Abstract
Conventional functional magnetic resonance imaging (fMRI) technique known as gradient-recalled echo (GRE) echo-planar imaging (EPI) is sensitive to image distortion and degradation caused by local magnetic field inhomogeneity at high magnetic fields. Non-EPI sequences such as spoiled gradient echo and balanced steady-state free precession (bSSFP) have been proposed as an alternative high-resolution fMRI technique; however, the temporal resolution of these sequences is lower than the typically used GRE-EPI fMRI. One potential approach to improve the temporal resolution is to use compressed sensing (CS). In this study, we tested the feasibility of k-t FOCUSS—one of the high performance CS algorithms for dynamic MRI—for non-EPI fMRI at 9.4T using the model of rat somatosensory stimulation. To optimize the performance of CS reconstruction, different sampling patterns and k-t FOCUSS variations were investigated. Experimental results show that an optimized k-t FOCUSS algorithm with acceleration by a factor of 4 works well for non-EPI fMRI at high field under various statistical criteria, which confirms that a combination of CS and a non-EPI sequence may be a good solution for high-resolution fMRI at high fields.
Highlights
Functional magnetic resonance imaging has had a wide impact in both the research and clinical community since its development
In conventional Functional magnetic resonance imaging (fMRI) studies, positive blood oxygen level-dependent (BOLD) response signal is used as a measure to map neural activity in the brain [1], and the most common MR pulse sequence for acquiring BOLD fMRI images has been gradient-recalled echo (GRE) echo-planar imaging (EPI) due to its fast acquisition speed and high sensitivity to BOLD effect
All further analyses were performed with the determined NFOC values for each subject data, to evaluate the performance of k-t FOCal Underdetermined System Solver (FOCUSS) algorithms with the proposed stopping criterion
Summary
Functional magnetic resonance imaging (fMRI) has had a wide impact in both the research and clinical community since its development. In conventional fMRI studies, positive blood oxygen level-dependent (BOLD) response signal is used as a measure to map neural activity in the brain [1], and the most common MR pulse sequence for acquiring BOLD fMRI images has been gradient-recalled echo (GRE) echo-planar imaging (EPI) due to its fast acquisition speed and high sensitivity to BOLD effect. This technique is susceptible to local magnetic field inhomogeneity and becomes sensitive to image distortion and degradation especially at high magnetic fields. These requirements can be well satisfied in dynamic MRI, since arbitrary trajectories can be implemented to incoherently sample data and dynamic MR images can be sparsified due to high temporal redundancy [16, 17]
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