Abstract: Modern oncology aims at patient-specific therapy approaches, which triggered the development of biomedical imaging techniques to synergistically address tumor biology at the cellular and molecular level. PET/MR is a new hybrid modality that allows acquisition of high-resolution anatomic images and quantification of functional and metabolic information at the same time. Key steps of the Warburg effect-one of the hallmarks of tumors-can be measured non-invasively with this emerging technique. The aim of this study was to quantify and compare simultaneously imaged augmented glucose uptake and LDH activity in a subcutaneous breast cancer model in rats (MAT-B-III) and to study the effect of varying tumor cellularity on image-derived metabolic information. Methods: For this purpose, we established and validated a multimodal imaging workflow for a clinical PET/MR system including proton magnetic resonance (MR) imaging to acquire accurate morphologic information and diffusion-weighted imaging (DWI) to address tumor cellularity. Metabolic data were measured with dynamic [18F]FDG-PET and hyperpolarized (HP) 13C-pyruvate MR spectroscopic imaging (MRSI). We applied our workflow in a longitudinal study and analyzed the effect of growth dependent variations of cellular density on glycolytic parameters. Results: Tumors of similar cellularity with similar apparent diffusion coefficients (ADC) showed a significant positive correlation of FDG uptake and pyruvate-to-lactate exchange. Longitudinal DWI data indicated a decreasing tumor cellularity with tumor growth, while ADCs exhibited a significant inverse correlation with PET standard uptake values (SUV). Similar but not significant trends were observed with HP-13C-MRSI, but we found that partial volume effects and point spread function artifacts are major confounders for the quantification of 13C-data when the spatial resolution is limited and major blood vessels are close to the tumor. Nevertheless, analysis of longitudinal data with varying tumor cellularity further detected a positive correlation between quantitative PET and 13C-data. Conclusions: Our workflow allows the quantification of simultaneously acquired PET, MRSI and DWI data in rodents on a clinical PET/MR scanner. The correlations and findings suggest that a major portion of consumed glucose is metabolized by aerobic glycolysis in the investigated tumor model. Furthermore, we conclude that variations in cell density affect PET and 13C-data in a similar manner and correlations of longitudinal metabolic data appear to reflect both biochemical processes and tumor cellularity

Abstract: pH is a tightly regulated physiological parameter that is often altered in diseased states like cancer. The development of biosensors that can be used to non-invasively image pH with hyperpolarized (HP) magnetic resonance spectroscopic imaging has therefore recently gained tremendous interest. However, most of the known HP-sensors have only individually and not comprehensively been analyzed for their biocompatibility, their pH sensitivity under physiological conditions, and the effects of chemical derivatization on their logarithmic acid dissociation constant (pKa). Proteinogenic amino acids are biocompatible, can be hyperpolarized and have at least two pH sensitive moieties. However, they do not exhibit a pH sensitivity in the physiologically relevant pH range. Here, we developed a systematic approach to tailor the pKa of molecules using modifications of carbon chain length and derivatization rendering these molecules interesting for pH biosensing. Notably, we identified several derivatives such as [1-13C]serine amide and [1-13C]-2,3-diaminopropionic acid as novel pH sensors. They bear several spin-1/2 nuclei (13C, 15N, 31P) with high sensitivity up to 4.8 ppm/pH and we show that 13C spins can be hyperpolarized with dissolution dynamic polarization (DNP). Our findings elucidate the molecular mechanisms of chemical shift pH sensors that might help to design tailored probes for specific pH in vivo imaging applications