Ultrafast multi-slice spatiotemporally encoded MRI with slice-selective dimension segmented

Arterial spin labeling using spatio-temporal encoding readout for robust perfusion imaging in inhomogenous magnetic fields

PURPOSE

To evaluate the feasibility of spatio-temporal encoding (SPEN) readout for pseudo-continuous ASL (pCASL) in brain, and its robustness to susceptibility artifacts as introduced by aneurysm clips.

METHODS

A 2D self-refocused T₂ *-compensated hybrid SPEN scheme, with super-resolution reconstruction was implemented on a 1.5T Philips system. Q (=BW_chirp *T_chirp ) was varied and, the aneurysm clip-induced artifact was evaluated in phantom (label-images) as well as in vivo (perfusion-weighted signal (PWS)-maps and temporal SNR (tSNR)). In vivo results were compared to gradient-echo EPI (GE-EPI) and spin-echo EPI (SE-EPI). The dependence of tSNR on TR was evaluated separately for SPEN and SE-EPI. SPEN with Q ˜ 75 encodes with the same off-resonance robustness as EPI.

RESULTS

The clip-induced artifact with SPEN decreased with increase in Q, and was smaller compared to SE-EPI and GE-EPI in vivo. tSNR decreased with Q and the tSNR of GE-EPI and SE-EPI corresponded to SPEN with a Q-value of approximately ˜85 and ˜108, respectively. In addition, SPEN perfusion images showed a higher tSNR (p < 0.05) for TR = 4000 ms compared to TR = 2100 ms, while SE-EPI did not. tSNR remained relatively stable when the time between SPEN-excitation and start of the next labeling-module was more than ˜1000 ms.

CONCLUSION

Feasibility of combining SPEN with pCASL imaging was demonstrated, enabling cerebral perfusion measurements with a higher robustness to field inhomogeneity (Q > 75) compared to SE-EPI and GE-EPI. However, the SPEN chirp-pulse saturates incoming blood, thereby reducing pCASL labeling efficiency of the next acquisition for short TRs. Future developments are needed to enable 3D scanning.

Super-resolved water/fat image reconstruction based on single-shot spatiotemporally encoded MRI

Single-shot spatiotemporally encoded (SPEN) MRI has been validated to possess considerable performance in both spatial and temporal resolution. Water/fat separation is essential for MRI applications in which only water signal is needed. In this article, a super-resolved water/fat image reconstruction method (dubbed SWAF) combined prior knowledge was developed based on single-shot SPEN MRI. The point spread function of spatiotemporal encoding under multiple chemical shifts situation was derived and used for constructing an equation for SWAF image reconstruction. By processing the prior chemical shift information with filtering operation, an initial spin density profile of water/fat and a weighting matrix for water/fat residual artifacts suppression were obtained to guide the reconstruction process. A l₁ norm minimization problem with regularization was exploited to reconstruct separated water/fat images with high spatial resolution and less residual/aliasing artifacts. Numeric simulation and experiments on water-oil phantom and rat abdomen/neck imaging demonstrated the effectiveness and robustness of this new method. The SWAF method proposed herein would promote the application of SPEN MRI in the cases where water/fat separation is required.

Ultrafast multi-slice chemical exchange saturation transfer imaging scheme based on segmented spatiotemporal encoding

Chemical exchange saturation transfer (CEST) imaging is an important magnetic resonance molecular imaging technology. However, long acquisition time limits its clinical application, especially when multi-slice CEST imaging is needed. Though single-shot EPI can be used to accelerate CEST imaging, images are often distorted under inhomogeneous magnetic fields. In this work, we propose a new method called CEST-SeSPEN for ultrafast multi-slice CEST imaging based on segmented spatiotemporally encoded (SeSPEN) MRI. Experiments were performed on creatine phantom and hen egg. The results show that CEST-SeSPEN can provide good CEST contrast images. Its acquisition time is much shorter than other multi-slice CEST methods currently available. It may be used in challenging situation where high temporal resolution and robustness to field inhomogeneity are vital.

Accelerating multi-slice spatiotemporally encoded MRI with simultaneous echo refocusing

Single-shot spatiotemporally encoded (SPEN) ultrafast magnetic resonance imaging (MRI) is of great value to both scientific research and clinical application owing to its capability for delivering MR images with greater robustness to magnetic field inhomogeneity and chemical-shift displacement effects than conventional methods like EPI due to high effective phase-encoded bandwidth. Many SPEN MRI methods have been developed, among which multi-slice SPEN MRI arises as a promising supplement to ultrafast multi-slice sampling. In this work, we propose a new multi-slice SPEN MRI method, termed multi-echo segmented SPEN (ME-SeSPEN) method, which produces multiple images within a single train of echoes and successively samples widely separated slices. The resulting images were reconstructed using de-convolution super-resolved algorithm. The robustness and efficiency of the proposed method were demonstrated by phantom, lemon and in vivo experiments in comparison with spin-echo EPI, spin-echo simultaneous echo refocusing (SER), and segmented SPEN (SeSPEN) MRI. The results indicate that the new method effectively shortens the sampling time (20% reduction practically in comparison with SeSPEN when two slices are simultaneously sampled). ME-SeSPEN also reduces eddy current effects while maintaining the benefits of SPEN MRI, such as similar robustness to field inhomogeneity, spatial resolution and signal-to-noise ratio to SeSPEN MRI. The new method will promote the versatility of multi-slice MRI in practical applications.

Variable density sampling and non-Cartesian super-resolved reconstruction for spatiotemporally encoded single-shot MRI

Spatiotemporally encoded (SPEN) single-shot MRI is an emerging ultrafast technique, which is capable of spatially selective acquisition and reduced field-of-view imaging. Compared to uniform sampling, variable density sampling has great potential in reducing aliasing artifacts and improving sampling efficiency. In this study, variable density spiral trajectory and non-Cartesian super-resolved (SR) reconstruction method are developed for SPEN MRI. The gradient waveforms design of spiral trajectory is mathematically described as an optimization problem subjected to the limitations of hardware. Non-Cartesian SR reconstruction with specific gridding method is developed to retrieve a resolution enhanced image from raw SPEN data. The robustness and efficiency of the proposed methods are demonstrated by numerical simulation and various experiments. The results indicate that variable density SPEN MRI can provide better spatial resolution and fewer aliasing artifacts compared to Cartesian counterpart. The proposed methods will facilitate the development of variable density SPEN MRI.