Motion Compensation for Free-Breathing Diffusion-Weighted Imaging (MoCo DWI) in Whole Body Integrated PET-MRI

摘要

The acquisition duration of diffusion-weighted imaging (DWI) in the abdomen may cause motion blurring artifacts due to respiratory motion. The prevention or removal of respiratory motion artifacts can be done by breath holding [1] , prospective (automated) triggering during image acquisition, or retrospective motion compensation. Due to a typical acquisition duration of 4 min [1] , multiple breath holds are required, making this approach unfavorable for routine use. The alternative prospective triggering prolongs the acquisition roughly twofold. Retrospective motion compensation (MoCo) aims mainly at correction of phase errors or detects motion directly on the DW images. However, image-based motion detection is challenging as DWI predominantly shows tissue with restricted diffusion and has decreasing signal-to-noise ratio with increasing b -value [2] . Therefore, we propose a novel approach by using a stack-of-stars spoiled gradient-echo (GRE) sequence to create a motion model to correct a free-breathing DWI acquisition. This work aims towards PET-MR diagnostics where the same stack-of-stars sequence can be used for PET motion correction [3] . Hence, the motion model would be re-used and the overall acquisition time would not be extended by the new motion compensated DWI.