Germino Mary, Gallezot Jean-Dominque, Yan Jianhua, Carson Richard E
Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America.
Phys Med Biol. 2017 Jul 7;62(13):5344-5364. doi: 10.1088/1361-6560/aa731f. Epub 2017 May 15.
Parametric images for dynamic positron emission tomography (PET) are typically generated by an indirect method, i.e. reconstructing a time series of emission images, then fitting a kinetic model to each voxel time activity curve. Alternatively, 'direct reconstruction', incorporates the kinetic model into the reconstruction algorithm itself, directly producing parametric images from projection data. Direct reconstruction has been shown to achieve parametric images with lower standard error than the indirect method. Here, we present direct reconstruction for brain PET using event-by-event motion correction of list-mode data, applied to two tracers. Event-by-event motion correction was implemented for direct reconstruction in the Parametric Motion-compensation OSEM List-mode Algorithm for Resolution-recovery reconstruction. The direct implementation was tested on simulated and human datasets with tracers [C]AFM (serotonin transporter) and [C]UCB-J (synaptic density), which follow the 1-tissue compartment model. Rigid head motion was tracked with the Vicra system. Parametric images of K and distribution volume (V = K /k ) were compared to those generated by the indirect method by regional coefficient of variation (CoV). Performance across count levels was assessed using sub-sampled datasets. For simulated and real datasets at high counts, the two methods estimated K and V with comparable accuracy. At lower count levels, the direct method was substantially more robust to outliers than the indirect method. Compared to the indirect method, direct reconstruction reduced regional K CoV by 35-48% (simulated dataset), 39-43% ([C]AFM dataset) and 30-36% ([C]UCB-J dataset) across count levels (averaged over regions at matched iteration); V CoV was reduced by 51-58%, 54-60% and 30-46%, respectively. Motion correction played an important role in the dataset with larger motion: correction increased regional V by 51% on average in the [C]UCB-J dataset. Direct reconstruction of dynamic brain PET with event-by-event motion correction is achievable and dramatically more robust to noise in V images than the indirect method.
动态正电子发射断层扫描（PET）的参数图像通常通过间接方法生成，即重建发射图像的时间序列，然后将动力学模型拟合到每个体素时间活动曲线。或者，“直接重建”将动力学模型纳入重建算法本身，直接从投影数据生成参数图像。已证明直接重建比间接方法能获得标准误差更低的参数图像。在此，我们展示了使用列表模式数据的逐事件运动校正对脑PET进行直接重建，并将其应用于两种示踪剂。在用于分辨率恢复重建的参数运动补偿OSEM列表模式算法中，为直接重建实现了逐事件运动校正。在模拟数据集和人体数据集上，使用示踪剂[C]AFM（血清素转运体）和[C]UCB - J（突触密度）对直接实现进行了测试，这两种示踪剂遵循单组织隔室模型。使用Vicra系统跟踪头部刚性运动。通过区域变异系数（CoV）将K和分布容积（V = K /k） 的参数图像与间接方法生成的图像进行比较。使用子采样数据集评估不同计数水平下的性能。对于高计数的模拟数据集和真实数据集，两种方法估计K和V的准确性相当。在较低计数水平下，直接方法比间接方法对异常值的鲁棒性要强得多。与间接方法相比，直接重建在不同计数水平下（在匹配迭代的区域上平均）使区域K的CoV降低了35 - 48%（模拟数据集）、39 - 43%（[C]AFM数据集）和30 - 36%（[C]UCB - J数据集）；V的CoV分别降低了51 - 58%、54 - 60%和30 - 46%。运动校正在运动较大的数据集中起着重要作用：在[C]UCB - J数据集中，校正使区域V平均增加了51%。对动态脑PET进行带逐事件运动校正的直接重建是可行的，并且在V图像中对噪声的鲁棒性比间接方法显著更强。
