Motion robust GRAPPA for echo-planar imaging.

Area of Science:

• Magnetic Resonance Imaging
• Image Acquisition Techniques

Background:

• Robust calibration data is crucial for Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) in echo-planar imaging (EPI).
• Existing methods like interleaved and single-shot calibration are susceptible to motion and B0 inhomogeneity artifacts.

Purpose of the Study:

• To propose and evaluate a novel readout-segmented method for acquiring GRAPPA calibration data in EPI.
• To compare the proposed method against interleaved and single-shot techniques.

Main Methods:

• The readout-segmented method acquires adjacent phase encode lines within a single shot, reducing motion sensitivity.
• It employs multiple segments with shortened frequency encode extent to mitigate B0 inhomogeneity.
• Simulations and EPI brain scans in healthy volunteers were used for testing.

Main Results:

• The interleaved method showed high motion sensitivity.
• The single-shot method had residual artifacts due to B0 inhomogeneity mismatch.
• The readout-segmented method demonstrated no significant artifacts, with 30% less ghosting than single-shot and 90% less than interleaved methods.

Conclusions:

• The readout-segmented calibration scan effectively mitigates artifacts from B0 inhomogeneity and motion in EPI GRAPPA.
• This method enhances the robustness of EPI imaging by improving calibration data quality.