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Highly Efficient Motion-Corrected Simultaneous Cardiac PET-MR Imaging

机译:高效的运动校正同步心脏PET-MR成像

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摘要

MR-based motion correction of PET data has been proposed as a high-impact application for improving image quality and myocardial tissue quantification in cardiac PET-MR imaging. However, current PET-MR motion compensation schemes acquire only motion information from MR data during PET acquisition time and diagnostic MR afterwards, significantly increasing total exam time. Here we propose an efficient acquisition and reconstruction scheme for simultaneous cardiac PET-MR imaging that acquires both diagnostic and motion information from MR, with motion information being used to correct both PET and MR data. The proposed MR acquisition scheme includes acquiring low-resolution 2D image navigators at each heartbeat by spatially encoding the start-up echoes of an ECG-gated gradient echo sequence, allowing for 100% MR scan efficiency (i.e. all data is accepted for reconstruction, reducing scan time). These 2D image navigators are then used to estimate foot-head and right-left motion of the heart during the respiratory cycle in a beat-to-beat fashion, providing motion estimates to translationally correct and bin the MR data. MR images from each respiratory bin are used to estimate 3D non-rigid motion between respiratory bins. These non-rigid motion fields are then used for correcting both the MR and PET data. Results from healthy volunteers show that motion correction improves MR visualisation of the right and left anterior descending coronary arteries. A simulated PET acquisition showed improvements in contrast of the myocardium and better depiction of papillary muscles when applying motion correction. The presented framework improves image quality and contrast compared with uncorrected images for both MR and PET images.
机译:已提出将基于MR的PET数据进行运动校正作为一种有影响力的应用程序,以改善心脏PET-MR成像中的图像质量和心肌组织定量。但是,当前的PET-MR运动补偿方案在PET采集时间和诊断MR之后仅从MR数据中获取运动信息,从而大大增加了总检查时间。在这里,我们提出了一种用于同步心脏PET-MR成像的有效采集和重建方案,该方案可以从MR获取诊断信息和运动信息,同时使用运动信息来校正PET和MR数据。拟议的MR采集方案包括通过对ECG门控梯度回波序列的启动回波进行空间编码来在每个心跳处采集低分辨率2D图像导航器,从而实现100%MR扫描效率(即,接受所有数据进行重建,降低扫描时间)。然后使用这些2D图像导航器以逐跳的方式估计呼吸周期内心脏的脚头和左右运动,从而提供运动估计值以平移校正和合并MR数据。来自每个呼吸箱的MR图像用于估计呼吸箱之间的3D非刚性运动。然后将这些非刚性运动场用于校正MR和PET数据。健康志愿者的结果表明,运动校正可改善右前和左前冠状动脉的MR可视化。模拟PET采集显示,在进行运动校正时,心肌的对比度得到改善,乳头肌的描绘更好。与未校正的MR和PET图像相比,该框架可以改善图像质量和对比度。

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