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Susceptibility artifact correction for sub-millimeter fMRI using inverse phase encoding registration and T1 weighted

S T M Duong1, S L Phung1, A Bouzerdoum2

  • 1School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia.

Journal of Neuroscience Methods
|February 17, 2020
PubMed
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This study introduces a new method to correct brain imaging distortions in functional magnetic resonance imaging (fMRI). The technique improves the accuracy of high-resolution fMRI scans by reducing artifacts, aiding brain function research.

Area of Science:

  • Neuroimaging
  • Biomedical Engineering

Background:

  • Functional magnetic resonance imaging (fMRI) allows non-invasive brain examination.
  • High spatial-resolution fMRI research faces challenges from unavoidable susceptibility artifacts in echo-planar imaging (EPI).
  • These distortions can misrepresent brain function, especially in sub-millimeter resolution studies.

Purpose of the Study:

  • To present a novel method for correcting susceptibility artifacts in fMRI.
  • To improve the accuracy of intra-cortex and layer-specific fMRI studies.
  • To offer a robust solution for sub-millimeter fMRI data.

Main Methods:

  • Combines T1-weighted (T1w) images with inverse phase-encoding (PE) based registration.
  • Utilizes two EPI images with inverse-PE directions for registration.
Keywords:
Echo-planar imagingInverse phase-encodingSub-millimeter fMRISusceptibility artifactguided regularization

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  • Employs the T1w image for regularization and automatic parameter selection.

    • Main Results:

    • The method demonstrated improved artifact corrections on sub-millimeter EPI-fMRI datasets (3T and 7T).
    • Corrections were well-aligned with the anatomical reference provided by the T1w image.
    • The approach yielded more robust and sharper corrections compared to existing methods.

    Conclusions:

    • The proposed method offers a promising approach for susceptibility artifact correction in fMRI.
    • It provides faster and more accurate results than state-of-the-art methods like HySCO and TOPUP.
    • This technique is particularly relevant given the increasing popularity of sub-millimeter fMRI.