Traumatic and nontraumatic spinal cord injury: pathological insights from neuroimaging

Abstract

Pathophysiological changes in the spinal cord white and grey matter resulting from injury can be observed with MRI techniques. These techniques provide sensitive markers of macrostructural and microstructural tissue integrity, which correlate with histological findings. Spinal cord MRI findings in traumatic spinal cord injury (tSCI) and nontraumatic spinal cord injury — the most common form of which is degenerative cervical myelopathy (DCM) — have provided important insights into the pathophysiological processes taking place not just at the focal injury site but also rostral and caudal to the spinal injury. Although tSCI and DCM have different aetiologies, they show similar degrees of spinal cord pathology remote from the injury site, suggesting the involvement of similar secondary degenerative mechanisms. Advanced quantitative MRI protocols that are sensitive to spinal cord pathology have the potential to improve diagnosis and, more importantly, predict outcomes in patients with tSCI or nontraumatic spinal cord injury. This Review describes the insights into tSCI and DCM that have been revealed by neuroimaging and outlines current activities and future directions for the field.

Key points

  • Traumatic spinal cord injury (tSCI) and (nontraumatic) degenerative cervical myelopathy (DCM) have different aetiologies but lead to similar secondary degenerative changes in the spinal cord.

  • Advanced MRI techniques have been used to improve the sensitivity and specificity with which spinal degenerative changes can be detected.

  • Diffusion tensor imaging (DTI) is an advanced MRI technique that characterizes tissue microstructure by measuring the water diffusion profile of the tissue.

  • In tSCI and DCM, DTI has been used to identify changes in microstructure above and below the lesion or stenosis that are not visible with conventional MRI.

  • Spinal cord DTI metrics correlate with neurological and electrophysiological outcomes after tSCI and DCM.

  • Further advances in data acquisition, processing and modelling are needed to improve the reliability and specificity of quantitative MRI metrics as predictors of patient outcome.

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Fig. 1: Primary and secondary injury mechanisms in DCM and tSCI.
Fig. 2: Radiological characteristics of DCM and tSCI.
Fig. 3: Main concepts of DTI.
Fig. 4: Voxel-wise analysis of DTI metrics in chronic tSCI.
Fig. 5: Voxel-wise analysis of DTI metrics in DCM.

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Acknowledgements

S.M. has received funding from the ERA-NET NEURON (hMRIofSCI) and the Bundesministerium für Bildung und Forschung (BMBF; 01EW1711A and B) and is supported by the Deutsche Forschungsgemeinschaft (grant MO 2397/4-1) and the Forschungszentrums Medizintechnik Hamburg (fmthh; grant 01fmthh2017). A.R.M. has received support from the Canadian Institutes of Health Research (CHIR; 359116). J.C.-A. holds funding from the Canada Research Chair in Quantitative Magnetic Resonance Imaging (950–230815), the CIHR (FDN-143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Québec – Santé (28826), the Natural Sciences and Engineering Research Council of Canada (435897-2013), the Canada First Research Excellence Fund (IVADO and TransMedTech) and the Quebec BioImaging Network (5886), Spinal Research and Wings for Life (INSPIRED project). N.W. reports grants from the European Research Council/ERC grant agreement no. 616905, grants from the BMBF (01EW1711A B) in the framework of ERA-NET NEURON, grants from the BRAINTRAIN European research network (Collaborative Project) supported by the European Commission (grant agreement no. 602186), grants from NISCI supported by the European Union’s Horizon 2020 research and innovation program under the grant agreement no. 681094, and supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 15.0137, and grants from UCL Impact Awards; The Wellcome Centre for Human Neuroimaging and Max Planck Institute for Human Cognitive and Brain Sciences have institutional research agreements with Siemens Healthcare. P.F. reports grants from ERA-NET NEURON (hMRIofSCI no. 32NE30_173678), grants from NISCI supported by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 681094, and supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 15.0137, grants from the Wings for life charity (no. WFL-CH-007/14) and grants from the International Foundation for Research (IRP-158). P.F. is funded by a SNF Eccellenza Professorial Fellowship grant (PCEFP3_181362/1). A.T. acknowledges support from the UCL/UCLH NIHR Biomedical Research Centre.

Review criteria

PubMed and MEDLINE were searched for articles published in English from 1 January 2010 to 31 March 2019. The search terms “traumatic spinal cord injury”, “cervical spondylotic myelopathy” and “degenerative spondylotic myelopathy” were used in combination with each of the terms “diffusion MRI”, “diffusion tensor imaging”, “DTI”, “conventional MRI”, and “atrophy”. The reference lists of the identified papers were also searched for further articles. The final reference list for inclusion in this Review was generated on the basis of originality and relevance to the topics covered.

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All authors provided substantial contributions to discussion of the content of the article, wrote the article and undertook the review and/or editing of the manuscript before submission. G.D and P.F also researched data for the article.

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Correspondence to Patrick Freund.

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Competing interests

A.T. reports personal fees paid to his institution from Eisai Ltd. and fees and support for travel from Hoffmann-La Roche outside the submitted work. A.T. is an Editorial Board member of The Lancet Neurology and receives a free subscription. A.T. is the Editor-in-Chief of the Multiple Sclerosis Journal and receives an honorarium from SAGE Publications. A.T. receives support for travel as Chair, Scientific Advisory Committee, International Progressive MS Alliance, and member, National MS Society (USA), Research Programs Advisory Committee. A.T. has received honoraria and support for travel for lecturing from Almirall and EXCEMED. N.W. is supported by Siemens Healthcare. The other authors declare no competing interests.

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Nature Reviews Neurology thanks L. Holly, S. Kurpad and P. Narayana for their contribution to the peer review of this work.

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Glossary

T1-weighted

T1-weighted MRI pulse sequences are optimized to create an image contrast that primarily depends on the T1 (longitudinal or spin-lattice) relaxation time of the tissue. In T1-weighted images, white matter appears bright and grey matter appears dark.

T2-weighted

T2-weighted MRI pulse sequences are optimized to create an image contrast that primarily depends on the T2 (transversal or spin-spin) relaxation time of the tissue. In T2-weighted images, areas of water accumulation (for example, oedema or lesions) appear bright in contrast with other tissue.

Anisotropic

A type of diffusion with direction dependency; that is, the diffusion is not the same in all spatial directions (for example, in white matter).

Tensor

Mathematical object used to describe diffusion in homogeneous anisotropic media, having the form of a 3 × 3 symmetrical matrix for 3D diffusion.

Scalar

A scalar is a quantity that is completely described by its magnitude.

Isotropic

A type of diffusion with no directional dependency; that is, the diffusion is the same in all spatial directions (for example, in a glass of water).

Wallerian degeneration

A degenerative process that involves the breakdown of the distal part of a severed axon.

Pulse sequences

In MRI, a pulse sequence refers to a particular setting of measurement parameters. Each pulse sequence results in a particular image appearance, with T1-weighted, T2-weighted, and diffusion-weighted pulse sequences resulting in T1, T2, and diffusion image contrasts, respectively.

Gradient echo-based T2*-weighted sequences

MRI pulse sequences that are optimized to create an image contrast that depends primarily on T2* (effective transversal) relaxation time. T2*-weighted images offer good distinction between grey and white matter in the spinal cord and form the basis of grey matter segmentation.

Partial volume effects

Artefacts that arise at tissue interfaces where multiple tissues are contained in a single voxel. These artefacts are more severe at lower resolution.

Susceptibility artefacts

Artefacts resulting from the different magnetic properties of tissues. They appear at and near tissue interfaces and lead to image distortions and signal dropouts.

Coil coverage

Part of the body that falls into the receptive field of the receiver coils.

Receive coil

Part of the MRI hardware that is responsible for receiving the signal and is crucial for acquiring images with high signal-to-noise ratios.

Shimming

A procedure that aims to make the magnetic field homogeneous within the imaging volume, which is crucial for good-quality, distortion-free images.

Field fluctuations

Variations in the magnetic field within the body caused by susceptibility artefacts and imperfect shimming.

Pulsed field gradient design

A pair of spatially varying magnetic fields (gradients) applied in succession to encode the water diffusion along a particular direction in diffusion-weighted MRI scans.

Double diffusion encoding

In contrast to the pulsed field gradient design, this technique encodes diffusion along two directions in the images.

Nonlinear diffusion encoding

A modification of the pulsed field gradient design, where the variation of the applied spatially varying magnetic field is not linear.

b-value

A scalar measure that describes the amount of diffusion weighting in the images; a higher b-value means more diffusion weighting but also less signal.

Restricted diffusion component

Usually refers to the intracellular space of white matter, which is assumed to show a restricted diffusion profile, meaning that the myelinated axons are impermeable to water molecules.

Multicontrast biophysical models

Models that incorporate information from multiple types of MRI acquisitions (contrasts) to estimate a meaningful tissue parameter such as axonal or myelin volume fraction.

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David, G., Mohammadi, S., Martin, A.R. et al. Traumatic and nontraumatic spinal cord injury: pathological insights from neuroimaging. Nat Rev Neurol 15, 718–731 (2019). https://doi.org/10.1038/s41582-019-0270-5

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