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  Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Cohen-Adad, J., Alonso-Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., et al. (2021). Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Scientific Data, 8: 219. doi:10.1038/s41597-021-00941-8.

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Cohen-Adad, Julien1, Autor
Alonso-Ortiz, Eva1, Autor
Abramovic, Mihael1, Autor
Arneitz, Carina1, Autor
Atcheson, Nicole1, Autor
Barlow, Laura1, Autor
Barry, Robert L.1, Autor
Barth, Markus1, Autor
Battiston, Marco1, Autor
Büchel, Christian1, Autor
Budde, Matthew1, Autor
Callot, Virginie1, Autor
Combes, Anna J. E.1, Autor
De Leener, Benjamin1, Autor
Descoteaux, Maxime1, Autor
de Sousa, Paulo Loureiro1, Autor
Dostál, Marek1, Autor
Doyon, Julien1, Autor
Dvorak, Adam1, Autor
Eippert, Falk2, Autor           
Epperson, Karla R.1, AutorEpperson, Kevin S.1, AutorFreund, Patrick3, Autor           Finsterbusch, Jürgen1, AutorFoias, Alexandru1, AutorFratini, Michela1, AutorFukunaga, Issei1, AutorGandini Wheeler-Kingshott, Claudia A. M.1, AutorGermani, Giancarlo1, AutorGilbert, Guillaume1, AutorGiove, Federico1, AutorGros, Charley1, AutorGrussu, Francesco1, AutorHagiwara, Akifumi1, AutorHenry, Pierre-Gilles1, AutorHorák, Tomáš1, AutorHori, Masaaki1, AutorJoers, James1, AutorKamiya, Kouhei1, AutorKarbasforoushan, Haleh1, AutorKeřkovský, Miloš1, AutorKhatibi, Ali1, AutorKim, Joo-Won1, AutorKinany, Nawal1, AutorKitzler, Hagen H.1, AutorKolind, Shannon1, AutorKong, Yazhuo1, AutorKudlička, Petr1, AutorKuntke, Paul1, AutorKurniawan, Nyoman D.1, AutorKusmia, Slawomir1, AutorLabounek, René1, AutorLaganà, Maria Marcella1, AutorLaule, Cornelia1, AutorLaw, Christine S.1, AutorLenglet, Christophe1, AutorLeutritz, Tobias3, Autor           Liu, Yaou1, AutorLlufriu, Sara1, AutorMackey, Sean1, AutorMartinez-Heras, Eloy1, AutorMattera, Loan1, AutorNestrasil, Igor1, AutorO’Grady, Kristin P.1, AutorPapinutto, Nico1, AutorPapp, Daniel1, AutorPareto, Deborah1, AutorParrish, Todd B.1, AutorPichiecchio, Anna1, AutorPrados, Ferran1, AutorRovira, Àlex1, AutorRuitenberg, Marc J.1, AutorSamson, Rebecca S.1, AutorSavini, Giovanni1, AutorSeif, Maryam1, AutorSeifert, Alan C.1, AutorSmith, Alex K.1, AutorSmith, Seth A.1, AutorSmith, Zachary A.1, AutorSolana, Elisabeth1, AutorSuzuki, Y.1, AutorTackley, George1, AutorTinnermann, Alexandra1, AutorValošek, Jan1, AutorVan De Ville, Dimitri1, AutorYiannakas, Marios C.1, AutorWeber II, Kenneth A.1, AutorWeiskopf, Nikolaus3, Autor           Wise, Richard G.1, AutorWyss, Patrik O.1, AutorXu, Junqian1, Autor mehr..
Affiliations:
1External Organizations, ou_persistent22              
2Max Planck Research Group Pain Perception, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2497695              
3Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              

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Schlagwörter: Databases; Imaging techniques; Spinal cord diseases
 Zusammenfassung: In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

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Sprache(n): eng - English
 Datum: 2020-12-092021-03-262021-08-16
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1038/s41597-021-00941-8
PMID: 34400655
 Art des Abschluß: -

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Titel: Scientific Data
  Kurztitel : Sci. Data
Genre der Quelle: Zeitschrift
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Affiliations:
Ort, Verlag, Ausgabe: London, United Kingdom : Nature Publishing Group
Seiten: - Band / Heft: 8 Artikelnummer: 219 Start- / Endseite: - Identifikator: ISSN: 2052-4463
CoNE: https://pure.mpg.de/cone/journals/resource/2052-4463