Increasing spatial coverage for high-resolution functional MRI

For high-resolution functional MRI (fMRI) studies, one of the major challenges is limited spatial coverage, which results because of the tradeoffs between temporal resolution and covering more k-space. Given the same temporal resolution, fewer slices can be collected for high-resolution fMRI. If the number of slices is not large enough to cover all regions of interest, additional scans may become necessary, which increases both the total scan time and the complexity of interpreting data. In this work, we propose a method that combines the undersampled 3D stack-of-spirals acquisition method with the UNFOLD technique to significantly increase the spatial coverage for high-resolution fMRI. Undersampling allows more slices to be fit into a given temporal resolution. The signal-to-noise ratio (SNR) drop associated with undersampling can be compensated by the increase in the excited volume in 3D acquisitions. Theoretical analysis shows that although there is a negligible increase in temporal coherence due to spectral filtering in the UNFOLD technique, twice the spatial coverage can be achieved given the same total scan time and similar quality of activation maps, which was confirmed by experiments on normal subjects.