NIMG-35. EFFECT OF BEVACIZUMAB ON TUMOR GLUCOSE UPTAKE IN PATIENTS WITH HIGH GRADE GLIOMASстатья из журнала
Аннотация: Bevacizumab, is a monoclonal antibody directed against the vascular endothelial growth factor receptor. It alters tumor vasculature and likely underlying tumor cell metabolism. Studies using metabolic positron emission tomography (PET) methods like [18F]-fluoro-3-deoxy-3-L-fluorothymidine and 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine have shown that changes in PET uptake after bevacizumab infusion are predictive of progression-free and overall survival. The effect of bevacizumab on glioma glucose uptake as evaluated by 18F-fluorodeoxyglucose (FDG) PET is unknown. Establishing an imaging biomarker capable of identifying tumor response during treatment with anti-angiogenic therapy may be worthwhile. Under an institutional review board approved retrospective protocol, uptake values of FDG-PET scans performed before and after bevacizumab infusion were analyzed in 47 cases of recurrent high grade gliomas (30 glioblastomas, 12 anaplastic astrocytomas, 3 anaplastic oligodendrogliomas and 2 anaplastic oligoastrocytomas). Baseline FDG-PET scans prior to bevacizumab infusion revealed that 41 patients (87.2%) showed a high FDG uptake, 4 patients (8.5%) showed an intermediate FDG uptake signal between white and gray matter, and 2 patients (4.3%) showed no increased FDG uptake. After bevacizumab infusion, 20 patients (42.5%) showed a decreased FDG uptake. Twenty-five patients (53.2%) had no change in FDG uptake after bevacizumab infusion. Two patients (4.3%) showed an increase in FDG uptake as compared to baseline FDG-PET scan. Tumor metabolism as assessed by FDG uptake was decreased in nearly half of the recurrent high grade gliomas after bevacizumab infusion. Further studies are needed to determine if this decrease in FDG-PET signal after bevacizumab is an early predictive signal of therapeutic response to anti-angiogenic agents.
Год издания: 2016
Авторы: Surabhi Ranjan, Jing Wu
Издательство: Oxford University Press
Источник: Neuro-Oncology
Ключевые слова: Glioma Diagnosis and Treatment, Cancer, Hypoxia, and Metabolism, Radiomics and Machine Learning in Medical Imaging
Открытый доступ: bronze
Том: 18
Выпуск: suppl_6
Страницы: vi132–vi132