Improved T2-Weighted Cardiac Imaging using Retrospective Motion Correction and Optimal Image Combination

Introduction T2-weighted (T2w) cardiac MR imaging has established reputation as a sensitive technique to depict myocardial edema related to acute infarction. Together with delayed enhancement technique, T2w demonstrated valuable clinical potentials to differentiate acute damage from chronic infarction [1]. To minimize the myocardial signal loss caused by through-plane motion, T2w can be performed in a single-shot fashion using a recently developed T2-prepared SSFP (T2p-SSFP) sequences which outperformed established turbo spin echo based techniques for fewer artifacts and better diagnostic accuracy [2]. Instead of performing segmented imaging which requires multiple breath-holds to image the heart, the clinical acquisition tends to execute free-breathing studies, partly due to considerable difficulties/discomfort of breath-holding for patients who had recently experienced an acute myocardial infarction. As a shortcoming, the free-breathing, single-shot T2w imaging often has to compromise spatial/temporal resolution or sacrifice signal-to-noise ratio (SNR) to fit into a tight acquisition window within the cardiac cycle, despite the broad use of parallel imaging and rapid imaging sequences. On the other hand, recent development in cardiac MR shows that improved SNR can be achieved by selectively averaging motion-corrected free-breathing images using non-rigid image registration methods. Substantial SNR gains have been reported for high spatial and temporal resolution cardiac cine [3], free-breathing delayed enhancement imaging [4], and free-breathing single-shot fat-water separated cardiac imaging [5]. All these studies rely on retrospectively applying image registration to correct heart motion across multiple heart beats. The corrected images can be averaged to achieve good noise suppression. In this work we present dedicated retrospective techniques to improve the free-breathing, single-shot T2w imaging using motion correction and image combination. Unlike previous studies where heuristic criteria were applied to exclude some frames from final averaging to avoid visible artifacts introduced by imperfect non-rigid motion correction, an optimal image combination algorithm was utilized here, computing a weighting function to minimize the total deformation brought into the averaging.