Abstract #1262

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

Renzo Huber¹, Michael Koehler², Rüdiger Stirnberg³, Jennifer Evans¹, Lasse Knudsen⁴, A. Tyler Morgan¹, David Feinberg⁵, Daniel Handwerker¹, Marly Rubin¹, Burak Akin¹, Stephanie Swegle¹, and Peter Bandettini¹

¹NIH, Bethesda, MD, United States, ²SIEMENS Healthineers, Erlangen, Germany, ³DZNE, Bonn, Germany, ⁴Aarhus University, Denmark & Chinese Academy of Sciences, Bejing, China, ⁵UC, Berkeley, CA, United States

Synopsis

Keywords: fMRI Acquisition, fMRI Acquisition, layer-fMRI, UHF, EPI, sub-millimeter fMRI, 7 tesla

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).

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