• NeuroImage · Apr 2011

    Real-time feedback optimization of z-shim gradient for automatic compensation of susceptibility-induced signal loss in EPI.

    • Yu-Wei Tang and Teng-Yi Huang.
    • Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC.
    • Neuroimage. 2011 Apr 15; 55 (4): 1587-92.

    AbstractSignal loss in gradient-echo echo planar imaging (GE-EPI) due to susceptibility-induced magnetic field inhomogeneity makes it difficult to assess the blood oxygenation level-dependent (BOLD) effect in fMRI investigations. The z-shim method that applies an additional gradient moment is one of the more popular methods of compensating for GE-EPI signal loss. However, this method requires a calibration sweep scan and post-processing to identify the optimal z-shim gradients, which slows down fMRI experiments. This study attempts to decrease the calibration time by introducing a real-time feedback framework. Creating a feedback loop between the image processing and the GE-EPI pulse sequence converts the calibration of z-shim gradients to an optimization problem, which can be accelerated by local search methods. This study proposes an interleaved scan that allows the simultaneous optimization of two z-shim gradient moments and allocates sufficient processing time for networking and computation. The z-shim compensated images obtained by the proposed real-time method are comparable to those created by the sweep method. The optimization procedure for obtaining negative and positive gradient moments generally requires about twenty GE-EPI repetitions. In conclusion, the proposed z-shim method includes an automated real-time framework to achieve a significant reduction in susceptibility-induced signal loss in GE-EPI with a minimal increase in calibration time. The proposed procedure is fully automatic and compatible with conventional GE-EPI and can thus serve as a pre-adjustment module in EPI-based fMRI researches.Copyright © 2011 Elsevier Inc. All rights reserved.

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