Optimizing the T1-mapping GOAL-SNAP MRA with Histogram-Matching-Based Multi-Frame Combination

Motivation: GOAL-SNAP, a sequence designed for T1 value measurement of vessel walls, shows promise in generating MRA images for intracranial vessel visualization, albeit with opportunities for further improvement. Goal(s): To introduce a novel approach to optimize GOAL-SNAP MRA. Approach: A histogram-matching-based approach was developed to optimize GOAL-SNAP MRA. This technique combined multiple GOAL-SNAP frames and utilizes histogram matching to suppress background signals and improve the contrast between vessels and background. Results: Contrast-to-noise (CNR) and visualization evaluation demonstrated the effectiveness of the optimized GOAL-SNAP MRA, exhibiting comparable performance to TOF and superior visualization of distal vessels. Impact: A novel histogram-matching-based multi-frame combination approach improved GOAL-SNAP MRA for intracranial vessel visualization and vascular stenosis assessment, with comparable performance to TOF and superior visualization of distal vessels.