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OBJECTIVES: Both Reporting and Data System (CO-RADS) and CT-involvement scores (CTIS) have been proposed for evaluation of COVID-19 on chest CT. The purpose of this single-center, retrospective study was to evaluate both scoring systems to diagnose COVID-19 infection in a high-prevalence area. MATERIALS AND METHODS: Chest CT datasets (n = 200) and available reverse transcription polymerase chain reaction (RT-PCR) on nasopharyngeal swab were included. CT scans were assigned to four 'imaging groups' after scoring for both CO-RADS and CTIS. Diagnostic accuracy of chest CT was calculated respectively using RT-PCR and clinical diagnosis as gold standards: False-negatives and false-positives of chest CT regarding RT-PCR were studied in more depth using the medical files. RESULTS: The 'imaging group' including CO-RADS 4/5 scores reached the highest diagnostic values for COVID-19 considering either the initial RT-PCR or the final clinical diagnosis as the standard of reference: accuracies of 172/200 (86%) to 181/200 (90.5%), sensitivities of 60/80 (88.2%) to 70/79 (88.6%), specificities of 112/132 (84.9%) to 111/121 (91.7%), negative predictive values (NPV) of 112/120 (93.3%) to 111/120 (92.5%), respectively. False-negative CTs regarding RT-PCR were mainly explained by imaging very early in the disease course (5 out of 8 cases) or COVID-19 infection with no/minor respiratory symptoms (3 out of 8 cases). CONCLUSION: Assessing chest CT using CO-RADS is a valuable diagnostic approach for COVID-19 infection in a high-prevalence area, with a higher accuracy than CTIS.
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PURPOSE: The aim of this study is to compare a qualitative and a quantitative assessment of brain diffusion-weighted imaging (DWI) in predicting outcome of comatose patients after cardiac arrest (CA). METHODS: Two observers used a scoring template to analyze the DWI of 75 patients. A total of 13 regions were scored from 0 to 3 (0 = normal, 1 = probably normal, 2 = probably abnormal, 3 = definitely abnormal). The total cerebral cortex (TCC), the total deep grey nuclei (TDGN), the total brain stem, the total cerebellum, and the total brain score were calculated. Intra- and inter-observer variability were tested. The mean whole brain apparent diffusion coefficient (ADC) values and percentage of voxels below a specific ADC value cut-off were calculated. The data were correlated with clinical outcome (cerebral performance category score after 180 days, dichotomized in a score 1-2 with favorable outcome and score 3-5 with unfavorable outcome) using ROC analysis. RESULTS: Intra-observer variability was excellent for the TCC score (ICC 0.95 and 0.86) and the TDGN score (ICC 0.89 and 0.75). Inter-observer variability was good to excellent for total cerebral cortex score and total deep grey nuclei score in both the first (ICC 0.78 and 0.69) and third (ICC 0.86 and 0.83) image assessment. TCC and TDGN score show the best correlation with clinical outcome (highest AUC values 0.87 and 0.87). Quantitative parameters did not show good correlation with clinical outcome (AUC values 0.57 and 0.60). CONCLUSION: A qualitative assessment of brain DWI using a scoring template provides useful data regarding patient outcome while quantitative data appeared less reliable.