Advanced Echo-planar Parallel Imaging with Gradient Harmonization (AEPIG): an optimization strategy for fast high resolution fMRI

Motivation: Sub-millimeter resolution fMRI with large coverage of the brain is limited by relatively long acquisition times. Shorter TRs with very high GRAPPA factors>8 are challenged by image artifacts. Goal(s): We aim to develop, optimize, and validate highly accelerated Cartesian EPI protocols for efficient whole-brain layer-fMRI. Approach: AEPIG (Advanced Echo-planar Parallel Imaging with Gradient Harmonization): a simple approach for mitigating GRAPPA artifacts by optimizing EPI trajectory accuracy. Results: We find that AEPIG allows acceleration up to a factor of 20. Further acceleration is limited by superlinear g-factor noise amplification. Impact: The proposed optimization approach AEPIG (Advanced Echo-planar Parallel Imaging with Gradient Harmonization) allows layer-fMRI protocols with GRAPPA acceleration factors up to R=20. This enabled researchers to perform whole brain layer-fMRI while maintaining common TRs (<3s).