Beyond a Universal Cut-Off: [18F]FET-PET Metrics for Distinguishing High-Grade Glioma Recurrence from Treatment-Related Changes
Background/Objectives: Differentiating tumour recurrence from treatment-related changes (TRC) after multimodal treatment of high-grade gliomas (HGGs) remains challenging because of the overlap in imaging findings on conventional magnetic resonance. This study compared the diagnostic performance of the main static semiquantitative O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography ([18F]FET-PET) parameters and assessed the diagnostic contribution of qualitative tracer uptake. Methods: This retrospective single-centre study included 77 scans from 61 adult patients with previously resected and chemoradiotherapy-treated HGGs undergoing [18F]FET-PET for suspected recurrence. Standardised uptake values (SUVs), tumour-to-background ratios (TBRs), and metabolic tumour volume (MTV) were analysed. Recurrence was determined using a composite histopathological and clinical–radiological reference standard. Diagnostic performance was assessed using receiver operating characteristic analysis, Youden-derived cut-offs and DeLong comparisons. Internal validation was performed by using patient-grouped five-fold cross-validation, in which cut-offs were re-derived within each training partition and applied to the held-out partition. Results: Forty-nine scans were classified as recurrence and 28 as TRC. All semiquantitative parameters except MTV were significantly higher in recurrent disease after false-discovery-rate correction. TBR mean ratio showed the highest accuracy (AUC, 0.80; cut-off, 1.85; sensitivity, 77.6%; specificity, 75.0%), followed by SUV max (AUC, 0.793). Neither prespecified comparison among TBR parameters was significant. The presence of pathological uptake achieved 100% sensitivity, 42.9% specificity, 100% NPV, and 79.2% accuracy. MTV was non-discriminative (AUC, 0.499). SUV max differed significantly between scanners (p = 0.008). Conclusions: Static semiquantitative [18F]FET-PET parameters, except MTV, showed comparable moderate-to-good performance for distinguishing recurrence from TRC. TBRmean may represent a pragmatic primary marker due to its background normalisation reduction of scanner-related variability. Guideline-recommended thresholds should be regarded as reference values requiring local validation and, when appropriate, centre- and protocol-specific calibration.
Authors
- Nadia Oberhofer (ORCID: https://orcid.org/0000-0002-5955-1865)
- Matteo Bonatti (ORCID: https://orcid.org/0000-0002-4477-8944)
- Alessandro Spimpolo (ORCID: https://orcid.org/0000-0001-5223-8756)
- Davide Costazza (ORCID: https://orcid.org/0000-0002-7876-0291)
- Pier Paolo Berti (ORCID: https://orcid.org/0000-0002-4373-3023)
- Luca Zavatto (ORCID: https://orcid.org/0009-0005-2185-128X)
- Francesco Erdini
- Francesco Doglietto (ORCID: https://orcid.org/0000-0002-7438-0734)
- Davide Drusiani
- Paolo Cecchi (ORCID: https://orcid.org/0000-0003-2725-2657)
- Mohsen Farsad (ORCID: https://orcid.org/0000-0002-7596-6948)
- Giuseppe Maria Della Pepa (ORCID: https://orcid.org/0000-0001-8698-3359)
- Vania Pirillo
- Andreas Schwarz
- Matteo Presa
- Leda Lorenzon
Institutions
- Free University of Bozen-Bolzano (IT)
- Agostino Gemelli University Polyclinic (IT)
- Ospedale di Bolzano (IT)
- Azienda Sanitaria dell'Alto Adige (IT)
Publication Details
- Journal
- Brain Sciences
- Published
- 2026-10-09
- DOI
- https://doi.org/10.3390/brainsci16101085
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00