DWI using navigated interleaved multishot EPI with realigned GRAPPA reconstruction.

Area of Science:

• Magnetic Resonance Imaging
• Biomedical Engineering
• Image Reconstruction

Background:

• Navigated interleaved multishot EPI (msEPI) is a technique for acquiring diffusion-weighted imaging (DWI) data.
• Challenges in msEPI include k-space undersampling and intershot phase variations.
• Existing reconstruction methods like SENSE may have limitations in handling these challenges.

Purpose of the Study:

• To propose a novel k-space reconstruction method for DWI using navigated interleaved msEPI.
• To address challenges of k-space undersampling and phase variations in msEPI.
• To evaluate the performance of the proposed method against a SENSE-based approach.

Main Methods:

• Interleaved msEPI data from each coil channel are treated as undersampled virtual multichannel data.
• The GRAPPA algorithm is employed for reconstruction after k-space realignment.
• Navigator echoes are used for auto-calibration to compensate for intershot phase variations within the GRAPPA framework.
• Multichannel msEPI data are integrated into a single GRAPPA reconstruction step.

Main Results:

• The proposed method demonstrates lower relative error in simulated images compared to the SENSE-based method.
• GRAPPA calibration inherently resolves inconsistent shot-to-shot phase variations without requiring separate phase map processing.
• High-quality brain DWI with submillimeter resolution was successfully achieved.

Conclusions:

• A novel k-space reconstruction method for msEPI has been developed.
• This method enables the generation of high-quality diffusion-weighted imaging.
• The technique effectively handles k-space undersampling and phase variations inherent in msEPI acquisition.