Chest Computed Tomography (CT) Severity Scales in COVID-19 Disease: A Validation Study

Area of Science:

• Radiology
• Infectious Diseases
• Pulmonology

Background:

• Quantitative imaging assessment of lung lesions is crucial for SARS-CoV-2 patient management.
• Existing scoring systems like Total Severity Score (TSS), Chest Computed Tomography Score (CT-S), and Chest CT Severity Score (CT-SS) require validation for assessing lung inflammation.
• Interobserver agreement and correlation with clinical status are key validation metrics.

Purpose of the Study:

• To validate the interobserver agreement of TSS, CT-S, and CT-SS in SARS-CoV-2 patients.
• To assess the correlation between these imaging scores and the patients' clinical condition.
• To determine the most reliable scoring system for reflecting disease severity.

Main Methods:

• Retrospective analysis of 77 chest CT scans from hospitalized SARS-CoV-2 patients.
• Independent assessment of CT scans by two radiologists using TSS, CT-S, and CT-SS.
• Calculation of interobserver agreement using Cohen's kappa and intraclass correlation coefficient (ICC).
• Correlation analysis with the Modified Early Warning Score (MEWS) to assess clinical condition.

Main Results:

• All three scales demonstrated very good interobserver agreement (kappa > 0.88, ICC > 0.89).
• The Chest CT Severity Score (CT-SS) showed the strongest positive correlation with the Modified Early Warning Score (r=0.627-0.653).
• TSS and CT-S also showed good correlation with clinical status.

Conclusions:

• The evaluated scoring scales (TSS, CT-S, CT-SS) exhibit high interobserver reliability for assessing lung inflammation in SARS-CoV-2.
• The CT-SS is the most effective imaging score for correlating with and potentially predicting patient clinical severity.
• These validated scores can aid in objective patient triage and therapeutic decision-making.