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Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing

BACKGROUND: Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective...

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Autores principales: Wiseman, Stewart J., Meijboom, Rozanna, Valdés Hernández, Maria del C., Pernet, Cyril, Sakka, Eleni, Job, Dominic, Waldman, Adam D., Wardlaw, Joanna M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323670/
https://www.ncbi.nlm.nih.gov/pubmed/30616680
http://dx.doi.org/10.1186/s13063-018-3113-6
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author Wiseman, Stewart J.
Meijboom, Rozanna
Valdés Hernández, Maria del C.
Pernet, Cyril
Sakka, Eleni
Job, Dominic
Waldman, Adam D.
Wardlaw, Joanna M.
author_facet Wiseman, Stewart J.
Meijboom, Rozanna
Valdés Hernández, Maria del C.
Pernet, Cyril
Sakka, Eleni
Job, Dominic
Waldman, Adam D.
Wardlaw, Joanna M.
author_sort Wiseman, Stewart J.
collection PubMed
description BACKGROUND: Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalisability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies. METHODS: We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss. RESULTS: The recommendations are grouped into seven categories: (1) planning, (2) defining the imaging endpoints, developing an imaging manual and managing the workflow, (3) performing a dummy run and testing the analysis methods, (4) acquiring the scans, (5) anonymising and transferring the data, (6) monitoring quality, and (7) using structured data and sharing data. CONCLUSIONS: Implementing these steps will lead to valuable and usable data and help to avoid imaging data wastage.
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spelling pubmed-63236702019-01-10 Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing Wiseman, Stewart J. Meijboom, Rozanna Valdés Hernández, Maria del C. Pernet, Cyril Sakka, Eleni Job, Dominic Waldman, Adam D. Wardlaw, Joanna M. Trials Methodology BACKGROUND: Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalisability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies. METHODS: We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss. RESULTS: The recommendations are grouped into seven categories: (1) planning, (2) defining the imaging endpoints, developing an imaging manual and managing the workflow, (3) performing a dummy run and testing the analysis methods, (4) acquiring the scans, (5) anonymising and transferring the data, (6) monitoring quality, and (7) using structured data and sharing data. CONCLUSIONS: Implementing these steps will lead to valuable and usable data and help to avoid imaging data wastage. BioMed Central 2019-01-07 /pmc/articles/PMC6323670/ /pubmed/30616680 http://dx.doi.org/10.1186/s13063-018-3113-6 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Wiseman, Stewart J.
Meijboom, Rozanna
Valdés Hernández, Maria del C.
Pernet, Cyril
Sakka, Eleni
Job, Dominic
Waldman, Adam D.
Wardlaw, Joanna M.
Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
title Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
title_full Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
title_fullStr Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
title_full_unstemmed Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
title_short Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
title_sort longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323670/
https://www.ncbi.nlm.nih.gov/pubmed/30616680
http://dx.doi.org/10.1186/s13063-018-3113-6
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