Diffusion Tensor Magnetic Resonance Imaging and Fiber Tracking in Spinal Cord Lesions: Current and Future Indications

Ducreux, D.; Fillard, Pierre; Facon, D.; Ozanne, Augustin; Lepeintre, J.-F.; Renoux, J.; Tadié, M; Lasjaunias, P.

doi:10.1016/j.nic.2006.11.005

Cited by 83 publications

(38 citation statements)

References 20 publications

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“…Tractography has been used primarily to assess the relationships of fiber tracts to intracranial lesions with only limited applications in spinal cord pathology. [17][18][19][20] In terms of axonal health, DTI is also used to measure fractional anisotropy (FA), a numerical value between 0 (isotropic) and 1 (anisotropic), which describes the relative directionality of the molecular motion of water. DTI detects SCI, as quantified by FA, by capitalizing on the disruption of the normally linear arrangement of white matter fiber tracts within the spinal cord.…”

Section: Introductionmentioning

confidence: 99%

Diffusion Tensor Imaging as a Predictor of Locomotor Function after Experimental Spinal Cord Injury and Recovery

Kelley

Harel

Kim

et al. 2014

Journal of Neurotrauma

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Traumatic spinal cord injury (SCI) causes long-term disability with limited functional recovery linked to the extent of axonal connectivity. Quantitative diffusion tensor imaging (DTI) of axonal integrity has been suggested as a potential biomarker for prognostic and therapeutic evaluation after trauma, but its correlation with functional outcomes has not been clearly defined. To examine this application, female Sprague-Dawley rats underwent midthoracic laminectomy followed by traumatic spinal cord contusion of differing severities or laminectomy without contusion. Locomotor scores and hindlimb kinematic data were collected for 4 weeks post-injury. Ex vivo DTI was then performed to assess axonal integrity using tractography and fractional anisotropy (FA), a numerical measure of relative white matter integrity, at the injury epicenter and at specific intervals rostral and caudal to the injury site. Immunohistochemistry for tissue sparing was also performed. Statistical correlation between imaging data and functional performance was assessed as the primary outcome. All injured animals showed some recovery of locomotor function, while hindlimb kinematics revealed graded deficits consistent with injury severity. Standard T2 magnetic resonance sequences illustrated conventional spinal cord morphology adjacent to contusions while corresponding FA maps indicated graded white matter pathology within these adjacent regions. Positive correlations between locomotor (Basso, Beattie, and Bresnahan score and gait kinematics) and imaging (FA values) parameters were also observed within these adjacent regions, most strongly within caudal segments beyond the lesion. Evaluation of axonal injury by DTI provides a mechanism for functional recovery assessment in a rodent SCI model. These findings suggest that focused DTI analysis of caudal spinal cord should be studied in human cases in relationship to motor outcome to augment outcome biomarkers for clinical cases.

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Section: Introductionmentioning

confidence: 99%

Diffusion Tensor Imaging as a Predictor of Locomotor Function after Experimental Spinal Cord Injury and Recovery

Kelley

Harel

Kim

et al. 2014

Journal of Neurotrauma

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“…Previous studies reported the success of DTI in characterizing different tissues of the spinal cord and demonstrated changes in diffusion characteristics along injured spinal cords. [7][8][9] DTI of the spinal cord is technically limited by various factors. The small cord volume (approximately 1 cm in diameter) leads to a low SNR.…”

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confidence: 99%

Diffusion Tensor Imaging of the Normal Pediatric Spinal Cord Using an Inner Field of View Echo-Planar Imaging Sequence

Barakat¹,

Mohamed²,

Hunter³

et al. 2012

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE: DTI in the brain has been well established, but its application in the spinal cord, especially in pediatrics, poses several challenges. The small cord size has inherent low SNR of the diffusion signal intensity, respiratory and cardiac movements induce artifacts, and EPI sequences used for obtaining diffusion indices cause eddy-current distortions. The purpose of this study was to 1) evaluate the accuracy of cervical spinal cord DTI in children using a newly developed iFOV sequence with spatially selective 2D-RF excitations, and 2) examine reproducibility of the DTI measures.

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“…Important application example of this tensor computing framework were provided in [27,28] with a statistically grounded estimation and regularization of DTI images. The white matter tractography that was allowed by these methods in clinical DTI images with very poor signal to noise ratios could lead to new clinical indications of DTI, for instance in the spinal chord [23].…”

Section: Example Of Metrics On Covariance Matricesmentioning

confidence: 99%

Statistical Computing on Non-Linear Spaces for Computational Anatomy

Pennec

Fillard

2015

Handbook of Biomedical Imaging

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Computational anatomy is an emerging discipline that aims at analyzing and modeling the individual anatomy of organs and their biological variability across a population. However, understanding and modeling the shape of organs is made difficult by the absence of physical models for comparing different subjects, the complexity of shapes, and the high number of degrees of freedom implied. Moreover, the geometric nature of the anatomical features usually extracted raises the need for statistics on objects like curves, surfaces and deformations that do not belong to standard Euclidean spaces. We explain in this chapter how the Riemannian structure can provide a powerful framework to build generic statistical computing tools. We show that few computational tools derive for each Riemannian metric can be used in practice as the basic atoms to build more complex generic algorithms such as interpolation, filtering and anisotropic diffusion on fields of geometric features. This computational framework is illustrated with the analysis of the shape of the scoliotic spine and the modeling of the brain variability from sulcal lines where the results suggest new anatomical findings.

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Diffusion Tensor Magnetic Resonance Imaging and Fiber Tracking in Spinal Cord Lesions: Current and Future Indications

Cited by 83 publications

References 20 publications

Diffusion Tensor Imaging as a Predictor of Locomotor Function after Experimental Spinal Cord Injury and Recovery

Diffusion Tensor Imaging as a Predictor of Locomotor Function after Experimental Spinal Cord Injury and Recovery

Diffusion Tensor Imaging of the Normal Pediatric Spinal Cord Using an Inner Field of View Echo-Planar Imaging Sequence

Statistical Computing on Non-Linear Spaces for Computational Anatomy

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