Diagnostic and Prognostic Potential of 18F-FET PET in the Differential Diagnosis of Glioma Recurrence and Treatment-Induced Changes After Chemoradiation Therapy - Celli, Monica; Caroli, Paola; Amadori, Elena; Arpa, Donatella; Gurrieri, Lorena; Ghigi, Giulia; Cenni, Patrizia; Paganelli, Giovanni; Matteucci, Federica (Frontiers in Oncology, 2021)
Background MRI-based differential diagnosis of glioma recurrence (GR) and treatment-induced changes (TICs) remain elusive in up to 30% of treated glioma patients. We aimed to determine 18F-FET PET diagnostic performance in this clinical scenario, its outcome dependency on established prognostic factors, optimal 18F-FET semi-quantitative thresholds, and whether 18F-FET parameters may instantly predict progression-free survival (PFS) and overall survival (OS). Methods We retrospectively analyzed 45 glioma patients treated with chemoradiation therapy (32 males; mean age: 51 years, glioma grade: n=26 WHO4; n=15 WHO3; n=4 WHO2) who underwent 18F-FET PET to resolve differential diagnosis of GR and TICs raised by MRI performed in the preceding 2 weeks and depicting any of the following changes in their radiation field: volumetric increase of contrast-enhancing lesions; new contrast-enhancing lesion; significant increase in T2/FLAIR non-enhancing lesion without reducing corticosteroids. 18F-FET PET outcome relied on evaluation of maximum tumor-to-brain ratio (TBRmax), time-to-peak (TTP), and time-activity curve pattern (TAC). Metabolic tumor volume (MTV) and total tumor metabolism (TTM) were calculated for prognostic purposes. Standard of reference was repeat MRI performed 4–6 weeks after the previous MRI. Non-parametric statistics tested 18F-FET-based parameters for dependency on established prognostic markers. ROC curve analysis determined optimal cutoff values for 18F-FET semi-quantitative parameters. 18F-FET parameters and prognostic factors were evaluated for PFS and OS by Kaplan-Meier, univariate, and multivariate analyses. Results 18F-FET PET sensitivity, specificity, positive predictive value, negative predictive value were 86.2, 81.3, 89.3, 76.5%, respectively; higher diagnostic accuracy was yielded in IDH-wild-type glioma patients compared to IDH-mutant glioma patients (sensitivity: 81.8 versus 88.9%; specificity: 80.8 versus 81.8%). KPS was the only prognostic factor differing according to 18F-FET PET outcome (negative versus positive). Optimal 18F-FET cutoff values for GR were TBRmax ≥ 2.1, SUVmax ≥ 3.5, and TTP ≤ 29 min. PFS differed based on 18F-FET outcome and related metrics and according to KPS; a different OS was observed according to KPS only. On multivariate analysis, 18F-FET PET outcome was the only significant PFS factor; KPS and age the only significant OS factors. Conclusion 18F-FET PET demonstrated good diagnostic performance. 18F-FET PET outcome and metrics were significantly predictive only for PFS.