Ping N Wang1, Julia V Velikina1, Roberta M Strigel1,2,3, Leah C Henze Bancroft2, Ty A Cashen4, Kevin M Johnson1, Alexey A Samsonov2, Ali Ersoz5, Edward F Jackson1,2,3, and James H Holmes2
1Department of Medical Physics, University of Wisconsin Madison, Madison, WI, United States, 2Department of Radiology, University of Wisconsin Madison, Madison, WI, United States, 3Carbone Cancer Center, University of Wisconsin Madison, Madison, WI, United States, 4Global MR Applications & Workflow, GE Healthcare, Madison, WI, United States, 5MR Engineering, GE Healthcare, Waukesha, WI, United States
Synopsis
Advanced data acquisition and reconstruction
methods have been proposed to improve temporal and spatial resolution DCE
imaging for breast. However, validation and comparison of these methods against
a known truth is challenging. In this work we propose a digital reference
object for breast pharmacokinetic simulation to evaluate different advanced reconstructions
including MOCCO and iGRASP. The approach allowed comparison of the reconstructed
temporal characteristics including pharmacokinetic analysis using different
reconstruction parameters against the assigned ground truth. Spatial sharpness was also measured to
compare with reference fully sampled images.
Introduction
Breast
dynamic contrast enhanced MRI (DCE-MRI) is widely accepted as the most
sensitive modality with moderate specificity for detection of breast cancer1. Quantitative
pharmacokinetic (PK) modeling of DCE-MRI has been proposed to improve the
specificity2. However high temporal resolution is required
for accurate estimation of the PK parameters while high spatial resolution is
needed to detect and characterize lesions3. Compressed
sensing (CS) reconstructions have shown promise to improve temporal resolution,
however it is often necessary to optimize reconstruction parameters for
application or even subject specific imaging scenarios4. Two
promising reconstruction approaches include iGRASP, which relies on a total variation (TV)
sparsifying transform5, and MOCCO6, which uses temporal
models estimated from the imaging data to
reduce the sensitivity to modeling error. Even though these advanced algorithms
achieved remarkable spatial recovery with high undersampling factors, the
accuracy of the temporal curves remains an open question due to the lack of
ground truth in patients. Digital
reference objects (DROs) provide a platform to validate the temporal accuracy
of different acquisition and reconstruction parameters7,8 in the presence of simulated signal changes
such as those provided by PK modeling. In this study, we demonstrate the use
of a breast PK simulation DRO for investigating the performance of advanced
reconstruction methods including SENSE, MOCCO, and iGRASP.Theory
Time-resolved
images were reconstructed using iGRASP and a modified MOCCO algorithm6. iGRASP
reconstructions were performed using publicly available code provided by Feng
et al5,9 including
temporal TV regularization. The underlying temporal model for MOCCO was
obtained from the low frequency region from fully-sampled central k-space data using
progressive learning with cubic spline approximation10,11 followed by complex independent component
analysis12.
Methods
DRO Simulations: Simulation 1 was performed to benchmark performance
of the DRO13 with iGRASP using the published acquisition and reconstruction
parameters from Kim et al.9 including temporal regularization
parameters of λ= 0.5 and 2. This
produced a 5-s temporal resolution (undersampling factor R=12). Simulation 2 was modeled after our local
clinical axial protocol (TR/TE= 5.5/2.4 ms, FOV= 340 x 340 mm, 448x448 in-plane
matrix, 142 z-phase encodes, 1.5x out-of-plane acceleration). The simulated
radial data were reconstructed at 10-s temporal resolution, corresponding to a higher
acceleration of R=44 (16 projections/frame). Values of 0.5 and 10 were chosen
for λ in iGRASP and MOCCO respectively to optimize spatial and temporal
resolution. An idealized fully sampled dataset using SENSE reconstruction was
generated at 10-s temporal resolution as a reference. Temporal curves from regions-of-interest placed in each lesion were also measured using normalized
root-mean-square error (nRMSE). PK model fitting was performed using extended
Tofts model13 to assess the ability to recover the initial contrast
kinetic parameters from the reconstructed data. In-vivo Assessment: A patient volunteer was imaged during contrast
injection (gadobenate dimeglumine, Multihance; Bracco Inc, Milan, Italy) on a
clinical 3T MRI (Signa Premier, GE Healthcare, Waukesha, WI) using a 16-channel
breast coil (Sentinelle, Invivo International, Gainsville, FL) for this
IRB-approved, HIPPA-compliant study. A 3D radial stack-of-stars gradient echo
sequence was used to collect 1344 unique radial projections and reconstructed
using MOCCO at 10-s temporal resolution.Results
Simulation1: Qualitative assessment found the choice of λ=0.5
for iGRASP provided the best compromise between spatial quality and temporal
recovery in the DRO (Fig. 1), resulting in uptake slopes that were well-matched
to the ground truth. Loss of temporal fidelity was observed at higher values (λ=2).
Simulation2: iGRASP with λ=0.5 resulted in high spatial
resolution but did retain some undersamplling artifacts (Fig2 c). Increasing
λ was found to reduce these undersampling artifacts but compromise temporal
fidelity (results not shown). iGRASP
with λ=0.5 performed well for recovering ktrans, which is consistent with the
well depicted wash-in slope (Fig 3). MOCCO using λ=10
showed overall similar image quality (Fig2 b) compared to reference images (Fig2
a). The
temporal curves were well recovered by MOCCO reconstruction with nRMSE less
than 10% (Fig 3), allowing good recovery of Ve. Simulated lesions with the most
rapid wash-in and wash-out slopes (lesions 3 and 5) were difficult to recover
for both techniques. iGRASP
with λ=0.5
was found to yield some temporal blurring in these regions of fast kinetics
leading to fitting errors in Ktrans, Ve, and Vp (Fig. 4). MOCCO
showed better recovery of the overall curve shapes but with slight
underestimation of the peak intensity resulting in limited errors in Ve and Vp.
In vivo results are shown for a patient volunteer using the optimized reconstruction
parameters based on simulation2.Discussion and conclusions
We demonstrated the feasibility of using a DRO breast phantom to optimize
and evaluate the performance of advanced reconstruction techniques for
recovering temporal kinetics in breast DCE-MRI. As a publically available technique,
iGRASP provides an accessible starting point for accelerated imaging applications. Analysis
found that λ=0.5
resulted in the optimal balance of temporal and spatial accuracy including capturing
the wash-in slope, which is consistent with prior work looking at use in
abbreviated breast protocols14. Evaluation
of the second method, MOCCO, showed high image quality with minimal loss of
temporal fidelity, indicating that it may be well suited to PK modeling or
treatment monitoring applications. Future work will look at evaluating the
predictions of these DRO simulations when applied to in vivo and disease
settings.Acknowledgements
The authors wish to acknowledge support from
NIH-R21EB018483, NIH-R01EB027087, GE Healthcare, the RSNA Research and
Education Foundation, and a Research and Development Grant from the Departments
of Radiology and Medical Physics, University of Wisconsin.References
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