Robust dual-module velocity-selective arterial spin labeling (dm-VSASL) with velocity-selective saturation and inversion

Purpose Compared to conventional arterial spin labeling (ASL) methods, velocity-selective ASL (VSASL) is more sensitive to artifacts from eddy currents, diffusion attenuation, and motion. Background suppression is typically suboptimal in VSASL, especially of CSF. As a result, the temporal SNR and quantification accuracy of VSASL are compromised, hindering its application despite its advantage of being delay-insensitive. Methods A novel dual-module VSASL (dm-VSASL) strategy is developed to improve the SNR efficiency and the temporal SNR with a more balanced gradient configuration in the label/control image acquisition. This strategy applies for both VS saturation (VSS) and VS inversion (VSI) labeling. The dm-VSASL schemes were compared with single-module labeling and a previously developed multi-module schemes for the SNR performance, background suppression efficacy, and sensitivity to artifacts in simulation and in vivo experiments, using pulsed ASL as the reference. Results Dm-VSASL enabled more robust labeling and efficient backgroud suppre across brain tissues, especially of CSF, resulting in significantly reduced artifacts and improved temporal SNR. Compared to single-module labeling, dm-VSASL significantly improved the temporal SNR in gray (by 90.8% and 94.9% for dm-VSS and dm-VSI, respectively; P < 0.001) and white (by 41.5% and 55.1% for dm-VSS and dm-VSI, respectively; P < 0.002) matter. Dm-VSI also improved the SNR of VSI by 5.4% (P = 0.018). Conclusion Dm-VSASL can significantly improve the robustness of VS labeling, reduce artifacts, and allow efficient background suppression. When implemented with VSI, it provides the highest SNR efficiency among VSASL methods. Dm-VSASL is a powerful ASL method for robust, accurate, and delay-insensitive perfusion mapping.

Automated summary

A novel dual-module velocity-selective arterial spin labeling (dm-VSASL) strategy is developed to improve the signal-to-noise ratio (SNR) efficiency and the temporal SNR for robust, accurate, and delay-insensitive perfusion mapping.