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The coronavirus 2019 (COVID-19) outbreak poses a serious public health risk. To date, the disease has affected almost all countries in the world. The enormous scale of the outbreak and the relative lack of knowledge and information regarding a new virus, as well as the unpredictability of events, make it challenging for leadership teams to respond. This paper shares how we have reconfigured our radiology leadership team into a smaller disease outbreak task force (DOTF) to respond and coordinate all related efforts during this ongoing COVID-19 pandemic. The DOTF format is modelled after the military with domain groups looking at manpower, intelligence, operations, and logistics matters on a daily basis so that timely decisions can be made and action plans executed promptly. In managing the DOTF, discipline, flexibility, and teamwork are key principles, and these are built upon a strong foundation of focus on infection prevention and control, and patient and staff safety as well as staff well-being. The DOTF has positioned us well to confront the many challenges to date. We believe it will also help us navigate the complex issues that will arise with future surges in cases and in formulating strategies to manage exit from the present and future lockdowns. KEY POINTS: • In a pandemic, regular and directed meetings by a smaller leadership core group are required, for prompt decision making and execution of action plans. • The military format, with domain groups to look at manpower, intelligence, operations, and logistics matters, is useful in managing a pandemic. • Discipline, flexibility, and teamwork with strong focus on infection prevention and control, and patient and staff safety as well as staff well-being are key principles for leadership teams managing a pandemic. [ABSTRACT FROM AUTHOR]

Objective: COVID-19 infection is a systemic disease with various cardiovascular symptoms and complications. Cardiac MRI with late gadolinium enhancement is the modality of choice for the assessment of myocardial involvement. T1 and T2 mapping can increase diagnostic accuracy and improve further management. Our study aimed to evaluate the different aspects of myocardial damage in cases of COVID-19 infection using cardiac MRI. Methods: This descriptive retrospective study included 86 cases, with a history of COVID-19 infection confirmed by positive RT-PCR, who met the inclusion criteria. Patients had progressive chest pain or dyspnoea with a suspected underlying cardiac cause, either by an abnormal electrocardiogram or elevated troponin levels. Cardiac MRI was performed with late contrast-enhanced (LGE) imaging, followed by T1 and T2 mapping. Results: Twenty-four patients have elevated hsTnT with a median hsTnT value of 133 ng/L (IQR: 102 to 159 ng/L); normal value < 14 ng/L. Other sixty-two patients showed elevated hsTnI with a median hsTnI value of 1637 ng/L (IQR: 1340 to 2540 ng/L); normal value < 40 ng/L. CMR showed 52 patients with acute myocarditis, 23 with Takotsubo cardiomyopathy, and 11 with myocardial infarction. Invasive coronary angiography was performed only in selected patients. Conclusion: Different COVID-19-related cardiac injuries may cause similar clinical symptoms. Cardiac MRI is the modality of choice to differentiate between the different types of myocardial injury such as Takotsubo cardiomyopathy and infection-related cardiomyopathy or even acute coronary syndrome secondary to vasculitis or oxygen-demand mismatch. Key Points: • It is essential to detect early COVID-related cardiac injury using different cardiac biomarkers and cardiac imaging, as it has a significant impact on patient management and outcome. • Cardiac MRI is the modality of choice to differentiate between the different aspects of COVID-related myocardial injury. [ABSTRACT FROM AUTHOR]

Objectives: To quantify reader agreement for the British Society of Thoracic Imaging (BSTI) diagnostic and severity classification for COVID-19 on chest radiographs (CXR), in particular agreement for an indeterminate CXR that could instigate CT imaging, from single and paired images. Methods: Twenty readers (four groups of five individuals)—consultant chest (CCR), general consultant (GCR), and specialist registrar (RSR) radiologists, and infectious diseases clinicians (IDR)—assigned BSTI categories and severity in addition to modified Covid-Radiographic Assessment of Lung Edema Score (Covid-RALES), to 305 CXRs (129 paired; 2 time points) from 176 guideline-defined COVID-19 patients. Percentage agreement with a consensus of two chest radiologists was calculated for (1) categorisation to those needing CT (indeterminate) versus those that did not (classic/probable, non-COVID-19); (2) severity; and (3) severity change on paired CXRs using the two scoring systems. Results: Agreement with consensus for the indeterminate category was low across all groups (28–37%). Agreement for other BSTI categories was highest for classic/probable for the other three reader groups (66–76%) compared to GCR (49%). Agreement for normal was similar across all radiologists (54–61%) but lower for IDR (31%). Agreement for a severe CXR was lower for GCR (65%), compared to the other three reader groups (84–95%). For all groups, agreement for changes across paired CXRs was modest. Conclusion: Agreement for the indeterminate BSTI COVID-19 CXR category is low, and generally moderate for the other BSTI categories and for severity change, suggesting that the test, rather than readers, is limited in utility for both deciding disposition and serial monitoring. Key Points: • Across different reader groups, agreement for COVID-19 diagnostic categorisation on CXR varies widely. • Agreement varies to a degree that may render CXR alone ineffective for triage, especially for indeterminate cases. • Agreement for serial CXR change is moderate, limiting utility in guiding management. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU). Methods: Six hundred fifty-four patients (212 deceased, 442 alive, 5645 total CXRs) were identified across two institutions. Imaging and clinical data from one institution were used to train five longitudinal transformer-based networks applying five-fold cross-validation. The models were tested on data from the other institution, and pairwise comparisons were used to determine the best-performing models. Results: A higher proportion of deceased patients had elevated white blood cell count, decreased absolute lymphocyte count, elevated creatine concentration, and incidence of cardiovascular and chronic kidney disease. A model based on pre-ICU CXRs achieved an AUC of 0.632 and an accuracy of 0.593, and a model based on ICU CXRs achieved an AUC of 0.697 and an accuracy of 0.657. A model based on all longitudinal CXRs (both pre-ICU and ICU) achieved an AUC of 0.702 and an accuracy of 0.694. A model based on clinical data alone achieved an AUC of 0.653 and an accuracy of 0.657. The addition of longitudinal imaging to clinical data in a combined model significantly improved performance, reaching an AUC of 0.727 (p = 0.039) and an accuracy of 0.732. Conclusions: The addition of longitudinal CXRs to clinical data significantly improves mortality prediction with deep learning for COVID-19 patients in the ICU. Key Points: • Deep learning was used to predict mortality in COVID-19 ICU patients. • Serial radiographs and clinical data were used. • The models could inform clinical decision-making and resource allocation. [ABSTRACT FROM AUTHOR]

Objectives: This study analyzed and compared CT findings and longitudinal variations after discharge between severe and non-severe coronavirus disease (COVID-19) patients who had residual pulmonary sequelae at pre-discharge. Methods: A total of 310 patients were included and stratified into severe and non-severe COVID-19 groups. Cross-sectional CT features across different time periods (T0: pre-discharge, T1: 1–4 weeks after discharge, T2: 5–8 weeks after discharge, T3: 9–12 weeks after discharge, T4: > 12 weeks after discharge) were compared, and the longitudinal variations of CT findings were analyzed and compared in both groups. Results: The cumulative absorption rate of fibrosis-like findings in the severe and non-severe groups at T4 was 24.3% (17/70) and 52.0% (53/102), respectively. In both groups, ground-glass opacity (GGO) with consolidation showed a clear decreasing trend at T1, after which they maintained similar lower levels. The GGO in the severe group showed an increasing trend first at T1 and then decreasing at T4; however, the incidence decreased gradually in the non-severe group. Most fibrosis-like findings showed a tendency to decrease rapidly and then remained stable. Bronchial dilatation in the severe group persisted at an intermediate level. Conclusions: After discharge, the characteristics and changing trends of pulmonary sequelae caused by COVID-19 were significantly different between the two groups. Pulmonary sequelae were more serious and recovery was slower in patients with severe/critical disease than in patients with moderate disease. A portion of the fibrosis-like findings were completely absorbed in patients with moderate and severe/critical diseases. Key Points: • Lung sequelae were more serious and recovery was slower in severe/critical COVID-19 patients. • Complete absorption of fibrosis-like findings after a short-term follow-up was observed in at least 17/70 (24.3%) of COVID-19 patients with severe/critical disease and 53/102 (52.0%) of COVID-19 patients with moderate disease. • The most common fibrosis-like findings was a parenchymal band; irregular interface was a nonspecific sign of COVID-19, and the percentage of bronchial dilatation in patients with severe/critical disease remained at a relatively stable medium level (range, 31.6 to 47.8%) at all stages. [ABSTRACT FROM AUTHOR]

Objective: To analyze and compare the imaging workflow, radiation dose, and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method. Materials and methods: One hundred twenty-seven adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time, and off-center distance of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups. Results: The AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP 1.56 cm ± 0.83 vs. MP 4.05 cm ± 2.40, p < 0.001) and higher proportion of positioning accuracy (AP 99% vs. MP 92%), resulting in 16% radiation dose reduction (AP 6.1 mSv ± 1.3 vs. MP 7.3 mSv ± 1.2, p < 0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas. Conclusion: The AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose and optimizing imaging workflow and image quality in imaging the chest. Key Points: • The AI-based automatic positioning (AP) operation was successful for all patients in our study. • AP method reduced the total positioning time by 28% compared with the manual positioning (MP). • AP method had less patient off-center distance and higher proportion of positioning accuracy than MP method, resulting in 16% radiation dose reduction and 9% image noise reduction in erector spinae. [ABSTRACT FROM AUTHOR]

Faced with the COVID-19 pandemic, many countries both in Europe and across the world implemented strict stay-at-home orders. These measures helped to slow the spread of the coronavirus but also led to increased mental and physical health issues for the domestically confined population, including an increase in the occurrence of intimate partner violence (IPV) in many countries. IPV is defined as behavior that inflicts physical, psychological, or sexual harm within an intimate relationship. We believe that as radiologists, we can make a difference by being cognizant of this condition, raising an alert when appropriate and treating suspected victims with care and empathy. The aim of this Special Report is to raise awareness of IPV among radiologists and to suggest strategies by which to identify and support IPV victims. Key Points: • The COVID-19 pandemic led to a marked increase in the number of intimate partner violence (IPV) cases, potentially leading to increased emergency department visits and radiological examinations. • Most IPV-related fractures affect the face, fingers, and upper trunk, and may easily be misinterpreted as routine trauma. • Radiologists should carefully review the medical history of suspicious cases, discuss the suspicion with the referring physician, and proactively engage in a private conversation with the patient, pointing to actionable resources for IPV victims. [ABSTRACT FROM AUTHOR]

Objectives: To retrospectively investigate the incidence of acute adrenal infarction (AAI) in patients who underwent chest CT for severe SARS-CoV-2 infection and to correlate findings with prognosis. Methods: The local ethics committee approved this retrospective study and waived the need of informed consent. From March 9 to April 10, 2020, all patients referred to our institution for a clinical suspicion of COVID-19 with moderate to severe symptoms underwent a chest CT for triage. Patients with a/parenchymal lesion characteristics of COVID-19 involving at least 50% of lung parenchyma and b/positive RT-PCR for SARS-CoV-2 were retrospectively included. Adrenal glands were reviewed by two independent readers to look for AAI. Additional demographics and potential biological markers of adrenal insufficiency were obtained. Correlations with ICU stay and mortality were sought. Results: Out of the 219 patients with critical (n = 52) and severe lung (n = 167) parenchyma lesions, 51 (23%) had CT scan signs of AAI, which was bilateral in 45 patients (88%). Four patients had an acute biological adrenal gland insufficiency (8%). Univariate analysis in AAI+ patients demonstrated a higher rate of ICU stay (67% vs. 45%, p < 0.05) and a longer stay (more than 15 days for 31% for AAI+ vs. 19%, p < 0.05) compared with AAI− patients. Mortality rate was similar (27%, p = 0.92). Conclusions: Acute adrenal infarction on initial chest evaluation of severe COVID-19 is frequent (51/219, 23%) and might be a sign of poorer prognosis. Key Points: • Acute adrenal infarction on initial chest CT evaluation of severe COVID-19 is frequent (51/219). • AAI might be a factor of poorer prognosis, with increased rate of ICU hospitalization and length of stay. [ABSTRACT FROM AUTHOR]

Objectives: To elucidate the CT manifestations and patterns of evolution in patients with COVID-19 pneumonia. Methods: This is a retrospective review of CT scans of 110 patients. All 110 patients had initial and second CT scans, 60 of 110 patients had three serial CT scans, and 17 of 60 patients had four serial CT scans. Numerous characteristics of pulmonary and extrapulmonary abnormalities and recognizable patterns of evolution were evaluated. Results: Of the 110 initial CT scans, ground-glass opacities without consolidation (65.4%) were more common than a consolidation or mixed pattern. The most common findings were subpleural involvement (77.2%), multifocal involvement (80.7%), and bilateral involvement (67.3%). Three serial CT scans of 60 patients showed four patterns of CT evolution: type 1 showing relatively high CT scores on initial CT (averaged 4 days after symptom onset), with mild progression and improvement on follow-up CT scans (25%); type 2 with progression of CT findings from initial CT to first follow-up CT (averaged 9 days after symptom onset) with subsequent improvement on second follow-up CT (averaged 13 days after symptom onset, 61.7%); type 3 with no CT changes (5.0%); and type 4 pattern was similar to type 2 but with a more prolonged course and more severe CT findings (8.3%). Conclusions: Predominant findings at initial CT scans were bilateral multifocal subpleural GGO. The most commonly shown evolution pattern was type 2: progression of disease with increased extent and density of opacities on first follow-up CT followed by improvement on second follow-up CT. Key Points: • Predominant findings at initial CT in patients with COVID-19 infection are bilateral multifocal subpleural ground-glass opacities. • Ill-defined patchy or nodular opacities were most commonly observed on CT scans with the right lower lobe most commonly involved. • The most commonly shown evolution pattern on chest CT was type 2: progression of CT findings from initial CT to first follow-up CT with subsequent improvement on second follow-up CT. [ABSTRACT FROM AUTHOR]

Objectives: To perform an online survey aimed at evaluating the impact of COVID-19 on Italian radiology departments. Methods: We launched a survey composed of 25 questions about how COVID-19 has changed the safety and organization of daily activity in Italian radiology units. Results: A total of 2136/10,564 (20.2%) radiologists of the Italian Society of Medical and Interventional Radiology participated. Two-thirds performed at least one diagnostic/interventional procedure on COVID-19 patients. The 88.1% reported a reduction in the elective imaging volumes, with US, mammography, and MRI having shown the greater decrease (41.1%, 23.9%, and 21.1%, respectively). In 69.6% of cases, institutions had trouble getting personal protective equipment (PPE), especially public hospitals and southern institutions. Less than 30% of participants were subjected to RT-PCR swab test, although 81.5% believed that it should be done on all health workers and 70% suggested it as the most important measure to improve safety at work. Slightly more than half of participants declared to work safely and felt to be adequately protected by their institutions. Up to 20% of northern participants were redeployed to clinical services. The first imaging examination performed by admitted COVID-19 patients was chest radiography in 76.3% of cases. Almost half of participants reported that less than 30% of health workers were infected in their radiology department, with higher rates in northern regions and public institutions. Conclusions: This snapshot of the current situation in Italian radiology departments could be used to harmonize the organization of working activity in order to safely and effectively face this pandemic. Key Points: • More than two-thirds of institutions had trouble getting PPE for health workers, with public hospitals and southern institutions that presented more procurement problems • A substantial drop of imaging volumes was observed in the vast majority of Italian radiology departments, mostly due to the decrease of ultrasound, mammography, and MRI, especially in private practice were working activity was stopped in 13.3% of institutions • RT-PCR swab to health workers was reported as the most suggested measure by Italian radiologists to improve safety at work, as more than 80% of them believed that it should be performed to all health workers, although less than 30% were subjected to this test [ABSTRACT FROM AUTHOR]

Objective: To explore the value of CT texture analysis (CTTA) for determining coronavirus disease 2019 (COVID-19) severity. Methods: The clinical and CT data of 81 patients with COVID-19 were retrospectively analyzed. The texture features were extracted using LK2.1. The two-sample t test or Mann–Whitney U test was used to find the significant features. Minimum redundancy and maximum relevance (MRMR) method was performed to find the features with maximum correlation and minimum redundancy. These features were then used to construct a radiomics texture model to discriminate the severe patients using multivariate logistic regression method. Besides, a clinical model was also built. ROC analyses were conducted to evaluate the performance of two models. The correlations of clinical features and textural features were analyzed using the Spearman correlation analysis. Results: Of the total cases included, 60 were common and 21 were severe. (1) For textural features, 20 radiomics features selected by MRMR showed good performance in discriminating the two groups (AUC > 70%). (2) For clinical features, chi-square tests or Mann–Whitney U tests identified 16 clinical features as significant, and 12 were discriminative (p < 0.05) between two groups analyzed by univariate logistic analysis. Of these, 10 had an AUC > 70%. (3) Prediction models for textural features and clinical features were established, and both showed high predictive accuracy. The AUC values of textural features and clinical features were 0.93 (0.86–1.00) and 0.95 (0.95–0.99), respectively. (4) The Spearman correlation analysis showed that most textural and clinical features had above-moderate correlations with disease severity (> 0.4). Conclusion: Texture analysis can provide reliable and objective information for differential diagnosis of COVID-19. Key Points: • CT texture analysis can well differentiate common and severe COVID-19 patients. • Some textural features showed above-moderate correlations with clinical factors. • CT texture analysis can provide useful information to judge the severity of COVID-19. [ABSTRACT FROM AUTHOR]

Objectives: To determine the patterns of chest computed tomography (CT) evolution according to disease severity in a large coronavirus disease 2019 (COVID-19) cohort in Jiangsu Province, China. Methods: This retrospective cohort study was conducted from January 10, 2020, to February 18, 2020. All patients diagnosed with COVID-19 in Jiangsu Province were included, retrospectively. Quantitative CT measurements of pulmonary opacities including volume, density, and location were extracted by deep learning algorithm. Dynamic evolution of these measurements was investigated from symptom onset (day 1) to beyond day 15. Comparison was made between severity groups. Results: A total of 484 patients (median age of 47 years, interquartile range 33–57) with 954 CT examinations were included, and each was assigned to one of the three groups: asymptomatic/mild (n = 63), moderate (n = 378), severe/critically ill (n = 43). Time series showed different evolution patterns of CT measurements in the groups. Following disease onset, posteroinferior subpleural area of the lung was the most common location for pulmonary opacities. Opacity volume continued to increase beyond 15 days in the severe/critically ill group, compared with peaking on days 13–15 in the moderate group. Asymptomatic/mild group had the lowest opacity volume which almost resolved after 15 days. The opacity density began to drop from day 10 to day 12 for moderately ill patients. Conclusions: Volume, density, and location of the pulmonary opacity and their evolution on CT varied with disease severity in COVID-19. These findings are valuable in understanding the nature of the disease and monitoring the patient's condition during the course of illness. Key Points: • Volume, density, and location of the pulmonary opacity on CT change over time in COVID-19. • The evolution of CT appearance follows specific pattern, varying with disease severity. [ABSTRACT FROM AUTHOR]

Objective: To retrospectively analyze the chest computed tomography (CT) features in patients with coronavirus disease 2019 (COVID-19) pneumonia.Methods: From January 9, 2020, to February 26, 2020, totally 56 laboratory-confirmed patients with COVID-19 underwent chest CT. For 40 patients, follow-up CT scans were obtained. The CT images were evaluated for the number, type and distribution of the opacity, and the affected lung lobes. Furthermore, the initial CT scan and the follow-up CT scans were compared.Results: Forty patients (83.6%) had two or more opacities in the lung. Eighteen (32.7%) patients had only ground-glass opacities; twenty-nine patients (52.7%) had ground-glass and consolidative opacities; and eight patients (14.5%) had only consolidation. A total of 43 patients (78.2%) showed two or more lobes involved. The opacities tended to be both in peripheral and central (30/55, 54.5%) or purely peripheral distribution (25/55, 45.5%). Fifty patients (90.9%) had the lower lobe involved. The first follow-up CT scans showed that twelve patients (30%) had improvement, 26 (65%) patients had mild-moderate progression, and two patients (5%) had severe progression with "white lungs." The second follow-up CT showed that 22 patients (71%) showed improvement compared with the first follow-up CT, four patients (12.9%) had aggravated progression, and five patients (16.1%) showed unchanged radiographic appearance.Conclusions: The common CT features of COVID-19 pneumonia are multiple lung opacities, multiple types of the opacity (ground-glass, ground-glass and consolidation, and consolidation alone), and multiple lobes especially the lower lobe involved. Follow-up CT could demonstrate the rapid progression of COVID-19 pneumonia (either in aggravation or absorption).Key Points: • The predominant CT features of COVID-19 pneumonia are multiple ground-glass opacities with or without consolidation and, with both lungs, multiple lobes and especially the lower lobe affected. • CT plays a crucial role in early diagnosis and assessment of COVID-19 pneumonia progression. • CT findings of COVID-19 pneumonia may not be consistent with the clinical symptoms or the initial RT-PCR test results. [ABSTRACT FROM AUTHOR]

Objectives: To investigate CT images of 100 confirmed COVID-19 pneumonia patients to describe the lesion distribution, CT signs, and evolution during different courses. Methods: A retrospective study of 100 COVID-19 pneumonia patients without ARDS was performed, and CT scans were reviewed. A COVID-19 pneumonia course diagram was drawn. Mann-Whitney U test was used to compare the lesion distribution and CT scores, χ2 test was used to compare the CT findings between different stages. Results: A total of 272 CT scans from 100 patients (mean age, 52.3 years ± 13.1) were investigated. Four patients with lung abnormalities on CT first showed negative RT-PCR result and turned positive afterwards. One hundred sixty-nine (62.1%) showed predominantly peripheral distribution. The CT scores of the upper zone (3.4 ± 3.6) were significantly lower than those of the middle (5.0 ± 3.9) and lower (4.8 ± 3.6) zones (p < 0.001). The CT scores of the anterior zones (4.9 ± 4.7) were significantly lower than those of the posterior zones (8.4 ± 6.2) (p < 0.001). In the early rapid progressive stage (1~7 days), ground glass opacity (GGO) plus reticular pattern (58.1%), GGO plus consolidation (43.0%), and GGO (41.9%) were all common. In the advanced stage (8~14 days), GGO plus consolidation (79.8%) and repairing CT signs (subpleural line, bronchus distortion, and fibrotic strips) showed a significant increase (p < 0.05). In the absorption stage, GGO plus consolidation (9.1%) sharply decreased (p < 0.05). Conclusion: CT imaging of COVID-19 pneumonia showed a predominantly peripheral, middle and lower, and posterior distribution. The early rapid progressive stage is 1~7 days from symptom onset, the advanced stage with peak levels of abnormalities on CT is 8~14 days, and the abnormalities started to improve after 14 days. Key Points: • The course of COVID-19 pneumonia consists of three stages: 1~7 days is the early rapid progressive stage, 8~14 days is the advanced stage, and after 14 days, the abnormalities started to decrease. • In the early rapid progressive stage, GGO plus a reticular pattern, GGO plus consolidation, and GGO were all common signs; in the advanced stage, signs of progression and absorption coexisted; lung abnormalities showed an asynchronous process with parts with absorption and parts progressing. • Lung abnormalities mainly showed predominantly peripheral, middle, and lower distribution. [ABSTRACT FROM AUTHOR]

Background: In the vast majority of the laboratory-confirmed coronavirus disease 2019 (COVID-19) patients, computed tomography (CT) examinations yield a typical pattern and the sensitivity of this modality has been reported to be 97% in a large-scale study. Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care. Purpose: To compose a comprehensive lexicon for description of the imaging findings and propose a grading system and structured reporting format for CT findings in COVID-19. Material and methods: We updated our published systematic review on imaging findings in COVID-19 to include 37 published studies pertaining to diagnostic features of COVID-19 in chest CT. Using the reported imaging findings of 3647 patients, we summarized the typical chest CT findings, atypical features, and temporal changes of COVID-19 in chest CT. Subsequently, we extracted a list of descriptive terms and mapped it to the terminology that is commonly used in imaging literature. Results: We composed a comprehensive lexicon that can be used for documentation and reporting of typical and atypical CT imaging findings in COVID-19 patients. Using the same data, we propose a grading system with five COVID-RADS categories. Each COVID-RADS grade corresponds to a low, moderate, or high level of suspicion for pulmonary involvement of COVID-19. Conclusion: The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients. Key Points: • Chest CT has high sensitivity in diagnosing the coronavirus disease 2019 (COVID-19). • Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care. • The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients. [ABSTRACT FROM AUTHOR]

Key Points: • Radiology services encountering the coronavirus disease-19 pandemic will need to modify their daily operational practices. • Leadership, patient risk stratification, adequate manpower, operational workflow clarity, and workplace/social responsibility will help Radiology services safely and sustainably deal with the current disease outbreak. [ABSTRACT FROM AUTHOR]

Almost the entire world, not only China, is currently experiencing the outbreak of a novel coronavirus that causes respiratory disease, severe pneumonia, and even death. The outbreak began in Wuhan, China, in December of 2019 and is currently still ongoing. This novel coronavirus is highly contagious and has resulted in a continuously increasing number of infections and deaths that have already surpassed the SARS-CoV outbreak that occurred in China between 2002 and 2003. It is now officially a pandemic, announced by WHO on the 11th of March. Currently, the 2019 novel coronavirus (SARS-CoV-2) can be identified by virus isolation or viral nucleic acid detection; however, false negatives associated with the nucleic acid detection provide a clinical challenge and thus make the imaging examination crucial. Imaging exams have been a main clinical diagnostic criteria for the 2019 novel coronavirus disease (COVID-19) in China. Imaging features of multiple patchy areas of ground glass opacity and consolidation predominately in the periphery of the lungs are characteristic manifestations on chest CT and extremely helpful in the early detection and diagnosis of this disease, which aids prompt diagnosis and the eventual control of this emerging global health emergency. Key Points • In December 2019, China, an outbreak of pneumonia caused by a novel, highly contagious coronavirus raised grave concerns and posed a huge threat to global public health. • Among the infected patients, characteristic findings on CT imaging include multiple, patchy, ground-glass opacity, crazy-paving pattern, and consolidation shadows, mainly distributed in the peripheral and subpleural areas of both lungs, which are very helpful for the frontline clinicians. • Imaging examination has become the indispensable means not only in the early detection and diagnosis but also in monitoring the clinical course, evaluating the disease severity, and may be presented as an important warning signal preceding the negative RT-PCR test results. [ABSTRACT FROM AUTHOR]

Objectives: To delineate the evolution of CT findings in patients with mild COVID-19 pneumonia. Methods: CT images and medical records of 88 patients with confirmed mild COVID-19 pneumonia, a baseline CT, and at least one follow-up CT were retrospectively reviewed. CT features including lobar distribution and presence of ground glass opacities (GGO), consolidation, and linear opacities were analyzed on per-patient basis during each of five time intervals spanning the 3 weeks after disease onset. Total severity scores were calculated. Results: Of patients, 85.2% had travel history to Wuhan or known contact with infected individuals. The most common symptoms were fever (84.1%) and cough (56.8%). The baseline CT was obtained on average 5 days from symptom onset. Four patients (4.5%) had negative initial CT. Significant differences were found among the time intervals in the proportion of pulmonary lesions that are (1) pure GGO, (2) mixed attenuation, (3) mixed attenuation with linear opacities, (4) consolidation with linear opacities, and (5) pure consolidation. The majority of patients had involvement of ≥ 3 lobes. Bilateral involvement was more prevalent than unilateral involvement. The proportions of patients observed to have pure GGO or GGO and consolidation decreased over time while the proportion of patients with GGO and linear opacities increased. Total severity score showed an increasing trend in the first 2 weeks. Conclusions: While bilateral GGO are predominant features, CT findings changed during different time intervals in the 3 weeks after symptom onset in patients with COVID-19. Key Points: • Four of 88 (4.5%) patients with COVID-19 had negative initial CT. • Majority of COVID-19 patients had abnormal CT findings in ≥ 3 lobes. • A proportion of patients with pure ground glass opacities decreased over the 3 weeks after symptom onset. [ABSTRACT FROM AUTHOR]

Objectives: To systematically analyze CT findings during the early and progressive stages of natural course of coronavirus disease 2019 and also to explore possible changes in pulmonary parenchymal abnormalities during these two stages.Methods: We retrospectively reviewed the initial chest CT data of 62 confirmed coronavirus disease 2019 patients (34 men, 28 women; age range 20-91 years old) who did not receive any antiviral treatment between January 21 and February 4, 2020, in Chongqing, China. Patients were assigned to the early-stage group (onset of symptoms within 4 days) or progressive-stage group (onset of symptoms within 4-7 days) for analysis. CT characteristics and the distribution, size, and CT score of pulmonary parenchymal abnormalities were assessed.Results: In our study, the major characteristic of coronavirus disease 2019 was ground-glass opacity (61.3%), followed by ground-glass opacity with consolidation (35.5%), rounded opacities (25.8%), a crazy-paving pattern (25.8%), and an air bronchogram (22.6%). No patient presented cavitation, a reticular pattern, or bronchial wall thickening. The CT scores of the progressive-stage group were significantly greater than those of the early-stage group (p = 0.004).Conclusions: Multiple ground-glass opacities with consolidations in the periphery of the lungs were the primary CT characteristic of coronavirus disease 2019. CT score can be used to evaluate the severity of the disease. If these typical alterations are found, then the differential diagnosis of coronavirus disease 2019 must be considered.Key Points: • Multiple GGOs with consolidations in the periphery of the lungs were the primary CT characteristic of COVID-19. • The halo sign may be a special CT feature in the early-stage COVID-19 patients. • Significantly increased CT score may indicate the aggravation of COVID-19 in the progressive stage. [ABSTRACT FROM AUTHOR]