Diffusion-weighted chemical shift imaging (DW-CSI) is a recently developed MRI modality that enables radiologists to reveal the diffusion properties of small molecules that act in metabolic reactions in-vivo. In order to extract this diffusion information from a patient, DW-CSI requires approximately one hour of scan time. This extensive scan time makes DW-CSI currently inapplicable for the clinical setting. This thesis describes the closely intertwined implementation of compressed sensing with parameter mapping (CS-PM) in the DW-CSI processing pipeline to accelerate its acquisition. The CS-PM algorithm enables DW-CSI to acquire less measurements (sample under Nyquist) and subsequently reconstruct the missing samples with the use of a custom designed, model-based sparsifying dictionary. As proof of concept, CS-PM was evaluated on the water signal of a non-water-suppressed DW-CSI scan. The results of the integration of CS-PM in the DW-CSI processing pipeline already indicates a feasible acceleration factor of 1.5 (scan time reduction of ca. 20 minutes) along with valuable insight to further improve the performance of DW-CSI in combination with CS-PM.