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Abstract #4835

Principal Spectra Analysis by Linear Modeling (PSALM)

Alexander Saunders1,2 and Stefan Blüml1,2
1Radiology, Children's Hospital Los Angeles, University of Southern California, Los Angeles, CA, United States, 2Rudi Schulte Research Institute, Santa Barbara, CA, United States


We hypothesized in vivo MR spectra can be sufficiently described by spectra representing predominant cell/tissue types rather than individual metabolites. We sought to extract two putative basis spectra of grey matter and white matter from 584 single-voxel 3T MR spectra using the principal spectra analysis by linear modeling (PSALM) custom algorithm. Two extracted PSALM bases explained >95% of fit variance; principal component analysis required 6-8 components to achieve the same. We found the algorithm produced high signal-to-noise, low linewidth basis spectra that robustly fit in vivo spectra from normal brain.

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