Prospective GIRF-based RF phase cycling to reduce eddy current-induced steady-state disruption in bSSFP imaging

Abstract

Purpose: To propose an explicit Balanced steady-state free precession (bSSFP) signal model that predicts eddy current-induced steady-state disruptions and to provide a prospective, practical, and general eddy current compensation method.

Theory and methods: Gradient impulse response functions (GIRF) were used to simulate trajectory-specific eddy current-induced phase errors at the end of a repetition block. These phase errors were included in bloch simulations to establish a bSSFP signal model to predict steady-state disruptions and their corresponding image artifacts. The signal model was embedded in the MR system and used to compensate the phase errors by prospectively modifying the phase cycling scheme of the RF pulse. The signal model and eddy current compensation method were validated in phantom and in vivo experiments. In addition, the signal model was used to analyze pre-existing eddy current mitigation methods, such as 2D tiny golden angle radial and 3D paired phase encoded Cartesian acquisitions.

Results: The signal model predicted eddy current-induced image artifacts, with the zeroth-order GIRF being the primary factor to predict the steady-state disruption. Prospective RF phase cycling schemes were automatically computed online and considerably reduced eddy current-induced image artifacts. The signal model provides a direct relationship for the smoothness of k-space trajectories, which explains the effectiveness of phase encode pairing and tiny golden angle trajectory.

Conclusions: The proposed signal model can accurately predict eddy current-induced steady-state disruptions for bSSFP imaging. The signal model can be used to derive the eddy current-induced phase errors required for trajectory-specific RF phase cycling schemes, which considerably reduce eddy current-induced image artifacts.

Keywords: GIRF; MRI; RF phase cycling; bSSFP; eddy current; non-Cartesian.