Jacob M. Johnson1, Leah C. Henze Bancroft2, James H. Holmes3, Edward F. Jackson1,2, Frank R. Korosec1,2, Courtney K. Morrison2, Roberta M. Strigel1, Kang Wang3, and Ryan J. Bosca1
1Radiology, University of Wisconsin, Madison, WI, United States, 2Medical Physics, University of Wisconsin, Madison, WI, United States, 3GE Healthcare, Madison, WI, United States
Synopsis
The recent development of a multi-modality, commercially
available, dynamic flow phantom has provided a means of assessing the repeatability,
reproducibility, and fidelity of contrast concentration time courses. In
this work, we aimed to develop and evaluate a methodology for assessing the
repeatability and reproducibility contrast concentration time courses derived from dynamic contrast-enhanced MR images of this
dynamic flow phantom.Purpose
Dynamic contrast enhanced (DCE) MRI is
increasingly being utilized as a clinical and research tool to derive
quantitative imaging biomarkers of perfusion. While numerous efforts (e.g.,
those of the Radiological Society of North America’s Quantitative Imaging
Biomarker Alliance and ISMRM Ad Hoc Committee on Standards for Quantitative MR)
have been made to evaluate and mitigate the various sources of bias and
variance in quantitative DCE-MRI studies, these groups have largely relied on static,
multi-compartment phantoms that mimic the expected in vivo relaxivities [1,2]. The
recent development of a multi-modality, commercially available, dynamic flow
phantom [3,4] has provided a means of assessing the repeatability,
reproducibility, and fidelity of contrast agent concentration time courses
(CTC). While work to establish the repeatability and reproducibility of CTCs
has been performed on CT scanners [4,5], similar work, to the best of the authors’
knowledge, has yet to be performed on MR. Therefore, the goal of this work was
to develop and evaluate a methodology for assessing the repeatability and
reproducibility of DCE-MRI derived CTCs using this dynamic flow phantom.
Methods
The DCE perfusion phantom (Shelley Medical Imaging
Technologies, London, ON) is represented schematically in Figure 1. To
determine an optimal MR imaging configuration for quantifying CTCs, three imaging
configurations were tested: (1) imaging the intended imaging block, (2) imaging
the perfusion cylinder in the intended horizontal position, and (3) imaging the
perfusion cylinder in an upright (vertical) position. An additional length of silicone
tube was added at the exit of the pump to reduce the output pulsatility. The
perfusion pump was set to a flow rate of 4mL/s and the control values were set
to achieve equivalent flow between the cylinder and distribution output (see
Figure 1). Prior to imaging, the pump was activated and given several minutes to
stabilize. Images were acquired on two 1.5T clinical MRI system (Signa HDxt and
Optima 450w, GE Healthcare, Waukesha, WI). All dynamic images were acquired
with a 3D fast spoiled gradient echo sequence and temporal resolution less than
8 seconds. At approximately 90s into the acquisition, the contrast agent was
injected using a power injector (5mL gadobenate dimeglumine followed by a 10mL
saline flush delivered at 2mL/s). The optimal phantom configuration (as
described in the results) was used to test the repeatability of the CTCs by
acquiring three consecutive DCE scans during the same session, while the
reproducibility was tracked by measurements made during three different
scanning sessions. The concentration of contrast agent was estimated from the cylinder
output (see Figure 2), and a gamma variate, given by $$C(t)=\kappa (t-t_0)^\alpha e^{\frac{t-t_0}{\beta}}$$ was fit to the resultant dynamic
curve using QUATTRO [5]. The areas under the fitted
curves (AUC) were calculated. Coefficients of variation (CV) were calculated
for all gamma-variate shape parameters (
$$$\alpha$$$ and
$$$\beta$$$) and AUCs within a given scanning session (repeatability)
and between all scanning sessions (reproducibility).
Results
Practical considerations such as avoidance of flow
artifacts, spatial/temporal resolution requirements, and pre-scanning
difficulties resulted in more reliable CTC measurements derived from the output
of the perfusion cylinder. Imaging of the cylinder in the upright (vertical)
orientation (i.e., configuration 3) improved mixing and reduced the retention
of contrast agent within cylinder, resulting in CTCs that were more consistent
with the expected gamma-variate model. Therefore, repeatability and
reproducibility data was acquired using configuration 3. All data exhibited
good agreement with the fitted gamma-variate model (R2>0.988), an
example of which is shown in Figure 3. The (repeatability) CVs calculated
within a given scanning session for each of the three consecutive scans were:
4.2%, 12.3%, and 4.5% ($$$\alpha$$$); 5.8%, 5.6%, and 1.1% (
$$$\beta$$$); and 11.9%,
2.5%, and 1.7% (AUC). The (reproducibility) CVs calculated from all
acquisitions were: 18.4% (
$$$\alpha$$$), 12.4% (
$$$\beta$$$), and 25.4% (AUC).
Conclusions
The CTC measurements with the DCE perfusion phantom arranged
in configuration 3 were the most repeatable with maximum CVs reaching only 12%,
while there was larger variability in longitudinal measurements
(reproducibility). A
number of potentially uncontrolled sources of variance require additional
study, such as, MR hardware differences, phantom setup differences (i.e.,
different tube routes, inclusion/exclusion of the imaging block, etc.), flow
ratio tuning, and power injector differences. With the high degree of repeatability observed, the
DCE perfusion phantom could potentially be used as a means of validating the
data fidelity of accelerated acquisition strategies used in the context of
quantitative perfusion studies.
Acknowledgements
The authors would like to acknowledge the support
from the NIH (T32CA009206), the University of Wisconsin Department of Radiology
R & D fund, RSNA, and GE healthcare.References
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