AI Summary & Key Takeaways
AI InsightIntegrating composite biomarkers, such as PIV, may refine the contextual interpretation of PET/CT findings and support preoperative risk stratification in patients with indeterminate pulmonary lesions.
📌 3 Key Takeaways
Abstract
Aims: Organizing pneumonia (OP) frequently presents as a diagnostic challenge because of its propensity to mimic lung malignancy on FDG-PET/CT. This study aimed to characterize the metabolic heterogeneity of OP and evaluate the relationship between systemic inflammatory burden and a hypermetabolic imaging phenotype. Methods: We retrospectively analyzed data of 61 patients with histopathologically confirmed OP with suspected malignancy who underwent preoperative FDG-PET/CT. Patients were stratified by the cohort-specific median primary lesion SUVmax of 5.1. Systemic inflammatory indices, including the pan-immune-inflammation value (PIV), were derived from baseline laboratory parameters. Independent predictors of high FDG uptake (SUVmax ≥5.1) were identified through multivariate logistic regression. Results: High SUVmax lesions were significantly associated with a history of smoking (83.9% vs. 60.0%; p=0.049), spiculated margins (38.7% vs. 10.0%; p=0.016), and metabolically active mediastinal lymph nodes (38.7% vs. 16.7%; p=0.036). Preoperative inflammatory indices, including monocyte-to-lymphocyte ratio (MLR) (p=0.024), platelet-to-lymphocyte ratio (PLR) (p=0.046), PIV (p=0.037), and Systemic Inflammatory Response Index (SIRI) (p=0.030), were significantly elevated in the high SUVmax group. In the multivariate analysis, PIV remained independently associated with a hypermetabolic phenotype (OR: [1.20; 95% CI]: 1.02-1.42; p=0.031). Notably, lesion size and nodal involvement did not emerge as independent predictors of primary lesion FDG avidity. Conclusion: OP encompasses a biologically heterogeneous spectrum in which a distinct subset mimics lung malignancy through intense FDG avidity. This hypermetabolic phenotype is primarily driven by systemic inflammatory intensity rather than lesion morphology alone. Integrating composite biomarkers, such as PIV, may refine the contextual interpretation of PET/CT findings and support preoperative risk stratification in patients with indeterminate pulmonary lesions.