Partially parallel MR spectroscopic imaging of gliomas at 3T

Magnetic resonance spectroscopic imaging (MRSI) has been used to more accurately diagnose, localize, and assess progression and treatment response for gliomas. The main limitation of the MRSI is the long data acquisition times. A current approach is to reduce the amount of k-space data sampled by limiting the data acquisition to a central elliptical portion of k-space. This study investigated the feasibility of reducing the data acquisition time further for the MRSI data using two parallel imaging techniques and investigating the relative performance of sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA).