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MR-based cardiac and respiratory motion correction of PET: Application to static and dynamic cardiac 18F-FDG imaging

机译:宠物MR的心脏和呼吸运动校正:应用于静态和动态心脏18F-FDG成像

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Motion of the myocardium deteriorates the quality and quantitative accuracy of cardiac PET images. We present a method for MR-based cardiac and respiratory motion correction of cardiac PET data and evaluate its impact on estimation of activity and kinetic parameters in human subjects. Three healthy subjects underwent simultaneous dynamic 18F-FDG PET and MRI on a hybrid PET/MR scanner. A cardiorespiratory motion field was determined for each subject using navigator, tagging and golden-angle radial MR acquisitions. Acquired coincidence events were binned into cardiac and respiratory phases using electrocardiogram and list mode-driven signals, respectively. Dynamic PET images were reconstructed with MR-based motion correction (MC) and without motion correction (NMC). Parametric images of 18F-FDG consumption rates (Ki) were estimated using Patlak's method for both MC and NMC images. MC alleviated motion artifacts in PET images, resulting in improved spatial resolution, improved recovery of activity in the myocardium wall and reduced spillover from the myocardium to the left ventricle cavity. Significantly higher myocardium contrast-to-noise ratio and lower apparent wall thickness were obtained in MC versus NMC images. Likewise, parametric images of Ki calculated with MC data had improved spatial resolution as compared to those obtained with NMC. Consistent with an increase in reconstructed activity concentration in the frames used during kinetic analyses, MC led to the estimation of higher Ki values almost everywhere in the myocardium, with up to 18% increase (mean across subjects) in the septum as compared to NMC. This study shows that MR-based motion correction of cardiac PET results in improved image quality that can benefit both static and dynamic studies. ? 2019 Institute of Physics and Engineering in Medicine.
机译:心肌的运动恶化了心脏宠物图像的质量和定量准确性。我们介绍了一种基于MR-PET数据的心脏和呼吸运动校正的方法,并评估其对人受试者活性和动力学参数的影响。三个健康的受试者在混合宠物/ MR扫描仪上进行了同时动态的18F-FDG PET和MRI。使用导航仪,标记和金色角径向MR采集确定每个受试者的心肺运动场。使用心电图和列表模式驱动信号分别被获取的巧合事件进入心脏和呼吸阶段。用基于MR的运动校正(MC)和没有运动校正(NMC)来重建动态PET图像。使用Patlak的MC和NMC图像的方法估计了18F-FDG消费率(KI)的参数图像。 MC缓解了PET图像中的运动伪影,导致了改善的空间分辨率,改善了心肌壁中的活性恢复,并从心肌溢出到左心室腔中。在MC与NMC图像中获得显着较高的心肌对比度和较低的表观壁厚。同样地,与MC数据计算的KI的参数图像与用NMC获得的那些相比具有改善的空间分辨率。与动力学分析期间使用的帧中使用的重建活性浓度的增加一致,MC几乎在心肌中几乎无所不在的估计较高的Ki值,与NMC相比,隔膜中的高达18%(对象横跨受试者)。本研究表明,心脏宠物的基于MR的运动校正导致改善的图像质量,可以有利于静态和动态研究。还是2019年医学院物理与工程研究所。

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