GOAL-SANP is a promising technique for carotid atherosclerotic plaque T1 mapping using 3D golden angle radial acquisition. However, sever patient abrupt motion is still a challenge for this sequence. In this study, a self-navigated retrospective motion correction scheme based on independent components analysis (ICA) and peak filtering was developed for GOAL-SNAP utilizing the advantage of its 3D golden angle radial trajectory. The results validated the feasibility of the proposed method to detect the abrupt motion (cough) and correct the related artifacts for carotid vessel wall imaging.
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