Rasim Boyacioglu1,2, Jenni Schulz1, and David G. Norris1,3
1Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands, 2Radiology, Case Western Reserve Univesity, Cleveland, OH, United States, 3Erwin L. Hahn Institute, University Duisberg-Essen, Essen, Germany
Synopsis
Multiband Echo-Shifted EPI (MESH) is a
combination of echo shifted 2D multi-slice EPI, in-plane and multiband
acceleration. An additional EPI readout is inserted in the dead-time between
slice selection and the multiband EPI readout. It is useful especially for low
static magnetic field strengths (long optimal TE) and lower spatial resolutions
(short EPI readout). It is shown that echo shifting gradients do not affect
tSNR. Compared to standard and multiband EPI similar RS fMRI results are
obtained at the group and individual subject level. MESH offers a further
acceleration in image acquisition for fMRI at no loss in sensitivity.Purpose
Multiband Echo-Shifted EPI (MESH) was presented;
combining the principles of echo shifted acquisition for 2D multi-slice EPI,
with both in-plane and multiband
acceleration by means of partial parallel imaging techniques
1. Here it is
compared to standard 2D EPI and multiband (MB) EPI in terms of temporal
stability (tSNR) and resting state (RS) fMRI.
Methods
Figure 1 illustrates the sequence diagram of MESH. The typical EPI sequence is
adapted by replacing the RF pulse with a standard MB pulse which is a
complex-sum of individually modulated RF pulses
2,3. Blipped CAIPI
4 was also incorporated
to shift the slices in the FOV along the phase-encoding direction. The
echo-shifting is achieved with the additional crushers and slice rephase gradients
along the slice direction
5 (see Figure 1).
Data were collected from 6 healthy subjects at a 1.5 T Avanto scanner (Siemens
Healthcare, Erlangen, Germany) with the product 32 channel head coil, after
previously obtaining informed consent. Three protocols with two different
effective TEs were compared in terms of tSNR (100 volumes): standard EPI,
MB-EPI (MB factor 3, blipped CAIPI FOV/2 shift, no echo-shift) and MESH (MB
factor 3, blipped CAIPI FOV/2 shift, Echo shift factors (ES) 1 and 2). To
achieve an unbiased comparison, the TR was kept constant and the total number
of slices was adjusted accordingly for each protocol. This way, the comparison
is independent of square root of TR corrections and effects arising from
different Ernst angles. The two echo shifting factors correspond to effective
TEs of 30 and 49 ms. In the case of fMRI data the protocols with 49 ms TE were
adjusted for whole brain RS acquisition (36 slices, 7 min, eyes open) with
corresponding TRs and Ernst angles: EPI TR = 2030 ms & FA = 74°, MB-EPI TR
= 688 ms & FA = 49° and MESH TR = 232 ms & FA = 30°. All protocols have
3 mm isotropic resolution, in plane acceleration factor of 3 and BW of 2480
Hz/Px. Reconstructions in the phase and slice directions were done in MATLAB
with GRAPPA
6 and Leak-Block
Slice-GRAPPA
7 algorithms,
respectively. MELODIC (FSL, http://www.fmrib.ox.ac.uk/fsl/) was used to perform
ICA on the group level RS data with 30 components and the following standard
preprocessing steps: spatial smoothing (5 mm kernel), drift removal, MCFLIRT
motion correction and registration to T1 weighted anatomical images. After dual
regression analysis
8 with the most
common 8 RSNs (http://www.fmrib.ox.ac.uk/analysis/royalsoc8/) and mixture
modeling to correct for inflated z-scores of low TR protocols DICE scores were
calculated for all subjects and networks.
Results & Discussion
Figure 2 shows the
reconstructed images and the corresponding tSNR maps for two representative subjects. Multiband lowers tSNR
9 when compared to standard EPI (rows 1&2)
, however the additional
crusher gradients used for the echo shifting do not affect tSNR (rows 2&3). Standard group level RSNs such as visual,
motor, default mode and (fronto-)parietal obtained with the three protocols are shown
in Figure 3. Similarity of RSN maps between the protocols indicates that
functional results do not suffer from the reduced tSNR of MB and MESH. Dual
regression results of DMN in Figure 4 provide the individual subject level results
which are linked to the same standard space maps and thus still comparable between
methods. Qualitatively it can be seen that the maps are spatially similar but
with the increased average z-scores for MESH. On the other hand, DICE scores in Figure 5
quantitatively show the match between the subject level and the standard
results. The scores correspond with the typically reported values in the
literature
10.
Conclusion
MESH
is suitable for fMRI in situations where there is sufficient time to insert an
additional EPI readout in the dead-time between slice selection and the multiband
EPI readout. In which situation it can further accelerate data acquisition
compared to standard multiband techniques. The method is particularly well
suited to low static magnetic field strengths (where the optimal TE is long)
and lower spatial resolutions (where the EPI readout is short). MESH provides
homogeneous spatial resolution and PSF. In conclusion, MESH offers a further
acceleration in image acquisition for fMRI at no loss in sensitivity.
Acknowledgements
No acknowledgement found.References
1. Norris DG, Schulz
J, Boyacioglu R. Multiband Echo-Shifted (MESH) EPI for Improved Acquisition
Efficiency of T2* Weighted EPI. ISMRM Proc. 2014:2988.
2. Larkman DJ, Hajnal J V, Herlihy a H, Coutts G a, Young IR, Ehnholm G. Use of
multicoil arrays for separation of signal from multiple slices simultaneously
excited. J Magn Reson Imaging 2001;13:313–317.
3. Moeller S, Yacoub E, Olman C a, Auerbach
E, Strupp J, Harel N, Ugurbil K. Multiband multislice GE-EPI at 7 tesla, with
16-fold acceleration using partial parallel imaging with application to high
spatial and temporal whole-brain fMRI. Magn Reson Med 2010;63:1144–1153.
4. Setsompop K, Gagoski BA, Polimeni JR,
Witzel T, Wedeen VJ, Wald LL. Blipped-controlled aliasing in parallel imaging
for simultaneous multislice echo planer imaging with reduced g-factor penalty.
Magn Reson Med 2012;67:1210–1224.
5. Gibson A, Peters AM, Bowtell R.
Echo-shifted multislice EPI for high-speed fMRI. Magn Reson Imaging 2006;24:433–42.
6. Griswold MA, Jakob PM, Heidemann RM,
Nittka M, Jellus V, Wang J, Kiefer B, Haase A. Generalized autocalibrating
partially parallel acquisitions (GRAPPA). Magn Reson Med 2002;47:1202–1210.
7. Cauley SF, Polimeni JR, Bhat H, Wald LL,
Setsompop K. Interslice leakage artifact reduction technique for simultaneous
multislice acquisitions. Magn Reson Med 2014;72:93–102.
8. Beckmann CF, Mackay CE, Filippini N,
Smith SM. Group comparison of resting-state FMRI data using multi-subject ICA
and dual regression. Neuroimage 47 (Supplement 1) 2009:OHBM, 39–41.
9. Chen L, Vu A, Xu J, Moeller S, Ugurbil
K, Yacoub E, Feinberg D. Evaluation of Highly Accelerated Simultaneous
Multi-Slice EPI for FMRI. Neuroimage 2015;104:452–459.
10. Boyacioglu R, Beckmann CF, Barth M. An
Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse
Imaging. Front. Hum. Neurosci. 2013;7:156.