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Updated: Aug 15, 2026
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Chest CT severity and quantitative lung involvement mirror systemic inflammation in hospitalized COVID-19: A
Andrzej Górecki1, Zuzanna Szostak2, Anna Bronikowska2
1Medical Diagnostic Center Voxel, Regional Hospital in Łańcut, Łańcut, Poland.
Purpose:
COVID-19 has a highly heterogeneous course, requiring objective tools for severity assessment. Chest CT quantifies parenchymal involvement, while laboratory biomarkers reflect systemic inflammatory, immunological, and metabolic responses. This study aimed to assess the associations between quantitative CT-derived measures of lung involvement and laboratory biomarkers in patients hospitalized with COVID-19.
Materials And Methods:
We analyzed a multicenter prospective cohort of 555 adults hospitalized for COVID-19 who underwent baseline low-dose chest CT and laboratory testing within 24 h of admission. Lung involvement was assessed using the CT Severity Score (CTSS; 5-25) and quantitative measures (overall percentage involvement and inflammatory lesion volume). Associations were evaluated using Spearman correlations, and multivariable linear regression was performed for CTSS.
Results:
CTSS correlated positively with CRP, LDH, ferritin, fibrinogen, and D-dimer, and negatively with lymphocyte percentage and serum albumin. The strongest association was for LDH (ρ = 0.68; p < 0.001). In multivariable analysis, LDH, glucose, creatinine, and lymphocyte percentage remained independently associated with CTSS, explaining ∼40% of its variance. Similar patterns were observed for overall percentage involvement and lesion volume. Lower lobes showed the greatest involvement and the strongest correlations with biomarkers.
Conclusions:
CT-derived severity metrics reflect systemic disease burden in hospitalized COVID-19 patients. Integrating quantitative CT measures with laboratory biomarkers may improve risk stratification and support clinical decision-making.
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