Synopsis
This lecture reviews state-of-the-art 2D and 3D sequences with a
focus on gradient echo EPI acceleration with controlled aliasing (CAIPIRINHA).
The audience should learn which rapid EPI-based
methods for BOLD fMRI are available and what to consider to minimize noise or artifacts due
to strong parallel imaging, if needed, for the respective study goal.
BOLD and echo planar imaging
Due to its
high sensitivity, the blood oxygen level-dependent contrast1 is the
basis for most functional MRI (fMRI) studies. Although lacking spatial
specificity (large draining veins), T2*-weighted echo planar imaging
(EPI2) is most often used for fMRI. To maximize BOLD contrast-to-noise
ratio, the echo time is usually selected in the order of 30-35/21-26ms (at 3T/7T,
respectively). Even without parallel imaging, the whole brain can be imaged at
a volume TR of 1-3s at typical spatial resolutions of 2-3mm isotropic. This is
sufficient to sample the slow BOLD signal change, according to the average hemodynamic
response function.
Parallel
imaging along the phase encode (PE) direction (R1>1) can be
applied to increase the PE bandwidth by a factor of R1, and thus
reduce susceptibility-induced artifacts (signal drop outs, geometric
distortions, T2* blur, etc.). This is because the PE bandwidth is inversely
proportional to the effective echo spacing (ESP), which is given by the actual ESP
divided by the PE blip [measured in PE lines]. Large R1 can also be
used to achieve higher spatial resolutions without increasing the EPI factor
(the number of echoes in the EPI train = PE matrix size/PE blip). However, if
spatial resolution is increased a lot, volume TRs can get very long.Simultaneous multi-slice (SMS) and 3D-EPI
Simultaneous
multi-slice (SMS) acquisition3 can be employed to significantly
speed up the imaging by acceleration. In slice-selective EPI, a stack of MB=R2>1
slices (MB: multiband factor) has to be excited simultaneously. The acquired
signal is later disentangled using multiband parallel imaging principles4.
Alternatively, 3D-EPI can be employed and reconstructed using conventional
volumetric parallel imaging5,6. Apart from the excitation and second
phase encoding, 3D-EPI and SMS-EPI are very similar sequence-wise. In terms of
(parallel imaging) reconstruction, the equivalence between SMS- and 3D-EPI has
been shown as well7-9.CAIPIRINHA, g-factor, temporal SNR and tSNR efficiency
Regardless
of SMS- or 3D-EPI, care should be taken to condition the parallel imaging
reconstruction as well as possible. Apart from optimal autocalibration
acquisition (FLEET10, FLASH11, dual-polarity GRAPPA12,
…), the undersampling pattern is very important. CAIPIRINHA sampling13,14,4
should be used to control the aliasing optimally and thus to avoid excessive
noise increase. The latter is commonly expressed by the g-factor, g≥1, which
depends on the number and the distribution of the receive-array coils and the (CAIPIRINHA)
undersampling pattern. The g-factor can be found in the in the relation5
SNR = SNR0/(g
√R)
where R=R1R2
is the total parallel imaging undersampling factor and SNR0 is the
(hypothetical) image SNR without parallel imaging and without physiological
noise15. Note that, applying the respective Ernst angles, SNR0
is larger for 3D-EPI than for a corresponding 2D-EPI protocol16, and
that SNR0 of SMS-EPI is somewhere in between17. On the other hand, more physiological noise adds to 3D-EPI than for
SMS-EPI, when thermal noise does not dominate18,19 (e.g. large voxels).
In practical
terms, the combined effect of g, R and physiology – which is ultimately relevant
for fMRI – can and should be compared in vivo by computing temporal SNR maps
(voxel-wise mean/standard deviation along the time dimension) using the
sequence and parameters under consideration. If one wants to compare between
different temporal resolutions, it makes sense to convert tSNR maps into tSNR
efficiency maps (tSNR per unit scan time), for instance: tSNR/√TRvol.Blipped-CAIPI, shot-selective CAIPI and beyond
CAIPIRINHA
sampling and EPI were first efficiently combined in SMS-EPI by adding
alternating blips along the slice direction to the usual PE blips4. The
same blipped-CAIPI sampling was applied later to 3D-EPI20. In
SMS-k-space (or 2D PE k-space), the combined effect of blips is to follow a
certain trajectory between samples of a selected 2D-CAIPIRINHA (short: CAIPI)
pattern, according to14 expressed as R1xR2(D).
D denotes the CAIPI shift along the second PE or slice direction (which
corresponds to a certain PE FOV shift in SMS-EPI). Like without slice
acceleration, the PE blip equals R1.
An
alternative shot-selective CAIPI EPI sampling was proposed for particularly
high-resolution imaging, where large PE blips are required to keep the PE
bandwidth high and EPI factor short21,22. Only those samples of the
same CAIPI pattern are acquired that don’t require slice blips. One can also understand
shot-selective CAIPI as interleaved multi-shot blipped-CAIPI with a
segmentation factor S>1 (cf. Fig 1 A/B). The PE blip, and thus the PE bandwidth,
is up to R2 times larger than with blipped-CAIPI, depending on the pattern.
The shot-selective approach has recently been adopted in SMS-EPI23.
Note that
the segmented blipped-CAIPI interpretation allows for further sampling
variations of EPI (more possible PE blips with identical CAIPI pattern) (cf. Fig. 1 C/D)24,25.Beyond parallel imaging
Since
parallel imaging is limited by receive-coil design, it can make sense to
consider alternative means to speed up imaging, and in turn consider reducing
the total undersampling factor. A few suggestions:
- Partial Fourier (PF) sampling is
often applied along PE to maintain TE short despite a large EPI factor. If the
latter is not a constrained, skipping late instead of early echoes may be a valuable
option for shortening TRvol with reduced impact on the PSF (skipping
only strongly decayed echoes).
-
In 3D-EPI, partial Fourier can also
be applied along the second PE direction16.
- Simultaneous PF along both PE
directions should be used with care, as some of the skipped k-space information
cannot be recovered.
- Generally, in T2*-weighted
EPI, PF should be used with care, as the image phase at long TEs is far from
homogeneous, and thus PF reconstruction is not as effective as in spin echo EPI
(diffusion MRI).
- Usually, fat-saturation is used for fat
suppression (~12ms per shot on Siemens systems). This prolongs TRvol
considerably (~20%). At ultra-high fields this can often be omitted, as T2*
of fat becomes very short26.
- With 3D-EPI, simple binomial water
excitation (slab- or non-selective) can often be used and fat saturation can be
omitted27.
- For 3D-EPI, semi-elliptical sampling
has been proposed, where only late echoes outside an elliptical k-space mask are
skipped with negligible consequences for the PSF28.
- It can make sense to acquire only
one phase correction scan (per time series or per volume) external of imaging
shots. Besides increased imaging efficiency, it also allows for shorter TE (or
larger EPI factors).
Beyond the
scope of this presentation, but something else to consider depending on the
research question, is the acquisition of multi-echo EPI data
29.
Apart from optimal post hoc combination of echo times as a function of location
(and hence off-resonance and effectively altered optimal TE)
30, the
added multi-echo information can also be used for differentiating BOLD and
non-BOLD signal
31.
DISCUSSION
Accelerated
EPI is the state-of-the-art in BOLD imaging. Given the different options (some
of which discussed above), it always makes sense to compare protocols in a study
pilot. All the more as there is no definite “better” or “worse” in general. Before
the piloting stage, one should consider, depending on the research question:
- What spatial coverage is required?
(whole-brain; reduced field-of-view or slab; single-slice)
- What temporal resolution is required?
(may be different for resting-state or task fMRI; has consequences for temporal
aliasing of physiological noise spectrum into the typical BOLD frequency range;
check temporal correlation)
- What spatial resolution is required?
(depends on structure of interest; check spatial specificity of BOLD)
- What the effect of physiological
noise removal and temporal filtering is
(motion, respiration, pulsation, derivatives, physiological noise model,
highpass or bandpass filtering, …)
- Whether the region-of-interest or
research question may benefit from multi-echo EPI
(signal drop-outs; physiology; task or resting-state; …)
CONCLUSION
State-of-the-art echo-planar BOLD acquisition benefits
largely from advanced parallel imaging techniques. Controlled aliasing
(CAIPIRINHA) should always be applied for both SMS-EPI and 3D-EPI. This specifically
includes a critical choice of the total undersampling factor (not too large) and
an optimal aliasing pattern (minimal g-factor). At the study piloting stage,
tSNR and tSNR efficiency should be criticially evaluated with and without physiological
noise removal.Acknowledgements
No acknowledgement found.References
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