Gilad Liberman1, Samuel F Cousin1, Eddy Solomon1, and Lucio Frydman1
1Chemical Physics, Weizmann Institute of Science, Rehovot, Israel
Synopsis
Spatiotemporal Encoding (SPEN) is an ultrafast imaging
technique where the low-bandwidth axis is rasterized in a joint spatial/k-domain.
SPEN benefits from increased robustness to inhomogeneities, folding-free
reconstruction of subsampled data, and an ability to combine multiple
interleaved or signal averaging scans in a referenceless fashion. SPEN’s
relatively high SAR, however, complicates its volumetric uses. Here we show how
this can be solved by merging a controlled aliasing for parallel imaging (CAIPIRINHA)
protocol involving phase-cycling of multi-banded excitation pulses in
independent scans, so as to enable a referenceless reconstruction of interleaved
multislice acquisitions delivering high in-plane definition and excellent inter-slice
decoupling.
INTRODUCTION
Controlled aliasing for parallel imaging (CAIPI,
CAIPIRINHA)1,2, enables
simultaneous multislice (SMS) excitation while reducing the noise amplification
resulting from similar coil sensitivity maps for different slices. This requires
specific slice-selective manipulations, which in combination with multi-coil
multiplexing decreases the coupling among the images. CAIPI’s blipping of the
slice-select (SS) gradient during the acquisition is particularly useful in
« ultrafast » experiments, aimed at covering large volumes using echo-planar
imaging (EPI)3.
SPatiotemporal ENcoding (SPEN) is an alternative ultrafast technique that
relies on a frequency-swept chirp pulses acting in combination with gradients
to spatially rasterize spins in a sample4. SPEN
provides images that are folding-free even if subsampled5;
it can successfully average and interleave multiple scans even in diffusion or
functional experiments, and it benefits from reduced distortions due to its use
of stronger gradients than EPI4. SPEN suffers,
however, from SAR values that are higher than EPI’s in proportion to the ratio
between the sequences’ PE-axis bandwidths. Here we demonstrate how to alleviate
these coverage complications, by invoking a CAIPIRINHA-like procedure whereby SMS
2D SPEN images are separated by coil- and phase-cycling multiscan procedures.
Further, these various scans are arranged so that each 2D SPEN image is
acquired in an interleaved fashion5. Suitable
processing therefore achieves both an in-plane resolution improvement and improved
multiband separation. Applications of this in human diffusion experiments are
presented.
METHODS
The pulse sequence for the interleaved SMS-SPEN experiment introduced
here is in Fig. 1A. The different scans use an interleaved approach meant to
improve resolution (Fig 1B)1. In
addition, different scans change each SMS band’s phase according to a CAIPIRINHA
phase-cycling scheme as shown in Fig. 1B for a two-band scenario. SPEN’s
reconstruction of these subsampled (but folding-free) data then proceeds by
suitable linear combinations, as shown in Fig. 1C. This leads to a robust
decoupling among the different bands2, and it
was preferred over its blipped CAIPI counterpart, owing to SPEN’s special
nature as a mixed spatial/k-space encoding technique. Indeed, the application
of CAIPI’s blips will phase-modulate the SMS bands in a conventional way, but
will only move them along SPEN (PE) dimension by a fraction of the
corresponding field-of-view given by the strength of SPEN’s encoding gradient. By
contrast, the phase-cycling approach cleanly separates the frequency bands. It
also exploits the fact that, unlike EPI, SPEN is compatible with multiscan
acquisitions even for diffusivity measurements. This, however, requires that
the multiscan
data be suitably
compatibilized among one another. To do so, the reconstruction approach shown
in Figure 2 was followed. It involves calculating the phase of each band independently
for every scan and diffusion weighting. These phase maps are then used in the
final reconstruction, where all the scans’ data are used, using a
super-resolution (SR) approach6 which
factors-in the per-scan phase maps, all the channels sensitivity maps, the scan
interleaving, and the CAIPIRINHA modulation.
The sequence in Figure 1A was programmed on a 3T
Siemens TrioTIM scanner equipped with a 32 channels head coil. SMS-SPEN was run
with an encoding bandwidth of 2.4 kHz, nPE= 96, Nshots=4,
CAIPIRINHA=2, encoding two bands positioned 3.3cm apart. 11 slices were thus
collected over a 19x21x6cm 3D volume, with a 1x1x3mm resolution in a TR=8sec
time. All human volunteers were scanned following suitable written consent.RESULTS & DISCUSSION
The suitability of the CAIPIRINHA-based processing for
removing multislice leakage can be appreciated from Figure 3. Shown on the bottom
part are experimental SPEN results arising from two bands excited as B1+B2
and B1-B2, reconstructed using only channel sensitivity
information. Given the 3cm separating
the bands, the separation is clearly imperfect and reflects the leakage arising
in an unaided multiband scheme. Shown on the upper part are the estimations arising
if the two scans B1±B2 are added/substracted.
By adding this CAIPIRINHIA approach to the multishot SPEN experiments, all slices
become well separated (Figure 4). Based on this success, the procedure was
applied to acquire whole-brain ADC and DWI data; taking in account the phase
induced by motion during b-weighted experiments (Figure 5). SPEN’s robustness
is visible in areas usually distorted in EPI, particularly in tissue-air
boundaries.CONCLUSION
A novel sequence and a reconstruction procedure for SMS-SPEN
experiments were described, whereby use of multiple scans are combined with
multiband phase cycling and interleaving, to achieve clear slice separations
with increased 3D coverage and good in-plane resolution –at negligible increase
in the SAR (which is dominated by the single π-sweep encoding all the slices)
or g-factor related SNR penalties. Despite its multiscan nature the method was successfully applied for diffusion experiments.Acknowledgements
We
are grateful to Dr. Sagit Shushan (Wolfson Medical Center) and Edna
Furman-Haran (Weizmann) for assistance in the scans. SfC thanks the Feinberg Graduate School
(Weizmann) and French Foreign Service for partial postdoctoral fellowships. Financial support came from the Israel
Science Foundation grant 2508/17, the EU through ERC-2016-PoC grant # 751106,
Minerva funding (#712277) from the Federal German Ministry for Education and
Research, the Kimmel Institute for Magnetic Resonance and the generosity of the
Perlman Family Foundation.References
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