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Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: Applications in healthy volunteers and in brain tumors

Szczepankiewicz, Filip LU ; Lasic, Samo; van Westen, Danielle; Sundgren, Pia C.; Englund, Elisabet; Westin, Carl-Fredrik; Ståhlberg, Freddy LU ; Latt, Jimmy; Topgaard, Daniel and Nilsson, Markus (2015) In NeuroImage 104. p.241-252
Abstract
The anisotropy of water diffusion in brain tissue is affected by both disease and development. This change can be detected using diffusion MRI and is often quantified by the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI). Although FA is sensitive to anisotropic cell structures, such as axons, it is also sensitive to their orientation dispersion. This is a major limitation to the use of FA as a biomarker for "tissue integrity", especially in regions of complex microarchitecture. In this work, we seek to circumvent this limitation by disentangling the effects of microscopic diffusion anisotropy from the orientation dispersion. The microscopic fractional anisotropy (mu FA) and the order parameter (OP) were calculated... (More)
The anisotropy of water diffusion in brain tissue is affected by both disease and development. This change can be detected using diffusion MRI and is often quantified by the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI). Although FA is sensitive to anisotropic cell structures, such as axons, it is also sensitive to their orientation dispersion. This is a major limitation to the use of FA as a biomarker for "tissue integrity", especially in regions of complex microarchitecture. In this work, we seek to circumvent this limitation by disentangling the effects of microscopic diffusion anisotropy from the orientation dispersion. The microscopic fractional anisotropy (mu FA) and the order parameter (OP) were calculated from the contrast between signal prepared with directional and isotropic diffusion encoding, where the latter was achieved by magic angle spinning of the q-vector (qMAS). These parameters were quantified in healthy volunteers and in two patients; one patient with meningioma and one with glioblastoma. Finally, we used simulations to elucidate the relation between FA and mu FA in various micro-architectures. Generally, mu FA was high in the white matter and low in the gray matter. In the white matter, the largest differences between mu FA and FA were found in crossing white matter and in interfaces between large white matter tracts, where mu FA was high while FA was low. Both tumor types exhibited a low FA, in contrast to the mu FA which was high in the meningioma and low in the glioblastoma, indicating that the meningioma contained disordered anisotropic structures, while the glioblastoma did not. This interpretation was confirmed by histological examination. We conclude that FA from DTI reflects both the amount of diffusion anisotropy and orientation dispersion. We suggest that the mu FA and OP may complement FA by independently quantifying the microscopic anisotropy and the level of orientation coherence. (C) 2014 The Authors. Published by Elsevier Inc. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Diffusion weighted imaging, Microscopic anisotropy, Microscopic, fractional anisotropy, Order parameter, Magic angle spinning of the, q-vector
in
NeuroImage
volume
104
pages
241 - 252
publisher
Elsevier
external identifiers
  • wos:000345393800024
  • scopus:84949115815
ISSN
1095-9572
DOI
10.1016/j.neuroimage.2014.09.057
language
English
LU publication?
yes
id
02e4eb2c-722e-45ad-8eb1-51c41b93f116 (old id 4965811)
date added to LUP
2015-02-03 07:07:48
date last changed
2017-11-05 03:07:35
@article{02e4eb2c-722e-45ad-8eb1-51c41b93f116,
  abstract     = {The anisotropy of water diffusion in brain tissue is affected by both disease and development. This change can be detected using diffusion MRI and is often quantified by the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI). Although FA is sensitive to anisotropic cell structures, such as axons, it is also sensitive to their orientation dispersion. This is a major limitation to the use of FA as a biomarker for "tissue integrity", especially in regions of complex microarchitecture. In this work, we seek to circumvent this limitation by disentangling the effects of microscopic diffusion anisotropy from the orientation dispersion. The microscopic fractional anisotropy (mu FA) and the order parameter (OP) were calculated from the contrast between signal prepared with directional and isotropic diffusion encoding, where the latter was achieved by magic angle spinning of the q-vector (qMAS). These parameters were quantified in healthy volunteers and in two patients; one patient with meningioma and one with glioblastoma. Finally, we used simulations to elucidate the relation between FA and mu FA in various micro-architectures. Generally, mu FA was high in the white matter and low in the gray matter. In the white matter, the largest differences between mu FA and FA were found in crossing white matter and in interfaces between large white matter tracts, where mu FA was high while FA was low. Both tumor types exhibited a low FA, in contrast to the mu FA which was high in the meningioma and low in the glioblastoma, indicating that the meningioma contained disordered anisotropic structures, while the glioblastoma did not. This interpretation was confirmed by histological examination. We conclude that FA from DTI reflects both the amount of diffusion anisotropy and orientation dispersion. We suggest that the mu FA and OP may complement FA by independently quantifying the microscopic anisotropy and the level of orientation coherence. (C) 2014 The Authors. Published by Elsevier Inc.},
  author       = {Szczepankiewicz, Filip and Lasic, Samo and van Westen, Danielle and Sundgren, Pia C. and Englund, Elisabet and Westin, Carl-Fredrik and Ståhlberg, Freddy and Latt, Jimmy and Topgaard, Daniel and Nilsson, Markus},
  issn         = {1095-9572},
  keyword      = {Diffusion weighted imaging,Microscopic anisotropy,Microscopic,fractional anisotropy,Order parameter,Magic angle spinning of the,q-vector},
  language     = {eng},
  pages        = {241--252},
  publisher    = {Elsevier},
  series       = {NeuroImage},
  title        = {Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: Applications in healthy volunteers and in brain tumors},
  url          = {http://dx.doi.org/10.1016/j.neuroimage.2014.09.057},
  volume       = {104},
  year         = {2015},
}