DEUTERIUM METABOLIC IMAGING (DMI) MEASURES THE WARBURG EFFECT IN BRAIN TUMORS

Abstract INTRODUCTION Metabolic changes in cancer have gained renewed interest as potential diagnostic and prognostic markers. The tendency to favor glycolysis in the presence of oxygen has been coined the Warburg Effect. We developed a magnetic resonance-based method that illustrates this metabolic shift. Deuterium Metabolic Imaging (DMI) observes glucose metabolism by tracing deuterium-labeled downstream metabolites, effectively representing the Warburg Effect. This pilot study uses DMI to visualize in vivo the Warburg Effect in subjects with brain tumors. METHODS We screened Yale Neuro-Oncology patients, excluding those with diabetes and MRI contraindications. Recruited subjects orally consumed 0.75g/kg of [6,6’-2H2]-glucose dissolved in water. Imaging studies were performed using a 4T magnet interfaced to a Bruker spectrometer. All data were analyzed in Matlab 8.3. Deuterium-labeled metabolite levels were overlaid on MRI to generate amplitude color maps for glucose, glutamate+glutamine (Glx), lactate, and the lactate/Glx ratio, representing the Warburg Effect. RESULTS Six brain tumor subjects were imaged. Age ranged from 53 to 72 years, and five subjects were men. Diagnoses included 4 glioblastomas (GBMs), 1 anaplastic oligodendroglioma (AO), and 1 meningioma. DMI mapping revealed regional differences between tumor sites and contralateral areas. All GBMs showed the Warburg Effect, while the AO and meningioma did not. CONCLUSION The Warburg Effect was not evident in DMI of every high-grade brain tumor, as it was not observed in the WHO grade III AO. While this tumor has a lower WHO grade than GBM, we speculate that this discrepancy relates to its molecular characterization, including an IDH1 R132H mutation, MGMT methylation, and 1p/19q codeletion. The brain tumor treatment paradigm is shifting from one based upon WHO grade to one centered around molecular features. We believe DMI provides detailed metabolic information about tumor aggressiveness, which may be linked to molecular characteristics, underscoring its clinical relevance for brain tumor diagnosis and management.