Comparison of multi-tensor diffusion models' performance for white matter integrity estimation in chronic stroke

on behalf of the 4D EEG Consortium

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Better insight into white matter (WM) alterations after stroke onset could help to understand the underlying recovery mechanisms and improve future interventions. MR diffusion imaging enables to assess such changes. Our goal was to investigate the relation of WM diffusion characteristics derived from diffusion models of increasing complexity with the motor function of the upper limb. Moreover, we aimed to evaluate the variation of such characteristics across different WM structures of chronic stroke patients in comparison to healthy subjects. Subjects were scanned with a two b-value diffusion-weighted MRI protocol to exploit multiple diffusion models: single tensor, single tensor with isotropic compartment, bi-tensor model, bi-tensor with isotropic compartment. From each model we derived the mean tract fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivities outside the lesion site based on a WM tracts atlas. Asymmetry of these measures was correlated with the Fugl-Meyer upper extremity assessment (FMA) score and compared between patient and control groups. Eighteen chronic stroke patients and eight age-matched healthy individuals participated in the study. Significant correlation of the outcome measures with the clinical scores of stroke recovery was found. The lowest correlation of the corticospinal tract FAasymmetry and FMA was with the single tensor model (r = -0.3, p = 0.2) whereas the other models reported results in the range of r = -0.79 ÷ -0.81 and p = 4E-5 ÷ 8E-5. The corticospinal tract and superior longitudinal fasciculus showed most alterations in our patient group relative to controls. Multiple compartment models yielded superior correlation of the diffusion measures and FMA compared to the single tensor model.

Original languageEnglish
Article number247
JournalFrontiers in Neuroscience
Volume12
Issue numberAPR
DOIs
Publication statusPublished - 23 Apr 2018

Fingerprint

Stroke
Pyramidal Tracts
Upper Extremity
Diffusion Magnetic Resonance Imaging
Atlases
Anisotropy
Healthy Volunteers
Outcome Assessment (Health Care)
White Matter
Control Groups

Keywords

  • Anatomic lateralization
  • Brain
  • Diffusion MRI
  • Diffusion tensor imaging/methods
  • Motor performance
  • Rehabilitation outcomes
  • Stroke

Cite this

@article{44a1766ee2724ad4b9b753f0add057ae,
title = "Comparison of multi-tensor diffusion models' performance for white matter integrity estimation in chronic stroke",
abstract = "Better insight into white matter (WM) alterations after stroke onset could help to understand the underlying recovery mechanisms and improve future interventions. MR diffusion imaging enables to assess such changes. Our goal was to investigate the relation of WM diffusion characteristics derived from diffusion models of increasing complexity with the motor function of the upper limb. Moreover, we aimed to evaluate the variation of such characteristics across different WM structures of chronic stroke patients in comparison to healthy subjects. Subjects were scanned with a two b-value diffusion-weighted MRI protocol to exploit multiple diffusion models: single tensor, single tensor with isotropic compartment, bi-tensor model, bi-tensor with isotropic compartment. From each model we derived the mean tract fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivities outside the lesion site based on a WM tracts atlas. Asymmetry of these measures was correlated with the Fugl-Meyer upper extremity assessment (FMA) score and compared between patient and control groups. Eighteen chronic stroke patients and eight age-matched healthy individuals participated in the study. Significant correlation of the outcome measures with the clinical scores of stroke recovery was found. The lowest correlation of the corticospinal tract FAasymmetry and FMA was with the single tensor model (r = -0.3, p = 0.2) whereas the other models reported results in the range of r = -0.79 ÷ -0.81 and p = 4E-5 ÷ 8E-5. The corticospinal tract and superior longitudinal fasciculus showed most alterations in our patient group relative to controls. Multiple compartment models yielded superior correlation of the diffusion measures and FMA compared to the single tensor model.",
keywords = "Anatomic lateralization, Brain, Diffusion MRI, Diffusion tensor imaging/methods, Motor performance, Rehabilitation outcomes, Stroke",
author = "Filatova, {Olena G.} and {van Vliet}, {Lucas J.} and Schouten, {Alfred C.} and Gert Kwakkel and {van der Helm}, {Frans C.T.} and Vos, {Frans M.} and {de Munck}, Jan and Carel Meskers and Mique Saes and Luuk Haring and Caroline Winters and Aukje Andringa and Dirk Hoevenaars and Fernandes, {Ines de Castro} and Sarah Zandvliet and Andreas Daffertshofer and {van Wegen}, Erwin and Jun Yao and Julius Dewald and Teodoro Solis-Escalante and Yuan Yang and {van de Ruit}, Mark and Martijn Vlaar and Konstantina Kalogianni and {on behalf of the 4D EEG Consortium}",
year = "2018",
month = "4",
day = "23",
doi = "10.3389/fnins.2018.00247",
language = "English",
volume = "12",
journal = "Frontiers in Neuroscience",
issn = "1662-4548",
publisher = "Frontiers Research Foundation",
number = "APR",

}

Comparison of multi-tensor diffusion models' performance for white matter integrity estimation in chronic stroke. / on behalf of the 4D EEG Consortium.

In: Frontiers in Neuroscience, Vol. 12, No. APR, 247, 23.04.2018.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Comparison of multi-tensor diffusion models' performance for white matter integrity estimation in chronic stroke

AU - Filatova, Olena G.

AU - van Vliet, Lucas J.

AU - Schouten, Alfred C.

AU - Kwakkel, Gert

AU - van der Helm, Frans C.T.

AU - Vos, Frans M.

AU - de Munck, Jan

AU - Meskers, Carel

AU - Saes, Mique

AU - Haring, Luuk

AU - Winters, Caroline

AU - Andringa, Aukje

AU - Hoevenaars, Dirk

AU - Fernandes, Ines de Castro

AU - Zandvliet, Sarah

AU - Daffertshofer, Andreas

AU - van Wegen, Erwin

AU - Yao, Jun

AU - Dewald, Julius

AU - Solis-Escalante, Teodoro

AU - Yang, Yuan

AU - van de Ruit, Mark

AU - Vlaar, Martijn

AU - Kalogianni, Konstantina

AU - on behalf of the 4D EEG Consortium

PY - 2018/4/23

Y1 - 2018/4/23

N2 - Better insight into white matter (WM) alterations after stroke onset could help to understand the underlying recovery mechanisms and improve future interventions. MR diffusion imaging enables to assess such changes. Our goal was to investigate the relation of WM diffusion characteristics derived from diffusion models of increasing complexity with the motor function of the upper limb. Moreover, we aimed to evaluate the variation of such characteristics across different WM structures of chronic stroke patients in comparison to healthy subjects. Subjects were scanned with a two b-value diffusion-weighted MRI protocol to exploit multiple diffusion models: single tensor, single tensor with isotropic compartment, bi-tensor model, bi-tensor with isotropic compartment. From each model we derived the mean tract fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivities outside the lesion site based on a WM tracts atlas. Asymmetry of these measures was correlated with the Fugl-Meyer upper extremity assessment (FMA) score and compared between patient and control groups. Eighteen chronic stroke patients and eight age-matched healthy individuals participated in the study. Significant correlation of the outcome measures with the clinical scores of stroke recovery was found. The lowest correlation of the corticospinal tract FAasymmetry and FMA was with the single tensor model (r = -0.3, p = 0.2) whereas the other models reported results in the range of r = -0.79 ÷ -0.81 and p = 4E-5 ÷ 8E-5. The corticospinal tract and superior longitudinal fasciculus showed most alterations in our patient group relative to controls. Multiple compartment models yielded superior correlation of the diffusion measures and FMA compared to the single tensor model.

AB - Better insight into white matter (WM) alterations after stroke onset could help to understand the underlying recovery mechanisms and improve future interventions. MR diffusion imaging enables to assess such changes. Our goal was to investigate the relation of WM diffusion characteristics derived from diffusion models of increasing complexity with the motor function of the upper limb. Moreover, we aimed to evaluate the variation of such characteristics across different WM structures of chronic stroke patients in comparison to healthy subjects. Subjects were scanned with a two b-value diffusion-weighted MRI protocol to exploit multiple diffusion models: single tensor, single tensor with isotropic compartment, bi-tensor model, bi-tensor with isotropic compartment. From each model we derived the mean tract fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivities outside the lesion site based on a WM tracts atlas. Asymmetry of these measures was correlated with the Fugl-Meyer upper extremity assessment (FMA) score and compared between patient and control groups. Eighteen chronic stroke patients and eight age-matched healthy individuals participated in the study. Significant correlation of the outcome measures with the clinical scores of stroke recovery was found. The lowest correlation of the corticospinal tract FAasymmetry and FMA was with the single tensor model (r = -0.3, p = 0.2) whereas the other models reported results in the range of r = -0.79 ÷ -0.81 and p = 4E-5 ÷ 8E-5. The corticospinal tract and superior longitudinal fasciculus showed most alterations in our patient group relative to controls. Multiple compartment models yielded superior correlation of the diffusion measures and FMA compared to the single tensor model.

KW - Anatomic lateralization

KW - Brain

KW - Diffusion MRI

KW - Diffusion tensor imaging/methods

KW - Motor performance

KW - Rehabilitation outcomes

KW - Stroke

UR - http://www.scopus.com/inward/record.url?scp=85046081420&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85046081420&partnerID=8YFLogxK

U2 - 10.3389/fnins.2018.00247

DO - 10.3389/fnins.2018.00247

M3 - Article

VL - 12

JO - Frontiers in Neuroscience

JF - Frontiers in Neuroscience

SN - 1662-4548

IS - APR

M1 - 247

ER -