Model-based Chemical Exchange Saturation Transfer MRI for Robust z-Spectrum Analysis

Abstract

This work introduces a novel, model-based chemical exchange saturation transfer (CEST) MRI, in which asymmetric spectra of interest are directly estimated from complete or incomplete measurements by incorporating subspace-based spectral signal decomposition into the measurement model of CEST MRI for robust z-spectrum analysis. Spectral signals are decomposed into symmetric and asymmetric components. The symmetric component, which varies smoothly, is delineated by linear superposition of a finite set of vectors in a basis trained from simulated (Lorentzian) signal vectors augmented with datadriven signal vectors, while the asymmetric component is to be inherently lower than or equal to zero due to saturation transfer phenomena. Spectral decomposition is performed directly on measured spectral data by solving a constrained optimization problem that employs the linearized spectral decomposition model for the symmetric component and the weighted Frobenius norm regularization for the asymmetric component while utilizing additional spatial sparsity and low rank priors. Simulations and in vivo experiments were performed to demonstrate the feasibility of the proposed method as a reliable molecular MRI. (c) 2018 IEEE.