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Abstract #0530

Spectroscopy with Linear Algebraic Modeling (SLAM): Speed and Quantification in Brain Tumor Studies

Yi Zhang1, 2, Refaat E. Gabr1, Jinyuan Zhou1, 3, Robert G. Weiss1, 4, Paul A. Bottomley1, 2

1Division o MR Research, Department of Radiolgoy, Johns Hopkins University, Baltimore, MD, United States; 2Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States; 3F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States; 4Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, United States

The inclusion of potentially useful MRS acquisitions in clinical MRI exams is often precluded by long study times for chemical shift imaging (CSI). Global- or lesion-averaged MRS-measurements can usually suffice for assessing metabolic status. A recently proposed methodspectroscopy with linear algebraic modeling (SLAM)could provide such assessments, in addition to a many-fold speed-up in scan-time. Here, SLAM applied retroactively to patients with brain tumors, is shown to yield quantitatively indistinguishable results from conventional 2D 1H CSI with an acceleration factor of six. Proactive studies demonstrate comparable results to CSI with a speedup factor of 14.