System and method for ultrafast magnetic resonance spectroscopic imaging using learned spectral features

Abstract

A new method is developed for ultrafast, high-resolution magnetic resonance spectroscopic imaging (MRSI) using learned spectral features. The method uses Free Induction Decay (FID) based ultrashort-TE and short-TR acquisition without any solvent suppression pulses to generate the desired spatiospectral encodings. The spectral features for the desired molecules are learned from specifically designed 'training' data by taking into account the resonance structure of each compound generated by quantum mechanical simulations. A union-of-subspaces model that incorporates the learned spectral features is used to effectively separate the unsuppressed water/lipid signals, the metabolite signals, and the macromolecule signals. The unsuppressed water spectroscopic signals in the data can be used for various purposes, e.g., removing the need of additional auxiliary scans for calibration, and for generating high quality quantitative tissue susceptiability mapping etc. Simultaneous spatiospectral reconstructions of water, lipids, metabolite and macromolecule can be obtained using a singleH-MRSI scan.