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.