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Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies

Clinical multicenter imaging studies are frequent and rely on a wide range of existing tools for sharing data and processing pipelines. This is not the case for preclinical (small animal) studies. Animal population imaging is still in infancy, especially because a complete standardization and contro...

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Autores principales: Kain, Michael, Bodin, Marjolaine, Loury, Simon, Chi, Yao, Louis, Julien, Simon, Mathieu, Lamy, Julien, Barillot, Christian, Dojat, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248267/
https://www.ncbi.nlm.nih.gov/pubmed/32508612
http://dx.doi.org/10.3389/fninf.2020.00020
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author Kain, Michael
Bodin, Marjolaine
Loury, Simon
Chi, Yao
Louis, Julien
Simon, Mathieu
Lamy, Julien
Barillot, Christian
Dojat, Michel
author_facet Kain, Michael
Bodin, Marjolaine
Loury, Simon
Chi, Yao
Louis, Julien
Simon, Mathieu
Lamy, Julien
Barillot, Christian
Dojat, Michel
author_sort Kain, Michael
collection PubMed
description Clinical multicenter imaging studies are frequent and rely on a wide range of existing tools for sharing data and processing pipelines. This is not the case for preclinical (small animal) studies. Animal population imaging is still in infancy, especially because a complete standardization and control of initial conditions in animal models across labs is still difficult and few studies aim at standardization of acquisition and post-processing techniques. Clearly, there is a need of appropriate tools for the management and sharing of data, post-processing and analysis methods dedicated to small animal imaging. Solutions developed for Human imaging studies cannot be directly applied to this specific domain. In this paper, we present the Small Animal Shanoir (SAS) solution for supporting animal population imaging using tools compatible with open data. The integration of automated workflow tools ensures accessibility and reproducibility of research outputs. By sharing data and imaging processing tools, hosted by SAS, we promote data preparation and tools for reproducibility and reuse, and participation in multicenter or replication “open science” studies contributing to the improvement of quality science in preclinical domain. SAS is a first step for promoting open science for small animal imaging and a contribution to the valorization of data and pipelines of reference.
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spelling pubmed-72482672020-06-05 Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies Kain, Michael Bodin, Marjolaine Loury, Simon Chi, Yao Louis, Julien Simon, Mathieu Lamy, Julien Barillot, Christian Dojat, Michel Front Neuroinform Neuroscience Clinical multicenter imaging studies are frequent and rely on a wide range of existing tools for sharing data and processing pipelines. This is not the case for preclinical (small animal) studies. Animal population imaging is still in infancy, especially because a complete standardization and control of initial conditions in animal models across labs is still difficult and few studies aim at standardization of acquisition and post-processing techniques. Clearly, there is a need of appropriate tools for the management and sharing of data, post-processing and analysis methods dedicated to small animal imaging. Solutions developed for Human imaging studies cannot be directly applied to this specific domain. In this paper, we present the Small Animal Shanoir (SAS) solution for supporting animal population imaging using tools compatible with open data. The integration of automated workflow tools ensures accessibility and reproducibility of research outputs. By sharing data and imaging processing tools, hosted by SAS, we promote data preparation and tools for reproducibility and reuse, and participation in multicenter or replication “open science” studies contributing to the improvement of quality science in preclinical domain. SAS is a first step for promoting open science for small animal imaging and a contribution to the valorization of data and pipelines of reference. Frontiers Media S.A. 2020-05-19 /pmc/articles/PMC7248267/ /pubmed/32508612 http://dx.doi.org/10.3389/fninf.2020.00020 Text en Copyright © 2020 Kain, Bodin, Loury, Chi, Louis, Simon, Lamy, Barillot and Dojat. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Kain, Michael
Bodin, Marjolaine
Loury, Simon
Chi, Yao
Louis, Julien
Simon, Mathieu
Lamy, Julien
Barillot, Christian
Dojat, Michel
Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies
title Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies
title_full Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies
title_fullStr Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies
title_full_unstemmed Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies
title_short Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies
title_sort small animal shanoir (sas) a cloud-based solution for managing preclinical mr brain imaging studies
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248267/
https://www.ncbi.nlm.nih.gov/pubmed/32508612
http://dx.doi.org/10.3389/fninf.2020.00020
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