Real-time feedback optimization of z-shim gradient for automatic compensation of susceptibility-induced signal loss in EPI.
Signal 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.
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC.
Yu-Wei
YW
Tang
Teng-Yi
TY
Huang
D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D003199:Computer Systems; D017352:Echo-Planar Imaging / Q000379:methods*; D005246:Feedback; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity