Ek T Tan1, Jonathan I Sperl2, Miguel Molina Romero2,3, Seung-Kyun Lee1, Matt A Bernstein4, and Thomas KF Foo1
1GE Global Research, Niskayuna, NY, United States, 2GE Global Research, Munich, Germany, 3Technical University of Munich, Munich, Germany, 4Mayo Clinic, Rochester, MN, United States
Synopsis
A high-performance head-only gradient
coil (Gmax=80 mT/m, SR=700 T/m/s) allows diffusion imaging at substantially shorter
echo-time and echo-spacing than conventional whole-body gradient coil systems.
This greatly benefits microstructure imaging with diffusion EPI, providing
reduced echo spacing by up-to two-fold and shorter TE by up-to 30%. Imaging
results demonstrate reduced distortion and improved white matter SNR.
Preliminary results on axonal radius mapping with high b-value imaging (up-to
b=12,000 s/mm2) demonstrate the feasibility of 2 mm-isotropic imaging with the
head-gradient.Purpose
As compared to
conventional whole-body MRI, a dedicated head-only MRI gradient system
1,2 can provide simultaneously high gradient amplitude (G
max=80 mT/m) and high slew rate (SR=700 T/m/s) without
limitations of whole-body peripheral nerve stimulation
3-4. While high Gmax is beneficial for reducing echo times (TE) in
diffusion imaging, the high SR allows EPI readout echo-spacing (ESP) to be
halved, which provides the dual benefit of reduced EPI distortion and further
reduction of TE due to shortened echo-train-length. These benefits are critical
to diffusion microstructure imaging, which as compared to conventional DWI/DTI
pulse sequences, require higher b-values and longer diffusion intervals (Δ) that lengthen TE
and reduce SNR. It is therefore of interest to explore the benefits to
diffusion microstructure imaging from this high-performance MRI system.
Methods
Two normal subjects (under an IRB-approved
protocol) underwent diffusion imaging using the dedicated head-only gradient coil
at 3T, and again using conventional 3T MRI (GE MR750), using the same
32-channel brain coil (Nova Medical, Wilmington MA). Single spin-echo diffusion
preparation with the minimum possible TE was utilized for axial brain imaging
at b-values of 1000, 3000, and 8000 s/mm2.
An AxCaliber5
sampling scheme was also acquired using only the head-only system with 4 diffusion
intervals of Δ={24, 32, 39, 51} ms and 8
evenly-spaced diffusion-encoding gradient amplitudes of G=10-80 mT/m in the
superior-inferior direction (FOV=21 cm, 2 mm-isotropic sampling, partial-ky=0.75,
2 signal averages, TR/TE=3000/85 ms, gradient pulse width δ=9.5 ms). No
parallel imaging and EPI-distortion correction were applied. To provide
orientation information, DTI sampling scheme was also acquired with b-values of
{1,000, 2,000, 12,000} s/mm2 keeping
constant Δ=51 ms,
TE=85 ms (30 gradient directions).
Multi-compartment-model fitting was performed
in the corpus callosum assuming two compartments (cylinder-zeppelin6) to obtain axonal radius, axonal
fraction (restricted), and orthogonal diffusivity. The parallel diffusivity of
the zeppelin compartment (hindered/extra-axonal) and the diffusivity of the cylinder
compartment (restricted/intra-axonal) were fixed to the parallel diffusivity as
obtained by a DTI fit. A least-squares fitting (formulation) was used,
initialized using a grid-search (grid size of 10) and optimization via the
interior-point algorithm. Fitting was performed with both the AxCaliber and DTI
data. To evaluate the effect of data at high b-value, fitting was performed by
incrementally adding DTI data at b-values of {1,000, 2,000, 12,000} s/mm2.
Results
The head-only system allowed the use of
higher EPI readout gradient amplitude of 45 mT/m compared to 24 mT/m of the
conventional whole-body system, effectively halving ESP (Table 1). As SNR would be reduced due to increased EPI
readout amplitude, a slightly increased EPI readout gradient amplitude was used
(29 mT/m) resulting in a reduction in ESP by a third. Both head-only images had
visibly reduced susceptibility effects (Figure 1). This reduction in ESP that
reduced echo-train-length accounted for approximately 6-9 ms reduction in TE
regardless of diffusion b-value. The net TE reduction was between 18 ms and 28 ms,
which resulted in visibly higher white-matter SNR between 9% and 29% (assuming
T2=80 ms). As a result of reduced TE, suppression of subcutaneous fat and tissue
was also reduced.
Imaging at the longer TE=85 ms provided adequate
SNR (Figure 2), even at b=12,000 s/mm2 where good white matter contrast was observed despite
Rician noise. The microstructure metrics in the corpus callosum were averaged
at five points along the corpus callosum in the anterior (genu) to posterior
(splenium) direction. The axonal radius was on average between 5-6 µm and was
not significantly different between the two subjects (Figure 3). The addition
of the b=12,000 s/mm2 reduced the variance of both axonal radius and
orthogonal diffusivity (Figure 4). There was a disparity of about 0.2 in the
axonal fraction of both subjects, which indicates that the parameters could be
better optimized and the model better conditioned. There was high residual fat
aliasing, which could improve with better fat suppresion7.
Discussion and Conclusion
In
our preliminary investigation of in-vivo microstructure imaging using the
head-only gradient coil in-vivo scanner, the diffusion scans provided adequate
image quality at 2 mm-isotropic spatial resolution. The scans were also well-tolerated
with no peripheral nerve stimulation reported. The axonal radii were
over-estimated, a result that was similar to that observed in other work
8 and that would improve with the
availability of better models and an even higher gradient amplitude for
diffusion-encoding. The reducd TE and ESP provided higher white matter SNR and
reduced EPI distortion without the use of parallel imaging and EPI-distortion
correction techniques.
Acknowledgements
This work was
supported in part by NIH R01EB010065. The views herein do not necessarily
represent those of NIH.References
1. Mathieu JB,
et al. ISMRM, 2015. 1019.
2. Huston J,
et al. ISMRM, 2015. 971.
3. Lee SK, et
al. Magn Reson Med (Accepted).
4. Lee SK, et
al. ISMRM, 2014. 310.
5. Assaf Y, et
al. Magn Reson Med, 2008. 59(6):1347-54.
6. Panagiotaki
E, et al. NeuroImage, 2012. 59(3):2241-54.
7. Middione M,
et al. ISMRM 2015. 958.
8. Zhang H, et
al. NeuroImage, 2011. 56:1301-15.