tetano
Editor, Senior Moderator
Eur Radiol
. 2020 Sep 23.
doi: 10.1007/s00330-020-07273-y. Online ahead of print.
Diagnostic accuracy and interobserver variability of CO-RADS in patients with suspected coronavirus disease-2019: a multireader validation study
Davide Bellini[SUP] 1 2 [/SUP], Nicola Panvini[SUP] 3 [/SUP], Marco Rengo[SUP] 3 [/SUP], Simone Vicini[SUP] 3 [/SUP], Miriam Lichtner[SUP] 4 [/SUP], Tiziana Tieghi[SUP] 4 [/SUP], Dea Ippoliti[SUP] 3 [/SUP], Federica Giulio[SUP] 3 [/SUP], Elena Orlando[SUP] 3 [/SUP], Mario Iozzino[SUP] 5 [/SUP], Maria Grazia Ciolfi[SUP] 5 [/SUP], Sarah Montechiarello[SUP] 5 [/SUP], Ugo d'Ambrosio[SUP] 5 [/SUP], Emanuele d'Adamo[SUP] 5 [/SUP], Chiara Gambaretto[SUP] 5 [/SUP], Stefano Panno[SUP] 5 [/SUP], Vanessa Caldon[SUP] 5 [/SUP], Cesare Ambrogi[SUP] 5 [/SUP], Iacopo Carbone[SUP] 3 [/SUP]
Affiliations
Abstract
Objective: To conduct a multireader validation study to evaluate the interobserver variability and the diagnostic accuracy for the lung involvement by COVID-19 of COVID-19 Reporting and Data System (CO-RADS) score.
Methods: This retrospective study included consecutive symptomatic patients who underwent chest CT and reverse transcriptase-polymerase chain reaction (RT-PCR) from March 2020 to May 2020 for suspected COVID-19. Twelve readers with different levels of expertise independently scored each CT using the CO-RADS scheme for detecting pulmonary involvement by COVID-19. Receiver operating characteristic (ROC) curves were computed to investigate diagnostic yield. Fleiss' kappa statistics was used to evaluate interreader agreement.
Results: A total of 572 patients (mean age, 63 ? 20 [standard deviation]; 329 men; 142 patients with COVID-19 and 430 patients without COVID-19) were evaluated. There was a moderate agreement for CO-RADS rating among all readers (Fleiss' K = 0.43 [95% CI 0.42-0.44]) with a substantial agreement for CO-RADS 1 category (Fleiss' K = 0.61 [95% CI 0.60-0.62]) and moderate agreement for CO-RADS 5 category (Fleiss' K = 0.60 [95% CI 0.58-0.61]). ROC analysis showed the CO-RADS score ≥ 4 as the optimal threshold, with a cumulative area under the curve of 0.72 (95% CI 66-78%), sensitivity 61% (95% CI 52-69%), and specificity 81% (95% CI 77-84%).
Conclusion: CO-RADS showed high diagnostic accuracy and moderate interrater agreement across readers with different levels of expertise. Specificity is higher than previously thought and that could lead to reconsider the role of CT in this clinical setting.
Key points: • COVID-19 Reporting and Data System (CO-RADS) demonstrated a good diagnostic accuracy for lung involvement by COVID-19 with an average AUC of 0.72 (95% CI 67-75%). • When a threshold of ≥ 4 was used, sensitivity and specificity were 61% (95% CI 52-69%) and 81% (95% CI 76-84%), respectively. • There was an overall moderate agreement for CO-RADS rating across readers with different levels of expertise (Fleiss' K = 0.43 [95% CI 0.42-0.44]).
Keywords: COVID-19; ROC curve; Sensitivity and specificity; Severe acute respiratory syndrome coronavirus 2; Tomography, X-ray computed.
. 2020 Sep 23.
doi: 10.1007/s00330-020-07273-y. Online ahead of print.
Diagnostic accuracy and interobserver variability of CO-RADS in patients with suspected coronavirus disease-2019: a multireader validation study
Davide Bellini[SUP] 1 2 [/SUP], Nicola Panvini[SUP] 3 [/SUP], Marco Rengo[SUP] 3 [/SUP], Simone Vicini[SUP] 3 [/SUP], Miriam Lichtner[SUP] 4 [/SUP], Tiziana Tieghi[SUP] 4 [/SUP], Dea Ippoliti[SUP] 3 [/SUP], Federica Giulio[SUP] 3 [/SUP], Elena Orlando[SUP] 3 [/SUP], Mario Iozzino[SUP] 5 [/SUP], Maria Grazia Ciolfi[SUP] 5 [/SUP], Sarah Montechiarello[SUP] 5 [/SUP], Ugo d'Ambrosio[SUP] 5 [/SUP], Emanuele d'Adamo[SUP] 5 [/SUP], Chiara Gambaretto[SUP] 5 [/SUP], Stefano Panno[SUP] 5 [/SUP], Vanessa Caldon[SUP] 5 [/SUP], Cesare Ambrogi[SUP] 5 [/SUP], Iacopo Carbone[SUP] 3 [/SUP]
Affiliations
- PMID: 32968883
- DOI: 10.1007/s00330-020-07273-y
Abstract
Objective: To conduct a multireader validation study to evaluate the interobserver variability and the diagnostic accuracy for the lung involvement by COVID-19 of COVID-19 Reporting and Data System (CO-RADS) score.
Methods: This retrospective study included consecutive symptomatic patients who underwent chest CT and reverse transcriptase-polymerase chain reaction (RT-PCR) from March 2020 to May 2020 for suspected COVID-19. Twelve readers with different levels of expertise independently scored each CT using the CO-RADS scheme for detecting pulmonary involvement by COVID-19. Receiver operating characteristic (ROC) curves were computed to investigate diagnostic yield. Fleiss' kappa statistics was used to evaluate interreader agreement.
Results: A total of 572 patients (mean age, 63 ? 20 [standard deviation]; 329 men; 142 patients with COVID-19 and 430 patients without COVID-19) were evaluated. There was a moderate agreement for CO-RADS rating among all readers (Fleiss' K = 0.43 [95% CI 0.42-0.44]) with a substantial agreement for CO-RADS 1 category (Fleiss' K = 0.61 [95% CI 0.60-0.62]) and moderate agreement for CO-RADS 5 category (Fleiss' K = 0.60 [95% CI 0.58-0.61]). ROC analysis showed the CO-RADS score ≥ 4 as the optimal threshold, with a cumulative area under the curve of 0.72 (95% CI 66-78%), sensitivity 61% (95% CI 52-69%), and specificity 81% (95% CI 77-84%).
Conclusion: CO-RADS showed high diagnostic accuracy and moderate interrater agreement across readers with different levels of expertise. Specificity is higher than previously thought and that could lead to reconsider the role of CT in this clinical setting.
Key points: • COVID-19 Reporting and Data System (CO-RADS) demonstrated a good diagnostic accuracy for lung involvement by COVID-19 with an average AUC of 0.72 (95% CI 67-75%). • When a threshold of ≥ 4 was used, sensitivity and specificity were 61% (95% CI 52-69%) and 81% (95% CI 76-84%), respectively. • There was an overall moderate agreement for CO-RADS rating across readers with different levels of expertise (Fleiss' K = 0.43 [95% CI 0.42-0.44]).
Keywords: COVID-19; ROC curve; Sensitivity and specificity; Severe acute respiratory syndrome coronavirus 2; Tomography, X-ray computed.