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Abstract #0709

Dramatic Speedup in 1D-, 2D- & 3D-MRS Scan Times with Linear Algebraic Modeling (SLAM)

MAGNA25Yi Zhang1, 2, Refaat E. Gabr1, Michael Schr1, 3, He Zhu1, 4, Peter Barker1, 4, Robert G. Weiss1, 5, Paul A. Bottomley1, 2

1Division of MR Research, Department of Radiology, Johns Hopkins Univesity, Baltimore, MD, United States; 2Department of Electrical and Computer Engineering, Johns Hopkins Univesity, Baltimore, MD, United States; 3Philips Healthcare, Cleveland, OH, United States; 4F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States; 5Division of Cardiology, Department of Medicine, Johns Hopkins Univesity, Baltimore, MD, United States

Scan-time is a central concern for chemical shift imaging (CSI). While model-based MRS reconstruction methods could reduce scan times significantly, their in vivo application is limited and focused on suppressing inter-compartmental leakage. Here, spectroscopy localization with linear algebraic modeling (SLAM) is introduced to dramatically speed-up scan-time. SLAM uses a minimal number of phase-encoding steps that are selected from central k-space, to reconstruct average spectra from pre-selected sample compartments. We demonstrate that SLAM yields essentially the same spectra as compartmentally averaged 1D, 2D and 3D CSI spectra, but 4-, 16- and 100-fold faster, respectively. The signal-to-noise ratio cost was ≤50%.