Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2*-weighted magnetic resonance imaging at 7 T

Qin, Shanlin, Liu, Fawang, Turner, Ian W., Yu, Qiang, Yang, Qianqian and Vegh, Viktor (2016) Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2*-weighted magnetic resonance imaging at 7 T. Magnetic Resonance in Medicine, 77 4: 1485-1494. doi:10.1002/mrm.26222


Author Qin, Shanlin
Liu, Fawang
Turner, Ian W.
Yu, Qiang
Yang, Qianqian
Vegh, Viktor
Title Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2*-weighted magnetic resonance imaging at 7 T
Formatted title
Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2*-weighted magnetic resonance imaging at 7 T
Journal name Magnetic Resonance in Medicine   Check publisher's open access policy
ISSN 1522-2594
0740-3194
Publication date 2016-03-26
Year available 2016
Sub-type Article (original research)
DOI 10.1002/mrm.26222
Open Access Status Not Open Access
Volume 77
Issue 4
Start page 1485
End page 1494
Total pages 10
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Formatted abstract
Purpose: To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain.

Methods: We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters.

Results: We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift.

Conclusions: We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.
Keyword Magnetic resonance imaging
Bloch equation
Ultrahigh field
Anomalous relaxation
T2
Fractional derivative
Human brain
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
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Tue, 12 Apr 2016, 11:45:13 EST by System User on behalf of Learning and Research Services (UQ Library)