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Table of Contents    
Year : 2017  |  Volume : 65  |  Issue : 5  |  Page : 966-967

Spinal cord diffusion tensor imaging: Developing a research tool for clinical use

Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA

Date of Web Publication6-Sep-2017

Correspondence Address:
Aditya Vedantam
Department of Neurosurgery, Baylor College of Medicine, 7200 Cambridge, Suite 9A, MS: BCM650, Houston, TX 77030
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/neuroindia.NI_740_17

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How to cite this article:
Vedantam A. Spinal cord diffusion tensor imaging: Developing a research tool for clinical use. Neurol India 2017;65:966-7

How to cite this URL:
Vedantam A. Spinal cord diffusion tensor imaging: Developing a research tool for clinical use. Neurol India [serial online] 2017 [cited 2020 Feb 24];65:966-7. Available from:

Advances in neuroimaging have dramatically impacted the practice of neurology and neurosurgery. The advent of magnetic resonance imaging (MRI) has greatly improved the visualization of cranial and spinal pathology. Advanced neuroimaging such as diffusion tensor imaging (DTI) is now commonly used in the evaluation of patients with intracranial pathology. For example, DTI is useful in the surgical planning for patients with brain tumors near eloquent regions of the brain.[1] However, the routine clinical use of advanced neuroimaging for spinal pathology is less prevalent, and there is a need to further investigate these techniques for patients with spinal disorders.

Some challenges in the advanced MR imaging of the spine are highlighted below. In comparison to the brain, the small dimensions of the spinal cord and inhomogeneous magnetic field due to bone, soft tissue and muscles around the spinal cord can reduce the signal-to-noise ratios. In addition, image quality can suffer due to swallowing, respiratory and cardiac motion.[2] In spite of these challenges, a growing group of researchers have refined imaging sequences, and are attempting to improve utilization of advanced spine imaging for various neurological and neurosurgical pathologies.

Li et al.,[3] present a review on the use of DTI for the evaluation and prognostication of spinal pathology. The authors present a well-researched manuscript describing the current status of DTI for spinal cord injury, spinal cord tumors, cervical spondylotic myelopathy, amyotrophic lateral sclerosis and multiple sclerosis. The article highlights the utility of DTI indices in assessing microstructural changes within the spinal cord, and in using these indices to quantify the severity of disease and prognosticate patients. One of the proposed advantages of DTI is that changes in DTI metrics are detected in regions of the spinal cord that appear normal on conventional T2-weighted imaging. These findings suggest that DTI is more sensitive than the conventional imaging and may be able to identify early spinal cord damage, possibly even before the onset of symptoms.

The use of DTI in the evaluation and prognostication of patients appears to be most promising for patients with cervical spondylotic myelopathy. As described by Li et al.,[3] a number of prospective studies have shown significant changes in fractional anisotropy and mean diffusivity at the level of maximal compression, as well as correlation of these metrics with postoperative outcomes. Patients with degenerative cervical spine disease can sometimes demonstrate a dissociation between radiological features and clinical findings. Some patients demonstrate spinal cord compression on the conventional MRI but have few clinical symptoms or signs, while others show an overt myelopathy with limited cord compression and no cord signal change on T2-weighted MRI. The surgical decision making for presymptomatic or minimally symptomatic patients is challenging. The follow-up conventional MR imaging may not show significant changes in the degree of cord compression; yet, it is unknown if neural damage within the spinal cord is worsening. Perhaps, DTI could detect progressive spinal cord damage, and deciding on an earlier surgical intervention in these patients may prevent further neurological deficits. Additionally, prognostication of patients with cervical spondylotic myelopathy is challenging and DTI may be better than the conventional imaging in predicting outcome after surgery. The predictive value of DTI for outcomes in cervical spondylotic myelopathy, however, are not excellent and it is possible that a combination of clinical findings and radiological features may be needed for an accurate prognostication.

DTI has an immense potential in improving the evaluation and treatment of patients with spinal cord injury. From numerous pre-clinical studies, we know that DTI metrics change in a predictable manner in the acute and chronic phase after the injury. In humans, DTI metrics within the injured cord have been shown to correlate with neurological deficits, as well as with DTI metrics of white matter tracts in the brain.[4] DTI could be an important non-invasive biomarker of neural injury. DTI, therefore, provides valuable insights into neural plasticity, and may be used as a biomarker after therapeutic interventions for spinal cord injury.

There are many challenges to adopting DTI as a routine clinical tool. The majority of the prior studies have shown statistically significant group statistics between patients and controls. At present, for instance, we do not know if a fractional anisotropy of 0.5 at the level of maximum cord compression represents clinically significant neural injury for the individual patient. We are yet to establish DTI thresholds for defining spinal cord damage. We do know that fractional anisotropy within the spinal cord changes with age,[5] so these thresholds would likely be different for a 30-year old versus an 80-year old patient. There is variability in the scanning parameters as well as MR machines used amongst different studies. Importantly, post-processing of DTI scans is not uniform and a number of different software packages are used. These factors do affect the uniformity and reliability of spinal cord DTI. Automated, standardized image processing is necessary to encourage the routine clinical use of DTI. Investigators acknowledge these challenges, and steps are being taken to standardize imaging techniques as well as processing algorithms.

The authors of this review need to be commended for presenting the current status of spinal cord DTI in a succinct and clear form. One way to increase the adoption and utility of spinal cord DTI is to bridge the knowledge gap for surgeons and physicians taking care of patients with spinal cord pathology. Increased awareness of the utility of DTI may encourage clinicians to use the technique for challenging cases. For now, DTI of the spinal cord is a powerful research tool, and articles such as the one by Li et al.,[3] serve to highlight the potential clinical use of DTI for patients with spinal cord pathology.

  References Top

Cao Z, Lv J, Wei X, Quan W. Appliance of preoperative diffusion tensor imaging and fiber tractography in patients with brainstem lesions. Neurol India 2010;58:886-890.  Back to cited text no. 1
[PUBMED]  [Full text]  
Stroman PW, Wheeler-Kingshott C, Bacon M, Schwab JM, Bosma R, Brooks J, et al. The current state-of-the-art of spinal cord imaging: Methods. Neuroimage 2014;84:1070-81.  Back to cited text no. 2
Li DC, Malcolm JG, Rindler RS, Baum GR, Rao A, Kurpad SN, et al. The role of diffusion tensor imaging in spinal pathoogy. Neurol India 2017;65:982-92.  Back to cited text no. 3
  [Full text]  
Vedantam A, Jirjis MB, Schmit BD, Wang MC, Ulmer JL, Kurpad SN. Diffusion tensor imaging of the spinal cord: Insights from animal and human studies. Neurosurgery 2014;74:1-8.  Back to cited text no. 4
Vedantam A, Jirjis MB, Schmit BD, Wang MC, Ulmer JL, Kurpad SN. Characterization and limitations of diffusion tensor imaging metrics in the cervical spinal cord in neurologically intact subjects. J Magn Reson Imaging 2013;38:861-7.  Back to cited text no. 5


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