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 2/FiO
2 ratio. Multiple linear regression results indicated
GGO was associated with PaO 2/FiO 2.
Meanwhile, the consolidation was correlated with PaCO 2
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 2 levels and
inflammation, which may affect aeration in the lungs.