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Updated: Oct 31, 2025
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Study of Thoracic CT in COVID-19: The STOIC Project
Marie-Pierre Revel1, Samia Boussouar1, Constance de Margerie-Mellon1
1From the Department of Radiology, Université de Paris, APHP, Hôpital Cochin, 27 rue du Fg Saint Jacques, 75014 Paris, France (M.P.R., I.S., G.C., S. Bennani, F.B., S.D., C.H., C.J.); Department of Radiology, Sorbonne Université, APHP, Hôpital Pitié Salpétrière, Paris, France (S. Boussouar, A.R.); Department of Radiology, Université de Paris, APHP, Hôpital Saint-Louis, Paris, France (C.d.M.M.); Department of Radiology, Université Rennes 1, Hôpital Pontchaillou, Rennes, France (T.L., M.L.); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Raymond Poincaré, Garches, France (D.M.); Department of Radiology, Sorbonne Université, APHP, Hôpital Tenon, Paris, France (A.M.); Department of Radiology, Université de Strasbourg, Hôpital de Hautepierre, Strasbourg, France (S.M.); Department of Radiology, Université de Paris, APHP, Hôpital Bichat, Paris, France (M.P.D., A.K.); Department of Radiology, Université de Strasbourg, Nouvel Hôpital Civil, Strasbourg, France (M.O.); Department of Radiology, Université de Montpellier, Hôpital Arnaud de Villeneuve, Montpellier France (S. Bommart); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Ambroise Paré, Boulogne, France (M.E.H.); Department of Radiology, Université de Lorraine, Hôpital Brabois, Vandoeuvre, France (I.P.); Department of Radiology, Université de Paris, APHP, Hôpital Européen Georges Pompidou, INSERM U970, PARCC, Paris, France (L.F.); Department of Radiology, Sorbonne Université, APHP, Hôpital Avicenne, Bobigny, France (P.Y.B.); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Bicêtre, Le Kremlin-Bicêtre, France (M.F.B.); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Antoine Béclère, Clamart, France (L.R.); Department of Radiology, Université de Paris, APHP, Hôpital Lariboisière, Paris, France (V.B.); Department of Radiology, Université Claude Bernard Lyon 1, Hospices Civils de Lyon, Hôpital Lyon Sud, Pierre-Benite, France (P.R.); Department of Radiology, Université de Paris, APHP, Hôpital Beaujon, Clichy, France (J.G.); Department of Radiology, Université Paris Est, APHP, Hôpital Henri Mondor, Créteil, France (J.F.D.); Departments of Radiology (E.D.) and Clinical Epidemiology (R.P.), Université de Paris, APHP, Hôtel-Dieu, Paris, France; Sorbonne Université, APHP, Hôpital Avicenne, Department of Pneumology, INSERM UMR 1272, Bobigny, France (D.V.); and Université de Paris APHP, Clinical Research Unit Paris Centre, Paris, France (L.J., H.A.).
Abstract:
Background There are conflicting data regarding the diagnostic performance of chest CT for COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis. Purpose To create a large publicly available data set and assess the diagnostic and prognostic value of CT in COVID-19 pneumonia. Materials and Methods This multicenter, observational, retrospective cohort study involved 20 French university hospitals. Eligible patients presented at the emergency departments of the hospitals involved between March 1 and April 30th, 2020, and underwent both thoracic CT and reverse transcription-polymerase chain reaction (RT-PCR) testing for suspected COVID-19 pneumonia. CT images were read blinded to initial reports, RT-PCR, demographic characteristics, clinical symptoms, and outcome. Readers classified CT scans as either positive or negative for COVID-19 based on criteria published by the French Society of Radiology. Multivariable logistic regression was used to develop a model predicting severe outcome (intubation or death) at 1-month follow-up in patients positive for both RT-PCR and CT, using clinical and radiologic features. Results Among 10 930 patients screened for eligibility, 10 735 (median age, 65 years; interquartile range, 51-77 years; 6147 men) were included and 6448 (60%) had a positive RT-PCR result. With RT-PCR as reference, the sensitivity and specificity of CT were 80.2% (95% CI: 79.3, 81.2) and 79.7% (95% CI: 78.5, 80.9), respectively, with strong agreement between junior and senior radiologists (Gwet AC1 coefficient, 0.79). Of all the variables analyzed, the extent of pneumonia at CT (odds ratio, 3.25; 95% CI: 2.71, 3.89) was the best predictor of severe outcome at 1 month. A score based solely on clinical variables predicted a severe outcome with an area under the curve of 0.64 (95% CI: 0.62, 0.66), improving to 0.69 (95% CI: 0.6, 0.71) when it also included the extent of pneumonia and coronary calcium score at CT. Conclusion Using predefined criteria, CT reading is not influenced by reader's experience and helps predict the outcome at 1 month. ClinicalTrials.gov identifier: NCT04355507 Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Rubin in this issue.
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