Validation of imaging brain tumor metabolism using deuterated glucose

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Aberrant metabolism is increasingly recognized as a hallmark of cancer. The Warburg effect is a well-known example of such abnormal cancer metabolism, which entails a shift away from oxidative to glycolytic glucose metabolism (despite the presence of oxygen) and usually also increased glucose uptake. The detection of this increased glucose uptake, via a radioactive analogue (2-18F-fluoro-2-deoxy-D-glucose, FDG) with positron emission tomography (PET), is often used for diagnosis, staging, and evaluating disease progression of tumors outside the brain. However, in patients with brain tumors FDG-PET is frequently inconclusive because the normal high glucose uptake in healthy brain is comparable to that in tumors, thereby obscuring the tumor-to-brain image contrast. As a result, FDG-PET is not frequently used in these patients. That leaves brain tumor patients without the benefits of metabolic imaging, which has a significant negative impact on the management of their disease. The recently developed MRI-based method, deuterium metabolic imaging (DMI) can be an alternative strategy to detect abnormal glucose metabolism. DMI is based on 3D deuterium (2H) magnetic resonance spectroscopic imaging (MRSI). After administration of the nonradioactive deuterated glucose, DMI can detect both glucose and its downstream metabolites lactate and glutamate. In cancer cells that show the Warburg effect the 2H-labeling in lactate and glutamate reflects the typical shift from oxidative to glycolytic metabolism. DMI can detect this 2H-labeling and reveal the cancer-specific glucose metabolism with high tumor-to-brain image contrast. Because of these features and the ease of use of the method, DMI can become a robust metabolic imaging technique for brain tumors that so far has been missing. The goal of this proposal is to validate DMI of glucose metabolism as a potential imaging tool for neurooncology, particularly for glioblastoma, the most common and lethal primary brain tumor. We envision that, for patients with brain tumors, DMI can provide a similar benefit as FDG-PET has for many patients with tumors outside of the brain. In Aim 1 we therefore seek to validate the 2H-labeling pattern in lactate and glutamate detected with DMI as surrogates of the Warburg effect, by comparing them with absolute measurements of the Warburg effect in rodent models of GBM. Aim 2 is focused on the potential of DMI to provide an early biomarker of response to standard of care chemotherapy. To confirm the improved performance of DMI relative to current clinically available methods, in Aim 3 metabolic maps generated by 1H MRSI, FDG-PET and DMI, are compared for tumor-to-brain image contrast in patients with GBM. The proposed aims will provide better understanding of the fundamental processes underlying the DMI-based image contrast, provide the first insight in its value for monitoring therapy and disease progression, and benchmark its performance as a new metabolic imaging method. These achievements will strengthen the foundation for further development of DMI as a clinically viable technology for metabolic imaging.