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Spatial correspondence of spinal cord white matter tracts using diffusion tensor imaging, fibre tractography, and atlas-based segmentation



Neuroimaging provides great utility in complex spinal surgeries, particularly when anatomical geometry is distorted by pathology (tumour, degeneration, etc.). Spinal cord MRI diffusion tractography can be used to generate streamlines; however, it is unclear how well they correspond with white matter tract locations along the cord microstructure. The goal of this work was to evaluate the spatial correspondence of DTI tractography with anatomical MRI in healthy anatomy (where anatomical locations can be well defined in T1-weighted images).


Ten healthy volunteers were scanned on a 3T system. T1-weighted (1 × 1 × 1 mm) and diffusion-weighted images (EPI readout, 2 × 2 × 2 mm, 30 gradient directions) were acquired and subsequently registered (Spinal Cord Toolbox (SCT)). Atlas-based (SCT) anatomic label maps of the left and right lateral corticospinal tracts were identified for each vertebral region (C2–C6) from T1 images. Tractography streamlines were generated with a customized approach, enabling seeding of specific spinal tract regions corresponding to individual vertebral levels. Spatial correspondence of generated fibre streamlines with anatomic tract segmentations was compared in unseeded regions of interest (ROIs).


Spatial correspondence of the lateral corticospinal tract streamlines was good over a single vertebral ROI (Dice’s similarity coefficient (DSC) = 0.75 ± 0.08, Hausdorff distance = 1.08 ± 0.17 mm). Over larger ROI, fair agreement between tractography and anatomical labels was achieved (two levels: DSC = 0.67 ± 0.13, three levels: DSC = 0.52 ± 0.19).


DTI tractography produced good spatial correspondence with anatomic white matter tracts, superior to the agreement between multiple manual tract segmentations (DSC ~ 0.5). This supports further development of spinal cord tractography for computer-assisted neurosurgery.

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Data availability

Imaging data was collected without obtaining consent for public disclosure. Therefore, it will not be made public. Specific requests for the data will be considered provided that ethics approval can be obtained for the new purpose and that a suitable transfer agreement can be established.


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This work was supported by research funding provided by FedDev Ontario, Mitacs post-doctoral fellowship support, and the Feldberg Chair for Spinal Research. Image datasets, in kind resources, and technical support were provided by Synaptive Medical Inc.

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Correspondence to Michael Raymond Hardisty.

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Conflict of interest

Stewart McLachlin’s stipend during the research project was provided by a Mitacs fellowship with matching funds from Synaptive Medical. Jason Leung has no conflicts. Vignesh Sivan has no conflicts. Pierre-Olivier Quirion has no conflicts. Phoenix Wilkie has no conflicts. Julien Cohen-Adad has no conflicts. Cari Marisa Whyne received grant matching funds for the research reported in this article from Synaptive Medical. Michael Raymond Hardisty has no conflicts.

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McLachlin, S., Leung, J., Sivan, V. et al. Spatial correspondence of spinal cord white matter tracts using diffusion tensor imaging, fibre tractography, and atlas-based segmentation. Neuroradiology 63, 373–380 (2021).

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  • Spinal cord
  • Diffusion tensor imaging
  • Tractography
  • Segmentation
  • Deformable registration