Application of k-space energy spectrum analysis for inherent and dynamic B0 mapping and deblurring in spiral imaging

Correcting image blur in spiral, retraced in/out (RIO) acquisitions using a maximized energy objective

PURPOSE

Images acquired with spiral k-space trajectories can suffer from off-resonance image blur. Previous work showed that averaging 2 images acquired with a retraced, in/out (RIO) trajectory self-corrects image blur so long as off-resonant spins accrue less than 1 half-cycle of relative phase over the readout. Practical scenarios frequently exceed this threshold. Here, we derive and characterize a more-robust off-resonance image blur correction method for RIO acquisitions.

METHODS

Phantom and human volunteer data were acquired using a RIO trajectory with readout durations ranging from 4 to 60 ms. The resulting images were deblurred using 3 candidate methods: conventional linear correction of the component images; semiautomatic deblurring of the component images using an established minimized phase objective function; and semiautomatic deblurring of the average of the component images using a maximized energy objective function, derived below. Deblurring errors were estimated relative to images acquired with 4 ms readouts.

RESULTS

All 3 methods converged to similar solutions in cases where less than 2 and 4 cycles of phase accrued over the readout in in vivo and phantom images, respectively (<13 ms readout at 3T). Above this threshold, the linear and minimized phase methods introduced several errors. The maximized energy function provided accurate deblurring so long as less than 6 and 10 cycles of phase accrued over the readout in in vivo and phantom images, respectively (<34 ms readout at 3T).

CONCLUSION

The maximized energy objective function can accurately deblur RIO acquisitions over a wide spectrum of off resonance frequencies.

B0 mapping using rewinding trajectories (BMART)

PURPOSE

To create a B₀ map and correct for off-resonance with minimal scan time increase for two-dimensional (2D) or 3D non-Cartesian acquisitions.

METHODS

Rewinding trajectories that bring the zeroth gradient moment to zero every repetition time (TR) were used to estimate the off-resonance with a center-out 3D cones trajectory, which required an increase in the minimum TR by 5%. The off-resonance estimation and correction was implemented using an algorithm based on binning and object-domain phase correction. B₀ maps using BMART (B₀ mapping using rewinding trajectories) were compared to maps obtained using separate scans with multiple echo time (TE) in a phantom and human brain.

RESULTS

Excellent agreement between BMART and the multiple-TE method were observed, and images corrected with BMART were deblurred.

CONCLUSION

BMART can correct for off-resonance without requiring an additional scan, and can be easily applied to center-out or projection trajectories (2D or 3D). Magn Reson Med 78:664-669, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

EPI Nyquist ghost and geometric distortion correction by two-frame phase labeling

PURPOSE

To develop a new Nyquist ghost and geometric distortion correction method in echo planar imaging (EPI) using parallel imaging.

METHODS

Two frames of EPI data are acquired with normal and phase-labeled sequence. The phase label is applied by modifying the PE prephase gradient to shift the central echo by one echo spacing. GRAPPA weights are trained from both frames and used to reconstruct images from positive or negative echoes in each frame to remove Nyquist ghost. Geometric distortion is then corrected by the B₀ field map generated from the phase difference between positive and negative echo images. Phantom and in vivo experiments at 7 Tesla (T) and 3T were performed to evaluate the proposed method.

RESULTS

Nyquist ghost was greatly reduced in all images even under oblique imaging and poor eddy current conditions, yielding significant improvements over the existing reference scan and image entropy minimization based methods. Image geometries were fully restored after distortion correction. Phantom results indicated that the signal-to-noise ratio efficiency was largely preserved while fMRI results showed no apparent degradation of temporal resolution.

CONCLUSION

The proposed method provides robust correction of both Nyquist ghost and geometric distortion in EPI, and it is particularly suitable for dynamic EPI applications. Magn Reson Med 77:1749-1761, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging

In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T₂^∗-weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications.

Automatic off-resonance correction in spiral imaging with piecewise linear autofocus

Off-resonance generates blurring artifacts in spiral images. Applications that often utilize spiral trajectories, such as fine-resolution imaging and rapid scanning, typically preclude the measurement of accurate field maps needed for effective off-resonance correction. Automatic deblurring, or autofocus, algorithms have been developed to estimate the field map directly from the corrupted data prior to off-resonance correction, eliminating the need for field map measurements. These algorithms rely in whole or in part on optimizing an objective function, and suffer from problems related to the accurate minimization and utility of the function. Here, a new method is presented to correct off-resonance blurring automatically without an objective function using a piecewise linear framework. Local linear field maps are estimated with a combination of k-space spectral analysis and mapdrift, an image feature-based correlation technique, for subsequent piecewise linear deblurring. This approach enables field map estimation without optimization, provides accurate off-resonance correction, is suitable for low signal-to-noise ratio and fine-resolution applications, and does not require access to the raw data. Deblurred images from fine-resolution spiral scans of a phantom and healthy volunteers at 3T show that the proposed method can be superior to conventional autofocus and comparable to field map-based correction.