Metabolic tumor volume by ¹⁸F-FDOPA PET is predictive of treatment response in patients with recurrent high-grade gliomas on anti-angiogenic therapy as early as 2 weeks after therapy initiation

Objectives Malignant glioma carries a very poor prognosis. To move novel therapies from last- to first-line, rapid assessment of therapeutic success is needed. This study aims to evaluate the prognostic value of ¹⁸F-FDOPA PET in treatment monitoring and to establish its use as a staging and restaging tool.

Methods 30 patients with recurrent high-grade gliomas were prospectively studied with ¹⁸F-FDOPA PET scans immediately before, and at 2 and 6 weeks after the start of bevacizumab combination therapy. Using SUV thresholds, metabolic tumor volumes (MTV) as well as max and mean SUV within this MTV were obtained. MRI treatment response was assessed at 6 weeks according to the response assessment in neurooncology (RANO) criteria. The predictive power of ¹⁸F-FDOPA PET and MRI response assessment were evaluated with regard to progression-free survival (PFS) and overall survival (OS) using Kaplan-Meier analysis.

Results ¹⁸F-FDOPA PET SUVs as well as their changes through therapy are not predictive of treatment response. However, various metabolic tumor volume parameters at follow up scans, such as MTV, MTV changes, and tumor burden (MTV multiplied by SUVmean) are highly prognostic. ¹⁸F-FDOPA PET MTV at 2 weeks is the most significant predictor for OS (P = 0.001) as well as PFS (P = 0.002). Metabolic responders (n=17) survived 3.5 times long (12.1 mo v 3.5 mo, P < 0.001) than non-responders (n=11). Whereas responders based on MRI (N = 9) lived 1.4 times long (12.9 vs 9.0 mo, P = 0.05) than non-responders (N = 20). Discrepant cases based on PET and MRI were compared. In 8 out 9 cases, ¹⁸F-FDOPA PET was able to demonstrate response earlier than MRI.

Conclusions ¹⁸F-FDOPA PET identifies treatment responders to antiangiogenic therapy as early as two weeks after treatment initiation. Metabolic tumor volume at follow up is the most significant survival predictor.

Research Support This study was supported by grants P50 CA086306 from the National Institutes of Health - National Cancer Institute, and U.S Department of Energy contract DE-FC03-87-ER60615