Self‐Navigated, Retrospective, Data‐Consistent Motion Correction for MPnRAGE
Year: 2025
Type: article
Abstract: ABSTRACT Purpose To extend and automate a data‐consistent, self‐navigated motion‐correction method for 3D radial T1‐weighted imaging. Methods This method incorporated rigid‐body motion effects into the forward model, solving for parameters that maximize consistency with the data. The method was tested on five datasets with a range of motion types and severities. A separate collection of datasets was used to study the effect that the method has on the test‐retest reliability of cortical thickness estimates. Results Image quality was improved across a wide range of distinct motion types, including some cases that would have been unusable if left uncorrected. The error‐based weighting scheme and the increased timing resolution afforded by the proposed method were especially useful in cases of extreme and rapid motions. Moreover, the method improved test‐retest reliability of cortical thickness measures in pediatric subjects, decreasing the average coefficient of variation from in uncorrected images (with freesurfer failing on one subject) down to for images corrected at timing resolution and when corrected at faster temporal rates. Conclusion This method was found to be effective when used on T1‐weighted radial data, both qualitatively and quantitatively. The fine‐scale timing resolution and error‐based weighting afforded by this technique will likely provide only a small benefit, unless one is investigating motion‐prone populations or is searching for a very small effect size.
Source: Magnetic Resonance in Medicine
DOI: 10.1002/mrm.70126
Institution: University of Wisconsin–Madison
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,680
Funders: National Institutes of Health, National Institute on Aging, National Institute of Mental Health, National Institute on Deafness and Other Communication Disorders, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Office of Research Infrastructure Programs, National Institutes of Health
OpenAlex ID: W4415099917