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Functional MRI using regularized parallel imaging acquisition
Author(s) -
Lin FaHsuan,
Huang TengYi,
Chen NanKuei,
Wang FuNien,
Stufflebeam Steven M.,
Belliveau John W.,
Wald Lawrence L.,
Kwong Kenneth K.
Publication year - 2005
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.20555
Subject(s) - regularization (linguistics) , computer science , artificial intelligence , sensitivity (control systems) , functional magnetic resonance imaging , algorithm , computer vision , pattern recognition (psychology) , nuclear magnetic resonance , physics , neuroscience , electronic engineering , engineering , biology
Abstract Parallel MRI techniques reconstruct full‐FOV images from undersampled k‐ space data by using the uncorrelated information from RF array coil elements. One disadvantage of parallel MRI is that the image signal‐to‐noise ratio (SNR) is degraded because of the reduced data samples and the spatially correlated nature of multiple RF receivers. Regularization has been proposed to mitigate the SNR loss originating due to the latter reason. Since it is necessary to utilize static prior to regularization, the dynamic contrast‐to‐noise ratio (CNR) in parallel MRI will be affected. In this paper we investigate the CNR of regularized sensitivity encoding (SENSE) acquisitions. We propose to implement regularized parallel MRI acquisitions in functional MRI (fMRI) experiments by incorporating the prior from combined segmented echo‐planar imaging (EPI) acquisition into SENSE reconstructions. We investigated the impact of regularization on the CNR by performing parametric simulations at various BOLD contrasts, acceleration rates, and sizes of the active brain areas. As quantified by receiver operating characteristic (ROC) analysis, the simulations suggest that the detection power of SENSE fMRI can be improved by regularized reconstructions, compared to unregularized reconstructions. Human motor and visual fMRI data acquired at different field strengths and array coils also demonstrate that regularized SENSE improves the detection of functionally active brain regions. Magn Reson Med 54:343–353, 2005. © 2005 Wiley‐Liss, Inc.