Interleaved EPI diffusion imaging using SPIRiT-based reconstruction with virtual coil compression.

Area of Science:

• Magnetic Resonance Imaging
• Image Reconstruction
• Diffusion Imaging

Background:

• Iterative self-consistent parallel imaging reconstruction (SPIRiT) offers improved k-space reconstruction over traditional generalized autocalibrating partially parallel acquisitions (GRAPPA).
• Multishot interleaved echo planar imaging (iEPI) is a diffusion imaging technique that can benefit from advanced reconstruction methods.

Purpose of the Study:

• To develop a novel diffusion imaging reconstruction framework using SPIRiT for multishot iEPI.
• To accelerate computation through virtual coil compression.

Main Methods:

• A SPIRiT framework incorporating coil sensitivity and phase variation as virtual coils was applied to 2D navigated iEPI diffusion imaging.
• A novel shot-coil compression method was proposed for computational acceleration in Cartesian sampling.
• Simulations and in vivo experiments were performed for evaluation.

Main Results:

• The proposed shot-coil compression achieved higher compression rates and reduced errors compared to conventional coil compression.
• SPIRiT-based reconstruction outperformed realigned GRAPPA, yielding superior images with fewer artifacts.
• The method was validated through both simulations and in vivo experiments.

Conclusions:

• The SPIRiT-based reconstruction with virtual coil compression provides a reliable approach for high-resolution iEPI diffusion imaging.
• This framework enhances image quality and computational efficiency in diffusion MRI.