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Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge

The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same...

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Autores principales: Veronese, Mattia, Rizzo, Gaia, Belzunce, Martin, Schubert, Julia, Searle, Graham, Whittington, Alex, Mansur, Ayla, Dunn, Joel, Reader, Andrew, Gunn, Roger N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504414/
https://www.ncbi.nlm.nih.gov/pubmed/33993794
http://dx.doi.org/10.1177/0271678X211015101
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author Veronese, Mattia
Rizzo, Gaia
Belzunce, Martin
Schubert, Julia
Searle, Graham
Whittington, Alex
Mansur, Ayla
Dunn, Joel
Reader, Andrew
Gunn, Roger N
author_facet Veronese, Mattia
Rizzo, Gaia
Belzunce, Martin
Schubert, Julia
Searle, Graham
Whittington, Alex
Mansur, Ayla
Dunn, Joel
Reader, Andrew
Gunn, Roger N
author_sort Veronese, Mattia
collection PubMed
description The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same data are analysed. This problem is well-known in MRI studies, where the indisputable value of the method has been complicated by a number of studies that produce discrepant results. However, any research domain with complex data and flexible analytical procedures can experience a similar lack of reproducibility. In this paper we investigate this issue for brain PET imaging. During the 2018 NeuroReceptor Mapping conference, the brain PET community was challenged with a computational contest involving a simulated neurotransmitter release experiment. Fourteen international teams analysed the same imaging dataset, for which the ground-truth was known. Despite a plurality of methods, the solutions were consistent across participants, although not identical. These results should create awareness that the increased sharing of PET data alone will only be one component of enhancing confidence in neuroimaging results and that it will be important to complement this with full details of the analysis pipelines and procedures that have been used to quantify data.
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spelling pubmed-85044142021-10-12 Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge Veronese, Mattia Rizzo, Gaia Belzunce, Martin Schubert, Julia Searle, Graham Whittington, Alex Mansur, Ayla Dunn, Joel Reader, Andrew Gunn, Roger N J Cereb Blood Flow Metab Original Articles The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same data are analysed. This problem is well-known in MRI studies, where the indisputable value of the method has been complicated by a number of studies that produce discrepant results. However, any research domain with complex data and flexible analytical procedures can experience a similar lack of reproducibility. In this paper we investigate this issue for brain PET imaging. During the 2018 NeuroReceptor Mapping conference, the brain PET community was challenged with a computational contest involving a simulated neurotransmitter release experiment. Fourteen international teams analysed the same imaging dataset, for which the ground-truth was known. Despite a plurality of methods, the solutions were consistent across participants, although not identical. These results should create awareness that the increased sharing of PET data alone will only be one component of enhancing confidence in neuroimaging results and that it will be important to complement this with full details of the analysis pipelines and procedures that have been used to quantify data. SAGE Publications 2021-05-17 2021-10 /pmc/articles/PMC8504414/ /pubmed/33993794 http://dx.doi.org/10.1177/0271678X211015101 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Articles
Veronese, Mattia
Rizzo, Gaia
Belzunce, Martin
Schubert, Julia
Searle, Graham
Whittington, Alex
Mansur, Ayla
Dunn, Joel
Reader, Andrew
Gunn, Roger N
Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
title Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
title_full Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
title_fullStr Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
title_full_unstemmed Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
title_short Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge
title_sort reproducibility of findings in modern pet neuroimaging: insight from the nrm2018 grand challenge
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504414/
https://www.ncbi.nlm.nih.gov/pubmed/33993794
http://dx.doi.org/10.1177/0271678X211015101
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