Essentials for Radiologists on COVID-19: an Update-Radiology Scientific Expert Panel.

HomeRadiologyVol. 296, No. 2 PreviousNext Reviews and CommentaryFree AccessEditorialEssentials for Radiologists on COVID-19: An Update—Radiology Scientific Expert PanelJeffrey P. Kanne , Brent P. Little, Jonathan H. Chung, Brett M. Elicker, Loren H. KetaiJeffrey P. Kanne , Brent P. Little, Jonathan H. Chung, Brett M. Elicker, Loren H. KetaiAuthor AffiliationsFrom the Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, MC 3252, Madison, WI 53792-3252 (J.P.K.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (B.P.L.); Department of Radiology, University of Chicago, Chicago, Ill (J.H.C.); Department of Radiology, University of California San Francisco, San Francisco, Calif (B.M.E.); and Department of Radiology, University of New Mexico, Albuquerque, NM (L.H.K.).Address correspondence to J.P.K. (e-mail: [email protected]).Jeffrey P. Kanne Brent P. LittleJonathan H. ChungBrett M. ElickerLoren H. KetaiPublished Online:Feb 27 2020https://doi.org/10.1148/radiol.2020200527MoreSectionsPDF ToolsAdd to favoritesCiteTrack Citations ShareShare onFacebookXLinked In Infections by coronavirus disease 2019 (COVID-19) continue to increase in China and worldwide. The betacoronavirus was first reported in December 2019 in Wuhan, China. As of February 24, 2020, the World Health Organization (WHO) reported 78 811 laboratory-confirmed cases, including more than 2200 cases outside of China (1). Public health officials had thought the rate of new cases was slowing, but changes to diagnostic criteria led to an increased rate of new cases. In the past several weeks, many published studies, case series, and case reports have increased our knowledge of the clinical and radiologic manifestations of this infection. The purpose of this summary is to provide an update regarding recent information relevant to the radiologist.Most patients with lower respiratory tract infection caused by COVID-19 present with fever, cough, dyspnea, and myalgia. Acute respiratory distress syndrome is present in 17%–29% of patients (2,3). The fatality rate is estimated to be approximately 2.3%. One retrospective study (4) estimated the R0, or the average number of new infections from an infected person to a naive population, to be 3.28, which exceeds WHO estimates of 1.4–2.5. Values greater than 1.0 indicate the infection will likely spread rather than diminish. R0 values estimated from later studies tend to be more reliable due to increased awareness and intervention.The varied findings on chest radiographs remain difficult to interpret because of nonstandard and vague terminology such as “airspace disease,” “pneumonia,” “infiltrates,” “patchy opacities,” and “hazy opacities” (3,5). The more straightforward descriptions of CT findings can clarify findings on chest radiographs. The predominant CT findings of COVID-19 infection are bilateral, peripheral, and basal predominant ground-glass opacity, consolidation, or both (6,7). Opacities often have an extensive geographic distribution. Multiple discrete areas of ground-glass opacity, consolidation, or both occur in a subset of patients—often with round morphology or a reversed halo or atoll sign (https://pubs.rsna.org/2019-nCoV#images). Pleural effusion, extensive tiny lung nodules, and lymphadenopathy occur in a very small number of cases and are suggestive of bacterial superinfection or another diagnosis.Several investigators have reported on short-term CT follow-up of patients with COVID-19 infection. Pan et al (7) described the temporal evolution of 21 patients who recovered from COVID-19. Early-stage CT findings (0–4 days after symptom onset) from 24 CT scans were no lung opacities (17%), focal ground-glass opacity or consolidation (42%), or multifocal lung opacity (42%). Approximately 50% of patients had peripheral predominant lung opacities. Serial CT scans during middle stages of illness (5–13 days) showed progression of lung opacities. Peak lung involvement was characterized by development of crazy-paving pattern (19%), new or increasing lung consolidation (91%), and higher rates of bilateral and multilobar involvement (86%). Late-stage CT findings (14 days or longer) showed varying degrees of clearing but no resolution up to at least 26 days. Bernheim et al (6) report similar findings in a retrospective review of serial CT scans in 121 patients from four different medical centers in China. CT scans were normal in 20 of 36 patients (56%) within 0–2 days after onset of symptoms, yet only one of those 36 patients had negative findings at the initial real-time reverse-transcription polymerase chain reaction (RT-PCR) test for COVID-19.The RT-PCR test for COVID-19 is believed to have high specificity; however, sensitivity has been reported to be as low as 60%–70% (8,9). Thus, excluding a diagnosis of COVID-19 requires multiple negative tests, with test kits in short supply or unavailable in some regions of China. In response to reports of lung abnormalities on CT scans predating conversion to positive RT-PCR results, Chinese authorities initially broadened the official definition of infection to include patients with typical findings at CT, even with a first negative RT-PCR result. This broader definition has resulted in a higher number of presumptive cases of COVID-19 and an increasing role for CT in diagnosis. However, the presence of mild or no CT findings in many early cases of infection highlights the difficulties of early detection (6,10).In summary, COVID-19 infection causes a severe lower respiratory tract infection with bilateral, basal, and peripheral predominant ground-glass opacity, consolidation, or both as the most common reported CT findings—features typical of an organizing pneumonia pattern of lung injury. These findings peak around 9–13 days and slowly begin to resolve thereafter (Figure).The importance of CT for detecting COVID-19 infection continues to increase as public health authorities grapple with the clinical complexities of early diagnosis. Future challenges include distinguishing COVID-19 infection from other conditions that manifest with similar findings at radiography and CT. Serial CT imaging shows the progression of lung abnormalities with the development of crazy-paving and increase in consolidation, more extensive lung involvement, and slow resolution—the typical evolution of acute lung injury. The character and extent of abnormalities beyond 4 weeks remains unknown, but one can expect similarities to other acute lung injuries with resolution or residual scar. Furthermore, detailed pathologic analysis of patients infected with or who died of COVID-19 infection remains unreported. We advise all radiologists to be aware of typical chest CT findings of COVID-19 (https://pubs.rsna.org/2019-ncov). In the appropriate setting of patient exposure or in areas of endemic disease, chest CT findings have played a key role in the evaluation of COVID-19 infection.Summary of essential points for radiologists regarding CT findings of coronavirus disease 2019 (COVID-19). RT-PCR = reverse-transcription polymerase chain reaction.Download as PowerPointDisclosures of Conflicts of Interest: J.P.K. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: is a paid consultant for Parexel International. Other relationships: disclosed no relevant relationships. B.P.L. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: receives royalties from Elsevier. Other relationships: disclosed no relevant relationships. J.H.C. disclosed no relevant relationships. B.M.E. disclosed no relevant relationships. L.H.K. disclosed no relevant relationships.References1. World Health Organization. Novel Coronavirus (COVID-19) Situation Report 34. Geneva, Switzerland: World Health Organization, 2020. Google Scholar2. Chen N, Zhou M, Dong X, et al. 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Link, Google ScholarArticle HistoryReceived: Feb 16 2020Revision requested: Feb 20 2020Revision received: Feb 20 2020Accepted: Feb 26 2020Published online: Feb 27 2020Published in print: Aug 2020 FiguresReferencesRelatedDetailsCited ByAuto-detection of the coronavirus disease by using deep convolutional neural networks and X-ray photographsAhmad MohdAzizHussein, Abdulrauf GarbaSharifai, Osama Moh’dAlia, LaithAbualigah, Khaled H.Almotairi, Sohaib K. 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