Pavan Poojar1, Sairam Geethanath1,2, Ashok Kumar Reddy3, and Ramesh Venkatesan3
1Dayananda Sagar Institution, Bangalore, India, 2Columbia Magnetic Resonance Research Centre, Columbia University, New York, NY, United States, 3Wipro GE Healthcare, Bangalore, India
Synopsis
Rapid prOtotyping of 2D non-CartesIan K-space
trajEcTories (ROCKET) aims to aid researchers interested in
rapid development and testing of new MR methods starting from pulse sequence
design to image analysis. This was achieved by utilizing Pulseq for pulse
sequence design and graphical programming interface for image reconstruction and analysis.
ROCKET was demonstrated on two non-Cartesian k-space trajectories – FID based
radial and spiral. Each trajectory was tailored into three different trajectories
based on rotating angle – standard, golden angle and tiny golden angle.
All studies were performed on Siemens scanner demonstrated on in-vitro phantom
and in-vivo healthy brain acquisitions and SNRs were computed.
Introduction
Cartesian trajectory based
acquisition is routinely used in clinical MR studies. However, it takes long
time for acquisition which is the major limiting factor. Dynamic scans such as
cardiac MRI and dynamic contrast enhanced MRI demand fast acquisition, which
can be achieved by using non-Cartesian based acquisition. For researchers who
want to develop and test new sequences on the scanner, it takes considerable
amount of time. This work focuses on open-source software, rapid
prototyping of two 2D non-Cartesian k-space trajectories (radial and spiral), including
pulse sequence design, image reconstruction and image analysis for in-vitro phantom
and in-vivo healthy brain. Rapid prototyping was achieved by
utilizing Pulseq1
for pulse sequence design and GPI2 for image reconstruction and
analysis. Methods
The FID based radial trajectory was designed using equation $$$k_x=k_{width}cos\theta$$$ and $$$k_y=k_{width}sin\theta$$$, where $$$k_{width}$$$ is the maximum extent of k-space and defined as $$$k_{width}=N\delta k$$$, N is matrix size and $$$\delta k=1/FOV$$$, FOV is the field of
view. The general spiral trajectory was defined by equation3 $$$k(\tau)=\lambda \tau^{\alpha}e^{j\omega\tau}$$$ where, τ- function of time, α is the variable density
factor, λ=N/(2*FOV), N is
matrix size, ω=2πn, n is number of turns. As α increases, the density factory also increases. The
designed spiral trajectory is the modified version of the code4. Each trajectory was designed for three
rotating angles – standard, Golden Angle (GA) and Tiny Golden Angle (TGA). GA is obtained by dividing 1800 by the golden ratio of
1.618. The acquired data is spaced by a constant azimuthal increment of 111.260.
The limiting factor of GA is the rapid change of eddy currents. TGA provides
smaller angular increments by inheriting all the properties of GA.
ROCKET was demonstrated on two non-Cartesian
k-space trajectories (namely, FID based radial and spiral) with three rotating
angles. The standard rotating angle for radial/spiral was obtained by
dividing 3600 with the total number of spokes/interleaves. The GA and TGA angles were obtained by using equations from the paper5,6.
The radial/spiral GRE pulse sequence were designed with six different
gradient waveforms, and all were scanned on in-vivo healthy brain and in-vitro
Disease Neuroimaging Initiative (ADNI) phantom (Phantom laboratory, New York). The acquisition
parameters were shown in table 1. Figure 1 shows the rapid prototyping using
ROCKET. The non-Cartesian GRE pulse sequences were designed in Pulseq and the seq files were generated. Each seq
file is typically converted to the vendor specific files by using an
interpreter. Here, all the scans were performed on a Siemens 3T Prisma. The generated
seq files were exported directly to the MR scanner and raw data was
obtained. The trajectory and the k-space data were given as input to the GPI
network and images were reconstructed. Finally, line intensity profile was
plotted using GPI script (GPI/Recon.net)7 to compare the resolutions
of the reconstructed images obtained from in-vitro and in-vivo studies.
Results
Figure 2 depicts the three variants of
radial trajectories (first row) - standard, GA and TGA, gradient waveforms
(second row) and representative GRE pulse sequence diagram for 1 TR (third
row). Figure 3 shows the three variants of spiral trajectories, representative
gradient waveforms and GRE sequence for 1 TR. Figure 4 depicts the
reconstructed images in GPI for radial and spiral along with line intensity
plot. It can be witnessed from the radial in-vitro images (first column)
that there is a bright halo around edges of the phantom (blue arrows). This was
due to the delay caused by gradients. The horizontal streaking artefacts can be
observed for the images highlighted with green border. The deviation in the
line intensity plot (shown with blue arrows) can be observed for spiral in-vitro
and in-vivo (TGA) due to the streaking artefact. The SNRs of the
reconstructed images are: in-vitro radial with standard, GA and TGA are
32.11dB, 31.17dB and 30.46dB respectively. In-vivo radial with standard,
GA and TGA are 30.08dB, 30.64dB and 28.65dB respectively. In-vitro spiral
with standard, GA and TGA are 43.90dB, 43.42dB and 30.86dB respectively. In-vivo
spiral with standard, GA and TGA are 29.52dB, 28.16dB and 19.29dB respectively.Discussion and Conclusion
ROCKET is a framework that
facilitates the researchers for rapid prototyping of MR method development for
non-Cartesian based acquisition and reconstruction. This includes trajectory
design, pulse sequence design, perform scan upon deploying onto the scanner,
image reconstruction and image analysis. ROCKET can be utilized for prototyping
and testing other 2D pulse sequences by directly downloading the source-code
from GitHub7. Future works includes safety by incorporating
peripheral nerve stimulation and specific absorption ratio. It also involves
integrating ROCKET to the Pulseq-GPI8 framework as it currently
supports Cartesian based acquisition.Acknowledgements
No acknowledgement found.References
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