Restoring statistical validity in group analyses of motion-corrupted MRI data.
heteroscedasticity
motion artefact
quality control
quantitative MRI
statistical image analysis
Journal
Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065
Informations de publication
Date de publication:
15 04 2022
15 04 2022
Historique:
revised:
09
12
2021
received:
06
08
2021
accepted:
14
12
2021
pubmed:
4
2
2022
medline:
28
4
2022
entrez:
3
2
2022
Statut:
ppublish
Résumé
Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise 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 quantitative 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.
Identifiants
pubmed: 35112434
doi: 10.1002/hbm.25767
pmc: PMC8933245
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1973-1983Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203147/Z/16/Z
Pays : United Kingdom
Informations de copyright
© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
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