Hybrid-space reconstruction with add-on distortion correction for simultaneous multi-slab diffusion MRI

TL;DR

This paper introduces a hybrid-space reconstruction algorithm for simultaneous multi-slab diffusion MRI that corrects phase errors and distortions, improving image quality and reducing g-factor penalties, especially when combined with blipped-CAIPI gradients.

Contribution

The study presents a novel model-based hybrid-space reconstruction method that simultaneously corrects phase errors and distortions in blipped-SMSlab diffusion MRI, enhancing image quality and reducing g-factor penalties.

Findings

Corrects phase interference caused by blipped-CAIPI gradients.

Reduces g-factor penalty by around 50% with joint reconstruction.

Achieves comparable correction performance without blipped-CAIPI gradients.

Abstract

Purpose: This study aims to propose a model-based reconstruction algorithm for simultaneous multi-slab diffusion MRI acquired with blipped-CAIPI gradients (blipped-SMSlab), which can also incorporate distortion correction. Methods: We formulate blipped-SMSlab in a 4D k-space with kz gradients for the intra-slab slice encoding and km (blipped-CAIPI) gradients for the inter-slab encoding. Because kz and km gradients share the same physical axis, the blipped-CAIPI gradients introduce phase interference in the z-km domain while motion induces phase variations in the kz-m domain. Thus, our previous k-space-based reconstruction would need multiple steps to transform data back and forth between k-space and image space for phase correction. Here we propose a model-based hybrid-space reconstruction algorithm to correct the phase errors simultaneously. Moreover, the proposed algorithm is combined with distortion correction, and jointly reconstructs data acquired with the blip-up/down acquisition to reduce the g-factor penalty. Results: The blipped-CAIPI-induced phase interference is corrected by the hybrid-space reconstruction. Blipped-CAIPI can reduce the g-factor penalty compared to the non-blipped acquisition in the basic reconstruction. Additionally, the joint reconstruction simultaneously corrects the image distortions and improves the 1/g-factors by around 50%. Furthermore, through the joint reconstruction, SMSlab acquisitions without the blipped-CAIPI gradients also show comparable correction performance with blipped-SMSlab. Conclusion: The proposed model-based hybrid-space reconstruction can reconstruct blipped-SMSlab diffusion MRI successfully. Its extension to a joint reconstruction of the blip-up/down acquisition can correct EPI distortions and further reduce the g-factor penalty compared with the separate reconstruction.