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Introduction The nasopharynx and oropharynx are the main colonization sites of coronavirus. Therefore, patients with paranasal sinuses and pharyngeal problems (ear, nose, and throat [ENT] patients) predispose coronavirus infection. Ear, nose, and throat patients with concomitant asymptomatic coronavirus infection may develop severe pneumonia following surgical procedures. As a result, presurgical screening for coronavirus infection is a substantial concern. Objective We evaluated the usefulness of a spiral chest computed tomography (CT) scan in the diagnosis of asymptomatic coronavirus infection in the presurgical assessment of ENT patients Methods In this study, candidates of paranasal sinus or pharyngeal surgery were evaluated for coronavirus infection. Patients with neither history of coronavirus disease 2019 (COVID-19) nor compatible symptoms and signs were screened for asymptomatic coronavirus infection. These patients composed two groups: the first group underwent a reverse transcription polymerase chain reaction (RT-PCR) test of nasopharyngeal sample and spiral chest CT scan, but for the second one, only the latter was performed. Results In the first group, which consisted of 106 patients, 11 (10.4%) cases had positive RT-PCR test results, and 17 (16%) patients showed positive findings in favor of coronavirus infection in the spiral chest CT scan. In the second group, which consisted of 173 patients, 34 (19.7%) cases had positive chest CT scan results. Conclusion The chest CT scan has a valuable role in the early diagnosis of asymptomatic coronavirus carriers in patients highly predisposed to infection, especially in low resource areas, where the RT-PCR test is unavailable.
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The Coronavirus disease 2019 (COVID-19) presents open questions in how we clinically diagnose and assess disease course. Recently, chest computed tomography (CT) has shown utility for COVID-19 diagnosis. In this study, we developed Deep COVID DeteCT (DCD), a deep learning convolutional neural network (CNN) that uses the entire chest CT volume to automatically predict COVID-19 (COVID+) from non-COVID-19 (COVID-) pneumonia and normal controls. We discuss training strategies and differences in performance across 13 international institutions and 8 countries. The inclusion of non-China sites in training significantly improved classification performance with area under the curve (AUCs) and accuracies above 0.8 on most test sites. Furthermore, using available follow-up scans, we investigate methods to track patient disease course and predict prognosis.
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BACKGROUND: Chest computed tomography (CT) scan has been used widely to diagnose COVID-19 in Iran. OBJECTIVES: To trace the footsteps of COVID-19 in Iran by exploring the trend in using chest CT scans and its economic impact on radiology departments. Methods: In this cross-sectional study, the number of imaging examinations from 33 tertiary radiology departments in 9 large cities of Iran was collected from September 23, 2019 to March 20, 2020 (Months 1 to 6) and the corresponding months in 2018-2019. RESULTS: A 50.2% increase was noted in the chest CT scan utilization in 2019-2020 compared to 2018-2019. This increase was +15%, +15%, +27%, +2%, +1% in Months 1-5 of 2019-2020, respectively. In Month 6 of 2019-2020, a 251% increase in the acquisition of chest CT scans was observed compared to the Month 6 of 2018-2019. Following negative balance of revenue from Month 1 to 5 with respect to the inflation rate, the total income in Month 6 was further 1.5% less than the same Month in 2018-19. CONCLUSION: The observed peak in chest CT utilization in Month 3 prior to the surge in Month 6 could be explained by the seasonal influenza. However, unawareness about an emerging viral disease, i.e. COVID-19, might have underutilized chest CT in Months 4 and 5 before the official announcement in Month 6. The unbalanced increase in the workload of radiology departments in the shortage of cardiothoracic radiologists with the simultaneous decrease in income initiated a vicious cycle that worsened the economic repercussions of the pandemic.