Inverse reconstruction method for segmented multishot diffusion-weighted MRI with multiple coils.

Area of Science:

• Medical Imaging
• Magnetic Resonance Imaging
• Biophysics

Background:

• Multishot diffusion-weighted MRI (DW-MRI) is susceptible to motion-induced phase variations.
• Existing methods using low-resolution navigators struggle with high spatial frequencies in phase maps.
• Accurate phase mapping is crucial for artifact-free image reconstruction in DW-MRI.

Purpose of the Study:

• To develop an advanced inverse reconstruction method for segmented multishot DW-MRI.
• To improve the accuracy of phase map estimation by utilizing full k-space data and multiple receiver coils.
• To achieve artifact-free image reconstruction in brain DW-MRI.

Main Methods:

• Coil sensitivities were estimated using regularized nonlinear inversion from non-diffusion-weighted data.
• Accurate motion-associated phase maps were derived for each segment via iterative linear inversion.
• Artifact-free images were reconstructed using estimated coil sensitivities and phase maps through iterative linear inversion.

Main Results:

• The proposed method effectively estimates accurate phase maps, even with high spatial frequencies.
• The technique successfully reconstructs artifact-free images from segmented multishot DW-MRI data.
• Demonstrated efficiency in segmented diffusion-weighted stimulated echo acquisition mode MRI of the human brain.

Conclusions:

• The developed inverse reconstruction method offers a robust solution for phase correction in multishot DW-MRI.
• This approach significantly enhances image quality by mitigating motion-related artifacts.
• The method holds promise for improved diagnostic accuracy in brain imaging applications.