Background There is lack of guidance on specific CT protocols for imaging patients with coronavirus disease 2019 (COVID-19) pneumonia. Purpose To assess international variations in CT utilization, protocols, and radiation doses in patients with COVID-19 pneumonia. Materials and Methods In this retrospective data collection study, the International Atomic Energy Agency (IAEA) coordinated a survey between May and July 2020 regarding CT utilization, protocols, and radiation doses from 62 healthcare sites in 34 countries across five continents for CT exams performed in COVID-19 pneumonia. The questionnaire obtained information on local prevalence, method of diagnosis, most frequent imaging, indications for CT, and specific policies on use of CT in COVID-19 pneumonia. Collected data included general information (patient age, weight, clinical indication), CT equipment (CT make and model, year of installation, number of detector rows), scan protocols (body region, scan phases, tube current and potential), and radiation dose descriptors (CT dose index (CTDI vol ) and dose length product (DLP)). Descriptive statistics and generalized estimating equations were performed. Results Data from 782 patients (median age (interquartile range) of 59(15) years) from 54 healthcare sites in 28 countries were evaluated. Less than one-half of the healthcare sites used CT for initial diagnosis of COVID-19 pneumonia and three-fourth used CT for assessing disease severity. CTDI vol varied based on CT vendors (7-11mGy, p<0.001), number of detector-rows (8-9mGy, p<0.001), year of CT installation (7-10mGy, p=0.006), and reconstruction techniques (7-10mGy, p=0.03). Multiphase chest CT exams performed in 20% of sites (11 of 54) were associated with higher DLP compared with single-phase chest CT exams performed in 80% (43 of 54 sites) (p=0.008). Conclusion CT use, scan protocols, and radiation doses in patients with COVID-19 pneumonia showed wide variation across healthcare sites within the same and different countries. Many patients were scanned multiple times and/or with multiphase CT scan protocols. See also the editorial by Lee .
Highlights Holistic information in COVID-19 patients with imaging and non-imaging data can help predict patient outcome in terms of the need for ICU admission. Validation of model over multiple sites is important to establish its generalizablity. Both volume and radiomic features of pulmonary opacities are key to quantifying the extent of lung involvement.
Purpose To compare prediction of disease outcome, severity, and patient triage in COVID-19 pneumonia with whole lung radiomics, radiologists’ interpretation, and clinical variables. Methods Our IRB-approved retrospective study included 315 adult patients (mean age 56 (21-100) years, 190 males, 125 females) with COVID-19 pneumonia who underwent non-contrast chest CT. All patients (inpatients, n=210; outpatients, n=105) were followed up for at least two-weeks to record disease outcome. Clinical variables such as presenting symptoms, laboratory data, peripheral oxygen saturation, and comorbid diseases were recorded. Two radiologists assessed each CT in consensus and graded the extent of pulmonary involvement (by percentage of involved lobe) and type of opacities within each lobe. We obtained radiomics for the entire lung and multiple logistic regression analyses with areas under the curve (AUC) as outputs were performed. Results Most patients (276/315,88%) recovered from COVID-19 pneumonia; 36/315 patients (11%) died and 3/315 patients (1%) remain admitted in the hospital. Radiomics differentiated chest CT in outpatient vs inpatient with an AUC of 0.84 (p<0.005), while radiologists’ interpretations of disease extent and opacity type had an AUC of 0.69 (p<0.0001). Whole lung radiomics were superior to the radiologists’ interpretation for predicting patient outcome in terms of ICU admission (AUC:0.75 vs 0.68) and death (AUC:0.81 vs 0.68) (p<0.002). Addition of clinical variables to radiomics improved the AUC to 0.84 for predicting ICU admission. Conclusion Radiomics from non-contrast chest CT were superior to radiologists’ assessment of extent and type of pulmonary opacities in predicting COVID-19 pneumonia outcome, disease severity, and patient triage.
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