Echo time-dependent quantitative susceptibility mapping contains information on tissue properties

Sood, Surabhi, Urriola, Javier, Reutens, David C., O'Brien, Kieran, Bollmann, Steffen, Barth, Markus and Vegh, Viktor (2016) Echo time-dependent quantitative susceptibility mapping contains information on tissue properties. Magnetic Resonance in Medicine, 77 5: 1946-1958. doi:10.1002/mrm.26281

Author Sood, Surabhi
Urriola, Javier
Reutens, David C.
O'Brien, Kieran
Bollmann, Steffen
Barth, Markus
Vegh, Viktor
Title Echo time-dependent quantitative susceptibility mapping contains information on tissue properties
Journal name Magnetic Resonance in Medicine   Check publisher's open access policy
ISSN 1522-2594
Publication date 2016-05-25
Year available 2016
Sub-type Article (original research)
DOI 10.1002/mrm.26281
Open Access Status Not Open Access
Volume 77
Issue 5
Start page 1946
End page 1958
Total pages 13
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Formatted abstract
Purpose: Magnetic susceptibility is a physical property of matter that varies depending on chemical composition and abundance of different molecular species. Interest is growing in mapping of magnetic susceptibility in the human brain using magnetic resonance imaging techniques, but the influences affecting the mapped values are not fully understood.

Methods: We performed quantitative susceptibility mapping on 7 Tesla (T) multiple echo time gradient recalled echo data and evaluated the trend in 10 regions of the human brain. Temporal plots of susceptibility were performed in the caudate, pallidum, putamen, thalamus, insula, red nucleus, substantia nigra, internal capsule, corpus callosum, and fornix. We implemented an existing three compartment signal model and used optimization to fit the experimental result to assess the influences that could be responsible for our findings.

Results: The temporal trend in susceptibility is different for different brain regions, and subsegmentation of specific regions suggests that differences are likely to be attributable to variations in tissue structure and composition. Using a signal model, we verified that a nonlinear temporal behavior in experimentally computed susceptibility within imaging voxels may be the result of the heterogeneous composition of tissue properties.

Conclusions: Decomposition of voxel constituents into meaningful parameters may lead to informative measures that reflect changes in tissue microstructure. 
Keyword Magnetic resonance imaging
Quantitative susceptibility mapping
Tissue composition
Tissue structure
Ultra-high field imaging
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Centre for Advanced Imaging Publications
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Created: Wed, 08 Jun 2016, 01:56:53 EST by Dr Viktor Vegh on behalf of Centre for Advanced Imaging