Magnetic Resonance Imaging Approaches for Predicting the Response to Hyperoxic Radiotherapy in Glioma-Bearing Rats

© 2019 by the authors.Despite important advances in multimodal therapeutic options, glioblastoma (GBM), the most frequent and aggressive form of all astrocytomas, remains with a median overall survival period of 15 months. A direct correlation between GBM hypoxia and higher aggressiveness, poor prognosis and greater resistance to different treatments has been established. However, because of intratumoral and interindividual heterogeneity, it has not been possible to assess accurately the hypoxia degree from physiopathological parameters or neuroimaging methods. This study aims to develop and evaluate a magnetic resonance imaging (MRI) approach to identify more precisely those tumors that could improve the outcome through an oxygen targeted therapy. Methods: To assess the efficacy of radiotherapy in animals irradiated under air and oxygen breathing, we implemented a GBM animal model obtained by intracranial injection of glioma C6 cells in rats. MRI studies, based on the oxygen-induced contrast in blood (BOLD) and tissues (TOLD), were carried out to evaluate the effect of the modulation in oxygen breathing conditions on the tumors in vivo. The efficacy of the oxygen breathing therapies was determined by the relative tumor volume at the end of the experiment, compared to its size on the day before the treatment. Results: Our results categorized the tumors in responding, non-responding and intermediate behaviors. While BOLD analysis did not show any statistical difference between animals, either breathing air or oxygen, TOLD parameters allowed for the identification of the tumors with higher responses to hyperoxygenic radiotherapy. Conclusions: The non-invasive oxygen enhanced MRI acquisitions proposed here show promising potential to identify those tumors that would generally improve their response to a hypoxia targeted treatment.This work was supported by grants from the Ministry of Economy, Industry and Competitiveness (SAF2017-83043-R), and by the Program MULTITARGET&VIEW-CM from the Community of Madrid (S-BIO-0170-2006), involving contributions from FEDER and FSE funds