Non-Model-Based Correction of Respiratory Motion Using Beat-to-Beat 3D Spiral Fat-Selective Imaging


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Abstract

Purpose:To demonstrate the feasibility of retrospective beat-to-beat correction of respiratory motion, without the need for a respiratory motion model.Materials and Methods:A high-resolution three-dimensional (3D) spiral black-blood scan of the right coronary artery (RCA) of six healthy volunteers was acquired over 160 cardiac cycles without respiratory gating. One spiral interleaf was acquired per cardiac cycle, prior to each of which a complete low-resolution fat-selective 3D spiral dataset was acquired. The respiratory motion (3D translation) on each cardiac cycle was determined by cross-correlating a region of interest (ROI) in the fat around the artery in the low-resolution datasets with that on a reference end-expiratory dataset. The measured translations were used to correct the raw data of the high-resolution spiral interleaves.Results:Beat-to-beat correction provided consistently good results, with the image quality being better than that obtained with a fixed superior–inferior tracking factor of 0.6 and better than (N = 5) or equal to (N = 1) that achieved using a subject-specific retrospective 3D translation motion model.Conclusion:Non-model-based correction of respiratory motion using 3D spiral fat-selective imaging is feasible, and in this small group of volunteers produced better-quality images than a subject-specific retrospective 3D translation motion model.

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