Potentials of pretreatment [18F]FDG PET/CT for non-invasive prediction of the tumor unfavorable pathological indices and microenvironment in NSCLC

Abstract

Purpose To investigate pretreatment [18F]FDG PET/CT in predicting tumor pathological features and microenvironment. Methodology Fifty-one patients with histo-pathologically proven non-small cell lung cancer (NSCLC) underwent pretreatment [18F]FDG PET/CT, and their clinicopathological data were collected. PET-derived biomarkers (SUVmax, mean, MTV, and TLG), consolidation-to-tumor ratio (CTR), and histopathological data (tumor grade, differentiation, tumor histological subtype, tumor-infiltrating lymphocytes (TILs), degree of desmoplasia, degree of necrosis, tumor budding, and nuclear grade), as well as a proposed risk stratification pathological scoring system, were all assessed. Results A CTR cut-off point of 0.34 was able to discriminate between low- and high-grade tumors with a sensitivity and specificity of 75.9% and 68.2%, respectively (p = 0.012). Low CTR was significantly associated with the tumor pathological subtype “adenocarcinoma,” low nuclear grade, negative tumor necrosis, and low pathological scores, respectively (p < 0.05). No significant associations were observed for CTR with tumor budding score, desmoplasia score, or TILs% (p-values > 0.05). High SUVmax (> 12.64) and high SUVmean (> 4.28) values were significantly associated with SCC tumors (p = 0.023 and 0.04, respectively). SUVmean was significantly associated with cytological differentiation (p = 0.023). A statistical trend was noted for SUVmax concerning nuclear grade and desmoplasia scores (p = 0.068 and 0.061, respectively). No statistically significant associations were revealed for MTV and TLG concerning different pathological features (p-values > 0.05). Primary lung tumors positive for desmoplasia revealed higher metabolic activity regarding SUVmax, with a statistical trend observed (p = 0.072). No statistically significant associations were observed concerning other metabolic parameters (p-values > 0.05). Conclusion PET/CT-derived biomarkers appear promising for predicting tumor unfavorable pathological features and microenvironment in NSCLC.