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International Conference on Neuro Oncology and Brain Tumor

Brisbane, Australia

Julie Bolcaen

Ghent University

Title: Diagnosis of neuro-oncology


Biography: Julie Bolcaen


Background: Discrimination between glioblastoma (GB) and radiation necrosis (RN) post-irradiation remains challenging but has a large impact on further treatment and prognosis. In this study, uptake of 18F-fluorodeoxyglucose (18F-FDG), 18F-fluoroethyltyrosine (18F-FET) and 18F-fluoromethylcholine (18F-FCho) positron emission tomography (PET) tracers were investigated in a F98 GB and RN rat model applying kinetic modeling (KM) and graphical analysis (GA), with the aim to clarify our previous results. Methods: Dynamic 18F-FDG (GB n=6 and RN n=5), 18F-FET (GB n=5 and RN n=5) and 18F-FCho PET (GB n=5 and RN n=5) were acquired with continuous arterial blood sampling. Arterial input function (AIF) corrections, KM and GA were performed. Results: The influx rate (Ki) of 18F-FDG uptake described by a 2-compartmental model (CM) or using Patlak GA, showed more trapping (k3) in GB (0.07 min-1) compared to RN (0.04 min-1) (p=0.017). K1 of 18F-FET was significantly higher in GB (0.06 ml/ccm/min) compared to RN (0.02 ml/ccm/min), quantified using a 1-CM and Logan GA (p=0.036). 18F-FCho was rapidly oxidized complicating data interpretation. Using a 1-CM and Logan GA no clear differences were found to discriminate GB from RN. Conclusions: Based on our results we concluded that using KM and GA both 18F-FDG and 18F-FET were able to discriminate GB from RN. Although KM is the only method for absolute quantification, based on our semi-quantitative results and due to the laborious set-up for obtaining an AIF, SUV is proposed for translation into the clinic. 18F-FCho PET did not allow discrimination between GB and RN.