Frequency‐modulated SSFP with radial sampling and subspace reconstruction: A time‐efficient alternative to phase‐cycled bSSFP

Abstract

Purpose A novel subspace‐based reconstruction method for frequency‐modulated balanced steady‐state free precession (fmSSFP) MRI is presented. In this work, suitable data acquisition schemes, subspace sizes, and efficiencies for banding removal are investigated. Theory and Methods By combining a fmSSFP MRI sequence with a 3D stack‐of‐stars trajectory, scan efficiency is maximized as spectral information is obtained without intermediate preparation phases. A memory‐efficient reconstruction routine is implemented by introducing the low‐frequency Fourier transform as a subspace which allows for the formulation of a convex reconstruction problem. The removal of banding artifacts is investigated by comparing the proposed acquisition and reconstruction technique to phase‐cycled bSSFP MRI. Aliasing properties of different undersampling schemes are analyzed and water/fat separation is demonstrated by reweighting the reconstructed subspace coefficients to generate virtual spectral responses in a post‐processing step. Results A simple root‐of‐sum‐of‐squares combination of the reconstructed subspace coefficients yields high‐SNR images with the characteristic bSSFP contrast but without banding artifacts. Compared to Golden‐Angle trajectories, turn‐based sampling schemes were superior in minimizing aliasing across reconstructed subspace coefficients. Water/fat separated images of the human knee were obtained by reweighting subspace coefficients. Conclusions The novel subspace‐based fmSSFP MRI technique emerges as a time‐efficient alternative to phase‐cycled bSFFP. The method does not need intermediate preparation phases, offers high SNR and avoids banding artifacts. Reweighting of the reconstructed subspace coefficients allows for generating virtual spectral responses with applications to water/fat separation.

Physics-based reconstruction methods for magnetic resonance imaging

“…In contrast to nonlinear models, in linear subspace methods the signal curves t → M(x, t, r) are approximated using a linear combination of basis functions [44][45][46][47][48][49][50][51][52], i.e.…”

“…Foxall and co-workers demonstrated that bSSFP sequences are tolerant to small but continuous changes in transmitter frequency [53]. In [49], we exploited this method to develop a time-efficient alternative to phase-cycled bSSFP that waives Reconstructed four complex coefficient maps (only magnitude is shown) using the linear subspace method for a human brain study. (b) Synthesized images (at inversion time 40 ms, 400 ms, 800 ms, 4000 ms) using (top) the above four complex coefficient maps of the linear subspace method and (bottom) the three physical maps of the nonlinear model-based reconstruction, respectively.…”

“…Foxall and co-workers demonstrated that bSSFP sequences are tolerant to small but continuous changes in transmitter frequency [ 53 ]. In [ 49 ], we exploited this method to develop a time-efficient alternative to phase-cycled bSSFP that waives intermediate preparation phases in phase-cycled bSSFP to establish different steady-states. Image reconstruction is performed in the low-frequency Fourier subspace and yields signal intensity and contrast comparable to on-resonant bSSFP.…”

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

“…• Condition for vertically-oriented ellipse: b < 2a 1+a 2 (7) Note that the ellipse for the measured bSSFP signals in Eq. ( 3) is a scaled and rotated version of the ellipse of the base signals in Eq.…”

“…A main difference is the sensitivity of the bSSFP signal to main field inhomogeneities, which causes banding artifacts near regions of large off-resonance shifts [2]. While a number of approaches were proposed to mitigate artifacts [3]- [7], arguably the most common method is phasecycled bSSFP imaging [8]. Multiple acquisitions of the same anatomy are first collected for a range of different RF phasecycling increments.…”