To demonstrate the accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of coronavirus disease 2019 infection in patients in the emergency department. Materials and Methods:This was a Health Insurance Portability and Accountability Act-compliant, institutional review board-approved retrospective study. From March 14 to 24, 2020, 192 patients in the emergency department with symptoms suggestive of COVID-19 infection were studied by using low-dose chest CT and real-time reverse transcription polymerase chain reaction (RT-PCR). Image analysis included the likelihood of COVID-19 infection and the semiquantitative extent of lung involvement. CT images were analyzed by two radiologists blinded to the RT-PCR results. Reproducibility was assessed using the McNemar test and intraclass correlation coefficient. Time between CT acquisition and report was measured.Results: When compared with RT-PCR, low-dose submillisievert chest CT demonstrated excellent sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosis of COVID-19 (86.7%, 93.6%, 91.1%, 90.3%, and 90.2%, respectively), in particular in patients with clinical symptoms for more than 48 hours (95.6%, 93.2%, 91.5%, 96.5%, and 94.4%, respectively). In patients with a positive CT result, the likelihood of disease increased from 43.2% (pretest probability) to 91.1% or 91.4% (posttest probability), while in patients with a negative CT result, the likelihood of disease decreased to 9.6% or 3.7% for all patients or those with clinical symptoms for .48 hours. The prevalence of alternative diagnoses based on chest CT in patients without COVID-19 infection was 17.6%. The mean effective radiation dose was 0.56 mSv 6 0.25 (standard deviation). Median time between CT acquisition and report was 25 minutes (interquartile range: 13-49 minutes). Intra-and interreader reproducibility of CT was excellent (all intraclass correlation coefficients  0.95) without significant bias in the Bland-Altman analysis. Conclusion:Low-dose submillisievert chest CT allows for rapid, accurate, and reproducible assessment of COVID-19 infection in patients in the emergency department, in particular in patients with symptoms lasting longer than 48 hours. Chest CT has the additional advantage of offering alternative diagnoses in a significant subset of patients.

To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients. Materials and Methods: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 15 to June 1, 2020, 250 RT-PCR confirmed COVID-19 patients were studied with low-dose chest CT at admission. Visual and AI-assisted analysis of lung involvement was performed by using a semi-quantitative CT score and a quantitative percentage of lung involvement. Adverse outcome was defined as intensive care unit (ICU) admission or death. Cox regression analysis, Kaplan-Meier curves, and cross-validated receiver operating characteristic curve with area under the curve (AUROC) analysis was performed to compare model performance. Intraclass correlation coefficients (ICCs) and Bland-Altman analysis was used to assess intra-and interreader reproducibility. Results: Adverse outcome occurred in 39 patients (11 deaths, 28 ICU admissions). AUC values from AI-assisted analysis were significantly higher than those from visual analysis for both semiquantitative CT scores and percentages of lung involvement (all P<0.001). Intrareader and interreader agreement rates were significantly higher for AI-assisted analysis than visual analysis (all ICC 0.960 versus 0.885). AI-assisted variability for quantitative percentage of lung involvement was 17.2% (coefficient of variation) versus 34.7% for visual analysis. The sample size to detect a 5% change in lung involvement with 90% power and an  error of 0.05 was 250 patients with AI-assisted analysis and 1014 patients with visual analysis. Conclusion: AI-assisted analysis of lung involvement on submillisievert low-dose chest CT outperformed conventional visual analysis in predicting outcome in COVID-19 patients while I n p r e s s 3 reducing CT variability. Lung involvement on chest CT could be used as a reliable metric in future clinical trials.

A 56-year-old woman was found hypothermic on her bathroom floor with a scalp wound, with laboratory results indicating long lie. She was lethargic and had difficulties finding words. CT scan revealed symmetric posterior temporal lobe hypodensities with punctiform hemorrhagic transformation (figure). Radiologic differential diagnosis included encephalitis, 1 but CSF showed normal cytosis, xanthochromia, and elevated protein. Contusions are the most common intra-axial injuries, caused by sudden deceleration and impact of the brain against bone or dura mater. 2 In this case, the impact occurred symmetrically against the tentorium cerebelli, presumably caused by a fall straight on the vertex while the patient was exiting the bathtub.