Enhanced Deuterium Metabolic Imaging (DMI) of Metabolic Reprogramming in Brain Tumors

Abstract Deuterium metabolic imaging (DMI) is an emerging MRI technique whereby deuterated substrates and their metabolic products are imaged in vivo. A primary application is the study of energy metabolism, a fundamental process for virtually all cells in the body. In particular, glucose (Glc) metabolism plays a critical role in cancer, with two key metrics of tumor metabolism being total glucose consumption and the relative fraction of Glc undergoing glycolysis (GLY) versus oxidative phosphorylation (OXPHOS). In contrast to normal tissues, most cancers exhibit a preponderance of GLY over OXPHOS. Known as the Warburg effect or, more generally metabolic reprogramming, these alterations are particularly pronounced in glioma and other brain tumors. Elevated GLY in high-grade brain tumors has been shown to be a marker of tumor growth and aggressiveness. From a therapeutic perspective, studies strongly support that this Warburg phenotype is necessary and sufficient for the cancer process, which provides the framework of a highly novel therapeutic strategy targeted at affecting these metabolic pathways. We contend that clinical translation is presently impeded not so much by a lack of agents, but by the difficulty in measuring these fundamental aspects of tumor metabolism in vivo. Of the available imaging techniques, 18F-FDG-PET is well-established for imaging glucose uptake, whereas robust in vivo measurements of GLY and OXPHOS are considerably more challenging. Triple 15O-PET can be used to assess oxygen consumption (and hence OXPHOS) but is clinically problematic due to the 2-min half- life of 15O and the challenges of coordinating multiple inhaled radioactive gases. MRI of hyperpolarized 13C- labeled pyruvate has been shown capable of assessing tumor GLY/OXPHOS ratios; however, this technique is very expensive with limited availability and unique challenges. More recently, the feasibility of using conventional 2H MRSI of deuterated glucose to measure both GLY and OXPHOS has been successfully demonstrated. Given the ubiquity of 3T scanners, we contend that 3T DMI would have maximal clinical impact, and initial results for the human brain reported at 4T, in combination with our own 3T DMI data, indicate limited spatial resolution, low SNR, and correspondingly long scan times are the primary limitations. This technical development project will address these challenges by enhancing DMI via the incorporation of multimodal information. Noting that 1H MRI and FDG-PET share significant mutual anatomic and metabolic information with DMI, we propose to significantly enhance 3T DMI using signal processing and machine learning approaches analogous to techniques using MRI to enhance FDG-PET resolution and SNR. The overall goal is to demonstrate enhanced DMI acquisitions and image processing pipelines for maximal clinical impact, with the initial application being the imaging of the Warburg effect in brain tumors.