Use of static and dynamic [(18)F]-F-DOPA PET parameters for detecting patients with glioma recurrence or progression

BACKGROUND: Static [(18)F]-F-DOPA PET images are currently used for identifying patients with glioma recurrence/progression after treatment, although the additional diagnostic value of dynamic parameters remains unknown in this setting. The aim of this study was to evaluate the performances of static and dynamic [(18)F]-F-DOPA PET parameters for detecting patients with glioma recurrence/progression as well as assess further relationships with patient outcome. METHODS: Fifty-one consecutive patients who underwent an [(18)F]-F-DOPA PET for a suspected glioma recurrence/progression at post-resection MRI, were retrospectively included. Static parameters, including mean and maximum tumor-to-normal-brain (TBR) ratios, tumor-to-striatum (TSR) ratios, and metabolic tumor volume (MTV), as well as dynamic parameters with time-to-peak (TTP) values and curve slope, were tested for predicting the following: (1) glioma recurrence/progression at 6 months after the PET exam and (2) survival on longer follow-up. RESULTS: All static parameters were significant predictors of glioma recurrence/progression (accuracy ≥ 94%) with all parameters also associated with mean progression-free survival (PFS) in the overall population (all p < 0.001, 29.7 vs. 0.4 months for TBR(max), TSR(max), and MTV). The curve slope was the sole dynamic PET predictor of glioma recurrence/progression (accuracy = 76.5%) and was also associated with mean PFS (p < 0.001, 18.0 vs. 0.4 months). However, no additional information was provided relative to static parameters in multivariate analysis. CONCLUSION: Although patients with glioma recurrence/progression can be detected by both static and dynamic [(18)F]-F-DOPA PET parameters, most of this diagnostic information can be achieved by conventional static parameters.