Background suppression (BGS) in arterial spin labeling (ASL) leads to perfusion images with a higher temporal signal-to-noise ratio (tSNR) compared to ASL without BGS. The optimal inversion times (TIs), and therefore the quality of the BGS, depend on the T1 relaxation times of the underlying tissue and on inhomogeneities of the scanner’s magnetic fields (B0, B1+). In this work, we designed and implemented a feedback mechanism that optimized the quality of background suppression in real time on the scanner. The results show an increased tSNR for the subject-specific optimization of BGS compared to standard BGS in 12 healthy volunteers.
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