Marta Vidorreta1,2, Yulin V Chang2, and John A Detre1,2
1Neurology, University of Pennsylvania, Philadelphia, PA, United States, 2Radiology, University of Pennsylvania, Philadelphia, PA, United States
Synopsis
The effects of labeling location were assessed in
pseudo-continuous ASL by performing kinetic modeling of data acquired at
multiple post-labeling delays and by assessing the ratio of mean ASL intensity
to M0. Labeling location differences
resulted in significant MT effects on raw ASL data, and produced nonlinear
effects on bolus arrival time across vascular distributions.Purpose
Arterial Spin Labeled (ASL) perfusion MRI
1
measures cerebral blood flow (CBF) in physiological units. To obtain accurate
CBF maps, a sufficiently long post-label delay (PLD) is required after the
labeling period in order to allow all labeled spins to reach the imaging
region, i.e. PLD has to be longer than the arterial transit time (ATT). ATT has
been assumed to vary linearly with velocity, and hence with the position of the
labeling plane with respect to the imaging slab, though little information exists
on the regional influence of labeling plane position on ATT. We assessed the
impact of varying the labeling plane location on the bolus arrival time (BAT)
using pseudo-continuous ASL (pCASL) and a multi-PLD strategy. We additionally
evaluate the impact of labeling location on MT effects in the
perfusion images.
Methods
Scanning protocol
Data on two healthy volunteers (male, 30 years old) were
collected on a 3T Siemens Prisma scanner, with a 64-channel head array. An
anatomical dataset was acquired with T1-MPRAGE and a Time-Of-Flight (TOF) was used
to identify labeling positions. Two labeling positions were selected, located
at 120 and 90 mm from the center of the ASL imaging slab (Fig.
1). For each position, 4-pair multi-PLD ASL scans were acquired at 3.75mm
isotropic resolution using a 4-shot, background-suppressed (BS) pCASL 3D RARE
Stack-Of-Spirals sequence2,
with labeling duration=1 s and PLD times=200, 500, 1100, 1400, 1800, 2200, 2600
and 3200 ms (3min acquisition per PLD). For Subject 2, only 7 PLD times were
acquired (missing PLD=200 ms). Other ASL parameters were: FA=25°,RFduration=500μs,
Gap=360μs, Gmax=6 and Gmean=1 mT/m. An M0 image with no ASL preparation and long TR
was also acquired for each PLD.
Data processing
Raw ASL images were realigned and registered to the T1
anatomical image using FSL and FreeSurfer tools. For each PLD and labeling
position, label-control images were subtracted to create a mean $$$\Delta$$$M image, and converted
into CBF units using the one-compartment model3.
The T1 image was segmented into GM and WM tissue maps using SPM’s New Segment
tool, to derive a whole-brain mask. Mean $$$\Delta$$$M
and CBF images were masked and smoothed (FWHM=6mm) to ensure a smooth parameter
estimation.
Data analysis
To study the presence of MT effects, all label and control
pairs were averaged $$$(Label+Control)/2$$$ within each acquisition to cancel
perfusion effects, normalized by the corresponding M0, and evaluated this ratio
as a function of position using a non-parametric Wilcoxon signed rank test. Lastly,
BASIL (Bayesian Inference for ASL MRI4, FSL) was employed to derive
an ATT map for each of the labeling positions, with correction for
macrovascular components.
Results and Discussion
Fig. 2A shows the normalized mean
$$$(Label+Control)/2$$$ values as a function of position, as well as mean M0. A
significant difference was observed in the ratio of mean ASL image intensity to
M0 as a function of labeling location (median=2.9% and 3.2% across all PLDs, p
= 0.0078). Fig. 2B shows the global perfusion curves for
both positions in the two subjects. Because of the use of BS with a 90% target
suppression level (90-92% measured), MT effects
of even a few percent are likely to impact CBF estimation accuracy.
Fig. 3 displays the mean $$$\Delta$$$M and CBF images obtained
for each PLD and labeling position for Subject 1. Fig. 4
shows the estimated ATT maps for each position, and the difference between them
(note change in scale). The estimated maps showed the expected distribution,
with minimum arrival times found in MCA (Middle Cerebral Artery) vascular
territories and greater time delays found in WM and watershed zones.
In anterior circulation (ACA + MCA) territories, the
increase in labeling distance contributed only slightly to the ATT (< 0.2 s –
green and yellow in Fig. 4). However, arrival time
differences in the 0.5-1s range were observed in the posterior
(vertebrobasilar) circulation territory (e.g. middle occipital lobe and
cerebellum), in agreement with previous results5. These differences
are larger than expected based only on the approximately 40% lower velocity in
the vertebral arteries as compared to the internal carotid arteries6, suggesting that additional
factors such as the increased tortuosity of the posterior circulation
contribute.
Conclusion
Bolus arrival time is not linearly dependent on the labeling
position distance, and there are large differences in the effects of labeling
position between anterior and posterior circulation territories. Labeling
position-dependent MT effects must be also considered, particularly for
background-suppressed ASL. Future work will explore these effects in a larger
sample.
Acknowledgements
NIH grants P41EB015893 and MH080729.References
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