Data-driven Motion Correction for Paced and Free Breathing Kidney Arterial Spin Labeling

Motivation: Arterial spin labeling (ASL) perfusion imaging outside the brain is challenging due to motion. Solution to this requires either changes to the acquisition, external hardware, or subject training. Goal(s): Develop retrospective motion correction to improve kidney perfusion and renal blood flow (RBF) maps from paced and free breathing ASL without modification to acquisition or external hardware. Approach: We choose a subset of the available ASL dynamics based on maximizing low-rank energy of the spatiotemporal dynamics. Results: he proposed motion correction framework increases cortex SNR in perfusion maps and increases corticomedullary RBF ratio on six subjects who performed paced breathing. Impact: This study demonstrates the potential to improve poor-quality paced-breathing kidney ASL and suggests broader applicability to free breathing scenarios. Other dynamic body MRI applications may also benefit from this simple motion correction approach.