Magnetic Resonance Spectroscopic Imaging (MRSI) is a functional MRI technique allowing non-invasive biochemical mapping of the brain. MRSI is advantageous for characterising many neurological conditions; however, its clinical application is limited by lengthy scan time and low spatial resolution, which are intrinsically linked.
This research investigated the potential of Compressed Sensing (CS) to speed-up MRSI or enhance spatial resolution. CS allows accelerated acquisition by reducing the data sampling requirements, whilst preserving image quality. The focus of this work was the effect of CS-MRSI at different acceleration factors upon spatial integrity.
CS reconstruction software was developed and applied to retrospective MRSI data. Imaging test objects and software simulations were developed to assess MRSI spatial resolution via metabolite edge response measurements. CS-MRSI was also investigated in realistic scenarios using data from healthy volunteers and a child with Optic Pathway Glioma (OPG). The potential of CS-MRSI to enable high-resolution MRSI in feasible scan times was investigated using simulations of focal and infiltrative OPG.
Results suggest that CS-MRSI can reduce scan duration by up to a factor of 5 whilst simultaneously eliminating ringing artefacts and increasing spatial resolution compared with conventionally filtered MRSI. Therefore, CS could greatly increase the clinical utility of MRSI
