Enabling free‐breathing background suppressed renal pCASL using fat imaging and retrospective motion correction

PURPOSE: For free‐breathing renal perfusion imaging using arterial spin labeling (ASL), retrospective image realignment has been found essential to reduce subtraction artifacts and, independently, background suppression has been demonstrated to reduce physiologic noise. However, negative results on ASL precision and accuracy have been reported for the combination of both. In this study, the effect of background suppression ‐level in combination with image registration on free‐breathing renal ASL signal quality, with registration either on ASL‐images themselves or guided by additionally acquired fat‐images, was investigated. The results from free‐breathing acquisitions were compared with the reference paced‐breathing motion compensation strategy. METHODS: Pseudocontinuous ASL (pCASL) data with additional fat‐images were acquired from 10 subjects at 1.5T with varying background suppression levels during free‐breathing and paced‐breathing. Images were registered using the ASL‐images themselves (ASLReg) or using their corresponding fat‐images (FatReg). Temporal signal‐to‐noise ratio (tSNR) served to evaluate precision and perfusion weighted signal (PWS) to assess accuracy. RESULTS: In combination with image registration, background suppression significantly improved tSNR by 50% (P < .05). For heavy suppression, ASLReg and FatReg showed similar performance in terms of tSNR and PWS. Background suppression with two inversion pulses induced a small, nonsignificant (P > .05) PWS reduction, but increased PWS accuracy. When applying heavy background suppression, free‐breathing acquisitions resulted in similar ASL‐quality to paced‐breathing acquisitions. CONCLUSION: Background suppression was found beneficial for free‐breathing renal pCASL precision without compromising accuracy, despite motion challenges. In combination with ASLReg or FatReg, background suppression enabled clinically viable free‐breathing renal pCASL.