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Abstract #4436

3D-cone acquisition for improved combined angiography, structural and perfusion imaging with subspace-based motion correction

Qijia Shen1, Wenchuan Wu1, Mark Chiew2, Yang Ji1, Joseph G. Woods1, and Thomas W. Okell1
1University of Oxford, Oxford, United Kingdom, 2University of Toronto, Toronto, ON, Canada

Synopsis

Keywords: Motion Correction, Motion Correction, Arterial spin labeling, perfusion, angiography

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.

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Keywords