Filter‐probe diffusion imaging improves spinal cord injury outcome prediction

Skinner, Nathan P.; Lee, Seung-Yi; Kurpad, Shekar N.; Schmit, Brian D.; Muftuler, L. Tugan; Budde, Matthew D.

doi:10.1002/ana.25260

Cited by 21 publications

(16 citation statements)

References 57 publications

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“…Despite the significant improvement, DCI still requires considerably more data than DTI, which may be a reasonable penalty in return for the demonstrated high tissue components specificity. A more practical in vivo DDE approach in the injured spinal cord that uses the first diffusion block with a constant, relatively high, b-value (effectively as filter) perpendicular to the tissue, while stepping the second orthogonal block, was recently suggested ( Skinner et al, 2017 ; 2018 ). While full 2D diffusion spectra map the entire diffusivities ranges in both axial and radial directions, this practical approach would ideally only capture water populations with slow radial diffusivity, and describe their mobility along the axial axis.…”

Section: Discussionmentioning

confidence: 99%

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

et al. 2020

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Section: Discussionmentioning

confidence: 99%

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

et al. 2020

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“…Despite the significant improvement, DCI still requires considerably more data than DTI, which may be a reasonable penalty in return for the demonstrated high tissue components specificity. A more practical in vivo DDE approach in the injured spinal cord that uses the first diffusion block with a constant, relatively high, b-value (effectively as filter) perpendicular to the tissue, while stepping the second orthogonal block, was recently suggested (Skinner et al, 2017(Skinner et al, , 2018. While full 2D diffusion spectra map the entire diffusivities ranges in both axial and radial directions, this practical approach would ideally only capture water populations with slow radial diffusivity, and describe their mobility along the axial axis.…”

Section: Discussionmentioning

confidence: 99%

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

Benjamini

Hutchinson

Komlosh

et al. 2020

Preprint

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We describe a practical two-dimensional (2D) diffusion MRI framework to deliver specificity and improve sensitivity to axonal injury in the spinal cord. This approach provides intravoxel distributions of correlations of water mobilities in orthogonal directions, revealing sub-voxel diffusion components. Here we use it to investigate water diffusivities along axial and radial orientations within spinal cord specimens with confirmed, tract-specific axonal injury. First, we show using transmission electron microscopy and immunohistochemistry that tract-specific axonal beading occurs following Wallerian degeneration in the cortico-spinal tract as direct sequelae to closed head injury. We demonstrate that although some voxel-averaged diffusion tensor imaging (DTI) metrics are sensitive to this axonal injury, they are non-specific, i.e., they do not reveal an underlying biophysical mechanism of injury. Then we employ 2D diffusion correlation imaging (DCI) to improve discrimination of different water microenvironments by measuring and mapping the joint water mobility distributions perpendicular and parallel to the spinal cord axis. We determine six distinct diffusion spectral components that differ according to their microscopic anisotropy and mobility. We show that at the injury site a highly anisotropic diffusion component completely disappears and instead becomes more isotropic. Based on these findings, an injury-specific MR image of the spinal cord was generated, and a radiological-pathological correlation with histological silver staining % area was performed. The resulting strong and significant correlation (r = 0.70, p < 0.0001) indicates the high specificity with which DCI detects injury-induced tissue alterations. We predict that the ability to selectively image microstructural changes following axonal injury in the spinal cord can be useful in clinical and research applications by enabling specific detection and increased sensitivity to injury-induced microstructural alterations. These results also encourage us to translate DCI to higher spatial dimensions to enable assessment of traumatic axonal injury, and possibly other diseases and disorders in the brain.

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“…Автори стверджують, що модель з високим ступенем імовірності дає змогу оцінити можливості досягнення потерпілим функціональної незалежності (Формула 2). Незважаючи на невелику кількість предикторов і слабку їх деталізацію, схему використовують у більшості клінічних досліджень [34][35][36].…”

Section: результатиunclassified

The usage of tractography of the spinal cord as a predictor of neurological disorders regression in patients with severe cervical spine and spinal cord injury

Слынько¹,

Nekhlopochyn²,

K³

2019

Ukr Neurosurg J

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the primary assessment of the prognostic features of tractography in patients with severe subaxial cervical spine and spinal cord injury. Materials and methods. The clinical group consisted of 5 patients admitted to the Department of Spine Surgery of Romodanov Neurosurgery Institute during the period from April to July 2019 with severe traumatic injury of the cervical spine and spinal cord. MRI was performed in the following modes: T1W, T2W, FLAIR, STIR, T2W FFE, CSF flow and DTI in 5-7 days after surgery. The dynamics of neurological disorders regression were evaluated according to the International Standards for Neurological Classification of Spinal Cord Injury. The level of spinal canal traumatic stenosis was determined by SCT both before and after surgical correction. Due to the small clinical group, statistical processing of the obtained digital indicators was not performed. The main task was to identify general patterns in order to determine the direction of further detailed studies.

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Filter‐probe diffusion imaging improves spinal cord injury outcome prediction

Cited by 21 publications

References 57 publications

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

The usage of tractography of the spinal cord as a predictor of neurological disorders regression in patients with severe cervical spine and spinal cord injury

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