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Updated: Jun 4, 2026

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

Frame-wise multi-echo distortion correction for superior functional MRI.

Andrew N Van^1,2, David F Montez^2,3, Timothy O Laumann³

¹Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States.

Imaging Neuroscience (Cambridge, Mass.)

|June 3, 2026

Summary

This summary is machine-generated.

This study introduces MEDIC, a new method using multi-echo fMRI to correct head motion distortions in real-time. MEDIC improves functional connectivity and anatomical alignment without needing separate field map scans.

Keywords:

distortion correction fMRI multi-echo

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Area of Science:

Neuroimaging
Magnetic Resonance Imaging (MRI)
Data Processing

Background:

Functional MRI (fMRI) data suffer from magnetic field (B0) inhomogeneities causing geometric distortions.
Existing correction methods require separate field map acquisitions, which are sensitive to participant head motion.
Head motion during field mapping corrupts data, hindering accurate distortion correction.

Purpose of the Study:

To develop and validate a dynamic, frame-by-frame distortion correction method for fMRI data.
To leverage multi-echo (ME) fMRI data to correct for magnetic field distortions caused by head motion.
To assess the impact of motion-corrected fMRI data on resting-state functional connectivity (RSFC) and anatomical alignment.

Main Methods:

Developed the Multi-Echo DIstortion Correction (MEDIC) pipeline using ME fMRI data.
MEDIC utilizes differences between echoes to estimate and correct magnetic field inhomogeneities on a frame-by-frame basis.
Compared MEDIC's performance against the established FSL TOPUP method for distortion correction.

Main Results:

MEDIC effectively corrects geometric distortions dynamically, frame-by-frame, mitigating head motion artifacts.
Frame-wise correction with MEDIC significantly reduces the impact of head motion on resting-state functional connectivity (RSFC) maps.
MEDIC demonstrates improved alignment to anatomical references compared to the standard FSL TOPUP approach.
The method eliminates the need for separate field map acquisition, simplifying the fMRI workflow.

Conclusions:

MEDIC provides a robust, motion-robust method for correcting fMRI geometric distortions using ME data.
This approach enhances the reliability of RSFC analyses and improves anatomical registration in fMRI studies.
MEDIC offers a significant advancement over traditional single-echo fMRI correction techniques, particularly in the presence of head motion.