ArticleNeuroImage2019
Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis.
Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Spinal cord imaging in multiple sclerosis: from diagnosis to disease progression.Journal of neurology · 2026Review
- Standard Model Imaging in the Brain and Spinal Cord of MS Patients: Initial Assessment and Comparison to Diffusion Tensor Imaging.NMR in biomedicine · 2026Article
- An MRI-based radiomics model for precision subtyping of hereditary spastic paraplegia: discriminating SPG4 from SPG5.Neuroradiology · 2026Article
- Pulvinar responsive neurostimulation for posterior quadrant epilepsy: an illustrative case with connectome projection.Neurosurgical review · 2025Article
- Characterization of neurite and soma organization in the brain and spinal cord with diffusion MRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord.Magnetic resonance imaging · 2024Article
- Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study.Frontiers in neuroimaging · 2024Article
- Spinal cord evaluation in multiple sclerosis: clinical and radiological associations, present and future.Brain communications · 2024Review
- Correlations of diffusion tensor imaging and clinical measures with spinal cord cross-sectional area measurements in pediatric spinal cord injury patients.The journal of spinal cord medicine · 2023Article
- Individualized targeting is warranted in subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression: A tractography analysis.Human brain mapping · 2023Article
- Article
- Application of Neurite Orientation Dispersion and Density Imaging to Evaluate and Predict the Surgical Outcome for Degenerative Cervical Myelopathy.Orthopaedic surgery · 2022Article
- Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions.NeuroImage. Clinical · 2022Review
- Use of computational fluid dynamics for 3D fiber tract visualization on human high-thickness histological slices: histological mesh tractography.Brain structure & function · 2021Article
- Imaging of the Spinal Cord in Multiple Sclerosis: Past, Present, Future.Brain sciences · 2020Review
- HARDI-ZOOMit protocol improves specificity to microstructural changes in presymptomatic myelopathy.Scientific reports · 2020Article
- Challenges for biophysical modeling of microstructure.Journal of neuroscience methods · 2020Review
- Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising.NeuroImage · 2020Article
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Authors and funding
8 authors.
Funding
Abstract
Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven valuable in the brain, offering novel indices sensitive to the tissue microstructural environment in vivo on clinical MRI scanners. However, application, characterization, and validation of these models in the spinal cord remain relatively under-studied. In this study, we apply a diffusion "signal" model (diffusion tensor imaging, DTI) and two commonly implemented "microstructural" models (neurite orientation dispersion and density imaging, NODDI; spherical mean technique, SMT) in the human cervical spinal cord of twenty-one healthy controls. We first provide normative values of DTI, SMT, and NODDI indices in a number of white matter ascending and descending pathways, as well as various gray matter regions. We then aim to validate the sensitivity and specificity of these diffusion-derived contrasts by relating these measures to indices of the tissue microenvironment provided by a histological template. We find that DTI indices are sensitive to a number of microstructural features, but lack specificity. The microstructural models also show sensitivity to a number of microstructure features; however, they do not capture the specific microstructural features explicitly modelled. Although often regarded as a simple extension of the brain in the central nervous system, it may be necessary to re-envision, or specifically adapt, diffusion microstructural models for application to the human spinal cord with clinically feasible acquisitions - specifically, adjusting, adapting, and re-validating the modeling as it relates to both theory (i.e. relevant biology, assumptions, and signal regimes) and parameter estimation (for example challenges of acquisition, artifacts, and processing).
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