Isabell K. Bones1, Suzanne L. Franklin1,2, Anita A. Harteveld1, Matthias J.P. van Osch2, Jeroen Hendrikse3, Chrit Moonen1, Marijn van Stralen1, and Clemens Bos1
1Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands, 2C.J.Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Netherlands, 3Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
Synopsis
Velocity selective arterial
spin labeling (VSASL) is a spatially non-selective method that labels spins
based on their flow velocity, thereby labeling closer to the target tissue, reducing the influence of
arterial transit time (ATT) and requiring no planning. In the abdomen, motion and complex vascular anatomy might, however,
require dedicated VS-labeling parameters. We assessed the feasibility of VSASL for renal perfusion measurement by
investigating its dependency on essential labeling parameters, and by comparing
it with pseudo-continuous ASL (pCASL) as a spatially-selective reference
ASL-technique. Our results show, that with carefully chosen sequence parameters,
VSASL is feasible for renal perfusion measurement.
Introduction
Velocity selective arterial spin labeling (VSASL)1 labels spins based on
their flow velocity, thereby also labeling in the imaging plane, thus reducing
arterial transit time (ATT) artifacts. Moreover, VSASL does not require planning
of a labeling slab, making it highly attractive for abdominal perfusion
measurements, where planning might be challenging due to complex (vascular)
anatomy. However, limited work has been done studying the application of VSASL
in the abdomen. In this study, the dependency of renal
VSASL on essential labeling parameters is assessed and its sensitivity to renal
perfusion evaluated by comparison with renal pseudo-continuous ASL (pCASL).Methods
Imaging: Kidneys of 15
volunteers (age 23-38, 6 men) were scanned on a 1.5T MRI (Ingenia, Philips, The
Netherlands) using a 28-element phased-array receiver-coil. Seven
angulated coronal slices were acquired with a gradient echo EPI readout (Table 1)
using VSASL2 and pCASL3 (1500ms label duration and PLD), including 10
label-control pairs. This
study focused on the following VSASL parameters (Table 2): VS-labeling
mode (single (s)VSASL and dual (d)VSASL), labeling
cut-off velocity (Vc), labeling
gradient orientation (GrOri), post-labeling
delay (PLD).
Experiments: Based on pilot experiments, a
baseline scan was defined (Vc=5cm/s, GrOri=FH, PLD=1200ms). For each
of the parameters Vc, GrOri and PLD, 5 subjects were scanned in which the
parameter was systematically varied, for both sVSASL and dVSASL labeling (Table 2). Additionally,
baseline-VSASL, pCASL and an M0 equilibrium image were acquired in all
volunteers. ASL scans included background suppression.
Analysis:
Images
were aligned using Elastix4, for each kidney separately. The influence of
labeling parameters on VSASL was
assessed by calculating the perfusion-weighted signal (PWS=ΔM/M0×100%) and voxel-wise
temporal SNR (tSNR) and were reported as a function of Vc, GrOri and
PLD. Occurrence of subtraction artifacts (spurious labeling) was visually assessed
per dynamic for scans with varying Vc, recognizable by homogeneously
high ΔM over the entire kidney. In addition, sensitivity to perfusion signal of
VSASL (baseline-settings)
was evaluated by PWS comparison with pCASL at the subject level, established by
the Pearson correlation-coefficient.
Results
With decreasing Vc, PWS and
tSNR increased for both single- and dual-VSASL (Figure 1a).
However, at low Vc(≤5cm/s), subtraction artefacts became evident (Figure 2) for 19%/28%
(left/right kidney) of the label-control pairs with Vc=2cm/s and 5%/3% with Vc=5cm/s.
GrOri had no effect on PWS for either sVSASL
or dVSASL (Figure 1b). tSNR was
slightly affected by the orientation, with labeling in FH direction yielding
highest tSNR.
Increasing PLD resulted in a PWS decrease for
sVSASL, while for dVSASL this effect was considerably smaller (Figure 1c).
Nevertheless, for short PLDs(≤800ms), especially for sVSASL, high PWS appeared
in the center of the kidneys. Highest tSNR for dVSASL was found using a PLD of
1200ms, while for sVSASL it occurred at shorter PLDs(≤800ms).
Overall, dVSASL yielded consistently lower
PWS and tSNR than sVSASL (Figure 1). When correlating the PWS per volunteer,
measured with baseline-VSASL to the reference technique pCASL, dVSASL showed a
stronger correlation than sVSASL with r=0.60 and r=0.52, respectively, with an
offset present for sVSASL (Figure 3).Discussion & Conclusions
Results showed that renal VSASL is dependent
on the Vc and PLD, but is relatively stable for different gradient
orientations. Subtraction artefacts were observed with Vc≤5cm/s, likely
caused by respiration-induced motion during VS-labeling.1,5
In this study, both dual and single VSASL
were studied. dVSASL does not only allow quantification by creating a fixed
temporal label width, but also eliminates venous signal. However, sVSASL is the
fundamental building-block determining the amount of label created. Signal
enhancement of sVSASL in the center of kidneys at short PLDs(<800ms) and the
offset when compared with pCASL, were probably caused by venous signal since both
were eliminated when using dVSASL6.
A good correlation between dVSASL and
pCASL was found, especially when taking into account that the ASL-data was not
quantified yet. Compared to dVSASL, pCASL will aggregate more label in the
target tissue due to the 1500ms label duration. Moreover, the second module in
dVSASL will also crush part of the arterial signal. These aspects make quantification necessary for fair
comparison, as it takes T1 differences of tissue and blood as well as label
input functions into account.
Our results show, that with carefully chosen
sequence parameters, challenges
such as subtraction artefacts and high signal from the venous side can be
accounted for. In
conclusion, (d)VSASL is feasible for renal perfusion measurement,
offering a planning-free, non-invasive technique which is less
dependent on altered ATT, such as found in elderly and tumor patients.Acknowledgements
This work is part of the research program
Applied and Engineering Sciences with project number 14951 which is (partly)
financed by the Netherlands Organization for Scientific Research (NWO). We
thank MeVis Medical Solutions AG (Bremen, Germany) for providing MeVisLab
medical image processing and visualization environment, which was used for
image analysis.References
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