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The disease caused by the new coronavirus, or COVID-19, has been recently described and became a health issue worldwide. Its diagnosis of certainty is given by polymerase chain reaction. High-resolution computed tomography, however, is useful in the current context of pandemic, especially for the most severe cases, in assessing disease extent, possible differential diagnoses and searching complications. In patients with suspected clinical symptoms and typical imaging findings, in which there is still no laboratory test result, or polymerase chain reaction is not available, the role of this test is still discussed. In addition, it is important to note that part of the patients present false-negative laboratory tests, especially in initial cases, which can delay isolation, favoring the spread of the disease. Thus, knowledge about the COVID-19 and its imaging manifestations is extremely relevant for all physicians involved in the patient care, clinicians or radiologists.

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Background: An expert consensus recently proposed a standardized coronavirus disease 2019 (COVID-19) reporting language for computed tomography (CT) findings of COVID-19 pneumonia. Purpose: The purpose of the study was to evaluate the performance of CT in differentiating COVID-19 from other viral infections using a standardized reporting classification. Methods: A total of 175 consecutive patients were retrospectively identified from a single tertiary-care medical center from March 15 to March 24, 2020, including 87 with positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19 and 88 with negative COVID-19 RT-PCR test, but positive respiratory pathogen panel. Two thoracic radiologists, who were blinded to RT-PCR and respiratory pathogen panel results, reviewed chest CT images independently and classified the imaging findings under 4 categories: “typical” appearance, “indeterminate,” “atypical,” and “negative” for pneumonia. The final classification was based on consensus between the readers. Results: Patients with COVID-19 were older than patients with other viral infections (P=0.038). The inter-rater agreement of CT categories between the readers ranged from good to excellent, κ=0.80 (0.73 to 0.87). Final CT categories were statistically different among COVID-19 and non-COVID-19 groups (P<0.001). CT “typical” appearance was more prevalent in the COVID-19 group (64/87, 73.6%) than in the non-COVID-19 group (2/88, 2.3%). When considering CT “typical” appearance as a positive test, a sensitivity of 73.6% (95% confidence interval [CI]: 63%-82.4%), specificity of 97.7% (95% CI: 92%-99.7%), positive predictive value of 97% (95% CI: 89.5%-99.6%), and negative predictive value of 78.9% (95% CI: 70%-86.1%) were observed. Conclusion: The standardized chest CT classification demonstrated high specificity and positive predictive value in differentiating COVID-19 from other viral infections when presenting a “typical” appearance in a high pretest probability environment. Good to excellent inter-rater agreement was found regarding the CT standardized categories between the readers.

Objective: To evaluate anthropometric and clinical data, muscle mass, subcutaneous fat, spine bone mineral density, extent of acute pulmonary disease related to COVID-19, quantification of pulmonary emphysema, coronary calcium, and hepatic steatosis using chest computed tomography of hospitalized patients with confirmed diagnosis of COVID-19 pneumonia and verify its association with disease severity. Methods: A total of 123 adults hospitalized due to COVID-19 pneumonia were enrolled in the present study, which evaluated the anthropometric, clinical and chest computed tomography data (pectoral and paravertebral muscle area and density, subcutaneous fat, thoracic vertebral bodies density, degree of pulmonary involvement by disease, coronary calcium quantification, liver attenuation measurement) and their association with poorer prognosis characterized through a combined outcome of intubation and mechanical ventilation, need of intensive care unit, and death. Results: Age (p=0.013), body mass index (p=0.009), lymphopenia (p=0.034), and degree of pulmonary involvement of COVID-19 pneumonia (p<0.001) were associated with poor prognosis. Extent of pulmonary involvement by COVID-19 pneumonia had an odds ratio of 1,329 for a poor prognosis and a cutoff value of 6.5 for increased risk, with a sensitivity of 64.9% and specificity of 67.1%. Conclusion: The present study found an association of high body mass index, older age, extent of pulmonary involvement by COVID-19, and lymphopenia with severity of COVID-19 pneumonia in hospitalized patients.

Figure 2. Bedside anteroposterior chest X-ray images demonstrate the radiographic evolution of the nosocomial infection with multiple areas of consolidation in both lungs

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