms during hospitalization. One case of possible virus transmission by a patient during the incubation period was highly suspected. Conclusions The epidemiological and clinical findings highlight the significance of asymptomatic infection with SARS-CoV-2. Inspecting the epidemiological history would facilitate the identification of asymptomatic cases. Evidence supports the chest scans for confirmed asymptomatic cases to evaluate the extent of lung involvement.

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Because of its benefits in terms of high speed, non-destructiveness, and three-dimensionality, as well as ease of integration with computer simulation, computed tomography (CT) technology is widely applied in reservoir geology research. However, rock imaging is restricted by the device used as there is not a win–win for both the image receptive field and corresponding resolution. Convolutional neural network-based super-resolution reconstruction has become a hot topic in improving the performance of CT images. With the help of a convolution kernel, it can effectively extract characteristics and ignore disturbance information. The dismal truth is that convolutional neural networks still have numerous issues, particularly unclear texture details. To address these challenges, a generative adversarial network (RDCA-SRGAN) was designed to improve rock CT image resolution using the combination of residual learning and a dual-channel attention mechanism. Specifically, our generator employs residual attention to extract additional features; similarly, the discriminator builds on dual-channel attention and residual learning to distinguish generated contextual information and decrease computational consumption. Quantitative and qualitative analyses demonstrate that the proposed model is superior to earlier advanced frameworks and is capable to constructure visually indistinguishable high-frequency details. The quantitative analysis shows our model contributes the highest value of structural similarity, enriching the more detailed texture information. From the qualitative analysis, in enlarged details of the reconstructed images, the edges of the images generated by the RDCA-SRGAN can be shown to be clearer and sharper. Our model not only performs well in subtle coal cracks but also enriches more dissolved carbonate and carbon minerals. The RDCA-SRGAN has substantially enhanced the reconstructed image resolution and our model has great potential to be used in geomorphological study and exploration.