Philip A Corrado1, Rafael Medero2, Kevin M. Johnson1,3, Christopher J François 3, Alejandro Roldán-Alzate2,4, and Oliver Wieben1,3
1Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 3Radiology, University of Wisconsin-Madison, Madison, WI, United States, 4Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States
Synopsis
Dual-Venc
4D flow MRI offers higher velocity sensitivity than single-Venc imaging but
requires increased scan time. Radial sampling, either with a 3D-radial or
hybrid stack-of-stars (SOS) trajectory, allows for acceleration that can offset
the increase, but the optimal technique depends on anatomical region and is not
apparent for imaging the left ventricle (LV). We compared 3D-radial and SOS velocity
images in an in-vitro LV model versus a reference dataset acquired with
particle imaging velocimetry (PIV), an experimental optical imaging technique.
3D-radial matched PIV velocities better than SOS, suggesting it is better for
accelerated, dual-Venc imaging of the LV.
Introduction
Four-dimensional (4D) flow MRI allows for comprehensive assessment
of in-vivo blood flow1. Velocity images require a
predefined maximum encoded velocity (Venc), which is typically set above the
maximum expected velocity. Noise in the velocity image is proportional to the Venc,
so regions of flow much slower than the Venc are difficult to capture
accurately. Dual-Venc imaging improves the dynamic range by acquiring two
datasets and using a high-Venc image to unwrap velocity aliasing in a low-Venc
image2,3. This technique requires additional
scan time, but accelerated acquisitions can help offset that increase. Radially
undersampled k-space acquisitions, either with a true 3D-radial or
stack-of-stars (SOS) trajectory, have been successfully utilized for
accelerated 4D flow MRI4,5. SOS is a hybrid technique with Cartesian
through-plane and radial in-plane encoding that enables shorter scan times when
acquiring a small number of slices. However,
when a moderate number of slices are required, such as in left ventricle (LV)
imaging, it is unclear which technique is best-suited. Here we compare 3D-radial
versus SOS techniques for dual-Venc imaging of the LV, using an in-vitro model
and particle imaging velocimetry (PIV) as a reference standard.Methods
A simplified rigid in-vitro model of the LV was constructed using
a published method6. The LV was segmented from a healthy
adult’s cardiac CT and 3D-printed in polyvinyl alcohol (PVA). The PVA model was
cured in silicone and then dissolved in water, leaving an LV cavity in the
silicone model. The model was connected to a pulsatile flow pump (PD-1100, BDC Laboratories,
Wheat Ridge, CO, flow rate=2.5L/min) and imaged with tomographic PIV - a 3D, high
spatiotemporal resolution experimental technique using high-speed cameras to measure
fluid velocities by tracking laser-illuminated fluorescent particles7. PIV data was acquired with a
Flowmaster system (LaVision, Göttingen, Germany) in 5mm slabs and stitched
together with a custom Matlab script. Figure 1 shows the model and PIV setup. The
model was also imaged in a 3T MRI scanner (Signa Premier, GE Healthcare, Waukesha,
WI) with four distinct 4D flow acquisitions: two with a product Cartesian single-Venc
sequence (1 fully sampled, 1 kt-ARC8 8-fold accelerated) and two with an
in-house-implemented, radial dual-Venc sequence (1 3D-radial, 1 SOS). From each
radial acquisition, 20 datasets were reconstructed: 5 levels of retrospective undersampling
x 2 encoding types (dual-Venc and high-Venc-only) x 2 reconstruction methods (gridding
and spatial-wavelet-transform compressed sensing [CS; λ=0.01 determined empirically]). Images were acquired with typical
in-vivo orientations and fields of view. Table 1 shows MRI parameters. MRI
images were manually registered to the PIV dataset, and then compared separately
to 2 different reference images: (1) PIV and (2) the most densely sampled MRI
dataset with the same trajectory. For each comparison, a velocity difference
image was computed as the magnitude of the vector difference between test and
reference image velocities for all voxels in the LV cavity.Results
Figure 2 shows velocity vector visualizations from the PIV,
3D-radial, and SOS MRI datasets. Figure 3 shows plots of average velocity error
relative to PIV and densely sampled MRI. 3D-radial velocities more closely
matched PIV velocities than did SOS velocities for all scan times,
reconstructions, and encoding strategies. Compared to CS-reconstructed data, gridding-reconstructed
data matched PIV better at long acquisition times but worse at short
acquisition times. With densely sampled MRI as the reference, 3D-radial images had
lower velocity error than SOS images, and dual-Venc images had lower velocity
error than single-Venc images. The kt-ARC-accelerated Cartesian dataset matched
its densely sampled reference as well as the dual-Venc 3D-radial images did but
diverged from PIV velocities more than both radial techniques. Figure 4 shows
velocity error maps relative to PIV for 5-minute 3D-radial and SOS MRI images.Discussion
In velocity vector images, flow patterns were qualitatively
similar in PIV, 3D-radial, and SOS images, but the PIV image appeared least
noisy. In the quantitative comparison, 3D-radial data outperformed SOS. The differences
between these images can be attributed to differential undersampling artifacts.
While the acceleration factors were higher in the 3D-radial than SOS images for
a given scan time, the SOS sampling pattern was more structured, resulting in a
more obtrusive undersampling artifact. Images reconstructed via gridding
exhibited a predictable tradeoff between scan time and velocity error, while CS
images contained similar error at all scan times. This suggests that much of
the velocity error in the CS images stemmed from sparsity enforcement rather
than from undersampling. A lower lambda value may have improved long-acquisition-time
CS images. Velocity-error-relative-to-PIV maps yielded similar patterns regardless
of radial trajectory, with some subtle differences in the LV apex. Since
experimental setup was kept as similar as possible between PIV and MRI
experiments, the portion of the error that was independent of MRI technique likely
reflects a bias between PIV and MRI rather than a difference in the true flow.Conclusion
We conclude that 3D-radial rather than SOS acquisition should
be used for radially-undersampled 4D flow MRI of the LV. We also determine that
CS-wavelet reconstruction is a reasonable choice for highly-undersampled radial
4D flow images of the LV. When used with dual-Venc acquisition and CS
reconstruction, 3D-radial 4D flow MRI can provide highly accurate velocity
estimation even at short scan times.Acknowledgements
Research reported in this publication was supported by the
National Heart, Lung, And Blood Institute of the National Institutes of Health
under Award Number F31HL144020. The content is solely the responsibility of the
authors and does not necessarily represent the official views of the National Institutes
of Health. We wish to
thank GE Healthcare who provides research support to the University of
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