Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.

In this paper we evaluate the three main methods for correcting the susceptibility-induced artefact in diffusion-weighted magnetic-resonance (DW-MR) data, and assess how correction is affected by the susceptibility field's interaction with motion. The susceptibility artefact adversely impacts a...

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Main Authors: Mark S Graham, Ivana Drobnjak, Mark Jenkinson, Hui Zhang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5624609?pdf=render
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spelling doaj-44da96d36c83474e8ac7c9c48385249f2020-11-25T00:04:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-011210e018564710.1371/journal.pone.0185647Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.Mark S GrahamIvana DrobnjakMark JenkinsonHui ZhangIn this paper we evaluate the three main methods for correcting the susceptibility-induced artefact in diffusion-weighted magnetic-resonance (DW-MR) data, and assess how correction is affected by the susceptibility field's interaction with motion. The susceptibility artefact adversely impacts analysis performed on the data and is typically corrected in post-processing. Correction strategies involve either registration to a structural image, the application of an acquired field-map or the use of additional images acquired with different phase-encoding. Unfortunately, the choice of which method to use is made difficult by the absence of any systematic comparisons of them. In this work we quantitatively evaluate these methods, by extending and employing a recently proposed framework that allows for the simulation of realistic DW-MR datasets with artefacts. Our analysis separately evaluates the ability for methods to correct for geometric distortions and to recover lost information in regions of signal compression. In terms of geometric distortions, we find that registration-based methods offer the poorest correction. Field-mapping techniques are better, but are influenced by noise and partial volume effects, whilst multiple phase-encode methods performed best. We use our simulations to validate a popular surrogate metric of correction quality, the comparison of corrected data acquired with AP and LR phase-encoding, and apply this surrogate to real datasets. Furthermore, we demonstrate that failing to account for the interaction of the susceptibility field with head movement leads to increased errors when analysing DW-MR data. None of the commonly used post-processing methods account for this interaction, and we suggest this may be a valuable area for future methods development.http://europepmc.org/articles/PMC5624609?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Mark S Graham
Ivana Drobnjak
Mark Jenkinson
Hui Zhang
spellingShingle Mark S Graham
Ivana Drobnjak
Mark Jenkinson
Hui Zhang
Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.
PLoS ONE
author_facet Mark S Graham
Ivana Drobnjak
Mark Jenkinson
Hui Zhang
author_sort Mark S Graham
title Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.
title_short Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.
title_full Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.
title_fullStr Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.
title_full_unstemmed Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI.
title_sort quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion mri.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description In this paper we evaluate the three main methods for correcting the susceptibility-induced artefact in diffusion-weighted magnetic-resonance (DW-MR) data, and assess how correction is affected by the susceptibility field's interaction with motion. The susceptibility artefact adversely impacts analysis performed on the data and is typically corrected in post-processing. Correction strategies involve either registration to a structural image, the application of an acquired field-map or the use of additional images acquired with different phase-encoding. Unfortunately, the choice of which method to use is made difficult by the absence of any systematic comparisons of them. In this work we quantitatively evaluate these methods, by extending and employing a recently proposed framework that allows for the simulation of realistic DW-MR datasets with artefacts. Our analysis separately evaluates the ability for methods to correct for geometric distortions and to recover lost information in regions of signal compression. In terms of geometric distortions, we find that registration-based methods offer the poorest correction. Field-mapping techniques are better, but are influenced by noise and partial volume effects, whilst multiple phase-encode methods performed best. We use our simulations to validate a popular surrogate metric of correction quality, the comparison of corrected data acquired with AP and LR phase-encoding, and apply this surrogate to real datasets. Furthermore, we demonstrate that failing to account for the interaction of the susceptibility field with head movement leads to increased errors when analysing DW-MR data. None of the commonly used post-processing methods account for this interaction, and we suggest this may be a valuable area for future methods development.
url http://europepmc.org/articles/PMC5624609?pdf=render
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