Assessing methods for geometric distortion compensation in 7 T gradient echo functional MRI data

Research output: Contribution to journalArticlepeer-review

Abstract

Echo planar imaging (EPI) is widely used in functional and diffusion-weighted MRI, but suffers from significant geometric distortions in the phase encoding direction caused by inhomogeneities in the static magnetic field (B0). This is a particular challenge for EPI at very high field (≥7 T), as distortion increases with higher field strength. A number of techniques for distortion correction exist, including those based on B0 field mapping and acquiring EPI scans with opposite phase encoding directions. However, few quantitative comparisons of distortion compensation methods have been performed using human EPI data, especially at very high field. Here, we compared distortion compensation using B0 field maps and opposite phase encoding scans in two different software packages (FSL and AFNI) applied to 7 T gradient echo (GE) EPI data from 31 human participants. We assessed distortion compensation quality by quantifying alignment to anatomical reference scans using Dice coefficients and mutual information. Performance between FSL and AFNI was equivalent. In our whole-brain analyses, we found superior distortion compensation using GE scans with opposite phase encoding directions, versus B0 field maps or spin echo (SE) opposite phase encoding scans. However, SE performed better when analyses were limited to ventromedial prefrontal cortex, a region with substantial dropout. Matching the type of opposite phase encoding scans to the EPI data being corrected (e.g., SE-to-SE) also yielded better distortion correction. While the ideal distortion compensation approach likely varies depending on methodological differences across experiments, this study provides a framework for quantitative comparison of different distortion compensation methods.

Original languageEnglish (US)
Pages (from-to)4205-4223
Number of pages19
JournalHuman Brain Mapping
Volume42
Issue number13
DOIs
StatePublished - Sep 2021

Bibliographical note

Funding Information:
The authors thank Jesslyn (Li Shen) Chong, Tori Espensen‐Sturges, Andrea N. Grant, Rohit S. Kamath, Timothy J. Lano, and Marisa J. Sanchez for their assistance with data collection. The authors also thank Bryon A. Mueller and Hannah R. Moser for help with data processing, and Essa Yacoub for supporting the design of the study. This work was supported by funding from the National Institutes of Health (U01 MH108150). Salary support for M.‐P. S. was provided by K01 MH120278. Salary support for C. A. O. was provided by R01 MH111447. Support for MR scanning at the University of Minnesota Center for Magnetic Resonance Research was provided by P41 EB015894 and P30 NS076408. This work used tools from the University of Minnesota Clinical and Translational Science Institute that were supported by UL1 TR002494. The authors declare that they have no conflicts of interest with regard to the publication of this manuscript.

Funding Information:
The authors thank Jesslyn (Li Shen) Chong, Tori Espensen-Sturges, Andrea N. Grant, Rohit S. Kamath, Timothy J. Lano, and Marisa J. Sanchez for their assistance with data collection. The authors also thank Bryon A. Mueller and Hannah R. Moser for help with data processing, and Essa Yacoub for supporting the design of the study. This work was supported by funding from the National Institutes of Health (U01 MH108150). Salary support for M.-P. S. was provided by K01 MH120278. Salary support for C. A. O. was provided by R01 MH111447. Support for MR scanning at the University of Minnesota Center for Magnetic Resonance Research was provided by P41 EB015894 and P30 NS076408. This work used tools from the University of Minnesota Clinical and Translational Science Institute that were supported by UL1 TR002494. The authors declare that they have no conflicts of interest with regard to the publication of this manuscript.

Publisher Copyright:
© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

Keywords

  • 7 Tesla
  • B inhomogeneity
  • distortion compensation
  • echo planar imaging
  • field map
  • functional MRI

PubMed: MeSH publication types

  • Journal Article

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