Rootlets-based registration to the PAM50 spinal cord template
Spinal cord functional MRI studies require precise localization of spinal levels for reliable voxel-wise group analyses. Traditional template-based registration of the spinal cord uses intervertebral discs for alignment. However, substantial anatomical variability across individuals exists between vertebral and spinal levels. This study proposes a novel registration approach that leverages spinal nerve rootlets to improve alignment accuracy and reproducibility across individuals. We developed a registration method leveraging dorsal cervical rootlets segmentation and aligning them non-linearly with the PAM50 spinal cord template. Validation was performed on a multi-subject, multi-site dataset (n = 267, 44 sites) and a multi-subject dataset with various neck positions (n = 10, 3 sessions). We further validated the method on task-based functional MRI (n = 23) to compare group-level activation maps using rootlet-based registration to traditional disc-based methods. Rootlet-based registration showed superior alignment across individuals compared with the traditional disc-based method on n = 226 individuals, and on n = 176 individuals for morphological analyses. Notably, rootlet positions were more stable across neck positions. Group-level analysis of task-based functional MRI using rootlet-based registration increased Z scores and activation cluster size compared with disc-based registration (number of active voxels from 3292 to 7978). Rootlet-based registration enhances both inter- and intra-subject anatomical alignment and yields better spatial normalization for group-level fMRI analyses. Our findings highlight the potential of rootlet-based registration to improve the precision and reliability of spinal cord neuroimaging group analysis.
Authors
- Julien Cohen‐Adad (ORCID: https://orcid.org/0000-0003-3662-9532)
- Jan Valošek (ORCID: https://orcid.org/0000-0002-7398-4990)
- Valeria Oliva (ORCID: https://orcid.org/0000-0001-7849-191X)
- Kenneth A. Weber (ORCID: https://orcid.org/0000-0002-0916-9174)
- Sandrine Bédard (ORCID: https://orcid.org/0000-0001-9859-1133)
Institutions
- Centre Hospitalier Universitaire Sainte-Justine (CA)
- Stanford Medicine (US)
- Mila - Quebec Artificial Intelligence Institute (CA)
- Polytechnique Montréal (CA)
- Palacký University Olomouc (CZ)
- Université de Montréal (CA)
Publication Details
- Journal
- Imaging Neuroscience
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1162/imag.a.123
- Citations
- 3
- Primary Topic
- Cervical and Thoracic Myelopathy
- Type
- article
- Field-Weighted Citation Impact
- 6.02
Funders
- Craig H. Neilsen Foundation
- European Commission
- Canada First Research Excellence Fund
- Institut de Valorisation des Données
- Natural Sciences and Engineering Research Council of Canada