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Tensor-valued diffusion MRI of human acute stroke

Zhou, Mi ; Stobbe, Robert ; Szczepankiewicz, Filip LU orcid ; Budde, Matthew ; Buck, Brian ; Kate, Mahesh ; Lloret, Mar ; Fairall, Paige ; Butcher, Ken and Shuaib, Ashfaq , et al. (2024) In Magnetic Resonance in Medicine 91(5). p.2126-2141
Abstract

Purpose: Tensor-valued diffusion encoding can disentangle orientation dispersion and subvoxel anisotropy, potentially offering insight into microstructural changes after cerebral ischemia. The purpose was to evaluate tensor-valued diffusion MRI in human acute ischemic stroke, assess potential confounders from diffusion time dependencies, and compare to Monte Carlo diffusion simulations of axon beading. Methods: Linear (LTE) and spherical (STE) b-tensor encoding with inherently different effective diffusion times were acquired in 21 acute ischemic stroke patients between 3 and 57 h post-onset at 3 T in 2.5 min. In an additional 10 patients, STE with 2 LTE yielding different effective diffusion times were acquired for comparison.... (More)

Purpose: Tensor-valued diffusion encoding can disentangle orientation dispersion and subvoxel anisotropy, potentially offering insight into microstructural changes after cerebral ischemia. The purpose was to evaluate tensor-valued diffusion MRI in human acute ischemic stroke, assess potential confounders from diffusion time dependencies, and compare to Monte Carlo diffusion simulations of axon beading. Methods: Linear (LTE) and spherical (STE) b-tensor encoding with inherently different effective diffusion times were acquired in 21 acute ischemic stroke patients between 3 and 57 h post-onset at 3 T in 2.5 min. In an additional 10 patients, STE with 2 LTE yielding different effective diffusion times were acquired for comparison. Diffusional variance decomposition (DIVIDE) was used to estimate microscopic anisotropy (μFA), as well as anisotropic, isotropic, and total diffusional variance (MKA, MKI, MKT). DIVIDE parameters, and diffusion tensor imaging (DTI)-derived mean diffusivity and fractional anisotropy (FA) were compared in lesion versus contralateral white matter. Monte Carlo diffusion simulations of various cylindrical geometries for all b-tensor protocols were used to interpret parameter measurements. Results: MD was ˜40% lower in lesions for all LTE/STE protocols. The DIVIDE parameters varied with effective diffusion time: higher μFA and MKA in lesion versus contralateral white matter for STE with longer effective diffusion time LTE, whereas the shorter effective diffusion time LTE protocol yielded lower μFA and MKA in lesions. Both protocols, regardless of diffusion time, were consistent with simulations of greater beading amplitude and intracellular volume fraction. Conclusion: DIVIDE parameters depend on diffusion time in acute stroke but consistently indicate neurite beading and larger intracellular volume fraction.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
b-tensor, diffusion time, Monte Carlo diffusion simulation, neurite beading, stroke, tensor-valued diffusion encoding
in
Magnetic Resonance in Medicine
volume
91
issue
5
pages
16 pages
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:38156813
  • scopus:85181197209
ISSN
0740-3194
DOI
10.1002/mrm.29975
language
English
LU publication?
yes
id
c1b7bc8c-2623-4769-9e2f-6349ac848ebf
date added to LUP
2024-07-09 14:31:15
date last changed
2024-07-09 14:32:43
@article{c1b7bc8c-2623-4769-9e2f-6349ac848ebf,
  abstract     = {{<p>Purpose: Tensor-valued diffusion encoding can disentangle orientation dispersion and subvoxel anisotropy, potentially offering insight into microstructural changes after cerebral ischemia. The purpose was to evaluate tensor-valued diffusion MRI in human acute ischemic stroke, assess potential confounders from diffusion time dependencies, and compare to Monte Carlo diffusion simulations of axon beading. Methods: Linear (LTE) and spherical (STE) b-tensor encoding with inherently different effective diffusion times were acquired in 21 acute ischemic stroke patients between 3 and 57 h post-onset at 3 T in 2.5 min. In an additional 10 patients, STE with 2 LTE yielding different effective diffusion times were acquired for comparison. Diffusional variance decomposition (DIVIDE) was used to estimate microscopic anisotropy (μFA), as well as anisotropic, isotropic, and total diffusional variance (MK<sub>A</sub>, MK<sub>I</sub>, MK<sub>T</sub>). DIVIDE parameters, and diffusion tensor imaging (DTI)-derived mean diffusivity and fractional anisotropy (FA) were compared in lesion versus contralateral white matter. Monte Carlo diffusion simulations of various cylindrical geometries for all b-tensor protocols were used to interpret parameter measurements. Results: MD was ˜40% lower in lesions for all LTE/STE protocols. The DIVIDE parameters varied with effective diffusion time: higher μFA and MK<sub>A</sub> in lesion versus contralateral white matter for STE with longer effective diffusion time LTE, whereas the shorter effective diffusion time LTE protocol yielded lower μFA and MK<sub>A</sub> in lesions. Both protocols, regardless of diffusion time, were consistent with simulations of greater beading amplitude and intracellular volume fraction. Conclusion: DIVIDE parameters depend on diffusion time in acute stroke but consistently indicate neurite beading and larger intracellular volume fraction.</p>}},
  author       = {{Zhou, Mi and Stobbe, Robert and Szczepankiewicz, Filip and Budde, Matthew and Buck, Brian and Kate, Mahesh and Lloret, Mar and Fairall, Paige and Butcher, Ken and Shuaib, Ashfaq and Emery, Derek and Nilsson, Markus and Westin, Carl Fredrik and Beaulieu, Christian}},
  issn         = {{0740-3194}},
  keywords     = {{b-tensor; diffusion time; Monte Carlo diffusion simulation; neurite beading; stroke; tensor-valued diffusion encoding}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{2126--2141}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Magnetic Resonance in Medicine}},
  title        = {{Tensor-valued diffusion MRI of human acute stroke}},
  url          = {{http://dx.doi.org/10.1002/mrm.29975}},
  doi          = {{10.1002/mrm.29975}},
  volume       = {{91}},
  year         = {{2024}},
}