Exploiting Four-way Phase-encoding Benefits for Robust Detection and Correction of EPI artifacts: Application to Residual Ghosts in Diffusion MRI.

Abstract

PurposeTo propose and develop an image processing-based methodology for detecting and correcting echo planar imaging (EPI) artifact that employs data from 4-way phase-encoding acquisitions. ApproachPrevious studies have demonstrated that acquiring images with four different phase-encoding directions can improve the reproducibility of diffusion derived quantitative maps while retaining the same acquisition time. This improvement is achieved by averaging across phase-encoding directions (PEDs) to reduce the impact of EPI artifacts. Building on this principle, the proposed method further improves this 4-way encoding approach by leveraging the properties of signal distributions to detect artifactual regions. Additionally, the method can be tailored for specific artifact manifestations by considering their localization due to underlying acquisition parameters. The proposed method is applied to and validated using both simulated data and in-vivo diffusion MRI data affected by residual ghost artifacts. ResultsSimulations with known ground-truth images demonstrated high artifact detection accuracy, achieving a Dice score of 0.91 for reconstructions without parallel imaging. In the in-vivo dataset, the method also improved longitudinal reproducibility, reducing variability by 30% in ghost-affected regions. ConclusionThe proposed correction method effectively detected and corrected residual ghost artifacts without the need of any additional k-space data. This retrospective approach can be directly integrated into existing processing pipelines to further improve the quality of EPI images and enhancing image quality in studies that utilize 4-way PEDs acquisition.