Abstract
To investigate the effects of prospective motion correction on turbo spin echo sequences and optimize motion correction approaches, mitigating signal dropout artifacts caused by the imperfections of motion tracking data. Signal dropout artifacts caused by undesired phase deviations introduced by tracking errors are analyzed theoretically. To reduce the adverse effect of such deviations, two approaches are proposed: (1) freezing the correction for example, for even-numbered or higher number of echoes and (2) shifting the correction event prior to the left crusher gradient preceding the refocusing pulse. A comprehensive analysis is presented, including both signal simulations and experimental verifications in phantoms and in vivo. Performance of the proposed approach is validated in two healthy volunteers imaged under two types of motion conditions simulating inadvertent fast motions associated with discomfort and continuous large motions. The results show that the proposed optimization is able to efficiently correct for the motion artifacts and at the same time avoid signal dropout artifacts. Specifically, performing correction every 4th echo prior to the left crusher gradient was shown to improve image quality. An optimization approach is proposed to exploit the potential of external tracking for intra-echo-train motion artifact correction for turbo spin echo sequences.
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