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Restoring statistical validity in group analyses of motion-corrupted MRI data

View ORCID ProfileAntoine Lutti, View ORCID ProfileNadège Corbin, View ORCID ProfileJohn Ashburner, View ORCID ProfileGabriel Ziegler, View ORCID ProfileBogdan Draganski, View ORCID ProfileChristophe Phillips, View ORCID ProfileFerath Kherif, View ORCID ProfileMartina F. Callaghan, View ORCID ProfileGiulia Di Domenicantonio
doi: https://doi.org/10.1101/2021.06.15.448467
Antoine Lutti
1Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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  • For correspondence: antoine.lutti@chuv.ch
Nadège Corbin
2Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/University Bordeaux, Bordeaux, France
3Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
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John Ashburner
3Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
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Gabriel Ziegler
4Institute for Cognitive Neurology and Dementia Research, University of Magdeburg, Germany
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Bogdan Draganski
1Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
5Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Christophe Phillips
6GIGA Cyclotron Research Centre – in vivo imaging, GIGA Institute, University of Liège, Liège, Belgium
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Ferath Kherif
1Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Martina F. Callaghan
3Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
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Giulia Di Domenicantonio
1Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Abstract

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterize disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data-driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of brain MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 16, 2021.
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Restoring statistical validity in group analyses of motion-corrupted MRI data
Antoine Lutti, Nadège Corbin, John Ashburner, Gabriel Ziegler, Bogdan Draganski, Christophe Phillips, Ferath Kherif, Martina F. Callaghan, Giulia Di Domenicantonio
bioRxiv 2021.06.15.448467; doi: https://doi.org/10.1101/2021.06.15.448467
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Restoring statistical validity in group analyses of motion-corrupted MRI data
Antoine Lutti, Nadège Corbin, John Ashburner, Gabriel Ziegler, Bogdan Draganski, Christophe Phillips, Ferath Kherif, Martina F. Callaghan, Giulia Di Domenicantonio
bioRxiv 2021.06.15.448467; doi: https://doi.org/10.1101/2021.06.15.448467

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