Room: Davidson Ballroom B
Purpose: Conventional magnetic resonance imaging (MRI), hyperpolarized MRI, and nuclear magnetic resonance (NMR) spectroscopy experiments were performed to measure in vivo tumor growth, in vivo pyruvate-to-lactate conversion, and ex vivo metabolite concentrations of glioblastoma at specific time-points of tumor development. We hypothesized that metabolic transformations observed with hyperpolarized MRI and NMR could be reliably detected before significant increases in tumor growth measured with conventional MRI.
Methods: Glioma sphere-forming cells (GSCs) were cultured from patient biopsies and intracranially injected into the brains of mice whose median survival was 35 days. Every 3 days, tumor volume was measured with T1-weighted, T2-weighted, and fluid-attenuated MRI sequences. At 20%, 30%, 40%, 60%, 80%, and 100% of median survival, hyperpolarized [1-Â¹Â³C] pyruvate MRI experiments were performed. Pyruvate-to-lactate conversion was quantified by the metric nLac. Tumors were then excised, flash-frozen, and prepared for NMR. The resonances of 25 metabolites were identified and their concentrations quantified. Statistical significance of the different measurements was determined using ANOVA with 95% confidence and multiple comparison corrections.
Results: From hyperpolarization experiments, nLac was significantly increased in the tumor-bearing mice compared to the controls beginning at the 40% time-point and continued to increase throughout tumor development. Tumor volume was not statistically different from its initial value until the 60% time-point. From the NMR experiments, glutamate and myo-inositol concentrations were significantly higher in tumors beginning at the 60% time-point and glycine was significantly increased at 100%.
Conclusion: Hyperpolarized MRI was able to reliably detect changes in tumor metabolism prior to changes in tumor volume measured with conventional MRI. Additionally, variations in several metabolite concentrations were identified over the course of tumor growth which are being investigated with pathway analysis. Metabolic imaging has the potential to significantly impact diagnosis as well as treatment monitoring by identifying changes in tumor function before anatomic changes occur.