Lung Quantitative Computer Tomography Analysis for Non-HIV Associated Pneumocystis Pneumonia Assessment：An Observational Clinical Cohort Study

Abstract

Abstract Introduction Pneumocystis pneumonia (PCP) is an opportunistic infection caused by Pneumocystis jirovecii. It always occurs secondary to HIV or tumors after chemotherapy or exposure to glucocorticoids. This infection can rapidly progress to respiratory failure, requiring ventilation support. CT is a significant tool for assessing the severity of PCP. Physicians commonly use descriptive features such as ground glass opacity (GGO), crazy paving, and consolidation in CT reports, but the relationship between these features and clinical physiopathological situations is unclear. In this study, we aim to investigate the association between quantitative CT features and clinical laboratory data for PCP. Method Between October 2018 and October 2022, 126 patients with PCP were enrolled in the study. 53 patients were included in the final cohort. Quantitative CT features, GGO, and consolidation were identified and marked using dedicated imaging software. Lung volume and percentage for each feature were estimated by 3D lung reconstruction. The Spearman correlation was used to illustrate the relationships among the CT features and laboratory items. Multiple linear regression, including the interaction of CT features, was performed to discuss the relationships between dedicated CT features and laboratory data. Finally, the ROC curve was used to determine the best cut-off value for predicting respiratory failure. Results GGO was the predominant finding (90%) in all CT slices, with 81.2% of CT slices demonstrating consolidation. Consolidation percentage was correlated with PaO2/FiO2, CRP, and NLR (r=-0.76, 0.66, and 0.59, respectively; all p=0.00). GGO percentage was also correlated with PaO2/FiO2, CRP, and NLR (r2=-0.35, 0.35, and 0.38, respectively; p=0.01, 0.005, and 0.009, respectively). The results of multiple linear regression indicated that consolidation percentage was associated with PaO2/FiO2(β=-26.69, 95%CI -42.93– -10.46, p=0.002) and NLR (β=1.38, 95%CI 0.02–2.75, p=0.04); the interaction of consolidation and GGO percentage was associated with CRP (β=0.28, 95%CI 0.04–0.52, p=0.03) when adjusted for time from onset to CT test. The best cut-off value of consolidation percentage for respiratory failure was 22.5% (sensitivity=0.452, specificity=0.955). Conclusion Although GGO is a common and typical pattern for PCP, the consolidation pattern is associated with a poor pathophysiological state. It could serve as a warning reminder for physicians in clinical practice.