Motion-corrected k-space reconstruction for interleaved EPI diffusion imaging.

Area of Science:

• Magnetic Resonance Imaging
• Diffusion Tensor Imaging
• Image Reconstruction

Background:

• Multishot interleaved echo-planar imaging is susceptible to physiological and macroscopic motion artifacts.
• These artifacts degrade image quality and reduce the accuracy of diffusion tensor calculations.
• Existing methods often struggle to correct for both types of motion simultaneously.

Purpose of the Study:

• To develop and validate a novel approach for correcting physiological and macroscopic motion in multishot interleaved echo-planar diffusion imaging.
• To enhance the accuracy of diffusion tensor imaging (DTI) metrics by mitigating motion-induced errors.
• To integrate advanced motion correction techniques into an existing iterative self-consistent parallel imaging reconstruction framework.

Main Methods:

• The study builds upon the SPIRiT (iterative self-consistent parallel imaging reconstruction) framework.
• In-plane rotation, translation correction, data rejection, and weighted combination strategies were incorporated.
• The method was evaluated using numerical simulations and in vivo experiments with induced bulk motion.

Main Results:

• The proposed method effectively reduced artifacts in diffusion-weighted images.
• Significant improvements in the accuracy of diffusion tensor parameters were observed.
• For in vivo data with motion, fractional anisotropy error in the genu of the corpus callosum decreased from 17.01±12.64% to 5.73±3.77%.

Conclusions:

• The developed approach successfully corrects for combined physiological and macroscopic motion in multishot diffusion imaging.
• High-resolution diffusion images with improved tensor calculation accuracy can be generated.
• This method offers a robust solution for motion-related challenges in diffusion MRI.