The diagnostic performance of deep-learning-based CT severity score to identify COVID-19 pneumonia

• Published in: British journal of radiology 2022-01, Vol.95 (1129), p.20210759-20210759
• Main Authors: Kardos, Anna Sára, Simon, Judit, Nardocci, Chiara, Szabó, István Viktor, Nagy, Norbert, Abdelrahman, Renad Heyam, Zsarnóczay, Emese, Fejér, Bence, Futácsi, Balázs, Müller, Veronika, Merkely, Béla, Maurovich-Horvat, Pál
• Format: Article
• Language: English
• Subjects: Adult; Aged; COVID-19 - diagnosis; COVID-19 - diagnostic imaging; COVID-19 - pathology; Deep Learning; False Negative Reactions; False Positive Reactions; Female; Humans; Image Processing, Computer-Assisted; Male; Radiography, Thoracic; Reproducibility of Results; Retrospective Studies; Sensitivity and Specificity; Severity of Illness Index; Tomography, X-Ray Computed
• ISSN: 0007-1285; 1748-880X
• DOI: 10.1259/bjr.20210759

To determine the diagnostic accuracy of a deep-learning (DL)-based algorithm using chest computed tomography (CT) scans for the rapid diagnosis of coronavirus disease 2019 (COVID-19), as compared to the reference standard reverse-transcription polymerase chain reaction (RT-PCR) test. In this retrospective analysis, data of COVID-19 suspected patients who underwent RT-PCR and chest CT examination for the diagnosis of COVID-19 were assessed. By quantifying the affected area of the lung parenchyma, severity score was evaluated for each lobe of the lung with the DL-based algorithm. The diagnosis was based on the total lung severity score ranging from 0 to 25. The data were randomly split into a 40% training set and a 60% test set. Optimal cut-off value was determined using Youden-index method on the training cohort. A total of 1259 patients were enrolled in this study. The prevalence of RT-PCR positivity in the overall investigated period was 51.5%. As compared to RT-PCR, sensitivity, specificity, positive predictive value, negative predictive value and accuracy on the test cohort were 39.0%, 80.2%, 68.0%, 55.0% and 58.9%, respectively. Regarding the whole data set, when adding those with positive RT-PCR test at any time during hospital stay or "COVID-19 without virus detection", as final diagnosis to the true positive cases, specificity increased from 80.3% to 88.1% and the positive predictive value increased from 68.4% to 81.7%. DL-based CT severity score was found to have a good specificity and positive predictive value, as compared to RT-PCR. This standardized scoring system can aid rapid diagnosis and clinical decision making. DL-based CT severity score can detect COVID-19-related lung alterations even at early stages, when RT-PCR is not yet positive.