Rootlets-based registration to the PAM50 spinal cord template
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View abstract on PubMed
Summary
This summary is machine-generated.A new spinal cord imaging method using nerve rootlets improves anatomical alignment for functional MRI (fMRI) group analyses. This rootlet-based registration enhances accuracy and reproducibility, leading to more reliable neuroimaging results.
Area Of Science
- Neuroimaging
- Spinal Cord Anatomy
- Medical Image Analysis
Background
- Spinal cord functional MRI (fMRI) requires precise anatomical localization for group analyses.
- Traditional methods using intervertebral discs for registration suffer from anatomical variability.
- Improved alignment is crucial for reliable voxel-wise group analyses in spinal cord studies.
Purpose Of The Study
- To develop and validate a novel registration method for spinal cord fMRI using dorsal cervical rootlets.
- To enhance alignment accuracy and reproducibility across individuals and varying neck positions.
- To compare the performance of rootlet-based registration against traditional disc-based methods in group-level fMRI analyses.
Main Methods
- Developed a non-linear registration method aligning segmented dorsal cervical rootlets with the PAM50 spinal cord template.
- Validated the method on large multi-subject, multi-site datasets (n=267) and datasets with varied neck positions (n=10).
- Compared group-level activation maps from task-based fMRI (n=23) using rootlet-based versus disc-based registration.
Main Results
- Rootlet-based registration demonstrated superior alignment compared to disc-based methods in 226 individuals for general analysis and 176 for morphological analysis.
- Rootlet positions showed greater stability across different neck positions.
- Task-based fMRI analysis revealed increased Z scores and significantly larger activation cluster sizes (3292 to 7978 voxels) with rootlet-based registration.
Conclusions
- Rootlet-based registration significantly improves inter- and intra-subject anatomical alignment in spinal cord imaging.
- This method enhances spatial normalization for group-level fMRI analyses, increasing precision and reliability.
- The findings support the potential of rootlet-based registration for advancing spinal cord neuroimaging.
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