Quantitative Chest CT Analysis in Relationships between CT Patterns, Virus Load, and Pathophysiological States in SARS-CoV-2 infected Patients: A Cross-Sectional Observational Study

Abstract

CT imaging is often used to confirm COVID-19, playing a crucial role in the diagnosis and assessment due to its high sensitivity. The purpose of this study is to investigate results of quantitative CT analysis for CT patterns in SARS-CoV-2 infected patients, and how these relate to viral load and pathophysiological states. We recruited patients who had confirmed SARS-CoV-2 infection and undergone chest CT within 24 hours of confirmation. By quantitative CT analysis, and collecting clinical data, we explored correlations between those variables. Our research included 253 patients, after screening by exclusion criteria, 171 patients were included in final cohort. The incidence of SARS-CoV-2 associated pneumonia was 74.3%. The ROC test results showed AUCs for leukomonocyte count, and virus genes were 0.703, 0.562, 0.567, and 0.582, respectively. GGO pattern in CT was correlated PaO /FiO ratio. Multiple linear regression results indicated GGO was associated with PaO /FiO . Meanwhile, the consolidation was correlated with PaCO level. Additionally, consolidation was also associated with neutrophil–lymphocyte ratio. Conclusion: Lymphocyte count may be a potential marker for predicting SARS-CoV-2 pneumonia, independent of virus load. Additionally, GGO is correlated with hypoxia, while consolidation is associated with PaCO levels and inflammation, which may affect aeration in the lungs.