Characteristic CT findings distinguishing 2019 novel coronavirus disease (COVID-19) from influenza pneumonia

Wang, Hao; Wei, Ran; Rao, Guihua; Zhu, Jie; Song, Bin

doi:10.1007/s00330-020-06880-z

Cited by 100 publications

(100 citation statements)

References 31 publications

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“…The interpretation of chest CT examinations may become particularly challenging during influenza season. Some studies suggest that a peripheral distribution of ground-glass opacities is a more typical finding of COVID-19 pneumonia (76)(77)(78), whereas other studies did not find these features helpful in discriminating COVID-19 pneumonia from influenza pneumonia (79).…”

Section: Diagnostic Accuracy Of Chest Ctmentioning

confidence: 99%

Chest CT in COVID-19: What the Radiologist Needs to Know

2020

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Chest CT has a potential role in the diagnosis, detection of complications, and prognostication of coronavirus disease 2019 (COVID-19). Implementation of appropriate precautionary safety measures, chest CT protocol optimization, and a standardized reporting system based on the pulmonary findings in this disease will enhance the clinical utility of chest CT. However, chest CT examinations may lead to both false-negative and false-positive results. Furthermore, the added value of chest CT in diagnostic decision making is dependent on several dynamic variables, most notably available resources (real-time reverse transcription-polymerase chain reaction [RT-PCR] tests, personal protective equipment, CT scanners, hospital and radiology personnel availability, and isolation room capacity) and the prevalence of both COVID-19 and other diseases with overlapping manifestations at chest CT. Chest CT is valuable to detect both alternative diagnoses and complications of COVID-19 (acute respiratory distress syndrome, pulmonary embolism, and heart failure), while its role for prognostication requires further investigation. The authors describe imaging and managing care of patients with COVID-19, with topics including (a) chest CT protocol, (b) chest CT findings of COVID-19 and its complications, (c) the diagnostic accuracy of chest CT and its role in diagnostic decision making and prognostication, and (d) reporting and communicating chest CT findings. The authors also review other specific topics, including the pathophysiology and clinical manifestations of COVID-19, the World Health Organization case definition, the value of performing RT-PCR tests, and the radiology department and personnel impact related to performing chest CT in COVID-19. ©

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Section: Diagnostic Accuracy Of Chest Ctmentioning

confidence: 99%

Chest CT in COVID-19: What the Radiologist Needs to Know

2020

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“…25,55 The differential diagnosis of COVID-19 pneumonia from other forms of viral pneumonia requires a careful evaluation of all clinical information, radiological pattern, and exposure history. [56][57][58][59] In this scenario, the implementation of Artificial Intelligence algorithms into radiologist workflow has shown promising results in improving diagnostic outcomes. 60,61 Nevertheless, the use of chest CT as a screening test in low disease prevalence regions may lead to a high number of false positive results with further unnecessary downstream diagnostic testing, increased healthcare costs and overload of the healthcare system.…”

Section: Diagnostic Performance Of Ct In the Diagnosis Of Covid-19 Pnmentioning

confidence: 99%

Role of computed tomography in COVID-19

Pontone

Scafuri

Mancini

et al. 2021

Journal of Cardiovascular Computed Tomography

118

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Coronavirus disease 2019 (COVID-19) has become a rapid worldwide pandemic. While COVID-19 primarily manifests as an interstitial pneumonia and severe acute respiratory distress syndrome, severe involvement of other organs has been documented. In this article, we will review the role of non-contrast chest computed tomography in the diagnosis, follow-up and prognosis of patients affected by COVID-19 pneumonia with a detailed description of the imaging findings that may be encountered. Given that patients with COVID-19 may also suffer from coagulopathy, we will discuss the role of CT pulmonary angiography in the detection of acute pulmonary embolism. Finally, we will describe more advanced applications of CT in the differential diagnosis of myocardial injury with an emphasis on ruling out acute coronary syndrome and myocarditis.

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“…One key factor has been proven to be the rapid and accurate identification of infected patients and their isolation among with social distancing for the general population [ 4 , 5 ]. While reverse-transcription polymerase chain reaction (RT-PCR) remains up to date the main diagnostic tool, the role of computed tomography (CT) of the chest as a complementary method or even a reliable alternative is increasingly recognized, given the vast numbers of potential carriers of the disease [ [6] , [7] , [8] , [9] , [10] ].…”

Section: Introductionmentioning

confidence: 99%

Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography

Javor

Kaplan

et al. 2020

European Journal of Radiology

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Introduction Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and risk stratification of the disease. Methods A novel deep learning derived machine learning (ML) classifier was developed using a simplified programming approach and an open source dataset consisting of 6868 chest CT images from 418 patients which was split into training and validation subsets. The diagnostic performance was then evaluated and compared to experienced radiologists on an independent testing dataset. Diagnostic performance metrics were calculated using Receiver Operating Characteristics (ROC) analysis. Operating points with high positive (>10) and low negative (<0.01) likelihood ratios to stratify the risk of COVID-19 being present were identified and validated. Results The model achieved an overall accuracy of 0.956 (AUC) on an independent testing dataset of 90 patients. Both rule-in and rule out thresholds were identified and tested. At the rule-in operating point, sensitivity and specificity were 84.4% and 93.3% and did not differ from both radiologists (p > 0.05). At the rule-out threshold, sensitivity (100%) and specificity (60%) differed significantly from the radiologists (p < 0.05). Likelihood ratios and a Fagan nomogram provide prevalence independent test performance estimates. Conclusion Accurate diagnosis of COVID-19 using a basic deep learning approach is feasible using open-source CT image data. In addition, the machine learning classifier provided validated rule-in and rule-out criteria could be used to stratify the risk of COVID-19 being present.

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Characteristic CT findings distinguishing 2019 novel coronavirus disease (COVID-19) from influenza pneumonia

Abstract: Objectives To investigate the different CT

Cited by 100 publications

References 31 publications

Chest CT in COVID-19: What the Radiologist Needs to Know

Chest CT in COVID-19: What the Radiologist Needs to Know

Role of computed tomography in COVID-19

Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography

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