Theoretical and experimental optimization of random vessel-encoded ASL to improve vascular territorial mapping and CBF quantification

Motivation: Planning-free random vessel-encoded ASL (rVE-ASL) greatly simplifies the vessel-selective ASL scan settings and shows great potential for vascular territorial imaging in clinical applications. Goal(s): To theoretically and experimentally optimize rVE-ASL to establish an efficient and reliable rVE-ASL protocol Approach: Simulation and in-vivo experiments were conducted to evaluate and optimize rVE-ASL in terms of labeling efficiency, total number of encoding steps, and reliability of vascular territorial and CBF measurements. Results: Reliable territorial mapping and CBF measurements from both ICA and VA can be achieved by optimized rVE-ASL. At least 20 encoding steps are needed to achieve reliable territorial mapping and CBF measurements in rVE-ASL. Impact: We have theoretically and experimentally optimized rVE-ASL, which can provide reliable vascular territorial mapping and CBF quantification. The rVE-ASL technique holds a potential to be a useful imaging tool for assessing vascular territorial alterations and collaterals in various clinical applications.