Highly accelerated chemical exchange saturation transfer (CEST) measurements with linear algebraic modeling.

PURPOSE: In clinical studies, compartmental average chemical exchange saturation transfer (CEST) measurements rather than voxel-by-voxel CEST images may suffice for evaluating its diagnostic value. A recently developed method-spectroscopy with linear algebraic modeling, or SLAM-could directly provide compartmental measures with dramatically reduced scan time and optimal signal-to-noise ratios. Here, we test whether SLAM can be adapted to significantly accelerate CEST acquisitions. THEORY AND METHODS: Conventional anatomical images and raw CEST image k-space data were acquired from seven brain tumor patients. SLAM was applied to the CEST data using acceleration factors of R = 1-45, after segmenting compartments from co-registered images. SLAM-CEST measures were compared with average values from the identical compartments obtained by conventional Fourier transform (FT) CEST.
RESULTS: SLAM generated compartmental average CEST z-spectra that were indistinguishable from conventional FT-CEST for R ≤ 45. SLAM-CEST z-spectra at ±3.5 ppm were highly correlated with FT-CEST measures (r(2)  ≥ 0.98 for R ≤ 9; r ≥ 0.995 for R ≤ 45). The average error of SLAM-CEST versus FT-CEST measures was ≤10% for R ≤ 45, in acquisitions requiring as few as a single k-space phase-encoding step.
CONCLUSION: Applied to patients with brain tumors, SLAM-CEST can yield results that are quantitatively equivalent to conventional CEST up to 45 times faster, which could prove enabling in clinical settings where scan time is limiting. Magn Reson Med 76:136-144, 2016.