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Validation strategies for the interpretation of microstructure imaging using diffusion MRI

Dyrby, Tim B.; Innocenti, Giorgio M.; Bech, Martin LU and Lundell, Henrik (2018) In NeuroImage 182. p.62-79
Abstract

Extracting microanatomical information beyond the image resolution of MRI would provide valuable tools for diagnostics and neuroscientific research. A number of mathematical models already suggest microstructural interpretations of diffusion MRI (dMRI) data. Examples of such microstructural features could be cell bodies and neurites, e.g. the axon's diameter or their orientational distribution for global connectivity analysis using tractography, and have previously only been possible to access through conventional histology of post mortem tissue or invasive biopsies. The prospect of gaining the same knowledge non-invasively from the whole living human brain could push the frontiers for the diagnosis of neurological and psychiatric... (More)

Extracting microanatomical information beyond the image resolution of MRI would provide valuable tools for diagnostics and neuroscientific research. A number of mathematical models already suggest microstructural interpretations of diffusion MRI (dMRI) data. Examples of such microstructural features could be cell bodies and neurites, e.g. the axon's diameter or their orientational distribution for global connectivity analysis using tractography, and have previously only been possible to access through conventional histology of post mortem tissue or invasive biopsies. The prospect of gaining the same knowledge non-invasively from the whole living human brain could push the frontiers for the diagnosis of neurological and psychiatric diseases. It could also provide a general understanding of the development and natural variability in the healthy brain across a population. However, due to a limited image resolution, most of the dMRI measures are indirect estimations and may depend on the whole chain from experimental parameter settings to model assumptions and implementation. Here, we review current literature in this field and highlight the integrative work across anatomical length scales that is needed to validate and trust a new dMRI method. We encourage interdisciplinary collaborations and data sharing in regards to applying and developing new validation techniques to improve the specificity of future dMRI methods.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
NeuroImage
volume
182
pages
62 - 79
publisher
Elsevier
external identifiers
  • scopus:85050145386
ISSN
1053-8119
DOI
10.1016/j.neuroimage.2018.06.049
language
English
LU publication?
yes
id
194c701f-0949-43f5-9855-833c343710ce
date added to LUP
2018-08-03 09:24:01
date last changed
2019-01-14 16:41:27
@article{194c701f-0949-43f5-9855-833c343710ce,
  abstract     = {<p>Extracting microanatomical information beyond the image resolution of MRI would provide valuable tools for diagnostics and neuroscientific research. A number of mathematical models already suggest microstructural interpretations of diffusion MRI (dMRI) data. Examples of such microstructural features could be cell bodies and neurites, e.g. the axon's diameter or their orientational distribution for global connectivity analysis using tractography, and have previously only been possible to access through conventional histology of post mortem tissue or invasive biopsies. The prospect of gaining the same knowledge non-invasively from the whole living human brain could push the frontiers for the diagnosis of neurological and psychiatric diseases. It could also provide a general understanding of the development and natural variability in the healthy brain across a population. However, due to a limited image resolution, most of the dMRI measures are indirect estimations and may depend on the whole chain from experimental parameter settings to model assumptions and implementation. Here, we review current literature in this field and highlight the integrative work across anatomical length scales that is needed to validate and trust a new dMRI method. We encourage interdisciplinary collaborations and data sharing in regards to applying and developing new validation techniques to improve the specificity of future dMRI methods.</p>},
  author       = {Dyrby, Tim B. and Innocenti, Giorgio M. and Bech, Martin and Lundell, Henrik},
  issn         = {1053-8119},
  language     = {eng},
  month        = {06},
  pages        = {62--79},
  publisher    = {Elsevier},
  series       = {NeuroImage},
  title        = {Validation strategies for the interpretation of microstructure imaging using diffusion MRI},
  url          = {http://dx.doi.org/10.1016/j.neuroimage.2018.06.049},
  volume       = {182},
  year         = {2018},
}