Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT

Abstract

Background Despite its high sensitivity in diagnosing coronavirus disease 2019 (COVID-19) in a screening population, the chest CT appearance of COVID-19 pneumonia is thought to be nonspecific. Purpose To assess the performance of radiologists in the United States and China in differentiating COVID-19 from viral pneumonia at chest CT. Materials and Methods In this study, 219 patients with positive COVID-19, as determined with reverse-transcription polymerase chain reaction (RT-PCR) and abnormal chest CT findings, were retrospectively identified from seven Chinese hospitals in Hunan Province, China, from January 6 to February 20, 2020. Two hundred five patients with positive respiratory pathogen panel results for viral pneumonia and CT findings consistent with or highly suspicious for pneumonia, according to original radiologic interpretation within 7 days of each other, were identified from Rhode Island Hospital in Providence, RI. Three radiologists from China reviewed all chest CT scans (n = 424) blinded to RT-PCR findings to differentiate COVID-19 from viral pneumonia. A sample of 58 age-matched patients was randomly selected and evaluated by four radiologists from the United States in a similar fashion. Different CT features were recorded and compared between the two groups. Results For all chest CT scans (n = 424), the accuracy of the three radiologists from China in differentiating COVID-19 from non-COVID-19 viral pneumonia was 83% (350 of 424), 80% (338 of 424), and 60% (255 of 424). In the randomly selected sample (n = 58), the sensitivities of three radiologists from China and four radiologists from the United States were 80%, 67%, 97%, 93%, 83%, 73%, and 70%, respectively. The corresponding specificities of the same readers were 100%, 93%, 7%, 100%, 93%, 93%, and 100%, respectively. Compared with non-COVID-19 pneumonia, COVID-19 pneumonia was more likely to have a peripheral distribution (80% vs 57%, P < .001), ground-glass opacity (91% vs 68%, P < .001), fine reticular opacity (56% vs 22%, P < .001), and vascular thickening (59% vs 22%, P < .001), but it was less likely to have a central and peripheral distribution (14% vs 35%, P < .001), pleural effusion (4% vs 39%, P < .001), or lymphadenopathy (3% vs 10%, P = .002). Conclusion Radiologists in China and in the United States distinguished coronavirus disease 2019 from viral pneumonia at chest CT with moderate to high accuracy. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

Figures

Figure 1:

Illustration of study flow RIH: Rhode Island Hospital

Figure 2:

Distribution of viral pathogens based on RPP test in the final cohort. It is an FDA approved assay that simultaneous detects 19 viruses (influenza A virus; influenza A H1 virus; influenza A 2009 H1 virus; influenza A H3 virus; influenza B virus; adenovirus; coronaviruses [HKU1, OC43, NL63, and 229E]; human rhinovirus/enterovirus; human metapneumovirus; parainfluenza viruses 1, 2, 3, and 4; and respiratory syncytial virus [RSV] [RSV subtype A and RSV subtype B]) and 2 bacteria (Mycoplasma pneumoniae and Chlamydia pneumoniae). The ePlex panel (16) has been proven to be a highly sensitive and specific multiplex assay for respiratory pathogen detection. In a multicentric study, the positive percent agreement values (equivalent to sensitivity when a perfect reference method is unavailable) ranged from 85.1% to 95.1% and the negative percent agreement values (equivalent to specificity) ranged from 99.5% to 99.8% when compared to another well-established RP panel from BioFire (Salt Lack City, UT) (17).

Figure 3a:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3b:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3c:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3d:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3e:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3f:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3g:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)

Figure 3h:

A. Cases in a 58-patient review process that are commonly misdiagnosed. Example cases where the majority of radiologists mistook non-COVID-19 pneumonia for COVID-19 (A and B) or other vice versa (C-H)