Compressed Sensing Reconstruction Improves Variable Density Spiral Functional MRI

Daniel Holland¹, Careesa Liu², Chris V. Bowen², Andy Sederman¹, Lynn Gladden¹, Steven D. Beyea²

We demonstrate that the use of Compressed Sensing reconstruction of variable density spiral fMRI data minimizes the aliasing artifact inherent to sparse k-space acquisitions that can result in additional signal fluctuations in the time course data. Our data demonstrate an improvement in the apparent fMRI sensitivity relative to the same images reconstructed without CS. CS reconstruction of a 50% undersampled VD spiral acquisition resulted in a 40% increase in whole brain activation volume relative to the same data reconstructed with conventional (non-CS) techniques, demonstrating that fMRI data obtained using VD trajectories should be reconstructed using Compressed Sensing.