Steffen Bollmann1, Simon Robinson2, Kieran O'Brien1,3, Viktor Vegh 1, Andrew Janke1, Lars Marstaller4, David Reutens1, and Markus Barth1
1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 2High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria, 3Siemens Healthcare Pty Ltd, Brisbane, Australia, 4Cardiff University, School of Psychology, Cardiff, United Kingdom
Synopsis
One challenge in quantitative
susceptibility mapping (QSM) at ultra-high field (> 3 T) is the combination
of phase data from phased array receive coils. We assessed the performance of
COMPOSER (COMbining Phase data using a Short Echo-time Reference scan) with
separate reference scans and with an intrinsic reference scan, as well as a
reference-free single-channel method. Our results show that reference scans can
bias QSM results at ultra-high field. We conclude that ultra-short echo-time
reference scans reduce quantitation bias and remove the transmit field phase
when using COMPOSER to combine phase data at ultra-high field.
Purpose
Quantitative
susceptibility mapping (QSM) provides novel insights into tissue composition, iron accumulation and myelination1–3. Susceptibility effects scale with the static magnetic field and as such QSM
profits from the availability of ultra-high field scanners. However, one
challenge at ultra-high field is the channel combination of phase data from
phased array receive coils. It is possible to avoid the combination of signal
phase across channels as a first step by calculating QSMs for each channel
separately. These can then be combined using an arithmetic mean across channels.
However, this requires each channel to have adequate coverage of the object and
sufficient SNR to allow an estimation of the background field and the solution
of the QSM inverse problem. This method has been shown to yield susceptibility
maps without obvious artifacts4, but it has not yet been tested how this
method compares to a reference-based approach - COMbining Phase data using a
Short Echo-time Reference scan (COMPOSER) – which can approximate the true phase
offsets5.Methods
After approval by the local human ethics
committee and written informed consent, 28 participants (21-34 years of age, 14 males) were investigated on a 7T
whole-body research scanner (Siemens Healthcare, Erlangen, Germany) and a 32-channel
head coil (Nova Medical, Wilmington, USA). We acquired a multiple-echo gradient-recalled
echo (GRE) 3D whole-brain dataset: TR=25ms, TE=4.4,7.25,10.2,13.25,16.4,19.65,23ms,
flip angle=13 degree, FOV=210x181.5x120mm3, matrix=280x242x160, GRAPPA = 2,
TA=7.9min. For the reference scans both, a GRE with 3 echoes (TR=8ms, TE=1.02,3.06,6.12ms,
flip angle=5 degree, FOV=245x245x182mm3, matrix=70x70x52, GRAPPA = 1,
TA=24s), and a prototype ultra-short-TE sequence PETRA6, were acquired (TR=1.99ms, TE=0.07ms, flip
angle=2 degree, FOV=288x288x288mm3, matrix=288x288x288, GRAPPA=1, TA=2min).
Susceptibility maps were
calculated using total generalized variation (TGV)7. The single-channel approach processed each
coil channel individually and the final susceptibility maps were calculated by computing
the mean across all channels. For COMPOSER, the short-TE GRE sequence (2 echoes: 1.02,
3.06ms) and the ultra-short-TE PETRA sequence (1 echo: 0.07ms) were
both used to attempt to correct the phase offsets and combine the phase data.
An atlas-based
segmentation8 was used to extract susceptibility values of
all subjects from manually segmented regions of interest (Figure 1). Results & Discussion
Figure 2 shows
the susceptibility maps computed based on the combined phase data and the
single-channel approach in the top row, most of which appear strikingly
similar. Therefore, all pipelines were also compared by calculating absolute-difference
susceptibility maps shown in Figure 3. The
PETRA reference scan and the first echo of the low resolution GRE (lrGRE1) show
similar results except for Gibbs ringing artifacts when using the low
resolution reference scan, which is more clearly seen in cortical regions (blue
arrows) in Figure 3. This
is due to the fact that only a low spatial resolution is achievable with a
short echo-time. When the second echo of the low resolution GRE (lrGRE2) is
used as a reference scan, one can see that the first combined echo shows a very
low contrast (see Figure 2).
Further, these reference scans also show a difference in subcortical regions
like the red nucleus in this participant (red arrow, Figure 3). As
expected, the high resolution GRE reference scan introduces slightly more noise
in the susceptibility maps due to an SNR decrease, but does not suffer from the
Gibbs ringing artifacts in comparison to the low resolution reference scans.
However, it shows a different gray/white matter contrast, which implies a
reference scan phase evolution difference between these regions, which in this
case, increases the contrast. Finally, in Figure 3, the
comparison between the single-channel approach and the PETRA reference scan
shows that there is a structured difference pattern (green arrows), which was
not apparent in Figure 2.
Assessment of computed susceptibility values in specific brain regions for all
28 subjects as a function of echo time are shown in Figure 4. A
marked deviation between pipelines exists for early echoes and reduces at later
echo times. The relative difference between all COMPOSER combinations and the
single-channel method is shown in Figure 5.
Statistically significant differences (FWER p < 0.001, 16 tests, Bonferroni corrected
p < 0.0000625) between the single-channel method and the COMPOSER
combinations are marked with an asterisk.Conclusions
Our comparison of the various coil
combination approaches in the tested QSM pipeline implies that deficiencies in reference
scans can bias QSM results. An ultra-short echo time reference scan reduces
this bias, and the single-channel approach provides a robust method and similar
results. Acknowledgements
SB acknowledges funding from UQ
Postdoctoral Research Fellowship grant and support via an NVIDIA hardware grant. MB
acknowledges funding from ARC Future Fellowship grant FT140100865. The
authors acknowledge the facilities of the National Imaging Facility at the
Centre for Advanced Imaging, University of Queensland and the scientific support of Siemens Ltd, Bowen
Hills, Australia.References
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