Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea

Abstract

Objective Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19. Materials and Methods CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0–1) and severe (2–5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis. Results Eighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021–42.457; p = 0.004), C-reactive protein (CRP) (HR, 1.080 per mg/dL; 95% CI, 1.010–1.156; p = 0.025), and COVID-affected lung proportion (CALP) (HR, 1.067 per percentage; 95% CI, 1.033–1.101; p < 0.001) were significantly associated with CEFS. CRP (HR, 1.164 per mg/dL; 95% CI, 1.006–1.347; p = 0.041) was independently associated with CEFS in the mild pneumonia group (n = 54). Normally aerated lung proportion (NALP) (HR, 0.872 per percentage; 95% CI, 0.794–0.957; p = 0.004) and NALP volume (NALPV) (HR, 1.002 per mL; 95% CI, 1.000–1.004; p = 0.019) were associated with a lower risk of critical events in the severe pneumonia group (n = 28). Conclusion CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.

Prognostic Implications of CT Feature Analysis in Patients with COVID-19: a Nationwide Cohort Study

“…These findings were consistent with other previous studies that evaluated risk factors associated with acute respiratory distress syndrome in patients with COVID-19. 11 13 26 27 Elevated CRP and procalcitonin levels in the severe group may have been associated with cytokine storms triggered by viral invasion or due to the presence of co-infections, as reported in a recent study. 28 …”

Value of quantitative analysis in lung computed tomography in patients severely ill with COVID-19

“…This means that in severely ill patients, after reaching a particular critical value, further progression of the disease will not influence the growth of inflammatory parameters, D-dimers, LDH or the decrease in the lymphocyte count. Park B. et al revealed that CRP in the mild pneumonia group and normally aerated lung proportion volume in the severe pneumonia group were independently associated with critical event-free survival in patients with COVID-19 [ 32 ].…”

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings

“…While viral testing remains the only specific method of diagnosis [ 5 ], CT plays a role in the workup of suspected pulmonary manifestations of COVID-19 and associated complications. There is growing evidence that radiographic [ 6 ] and chest CT [ 7 8 9 10 11 12 13 14 15 ] features are associated with disease severity in COVID-19 based on (semi)-manual assessment and visual scoring of pulmonary parameters. This study intends to build on these approaches and expand them in three aspects: First, by introducing a fully automated and user-independent evaluation method, which is especially relevant in pandemic period with heavy workloads on healthcare providers.…”