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Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T

In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from s...

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Autores principales: Sarlls, Joelle E., Lalonde, Francois, Rettmann, Dan, Shankaranarayanan, Ajit, Roopchansingh, Vinai, Talagala, S. Lalith
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6023162/
https://www.ncbi.nlm.nih.gov/pubmed/29953459
http://dx.doi.org/10.1371/journal.pone.0199372
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author Sarlls, Joelle E.
Lalonde, Francois
Rettmann, Dan
Shankaranarayanan, Ajit
Roopchansingh, Vinai
Talagala, S. Lalith
author_facet Sarlls, Joelle E.
Lalonde, Francois
Rettmann, Dan
Shankaranarayanan, Ajit
Roopchansingh, Vinai
Talagala, S. Lalith
author_sort Sarlls, Joelle E.
collection PubMed
description In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images. Prospective motion correction (PMC) techniques have been developed to help mitigate artifacts due to subject motion. In this work, high-resolution MPRAGE images are acquired during intentional head motion to evaluate the effectiveness of navigator-based PMC techniques to improve both the accuracy and reproducibility of cortical morphometry measures obtained from image segmentation. The contribution of reacquiring segments of k-space affected by motion to the overall performance of PMC is assessed. Additionally, the effect of subject motion on subcortical structure volumes is investigated. In the presence of head motion, navigator-based PMC is shown to improve both the accuracy and reproducibility of cortical and subcortical measures. It is shown that reacquiring segments of k-space data that are corrupted by motion is an essential part of navigator-based PMC performance. Subcortical structure volumes are not affected by motion in the same way as cortical measures; there is not a consistent underestimation.
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spelling pubmed-60231622018-07-07 Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T Sarlls, Joelle E. Lalonde, Francois Rettmann, Dan Shankaranarayanan, Ajit Roopchansingh, Vinai Talagala, S. Lalith PLoS One Research Article In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images. Prospective motion correction (PMC) techniques have been developed to help mitigate artifacts due to subject motion. In this work, high-resolution MPRAGE images are acquired during intentional head motion to evaluate the effectiveness of navigator-based PMC techniques to improve both the accuracy and reproducibility of cortical morphometry measures obtained from image segmentation. The contribution of reacquiring segments of k-space affected by motion to the overall performance of PMC is assessed. Additionally, the effect of subject motion on subcortical structure volumes is investigated. In the presence of head motion, navigator-based PMC is shown to improve both the accuracy and reproducibility of cortical and subcortical measures. It is shown that reacquiring segments of k-space data that are corrupted by motion is an essential part of navigator-based PMC performance. Subcortical structure volumes are not affected by motion in the same way as cortical measures; there is not a consistent underestimation. Public Library of Science 2018-06-28 /pmc/articles/PMC6023162/ /pubmed/29953459 http://dx.doi.org/10.1371/journal.pone.0199372 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Sarlls, Joelle E.
Lalonde, Francois
Rettmann, Dan
Shankaranarayanan, Ajit
Roopchansingh, Vinai
Talagala, S. Lalith
Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T
title Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T
title_full Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T
title_fullStr Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T
title_full_unstemmed Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T
title_short Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T
title_sort effectiveness of navigator-based prospective motion correction in mprage data acquired at 3t
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6023162/
https://www.ncbi.nlm.nih.gov/pubmed/29953459
http://dx.doi.org/10.1371/journal.pone.0199372
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