English

Rootlets-based registration to the spinal cord PAM50 template

Image and Video Processing 2025-05-02 v1 Computer Vision and Pattern Recognition

Abstract

Spinal cord functional MRI studies require precise localization of spinal levels for reliable voxelwise 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 to the traditional disc-based method. Notably, rootlet positions were more stable across neck positions. Group-level analysis of task-based functional MRI using rootlet-based increased Z scores and activation cluster size compared to 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.

Keywords

Cite

@article{arxiv.2505.00115,
  title  = {Rootlets-based registration to the spinal cord PAM50 template},
  author = {Sandrine Bédard and Jan Valošek and Valeria Oliva and Kenneth A. Weber and Julien Cohen-Adad},
  journal= {arXiv preprint arXiv:2505.00115},
  year   = {2025}
}
R2 v1 2026-06-28T23:17:20.947Z