Overlap-Kernel EPI: Estimating MRI Shot-to-Shot Phase Variations by Shifted-Kernel Extraction From Overlap Regions at...

In multi-shot EPI, shot-dependent phase fluctuations can introduce ghost artifacts, undermining advantages for enhancing resolution or reducing distortion, particularly in diffusion scans. Here, a novel self-navigation strategy based on shift-invariant kernel extraction is proposed, enabling robust estimation of phase inconsistencies from overlap bands at any k-space locations. It is inspired by RF sensitivity auto-calibration in parallel imaging, and extends traditional self-navigation trajectories beyond oversampled k-space center.

Our shot-to-shot correction method only requires shot-to-shot sampling trajectories to slightly overlap at arbitrary k-space locations. Such k-space overlaps can be defined as shot-dependent auto-calibrating-signal regions, where a GRAPPA/ESPIRiT-type operation can be applied to explicitly extract shot-to-shot signal variation maps in one step. This inherits GRAPPA/ESPIRiT's robustness, and offers much greater flexibility in designing self-navigated multi-shot sequences.

Our kernel extraction techniques in four self-navigated 2D SE-EPI and GE-EPI sequences are successfully demonstrated, as well as minor applications in extracting maps from navigator data and B₀ maps. Given sufficient SNR, self-navigation EPI can reach identical/better reconstruction quality compared to navigator corrections, applicable to various trajectories. Additionally, it is particularly suitable for the two-shot and four-shot mosaic EPI, where stronger shot-dependent eddy currents can also be removed, and the self-navigated ACS has higher SNR than the refocused navigator echoes.

This paper rigorously analyzes subspace algorithms for phase-stabilized multi-shot MRI, significantly broadens the self-navigation concept, and provides a more complete picture of the connections between signal fluctuations calibration in EPI and RF sensitivity calibration in parallel imaging.