Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker Review uri icon

Overview

MeSH Major

  • Algorithms
  • Biomarkers
  • Image Interpretation, Computer-Assisted
  • Magnetic Resonance Imaging
  • Molecular Imaging

abstract

  • In MRI, the main magnetic field polarizes the electron cloud of a molecule, generating a chemical shift for observer protons within the molecule and a magnetic susceptibility inhomogeneity field for observer protons outside the molecule. The number of water protons surrounding a molecule for detecting its magnetic susceptibility is vastly greater than the number of protons within the molecule for detecting its chemical shift. However, the study of tissue magnetic susceptibility has been hindered by poor molecular specificities of hitherto used methods based on MRI signal phase and T2* contrast, which depend convolutedly on surrounding susceptibility sources. Deconvolution of the MRI signal phase can determine tissue susceptibility but is challenged by the lack of MRI signal in the background and by the zeroes in the dipole kernel. Recently, physically meaningful regularizations, including the Bayesian approach, have been developed to enable accurate quantitative susceptibility mapping (QSM) for studying iron distribution, metabolic oxygen consumption, blood degradation, calcification, demyelination, and other pathophysiological susceptibility changes, as well as contrast agent biodistribution in MRI. This paper attempts to summarize the basic physical concepts and essential algorithmic steps in QSM, to describe clinical and technical issues under active development, and to provide references, codes, and testing data for readers interested in QSM. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

publication date

  • January 2014

Research

keywords

  • Review

Identity

Language

  • eng

PubMed Central ID

  • PMC4297605

Digital Object Identifier (DOI)

  • 10.1002/mrm.25358

PubMed ID

  • 25044035

Additional Document Info

volume

  • 73

number

  • 1