Mario O. Malavé1, Nii Okai Addy1, R. Reeve Ingle1, Joseph Y. Cheng1, Corey A. Baron1, and Dwight G. Nishimura1
1Electrical Engineering, Stanford University, Stanford, CA, United States
Synopsis
Motion and eddy current artifacts were investigated
with simulations, metric measures, and in vivo scans for three different cone
acquisition schemes: sequential, multidimensional golden means (MDGM), and
phyllotaxis readout orderings. We
demonstrate the idea of using the 3D cones phyllotaxis acquisition method for
improved motion behavior and low eddy current susceptibility. Also, the
sequential ordering method is shown to be more susceptible to motion artifacts
while the MDGM introduces eddy current artifacts. When using the phyllotaxis design,
the reconstruction demonstrates that a more spread out k-space traversal per heartbeat
is more robust to motion and can be obtained without introducing eddy currents.Introduction/Purpose
We
have developed an alternating-TR steady state free precession (SSFP) coronary
MR angiography (CMRA) sequence using a 3D cones k-space trajectory [1]. A consideration
during the data acquisition is the ordering and position of the cone readouts.
Specifically, we would like to acquire cone readouts in a fashion that exhibits
incoherent motion artifacts while minimizing eddy current effects with SSFP. In
this work, motion and eddy current artifacts were investigated with
simulations, metric measures, and in vivo scans for three different cone
acquisition schemes: sequential, multidimensional golden means (MDGM) [2], and
phyllotaxis [3].
Method
Cone Trajectory Design:
The
cones trajectories were designed using 10,980 readouts to image a 28x28x14 cm3
field of view (FOV) with 1.2 mm isotropic resolution. Each cone readout has an
initial radial traversal (exiting polar angle < φ, θ>), followed by a
spiral-like traversal [4]. The different design methods, shown in Fig. 1, that were evaluated include
sequential, MDGM [2] without and with pairing [5], and phyllotaxis [3].
Design Analysis:
The scan was segmented over each heartbeat where a
specified number of cone readouts was acquired. For any given segment, the distribution
of cones should have uniform spread in k-space while minimizing eddy currents when
using SSFP. Two metrics were used for analyzing distribution uniformity and
eddy current sensitivity: relative standard deviation (RSD) (Eqn. 1) and
average distance measure (Eqn. 2) [6]. N, HB, and Nseg represent total cones, total heartbeats, and cones per heartbeat respectively. $$(Eqn.1)RSD=\frac{\sqrt{\frac{1}{N\cdot4}\cdot\sum_{i=1,j=1}^{i=N,j=4}(d_{j,i}-\mu_{d})^{2}}}{\mu_{d}}\cdot100$$ $$\mu_{d}=\frac{1}{N\cdot4}\cdot\sum_{i=1,j=1}^{i=N,j=4}d_{j,i}$$ $$(Eqn.2)Avg.Dist.=\frac{1}{HB}\sum_{i=1:Nseg:N}^{N}\frac{1}{Nseg-1}\sum_{j=1}^{Nseg-1}d_{i(i+j)}$$ For a uniformly spread distribution, the
variation and the average distance between neighboring points are minimized and
maximized respectively. Thus, the RSD would give smaller values for more uniformly
spread distributions. The eddy current sensitivity is defined by calculating
the average distance between points (exiting angles) within each heartbeat.
Thus, lower values demonstrate that the distribution is more robust to eddy
currents [5,6].
To analyze motion for the different acquisition
ordering methods, the point spread function (PSF) was calculated with an added superior/inferior
(S/I) motion component. For each PSF, S/I motion data, obtained retrospectively from 2D image-based navigators (iNAVs) [1], was added using a linear
phase term on the cone readouts for each heartbeat.
In
vivo scans were performed on a 1.5T GE scanner using an 8-channel cardiac receiver coil.
All design methods acquired 18 cones per heartbeat with a total of 610
heartbeats.
Results and Discussion
Simulation:
The
RSD measure can be seen for four different cones trajectory designs in Fig. 2a.
The RSD, with a nearest neighbor of four, shows that the phyllotaxis design has
better distribution uniformity. The sequential design becomes more uniform
when the total number of cones is increased.
The
average distance measure is also shown for the different cone trajectories in Fig. 2b. As expected, the MDGM without pairing performed the worst due to the
large jumps in k-space within each heartbeats. Using “pairing” [5] can help to
alleviate the k-space jumps (eddy currents) as shown. Both MDGM methods, and
phyllotaxis perform better than sequential ordering until more cones are
used (~300 total heartbeats with 18 cones each).
The PSFs for
sequential ordering and phyllotaxis design methods are shown in Fig. 3. In the
coronal and sagittal slice, the motion artifacts are more concentrated along
the vertical axis for sequential whereas the motion is incoherently spread
around the center of k-space for phyllotaxis.
Experimental:
In Fig. 4, the central sagittal, coronal, and axial slices for an in vivo scan are
shown. Similar to the PSFs, the sequential acquisition shows more
coherent motion artifacts.
In Fig. 5, the right coronary artery (RCA), left coronary artery (LCA), and left anterior descending (LAD) are shown for all three cones acquisition methods. In
the images, the phyllotaxis acquisition resulted in sharper coronaries due to
the design uniformity and negligible eddy current effects. The MDGM with pairing method introduced
eddy current artifacts shown by degraded image quality in the ventricles, and
signal loss in the coronaries.
Conclusion
These results support the idea of using the 3D
cones phyllotaxis acquisition method for improved motion behavior and low eddy
current susceptibility. The sequential ordering method is more susceptible to
motion coherent artifacts while the MDGM introduces eddy
current artifacts due to rapid changing x, y and z gradients despite the use of pairing [5]. When using the
phyllotaxis design, the reconstruction demonstrates that a more spread out k-space
traversal per heartbeat is more robust to motion and can be obtained without
introducing eddy currents.
Acknowledgements
NIH T32 HL007846, NIH R01 HL127039, GE Healthcare
References
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