Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters

Loading...
Thumbnail Image
File version

Version of Record (VoR)

Author(s)
Thapaliya, Kiran
Vegh, Viktor
Bollmann, Steffen
Barth, Markus
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2020
Size
File type(s)
Location
Abstract

Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders. Ultra-high field magnetic resonance imaging (MRI) data obtained using a multi-echo gradient echo sequence have been shown to contain information on myelin, axonal, and extracellular compartments in tissue. Quantitative assessment of water fraction, relaxation time (T2*), and frequency shift using multi-compartment models has been shown to be useful in studying white matter properties via specific tissue parameters. It remains unclear how tissue parameters vary with model selection based on 7T multiple echo time gradient-recalled echo (GRE) MRI data. We applied existing signal compartment models to the corpus callosum and investigated whether a three-compartment model can be reduced to two compartments and still resolve white matter parameters [i.e., myelin water fraction (MWF) and g-ratio]. We show that MWF should be computed using a three-compartment model in the corpus callosum, and the g-ratios obtained using three compartment models are consistent with previous reports. We provide results for other parameters, such as signal compartment frequency shifts.

Journal Title

Frontiers in Neuroscience

Conference Title
Book Title
Edition
Volume

14

Issue
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© 2020 Thapaliya, Vegh, Bollmann and Barth. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Item Access Status
Note
Access the data
Related item(s)
Subject

Neurosciences

Psychology

Cognitive and computational psychology

corpus callosum

frequency shift

myelin imaging

phase unwrapping

signal compartmentalization

Persistent link to this record
Citation

Thapaliya, K; Vegh, V; Bollmann, S; Barth, M, Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters, Frontiers in Neuroscience, 2020, 14, pp. 271:1-271:13

Collections