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.

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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

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article

Rootlets-based registration to the PAM50 spinal cord template

Julien Cohen‐Adad, Jan Valošek, Valeria Oliva, Kenneth A. Weber et al.
3 citations
Imaging Neuroscience
Cervical and Thoracic Myelopathy
6.02
article

Rootlets-based registration to the PAM50 spinal cord template

Julien Cohen‐Adad, Jan Valošek, Valeria Oliva, Kenneth A. Weber, Sandrine Bédard
article en
3 citations

Abstract

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.

Imaging NeuroscienceVol. 3
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)
Craig H. Neilsen Foundation, European Commission, Canada First Research Excellence Fund, Institut de Valorisation des Données, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 4%
Cervical and Thoracic Myelopathy
6.02
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