Gap Cycling for SWIFT

TL;DR

This paper introduces 'gap cycling', a novel method to eliminate bulls-eye artifacts caused by inter-band crosstalk in SWIFT MRI, improving image quality through theoretical, simulated, and experimental validation.

Contribution

The paper presents a new gap cycling technique that effectively cancels inter-band crosstalk artifacts in SWIFT MRI, enhancing image clarity.

Findings

Gap cycling cancels bulls-eye artifacts in SWIFT images.

Theoretical analysis explains the mechanism of artifact removal.

Experimental results demonstrate artifact-free in-vivo images.

Abstract

Purpose: SWIFT (SWeep Imaging with Fourier Transformation) is a non- Cartesian MRI method with unique features and capabilities. In SWIFT, radiofrequency (RF) excitation and reception are performed nearly simultaneously, by rapidly switching between transmit and receive during a frequency-swept RF pulse. Because both the transmitted pulse and data acquisition are simultaneously amplitude-modulated in SWIFT (in contrast to continuous RF excitation and uninterrupted data acquisition in more familiar MRI sequences), crosstalk between different frequency bands occurs in the data. This crosstalk leads to a "bulls-eye" artifact in SWIFT images. We present a method to cancel this inter-band crosstalk by cycling the pulse and receive gap positions relative to the un-gapped pulse shape. We call this strategy "gap cycling." Methods: We carry out theoretical analysis, simulation and experiments to characterize the signal chain, resulting artifacts, and their elimination for SWIFT. Results: Theoretical analysis reveals the mechanism for gap-cycling's effectiveness in canceling inter-band crosstalk. We show phantom and in-vivo results demonstrating bulls-eye artifact free images. Conclusion: Gap cycling is an effective method to remove bulls-eye artifact resulting from inter-band crosstalk in SWIFT data.