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In‐scanner head motion and structural covariance networks
In‐scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion‐affected and low‐mo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9435006/ https://www.ncbi.nlm.nih.gov/pubmed/35593313 http://dx.doi.org/10.1002/hbm.25957 |
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author | Pardoe, Heath R. Martin, Samantha P. |
author_facet | Pardoe, Heath R. Martin, Samantha P. |
author_sort | Pardoe, Heath R. |
collection | PubMed |
description | In‐scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion‐affected and low‐motion whole brain T1‐weighted MRI in 29 healthy adult subjects and estimated relative regional gray matter volumes using a voxel‐based morphometry approach. Structural covariance network analyses were undertaken while systematically increasing the number of included motion‐affected scans. We demonstrate that the standard deviation in regional gray matter estimates increases as the number of motion‐affected scans increases. This increases pairwise correlations between regions, a key determinant for construction of structural covariance networks. We further demonstrate that head motion systematically alters graph theoretic metrics derived from these networks. Finally, we present evidence that weighting correlations using image quality metrics can mitigate the effects of head motion. Our findings suggest that in‐scanner head motion is a source of error that violates the assumption that structural covariance networks reflect neuroanatomical connectivity between brain regions. Results of structural covariance studies should be interpreted with caution, particularly when subject groups are likely to move their heads in the scanner. |
format | Online Article Text |
id | pubmed-9435006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94350062022-09-08 In‐scanner head motion and structural covariance networks Pardoe, Heath R. Martin, Samantha P. Hum Brain Mapp Research Articles In‐scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion‐affected and low‐motion whole brain T1‐weighted MRI in 29 healthy adult subjects and estimated relative regional gray matter volumes using a voxel‐based morphometry approach. Structural covariance network analyses were undertaken while systematically increasing the number of included motion‐affected scans. We demonstrate that the standard deviation in regional gray matter estimates increases as the number of motion‐affected scans increases. This increases pairwise correlations between regions, a key determinant for construction of structural covariance networks. We further demonstrate that head motion systematically alters graph theoretic metrics derived from these networks. Finally, we present evidence that weighting correlations using image quality metrics can mitigate the effects of head motion. Our findings suggest that in‐scanner head motion is a source of error that violates the assumption that structural covariance networks reflect neuroanatomical connectivity between brain regions. Results of structural covariance studies should be interpreted with caution, particularly when subject groups are likely to move their heads in the scanner. John Wiley & Sons, Inc. 2022-05-20 /pmc/articles/PMC9435006/ /pubmed/35593313 http://dx.doi.org/10.1002/hbm.25957 Text en © 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Pardoe, Heath R. Martin, Samantha P. In‐scanner head motion and structural covariance networks |
title | In‐scanner head motion and structural covariance networks |
title_full | In‐scanner head motion and structural covariance networks |
title_fullStr | In‐scanner head motion and structural covariance networks |
title_full_unstemmed | In‐scanner head motion and structural covariance networks |
title_short | In‐scanner head motion and structural covariance networks |
title_sort | in‐scanner head motion and structural covariance networks |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9435006/ https://www.ncbi.nlm.nih.gov/pubmed/35593313 http://dx.doi.org/10.1002/hbm.25957 |
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