Diagnostic performance of CT lung severity score and quantitative chest CT for stratification of COVID-19 patients

Radiol Med. 2022 Mar;127(3):309-317. doi: 10.1007/s11547-022-01458-9. Epub 2022 Feb 14.

Abstract

Purpose: Lung severity score (LSS) and quantitative chest CT (QCCT) analysis could have a relevant impact to stratify patients affected by COVID-19 pneumonia at the hospital admission. The study aims to assess LSS and QCCT performances in severity stratification of COVID-19 patients.

Materials and methods: From April 19, 2020, until May 3, 2020, patients with chest CT suggestive for interstitial pneumonia and tested positive for COVID-19 were retrospectively enrolled and stratified for hospital admission as Group 1, 2 and 3 (home isolation, low intensive care and intensive care, respectively). For LSS, lungs were divided in 20 regions and visually assessed by two radiologists who scored for each region from non-lung involvement as 0, < 50% assigned as 1 and > 50% as 2. QCCT was performed with a dedicated software that extracts pulmonary involvement expressed in liters and percentage. LSS and QCCT were analyzed with ROC curve analysis to predict the performance of both methods. P values < 0.05 were considered statistically significant.

Results: Final population enrolled included 136 patients (87 males, mean age 66 ± 16), 19 patients in Group 1, 86 in Group 2 and 31 in Group 3. Significant differences for LSS were observed in almost all comparisons, especially in Group 1 vs 3 (AUC 0.850, P < 0,0001) and Group 1 + 2 vs 3 (AUC 0.783, P < 0,0001). QCCT showed significant results in almost all comparisons, especially between Group 1 vs 3 (AUC 0.869, P < 0,0001). LSS and QCCT comparison between Group 1 and Group 2 did not show significant differences.

Conclusions: LSS and QCCT could represent promising tools to stratify COVID-19 patient severity at the admission.

Keywords: COVID-19; Chest CT; Lung quantification; Lung severity score; Severity stratification.

MeSH terms

  • Aged
  • Aged, 80 and over
  • COVID-19* / diagnostic imaging
  • Humans
  • Lung / diagnostic imaging
  • Male
  • Middle Aged
  • Retrospective Studies
  • SARS-CoV-2
  • Tomography, X-Ray Computed / methods