Recovery of features from noisy imaging scans: Dissolution Dynamic Nuclear Polarization (dDNP) method of hyperpolarization allowed the use of 13C labeled endogenous metabolic substrates such as pyruvate to have sufficient signal enhancement in 13C MRI and permit monitoring metabolic fluxes of specific biochemical pathways using 13C MRI. It is now a clinical modality in several centers. In spite of the orders of magnitude signal enhancement provided by dDNP, often times in preclinical and clinical 13C MRI studies the signals are suboptimal making the quantification of enzyme fluxes less reliable. A data-driven processing framework for dynamic HP 13C MR spectroscopic imaging (MRSI), Tensor Rank truncation Image enhancement (TRI) was developed to recover features from noisy imaging data. After validating this postprocessing approach in well defined preclinical studies, it is now tested in clinical datasets. Using patient data sets acquired from the brain, abdomen, and pelvis, we examined the theory and application of TRI. TRI provided a 31-fold gain for single-element configurations, which particularly improved quantification of the lowerSNR[13C]bicarbonate and alanine signals that were otherwise not detectable in many cases. This allowed for the first time assessment of multiple enzyme activities from the same data sets. Substantial SNR enhancements were observed for data sets that were acquired even with suboptimal experimental conditions, including delayed (114 s) injection (8 fold SNR gain solely by TRI), or from challenging anatomy or geometry, as in the case of a pediatric patient with brainstem tumor (fold using combined TRI and WSVD). Improved correlation between elevated pyruvate-to-lactate conversion, biopsy-confirmed cancer, and mp-MRI lesions demonstrated that TRI recovered quantitative diagnostic information. The TRI method of postprocessing image data sets has allowed recovery of features to make better quantification of enzyme activities in tumors making diagnoses more reliable. b) In vivo pharmacodynamic assessment of new generation LDHA inhibitors: The reliance of many cancers on aerobic glycolysis has stimulated efforts to develop lactate dehydrogenase (LDH) inhibitors. However, despite significant efforts, LDH inhibitors (LDHi) with sufficient specificity and in vivo activity to determine whether LDH is a feasible drug target are lacking. We used hyperpolarized 13C MRI to develop an in vivo pharmacodynamic imaging biomarker to assess the ontarget activity. We describe an LDHi with potent, on target, in vivo activity. Using hyperpolarized magnetic resonance spectroscopic imaging (HPMRSI), we demonstrate in vivo LDH inhibition in two glycolytic cancer models, MIA PaCa2 and HT29, and we correlate depth and duration of LDH inhibition with direct antitumor activity. HPMRSI also reveals a metabolic rewiring that occurs in vivo within 30 min of LDH inhibition, wherein pyruvate in a tumor is redirected toward mitochondrial metabolism. Using HPMRSI, we show that inhibition of mitochondrial complex 1 rapidly redirects tumor pyruvate toward lactate. Inhibition of both mitochondrial complex 1 and LDH suppresses metabolic plasticity, causing metabolic quiescence in vitro and tumor growth inhibition in vivo. c) Metabolic Imaging strategies with endogenous metabolic substrates: Metabolic differences among and within tumors can be an important determinant in cancer treatment outcome. However, methods for determining these differences noninvasively in vivo is lacking. Currently hyperpolarized tracers using dissolution DNP with 13C MRI is the only method available for preclinical and clinical research. However, this capability is available only in limited centers making the method's dissemination widely challenging. We have developed a noise reduction approach which allows 13C MRI with endogenous substrates without hyperpolarization, Using pancreatic ductal adenocarcinoma as a model, we demonstrate that tumor xenografts with a similar genetic background can be distinguished by their differing rates of the metabolism of 13C labeled glucose tracers, which can be imaged without hyperpolarization by using newly developed techniques for noise suppression. Using this method, cancer subtypes that appeared to have similar metabolic profiles based on steady state metabolic measurement can be distinguished from each other. The metabolic maps from 13Cglucose imaging localized lactate production and overall glucose metabolism to different regions of some tumors. Such tumor heterogeneity would be not detectable in FDGPET. This method of 13C MRI using 13C labeled endogenous substrates without hyperpolarization potentially widely disseminatable.