Accelerating CEST MRI in the mouse brain at 9.4 T by exploiting sparsity in the Z-spectrum domain.

Purpose Chemical exchange saturation transfer (CEST) is an MR contrast modality offering an enhanced sensitivity for the detection of dilute metabolites with exchangeable protons. Quantitative analysis requires the acquisition of a number of images (usually between 20 and 50 RF offsets) perZ-spectrum, leading to long acquisition times of the order of 5-40 min in practice. In this work, we explore the possibility of employing sparsity in theZ-spectrum domain (irradiation offset dimension) to provide an accelerated acquisition scheme without compromising the quality of reconstructed CEST spectra. Method and Theory Ex vivo and in vivo data were acquired on an experimental, small animal 9.4 T system. Three different reconstruction methods were tested:k-ZSPARSE,k-ZSLR andk-Zprincipal component analysis (PCA) using retrospective undersampling with net acceleration factorsR= 2, 3, 5. The quality of the reconstructed data was compared with respect to CEST spectra and full magnetization transfer ratio (MTR) asymmetry maps. Results In both phantom and in vivo data, CEST spectra and the resulting MTR asymmetry maps were reconstructed without significant deterioration in data quality. For a low acceleration factor (R= 2, 3) all applied methods resulted in similar data quality, while for high acceleration factor (R= 5) onlyk-ZPCA andk-ZSLR could be used. Loss in spatial resolution was observed in reconstruction withk-ZPCA for all acceleration factors. An example of prospective undersampling with acceleration factorR= 3 andk-ZPCA reconstruction demonstrates improved CEST maps when compared with fully sampled data acquisition with either three times longer scan duration or threefold prolonged acquisition window per frequency offset. Conclusion The acquisition time of CEST spectra can be significantly accelerated by exploiting the sparsity of theZ-domain. For prospective and retrospective analysis usingk-ZPCA, an acceleration factor of up toR= 3 can be used without significant loss in data quality.