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Complex data analysis in high‐resolution SSFP fMRI
Author(s) -
Lee Jongho,
Shahram Morteza,
Schwartzman Armin,
Pauly John M.
Publication year - 2007
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.21195
Subject(s) - voxel , steady state free precession imaging , nuclear magnetic resonance , signal (programming language) , magnitude (astronomy) , phase (matter) , magnetic resonance imaging , computer science , chemistry , physics , artificial intelligence , radiology , medicine , astronomy , programming language , organic chemistry
In transition‐band steady‐state free precession (SSFP) functional MRI (fMRI), functional contrast originates from a bulk frequency shift induced by a deoxygenated hemoglobin concentration change in the activated brain regions. This frequency shift causes a magnitude and/or phase‐signal change depending on the off‐resonance distribution of a voxel in the balanced‐SSFP (bSSFP) profile. However, in early low‐resolution studies, only the magnitude signal activations were shown. In this paper the task‐correlated phase‐signal change is presented in a high‐resolution (1 × 1 × 1 mm 3 ) study. To include this phase activation in a functional analysis, a new complex domain data analysis method is proposed. The results show statistically significant phase‐signal changes in a large number of voxels comparable to that of the magnitude‐activated voxels. The complex‐data analysis method successfully includes these phase activations in the activation map and thus provides wider coverage compared to magnitude‐data analysis results. Magn Reson Med 57:905–917, 2007. © 2007 Wiley‐Liss, Inc.