Comparison of compressed sensing reconstruction algorithms for P magnetic resonance spectroscopic imaging.

Phosphorus MR spectroscopy and spectroscopic imaging (P-MRS/MRSI) provide information about energy metabolism, membrane degradation and pH in vivo. In spite of their proven utility, P-MRS/MRSI are not often used primarily because of the challenges imposed by the low sensitivity and low concentration of metabolites leading to low signal to noise ratio (SNR), coarse spatial resolution and prolonged acquisition time. More recently there has been considerable interest in compressed sensing as an acceleration method for MR signal acquisition. This approach takes advantage of the intrinsic sparsity of the spectral data. In this work, we present a P-MRSI sequence that combines a flyback EPSI trajectory and compressed sensing, and we compared two different reconstruction methods, L1 norm minimization and low rank Hankel matrix completion. Our phantom results showed good preservation of spectral quality for both ×2.0 and ×3.0 acceleration factors, using both CS reconstruction methods. However, in vivo P-MRS brain data showed the low rank reconstruction approach was most suitable. Overall, this study shows the feasibility of combining a flyback EPSI trajectory and compressed sensing in the acquisition of P-MRSI as well as the better suitability of a low rank reconstruction approach.