Comparison of 2D and 3D single-shot ASL perfusion fMRI sequences

Abstract

Arterial Spin Labeling (ASL) can be implemented by combining different labeling schemes and readout sequences. In this study, the performance of 2D and 3D single-shot pulsed-continuous ASL (pCASL) sequences was assessed in a group of young healthy volunteers undergoing a baseline perfusion and a functional study with a sensory-motor activation paradigm. The evaluated sequences were 2D echo-planar imaging (2D EPI), 3D single-shot fast spin echo with in-plane spiral readout (3D FSE spiral), and 3D single-shot gradient-and-spin-echo (3D GRASE). The 3D sequences were implemented with and without the addition of an optimized background suppression (BS) scheme. Labeling efficiency, signal-to-noise ratio (SNR), and gray matter (GM) to white matter (WM) contrast ratio were assessed in baseline perfusion measurements. 3D acquisitions without BS yielded 2-fold increments in spatial SNR, but no change in temporal SNR. The addition of BS to the 3D sequences yielded a 3-fold temporal SNR increase compared to the unsuppressed sequences. 2D EPI provided better GM-to-WM contrast ratio than the 3D sequences. The analysis of functional data at the subject level showed a 3-fold increase in statistical power for the BS 3D sequences, although the improvement was attenuated at the group level. 3D without BS did not increase the maximum t-values, however, it yielded larger activation clusters than 2D. These results demonstrate that BS 3D single-shot imaging sequences improve the performance of pCASL in baseline and activation studies, particularly for individual subject analyses where the improvement in temporal SNR translates into markedly enhanced power for task activation detection.

Multi-vendor reliability of arterial spin labeling perfusion MRI using a near-identical sequence: Implications for multi-center studies

“…The largest difference between vendors in that study was the difference in spatial blurring between the readouts and reconstruction as used by both vendors, which was reflected in the GM-WM CBF contrast. Whereas the GM-WM CBF ratio differed by a factor 2 between 2D and 3D readouts, this ratio was very consistent in the present results, ranging from 3.5-3.9 for all vendors (Kilroy et al, 2014;Mutsaerts et al, 2014;Vidorreta et al, 2012). This indicates that if a similar readout and reconstruction is used, ASL results are comparable between vendors, despite residual hardware differences such as differences in gradient or coil specifications.…”

“…Although the SNR penalty by disabling the image enhancement features were counterbalanced by longer scanning as well as scanning healthy young volunteers, the results of the current study are expected to deviate from normal clinical or research practice. These enhancement features may reduce the intra-scanner variability because of increased SNR, but may increase the inter-vendor variability because they are implementations that may vary between vendors (Vidorreta et al, 2012). It remains unknown to what extent these features can affect the multi-center reproducibility of ASL.…”

“…1a Kilroy et al, 2014). On a group level, it is currently not possible to compare CBF-values from a single region of interest (ROI) in a multi-center study, mainly because of differences in readout between sequences from different vendors Vidorreta et al, 2012). Global CBF-values, however, show quantitative agreement between vendors .…”

Reliability comparison of spontaneous brain activities between BOLD and CBF contrasts in eyes-open and eyes-closed resting states

“…For those regions with ICC of CBF-ALFF and CBF-FC lower than 0.4, researchers should consider using corresponding metrics based on BOLD contrast. Future studies targeting improving reliability of CBF dynamics should aim at increasing its sensitivity and temporal resolution such as optimized background suppression (Maleki et al, 2012) and labeling schemes (Vidorreta et al, 2013).…”

Temporal and Spatial Variances in Arterial Spin-Labeling Are Inversely Related to Large-Artery Blood Velocity

“…Studies that have empirically estimated labeling efficiency by normalizing pseudocontinuous ASL-based whole-brain CBF to that measured with PC imaging report individual labeling efficiencies ranging from 0.7 to 1.1. 8,10 Recent work in a large middle-aged cohort, however, has questioned the validity of this normalization method due to substan-tial variability within individual measurements. 11 Rather than incorporating PC-based CBF as a normalization factor, corresponding knowledge of PC-based metrics, such as blood velocity, may be beneficial for planning ASL protocols because many labeling and acquisition parameters are timing-based.…”