Journal•ISSN: 2638-6135
Radiology: Cardiothoracic Imaging
Radiological Society of North America
About: Radiology: Cardiothoracic Imaging is an academic journal published by Radiological Society of North America. The journal publishes majorly in the area(s): Medicine & Internal medicine. It has an ISSN identifier of 2638-6135. Over the lifetime, 362 publications have been published receiving 6362 citations. The journal is also known as: Radiol Cardiothorac Imaging & Cardiothoracic imaging.
Topics: Medicine, Internal medicine, Pneumonia, Coronary artery disease, MEDLINE
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TL;DR: Pulmonary manifestation of COVID-19 infection is predominantly characterized by ground-glass opacification with occasional consolidation on CT, suggesting that CT is a more sensitive imaging modality for investigation.
Abstract: Chest radiographic and CT findings of 21 patients with confirmed COVID-19 are described along with a literature review of other publications describing the radiologic findings of this novel coronav...
867 citations
TL;DR: The CT-SS could be used to evaluate the severity of pulmonary involvement quickly and objectively in patients with COVID-19 and was found to be optimal for identifying severe CO VID-19.
Abstract: The chest CT severity score could be used to rapidly identify patients with severe forms of coronavirus disease 2019.
476 citations
University of Pennsylvania1, University of Texas Southwestern Medical Center2, Washington University in St. Louis3, University of Chicago4, Icahn School of Medicine at Mount Sinai5, University of California, San Francisco6, University of Wisconsin-Madison7, University of California, San Diego8, New York University9
TL;DR: In this article, the authors 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 COVID19.
Abstract: Routine screening CT for the identification of coronavirus disease 19 (COVID-19) pneumonia is currently not recommended by most radiology societies. However, the number of CT examinations performed in persons under investigation 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 health care providers, assisting management of patients during this pandemic. Published under a CC BY 4.0 license.
473 citations
TL;DR: A high incidence of subclinical CT changes in cases with COVID-19 is documented, with asymptomatic cases showing more GGO over consolidation and milder extension of disease on CT compared with symptomatic cases.
Abstract: This study revealed a high incidence of subclinical CT changes in COVID-19 infected cases, which showed more ground-glass opacity predominance over consolidation and milder severity on CT than in s...
399 citations
TL;DR: The quantification of lung opacification in COVID-19 measured at chest CT by using a commercially available deep learning–based tool was significantly different among groups with different clinical severity, which could potentially eliminate the subjectivity in the initial assessment and follow-up of pulmonary findings in CO VID-19.
Abstract: The quantification of lung opacification measured at chest CT using a commercially available deep-learning-based tool may be used to monitor the disease progression and understand the temporal evol...
347 citations