Accelerate Single-shot Data Acquisitions Using Compressed Sensing and FRONSAC Imaging

TL;DR

This paper combines FRONSAC nonlinear MRI encoding with compressed sensing to improve image reconstruction quality in highly undersampled MRI scans, especially at high acceleration factors.

Contribution

It introduces a novel combination of FRONSAC encoding with compressed sensing, enhancing image quality in accelerated MRI beyond previous methods.

Findings

FRONSAC encoding produces incoherent undersampling artifacts.

Combining FRONSAC with CS further improves image reconstruction.

Simulation results show enhanced image quality at low FRONSAC amplitudes.

Abstract

Nonlinear spatial encoding magnetic (SEM) fields have been studied to complement multichannel RF encoding and accelerate MRI scans. Published schemes include PatLoc, O-Space, Null Space, 4D-RIO, and others, but the large variety of possible approaches to exploiting nonlinear SEMs remains mostly unexplored. Before, we have presented a new approach, Fast ROtary Nonlinear Spatial ACquisition (FRONSAC) imaging, where the nonlinear fields provide a small rotating perturbation to standard linear trajectories. While FRONSAC encoding greatly improves image quality, at the highest accelerations or weakest FRONSAC fields, some undersampling artifacts remain. However, the under-sampling artifacts that occur with FRONSAC encoding are relatively incoherent and well suited to the compressed sensing (CS) reconstruction. CS provides a sparsity-promoting convex strategy to reconstruct images from highly undersampled datasets. The work presented here combines the benefits of FRONSAC and CS. Simulations illustrate that this combination can further improve image reconstruction with FRONSAC gradients of low amplitudes and frequencies.