Preoperative prognostic prediction for invasive pulmonary adenocarcinoma: Impact of 18F-FDG PET/CT semi-quantitative parameters associated with new histological subtype classification

To explore the preoperative predictive value of 18F-FDG PET/CT for poor prognostic histologic subtypes of invasive pulmonary adenocarcinoma (IPA) under new classification. This study included 316 patients. Histopathology of IPA was evaluated by recording the percentage of each histologic component. PET/CT parameters were compared among IPAs with different risks of recurrence. Optimum cutoff values of PET/CT parameters were calculated using ROC curve analysis. Overall survival (OS) and disease-free survival (DFS) were calculated using Kaplan–Meier method, and survival differences between groups were tested using log-rank test. Multivariate analysis for survival was performed using the Cox regression model. Patients were divided into low (LRR), intermediate (IRR), and modified high (mHRR) risk of recurrence group incorporating typical (HRR-T) and nontypical (HRR-NT) subgroups based on histologic patterns. There were significant differences in SUVmax, SUVmean, SUVmin, SUVSD, TLG, and tumor size among three groups. HRR-NT had lower SUVmax, SUVmean, SUVmin, SUVSD and TLG than HRR-T subgroup, and higher SUVmax, SUVmean, SUVmin, SUVSD, MTV, TLG and tumor size than IRR group. ROC curve analysis showed that SUVmax had highest AUC (0.815) in distinguishing LRR and IRR. TLG had highest AUC (0.741) in distinguishing IRR and mHRR. Multivariable analysis showed that tumor size and SUVmax were independent predictors of DFS and OS. High risk of recurrence of IPA exhibited higher 18F-FDG uptake and tumor size. Tumor size and SUVmax could be used as preoperative surrogates for the IASLC grading system. 18F-FDG PET/CT can improve the preoperative prognostic prediction for IPA patients. •High risk of recurrence of IPA exhibited higher 18F-FDG uptake and tumor size.•Diameter and SUVmax can be used as preoperative surrogates for IASLC grading.•PET/CT can improve preoperative prognostic prediction for IPA patients.