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

Hoonjae Lee, Julius Juhyun Chung, Joonyeol Lee, Seong Gi Kim, Jae Ho Han, Jaeseok Park

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)

    Abstract

    This paper introduces a novel, model-based chemical exchange saturation transfer (CEST) magnetic resonance imaging (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 a robust z-spectrum analysis. Spectral signals are decomposed into symmetric and asymmetric components. The symmetric component, which varies smoothly, is delineated by the linear superposition of a finite set of vectors in a basis trained from the simulated (Lorentzian) signal vectors augmented with data-driven 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 the 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. The simulations and in vivo experiments were performed to demonstrate the feasibility of the proposed method as a reliable molecular MRI.

    Original languageEnglish
    Article number8640851
    Pages (from-to)283-293
    Number of pages11
    JournalIEEE Transactions on Medical Imaging
    Volume39
    Issue number2
    DOIs
    Publication statusPublished - 2020 Feb

    Bibliographical note

    Publisher Copyright:
    © 1982-2012 IEEE.

    Keywords

    • Magnetic resonance imaging
    • chemical exchange saturation transfer
    • compressed sensing
    • fast imaging
    • z-spectrum

    ASJC Scopus subject areas

    • Software
    • Radiological and Ultrasound Technology
    • Computer Science Applications
    • Electrical and Electronic Engineering

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