CT imaging of coronavirus disease 2019 (COVID-19): from the qualitative to quantitative

Qi, Xiaolong; Lei, Junqiang; Yu, Qian; Xi, Yarong; Wang, Yuancheng; Ju, Shenghong

doi:10.21037/atm.2020.02.91

Cited by 15 publications

(13 citation statements)

References 9 publications

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“…An overall lung involvement score was reached by summing the 5 lobe scores (0-20). Besides, quantitative CT assessment methods and artificial intelligence applications can be successfully applied in the diagnosis of COVID-19 and in the evaluation of disease severity [37,52,53].…”

Section: The Severity Of Pulmonary Involvement On Ctmentioning

confidence: 99%

Chest CT features of the novel coronavirus disease (COVID-19)

Ufuk¹,

Savaş²

2020

Turk J Med Sci

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A new type of coronavirus (2019-nCoV) is rapidly spreading worldwide and causes pneumonia, respiratory distress, thromboembolic events, and death. Chest computed tomography (CT) plays an essential role in the diagnosis of viral pneumonia, monitoring disease progression, determination of disease severity, and evaluating therapeutic efficacy. Chest CT can show important clues of 2019-nCoV disease (also known as COVID-19) in patients with an appropriate clinic. Prompt diagnosis of COVID-19 is essential to prevent disease transmission and provides close clinical observation of patients with clinically severe disease. Therefore, radiologists and clinicians should be familiar with the CT imaging findings of COVID-19 pneumonia. Herein, we aimed to review the imaging findings of COVID-19 pneumonia and examine the critical points to be considered for imaging in cases with COVID-19 suspicion.

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Section: The Severity Of Pulmonary Involvement On Ctmentioning

confidence: 99%

Chest CT features of the novel coronavirus disease (COVID-19)

Ufuk¹,

Savaş²

2020

Turk J Med Sci

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“…However, how to accurately evaluate disease scope with CT imaging is a problem. This is where artificial intelligence (AI) may be a good new technique to quantitatively evaluate the disease [36].…”

Section: Role Of Chest Ct In the Diagnosis And Follow Up Of Covid-19mentioning

confidence: 99%

Chest CT features and their role in COVID-19

2020

Radiology of Infectious Diseases

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“…The clinical spectrum of COVID-19 pneumonia ranges from mild to critical cases, among which the diagnosis of ordinary, severe and critical cases were all correlated with chest CT findings 5,6 . Previously published studies have described the general typical and atypical CT image manifestations 6,7 , the time-course evolution of CT findings 8,9 , the correlation between CT features and clinical features 1,10 , and evaluated the CT severity of patients with COVID pneumonia 8,[11][12][13][14][15][16][17] . In order to reduce or eliminate the subjectivity in the qualitative and semi-quantitative visual evaluation of CT severity scores 8,15,17 , quantitative approaches for assessing lung opacification percentage of the whole lung have developed, such as deep learning method 18 , computer tool 16 or the calculation method of combing mean attenuation values and opacity volumes 14 .…”

Section: A C C E P T E D Introductionmentioning

confidence: 99%

The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics

et al. 2020

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This paper can be cited using the date of access and the unique DOI number which can be found in the footnotes. Objectives: To assess the clinical severity of COVID-19 pneumonia using qualitative and/or quantitative chest CT indicators and identify the CT characteristics of critical cases. Materials and Methods: Fifty-one patients with COVID-19 pneumonia including ordinary cases (group A,n=12), severe cases(group B, n=15) and critical cases (group C,n=24) were retrospectively enrolled. The qualitative and quantitative indicators from chest CT were recorded and compared using Fisher's exact test, one-way ANOVA, Kruskal-Wallis H test and receiver operating characteristic analysis. Results: Depending on the severity of the disease, the number of involved lung segments and lobes, the frequencies of consolidation, crazy-paving pattern and air bronchogram increased in more severe cases. Qualitative indicators including total severity score for the whole lung and total score for crazy-paving and consolidation could distinguish groups B and C from A(69% sensitivity, 83% specificity and 73% accuracy) but were similar between group B and group C. Combined qualitative and quantitative indicators could distinguish these three groups with high sensitivity(B+C vs.A ,90%; C vs. B, 92%),specificity(100%, 87%) and accuracy(92%, 90%). Critical cases had higher total severity score(>10) and higher total score for crazy-paving and consolidation(>4) than ordinary cases, and had higher mean lung density(>-779HU) and full width at half maximum(>128HU) but lower relative volume of normal lung density(≦50%) than ordinary/severe cases. In our critical cases, eight patients with relative volume of normal lung density smaller than 40% received mechanical ventilation for supportive treatment, and two of them had died.

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CT imaging of coronavirus disease 2019 (COVID-19): from the qualitative to quantitative

Cited by 15 publications

References 9 publications

Chest CT features of the novel coronavirus disease (COVID-19)

Chest CT features of the novel coronavirus disease (COVID-19)

Chest CT features and their role in COVID-19

The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics

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