At the end of 2019, a novel coronavirus (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) was detected in Wuhan, China, that spread rapidly around the world, with severe consequences for human health and the global economy Here, we assessed the replicative ability and pathogenesis of SARS-CoV-2 isolates in Syrian hamsters SARS-CoV-2 isolates replicated efficiently in the lungs of hamsters, causing severe pathological lung lesions following intranasal infection In addition, microcomputed tomographic imaging revealed severe lung injury that shared characteristics with SARS-CoV-2-infected human lung, including severe, bilateral, peripherally distributed, multilobular ground glass opacity, and regions of lung consolidation SARS-CoV-2-infected hamsters mounted neutralizing antibody responses and were protected against subsequent rechallenge with SARS-CoV-2 Moreover, passive transfer of convalescent serum to naive hamsters efficiently suppressed the replication of the virus in the lungs even when the serum was administrated 2 d postinfection of the serum-treated hamsters Collectively, these findings demonstrate that this Syrian hamster model will be useful for understanding SARS-CoV-2 pathogenesis and testing vaccines and antiviral drugs

https://www.pnas.org/content/pnas/117/28/16587.full.pdf

Syrian hamsters as a small animal model for SARS-CoV-2 infection and countermeasure development.

The ongoing outbreak of the novel coronavirus disease (COVID-19) has spread globally and poses a threat to public health in more than 200 countries. Reliable laboratory diagnosis of the disease has been one of the foremost priorities for promoting public health interventions. The routinely used reverse transcription polymerase chain reaction (RT-PCR) is currently the reference method for COVID-19 diagnosis. However, it also reported a number of false-positive or -negative cases, especially in the early stages of the novel virus outbreak. In this work, a dual-functional plasmonic biosensor combining the plasmonic photothermal (PPT) effect and localized surface plasmon resonance (LSPR) sensing transduction provides an alternative and promising solution for the clinical COVID-19 diagnosis. The two-dimensional gold nanoislands (AuNIs) functionalized with complementary DNA receptors can perform a sensitive detection of the selected sequences from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through nucleic acid hybridization. For better sensing performance, the thermoplasmonic heat is generated on the same AuNIs chip when illuminated at their plasmonic resonance frequency. The localized PPT heat is capable to elevate the in situ hybridization temperature and facilitate the accurate discrimination of two similar gene sequences. Our dual-functional LSPR biosensor exhibits a high sensitivity toward the selected SARS-CoV-2 sequences with a lower detection limit down to the concentration of 0.22 pM and allows precise detection of the specific target in a multigene mixture. This study gains insight into the thermoplasmonic enhancement and its applicability in the nucleic acid tests and viral disease diagnosis.

https://www.zora.uzh.ch/id/eprint/200017/1/200406_1_Manuscript_COVID_Clean_Copy.pdf

Dual-Functional Plasmonic Photothermal Biosensors for Highly Accurate Severe Acute Respiratory Syndrome Coronavirus 2 Detection.

Routine screening CT for the identification of COVID-19 pneumonia is currently not recommended by most radiology societies. However, the number of CTs performed in persons under investigation (PUI) for COVID-19 has increased. We also anticipate that some patients will have incidentally detected findings that could be attributable to COVID-19 pneumonia, requiring radiologists to decide whether or not to mention COVID-19 specifically as a differential diagnostic possibility. We aim to provide guidance to radiologists in reporting CT findings potentially attributable to COVID-19 pneumonia, including standardized language to reduce reporting variability when addressing the possibility of COVID-19. When typical or indeterminate features of COVID-19 pneumonia are present in endemic areas as an incidental finding, we recommend contacting the referring providers to discuss the likelihood of viral infection. These incidental findings do not necessarily need to be reported as COVID-19 pneumonia. In this setting, using the term "viral pneumonia" can be a reasonable and inclusive alternative. However, if one opts to use the term "COVID-19" in the incidental setting, consider the provided standardized reporting language. In addition, practice patterns may vary, and this document is meant to serve as a guide. Consultation with clinical colleagues at each institution is suggested to establish a consensus reporting approach. The goal of this expert consensus is to help radiologists recognize findings of COVID-19 pneumonia and aid their communication with other healthcare providers, assisting management of patients during this pandemic.

/pdf/radiological-society-of-north-america-expert-consensus-2inynsbrl6.pdf

Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA - Secondary Publication.

The pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused an unprecedented global social and economic impact, and high numbers of deaths. Many risk factors have been identified in the progression of COVID-19 into a severe and critical stage, including old age, male gender, underlying comorbidities such as hypertension, diabetes, obesity, chronic lung diseases, heart, liver and kidney diseases, tumors, clinically apparent immunodeficiencies, local immunodeficiencies, such as early type I interferon secretion capacity, and pregnancy. Possible complications include acute kidney injury, coagulation disorders, thoromboembolism. The development of lymphopenia and eosinopenia are laboratory indicators of COVID-19. Laboratory parameters to monitor disease progression include lactate dehydrogenase, procalcitonin, high-sensitivity C-reactive protein, proinflammatory cytokines such as interleukin (IL)-6, IL-1β, Krebs von den Lungen-6 (KL-6), and ferritin. The development of a cytokine storm and extensive chest computed tomography imaging patterns are indicators of a severe disease. In addition, socioeconomic status, diet, lifestyle, geographical differences, ethnicity, exposed viral load, day of initiation of treatment, and quality of health care have been reported to influence individual outcomes. In this review, we highlight the scientific evidence on the risk factors of severity of COVID-19.

Risk factors for severe and critically ill COVID-19 patients: A review.

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional healthcare strategy for tackling COVID-19. However, segmenting infected regions from CT slices faces several challenges, including high variation in infection characteristics, and low intensity contrast between infections and normal tissues. Further, collecting a large amount of data is impractical within a short time period, inhibiting the training of a deep model. To address these challenges, a novel COVID-19 Lung Infection Segmentation Deep Network ( Inf-Net ) is proposed to automatically identify infected regions from chest CT slices. In our Inf-Net , a parallel partial decoder is used to aggregate the high-level features and generate a global map. Then, the implicit reverse attention and explicit edge-attention are utilized to model the boundaries and enhance the representations. Moreover, to alleviate the shortage of labeled data, we present a semi-supervised segmentation framework based on a randomly selected propagation strategy, which only requires a few labeled images and leverages primarily unlabeled data. Our semi-supervised framework can improve the learning ability and achieve a higher performance. Extensive experiments on our COVID-SemiSeg and real CT volumes demonstrate that the proposed Inf-Net outperforms most cutting-edge segmentation models and advances the state-of-the-art performance.

/pdf/inf-net-automatic-covid-19-lung-infection-segmentation-from-ym3alblzt4.pdf

Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images

Coronavirus disease 2019 (COVID-19) outbreak, first reported in Wuhan, China, has rapidly swept around the world just within a month, causing global public health emergency. In diagnosis, chest computed tomography (CT) manifestations can supplement parts of limitations of real-time reverse transcription polymerase chain reaction (RT-PCR) assay. Based on a comprehensive literature review and the experience in the frontline, we aim to review the typical and relatively atypical CT manifestations with representative COVID-19 cases at our hospital, and hope to strengthen the recognition of these features with radiologists and help them make a quick and accurate diagnosis. Key Points • Ground glass opacities, consolidation, reticular pattern, and crazy paving pattern are typical CT manifestations of COVID-19.
 • Emerging atypical CT manifestations, including airway changes, pleural changes, fibrosis, nodules, etc., were demonstrated in COVID-19 patients.
 • CT manifestations may associate with the progression and prognosis of COVID-19.

/pdf/chest-ct-manifestations-of-new-coronavirus-disease-2019-1gyemab5p1.pdf

Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review.

Background The Liver Imaging Reporting and Data System treatment response algorithm (LI-RADS TRA) was developed to evaluate the tumor response of patients with hepatocellular carcinoma (HCC) after locoregional treatments. This study aimed to evaluate the performance of LI-RADS computed tomography (CT) TRA version 2018 in tumor response assessment and survival prediction of patients with single HCC after radiofrequency ablation (RFA). Methods Forty patients who underwent RFA for single HCC between 2010 and 2016 were included in this retrospective study. The overall survival (OS) data from all the patients after the first therapy was collected. Two readers independently assessed the pretreatment (within 7 d) and posttreatment (within 90 d after RFA) CT manifestations using the LI-RADS version 2018 CT TRA. Inter-reader agreement was assessed. Another radiologist re-evaluated any divergent results and came to the final conclusion. The performance of LI-RADS version 2018 CT TRA for tumor response assessment and predicting survival of patients with single HCC after RFA was evaluated. Results Interobserver agreement was moderate between the 2 readers [κ=0.602, 95% confidence interval (CI): 0.390-0.814] when using LI-RADS version 2018 TRA to evaluate tumor response for patients with single HCC after RFA. Patients classified as LR-TR viable had significantly lower OS than those classified as LR-TR nonviable (P=0.005) and LR-TR equivocal (P=0.036). However, the OS between LR-TR nonviable and LR-TR equivocal did not differ significantly (P=0.901). Conclusions LI-RADS version 2018 CT TRA can be applied to predict viable or nonviable HCC after RFA. Patients with LR-TR viable had significantly lower OS than those with LR-TR nonviable and LR-TR equivocal. More research is needed to validate the performance of LI-RADS version 2018 TRA in HCC tumor response evaluation, to better grasp the use of the tie-breaking rule, and to improve the accuracy of prediction for tumor viability.

/pdf/performance-of-li-rads-version-2018-ct-treatment-response-2gx4vvgidm.pdf

Performance of LI-RADS version 2018 CT treatment response algorithm in tumor response evaluation and survival prediction of patients with single hepatocellular carcinoma after radiofrequency ablation.

Sinusoidal obstruction syndrome (SOS) is a rare liver disorder due to hepatic vascular injury. Its rapid and accurate diagnosis is crucial for patient survival. SOS is often established clinically, based on Baltimore, modified Seattle, or European Society for Blood and Marrow Transplantation (EBMT) criteria. Unfortunately, such criteria are not highly specificity and fail to provide a timely, reliable differential diagnosis. The use of noninvasive imaging techniques, such as ultrasound (US), computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), has recently grown in this setting, some key imaging features offering diagnostic improvement. This review provides a synopsis of current noninvasive imaging techniques used for this purpose, summarizing accurate and reliable diagnostic features of SOS.

/pdf/noninvasive-imaging-diagnosis-of-sinusoidal-obstruction-1smsjiwciw.pdf

Noninvasive imaging diagnosis of sinusoidal obstruction syndrome: a pictorial review

Sinusoidal obstruction syndrome: A systematic review of etiologies, clinical symptoms, and magnetic resonance imaging features

Introduction Intrahepatic cholangiocarcinoma is the second most common liver cancer. Desmoplastic stroma may be revealed as distinctive histopathologic findings favoring intrahepatic cholangiocarcinoma. Meanwhile, a range of imaging manifestations is often accompanied with rich desmoplastic stroma in intrahepatic cholangiocarcinoma, which can indicate large bile duct ICC, and a higher level of cancer-associated fibroblasts with poor prognosis and weak treatment response. Areas covered We provide a comprehensive review of current state-of-the-art and recent advances in the imaging evaluation for diagnosis, staging, prognosis and treatment response of intrahepatic cholangiocarcinoma. In addition, we discuss precursor lesions, cells of origin, molecular mutation, which would cause the different histological classification. Moreover, histological classification and tumor microenvironment, which are related to the proportion of desmoplastic stroma with many imaging manifestations, would be also discussed. Expert opinion The diagnosis, prognosis, treatment response of intrahepatic cholangiocarcinoma may be revealed as the presence and the proportion of desmoplastic stroma with a range of imaging manifestations. With the utility of radiomics and artificial intelligence, imaging is helpful for ICC evaluation. Multicentre, large-scale, prospective studies with external validation are in need to develop comprehensive prediction models based on clinical data, imaging findings, genetic parameters, molecular, metabolic, and immune biomarkers.

Yun Zhang

Papers

Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review.

Performance of LI-RADS version 2018 CT treatment response algorithm in tumor response evaluation and survival prediction of patients with single hepatocellular carcinoma after radiofrequency ablation.

Noninvasive imaging diagnosis of sinusoidal obstruction syndrome: a pictorial review

Sinusoidal obstruction syndrome: A systematic review of etiologies, clinical symptoms, and magnetic resonance imaging features

Role of noninvasive imaging in the evaluation of intrahepatic cholangiocarcinoma: from diagnosis and prognosis to treatment response