Motivation: Arterial spin labeling (ASL) is prone to motion artifacts due to its intrinsically low signal-to-noise ratio and reliance on subtraction. Goal(s): To improve the motion robustness of an ASL-based combined imaging sequence. Approach: We integrated a cone trajectory and water-selective excitation into the imaging sequence, enabling more precise motion estimation with subspace-based self-navigation. Motion-corrected images were reconstructed and validated against reference scans. Results: Motion-corrected images showed significant improvements, with enhanced clarity and consistency. Motion correction improved correlations with motion-free reference data across structural, perfusion, and angiography modalities by 12%, 53%, and 159%, respectively. Impact: This work enhances the motion robustness of ASL imaging by improving navigator reconstruction under varying contrast and subtraction-based reconstruction with mismatched k-space. These improvements pave the way for broader clinical applications and more reliable diagnostic imaging.
Shen et al. (Tue,) studied this question.