Metabolism is very different in disease compared to healthy tissue, and  can be measured non-invasively by in-vivo MR spectroscopy (MRS). Mapping the spatial distribution of metabolites levels by MRS imaging (MRSI) is highly valuable for patient management, however because of low concentrations and spectral overlap of metabolites it is challenging to perform metabolic imaging using MRSI. In this lecture I will present advanced acquisition and reconstruction methods together with novel hardware that allow to push the limits of spatial resolution, reduce time, and improve data quality. This is possible due to advanced sampling and reconstruction techniques such as compressed sensing, low-rank modeling, real-time motion correction, shim update, integrated RF-receive/B0-shim array coils, and rapid quantification with AI based methods.