Comparison of visual and semiquantitative analysis of 18F-FDOPA-PET/CT for recurrence detection in glioblastoma patients
- PMID: 24305722
- PMCID: PMC3956344
- DOI: 10.1093/neuonc/not166
Comparison of visual and semiquantitative analysis of 18F-FDOPA-PET/CT for recurrence detection in glioblastoma patients
Abstract
Background: Amino acid transport imaging with 18F-FDOPA PET is increasingly used for detection of glioblastoma recurrence. However, a standardized image interpretation for 18F-FDOPA brain PET studies has not yet been established. This study compares visual and semiquantitative analysis parameters for detection of tumor recurrence and correlates them with progression-free survival (PFS).
Methods: One-hundred ten patients (72 male:38 female) with suspected tumor recurrence who underwent 18F-FDOPA PET imaging were studied. PET scans were analyzed visually (5-point scale) and semiquantitatively (lesion-to-striatum- and lesion- to-normal-brain-tissue ratios using both SUV(mean) and SUV(max)). Accuracies for recurrence detection were calculated using histopathology and clinical follow-up for validation. Receiving operator characteristic and Kaplan-Meier survival analysis were performed to derive imaging-based prediction of PFS and overall survival (OS).
Results: Accuracies for detection of glioblastoma recurrence were similar for visual (82%) and semiquantitative (range, 77%-82%) analysis. Both visual and semiquantitative indices were significant predictors of PFS, with mean lesion-to normal brain tissue ratios providing the best discriminator (mean survival, 39.4 vs 9.3 months; P < .001). None of the investigated parameters was predictive for OS.
Conclusions: Both visual and semiquantitative indices detected glioblastoma recurrence with high accuracy and were predictive for PFS. Lesion-to-normal-tissue ratios were the best discriminators of PFS; however, none of the investigated parameters predicted OS. These retrospectively established analysis parameters need to be confirmed prospectively.
Keywords: 18F-FDOPA; glioblastoma; recurrence detection.
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