Effect of labeling position on MT effects and Bolus Arrival Time
Marta Vidorreta1,2, Yulin V Chang2, and John A Detre1,2

### 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 MRI1 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

1. Detre JA, Leigh JS, Williams DS, Koretsky AP. Perfusion imaging. Magnetic resonance in medicine. 1992;23(1):37–45.

2. Vidorreta M, Balteau E, Wang Z, De Vita E, Pastor MA, Thomas DL, Detre JA, Fernández-Seara MA. Evaluation of segmented 3D acquisition schemes for whole-brain high-resolution arterial spin labeling at 3T. NMR in Biomedicine. 2014;27(11):1387–1396.

3. Wang J, Zhang Y, Wolf RL, Roc AC, Alsop DC, Detre JA. Amplitude-modulated Continuous Arterial Spin-labeling 3.0-T Perfusion MR Imaging with a Single Coil: Feasibility Study. Radiology. 2005;235:218–228.

4. Chappell MA, Groves A, Woolrich MW. Variational Bayesian inference for a non-linear forward model. IEEE transactions on signal processing. 2009;57(1):223–236.

5. Chen Y, Wang DJJ, Detre JA. Comparison of arterial transit times estimated using arterial spin labeling. Magnetic Resonance Materials In Physics Biology And Medicine. 2012;25(2):135–44.

6. Schoning M, Walter J, Scheel P. Estimation of cerebral blood flow through color duplex sonography of the carotid and vertebral arteries in healthy adults. Stroke. 1994;25(1):17–22.

### Figures

Sagittal and coronal views of the Time-Of-Flight (TOF) acquired in Subject 1, to illustrate the labeling plane positions chosen here (blue=120 mm, red=90 mm with respect to the center of the imaging slab). A sagittal view is also displayed for anatomical reference.

(A) Mean ASL image and M0 ratio as a function of position, showing a significant effect of labeling location (median=2.9% and 3.2% across all PLDs, p = 0.0078 Wilcoxon signed rank test). Mean M0 value is also shown for comparison. (B) Global perfusion time curves as a function of PLD and labeling location.

Mean perfusion ($\Delta$M) images and ATT map (last column) of Subject 1.

Estimated arterial transit time (ATT) maps and difference between labeling plane positions. In Subject 1, one extra PLD time with PLD=200 ms was acquired, likely enhancing the estimation of the shortest ATT regions.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
2883