Department of Biomedical Engineering, Yale University, P. O. Box 208048, New Haven, CT, 06520-8048, USA.
Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P. O. Box 208048, New Haven, CT, 06520-8048, USA.
Med Phys. 2018 Feb;45(2):639-654. doi: 10.1002/mp.12710. Epub 2017 Dec 30.
Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T).
PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated Rb dataset, including a perfusion defect, as well as a human Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a function of iteration.
Convergence of direct reconstruction was slow with uniform initialization; lower bias was achieved in fewer iterations by initializing with the filtered indirect iteration 1 images. For most parameters and regions evaluated, the direct method achieved the same or lower absolute bias at matched iteration as the indirect method, with 23%-65% lower noise. Additionally, the direct method gave better contrast between the perfusion defect and surrounding normal tissue than the indirect method. Gated parametric images from the human dataset had comparable relative performance of indirect and direct, in terms of mean parameter values per iteration. Changes in myocardial wall thickness and blood pool size across gates were readily visible in the gated parametric images, with higher contrast between myocardium and left ventricle blood pool in parametric images than gated SUV images.
Direct reconstruction can produce parametric images with less noise than the indirect method, opening the potential utility of gated parametric imaging for perfusion PET.
心脏灌注 PET 数据可以重建为动态序列，并进行动力学建模以定量测量心肌血流，也可以重建为静态门控图像以定量测量功能。传统上，动态 PET 的参数图像不进行门控，以便使用具有更低噪声的所有事件。动态 PET 的另一种方法是将动力学模型直接纳入重建算法本身，而不是生成发射图像的时间序列，从而直接生成参数图像。所谓的“直接重建”可以产生比传统方法噪声更低的参数图像，因为噪声分布在投影空间中比在图像空间中更容易建模。在这项工作中，我们通过扩展用于分辨率恢复重建的参数运动补偿有序子集最大似然算法（PMOLAR-1T），为 Rb PET 的心脏门控参数图像进行了直接重建。
PMOLAR-1T 进行了扩展，以适应模型项，以解释左心室和右心室向心肌溢出的影响。该算法在包括灌注缺陷的 4D 模拟 Rb 数据集以及人类 Rb 列表模式采集上进行了评估。模拟列表模式被重复采样，每个样本的计数与门控采集的一个门相当。对于模拟数据的 8 个低计数和 8 个正常计数重复，以及人类数据的 8 个心脏门，通过间接（单独重建和建模）和直接方法为每个数据产生了参数图像。对于直接方法，测试了两种初始化方案：均匀初始化和间接方法的滤波迭代 1 结果的初始化。对于人类数据集，包括了事件逐次的呼吸运动补偿。根据迭代，直接和间接方法在模拟数据集上的偏差和变异系数方面进行了比较。
均匀初始化时，直接重建的收敛速度较慢；通过用间接迭代 1 的滤波图像初始化，在较少的迭代中可以获得更低的偏差。对于大多数评估的参数和区域，直接方法在匹配迭代时达到了相同或更低的绝对偏差，噪声降低了 23%至 65%。此外，与间接方法相比，直接方法在灌注缺陷和周围正常组织之间产生了更好的对比度。从人类数据集获得的门控参数图像在间接和直接方法的每一次迭代中，参数值的平均性能都具有可比性。在门控参数图像中，可以清楚地看到心肌壁厚度和血池大小在门之间的变化，参数图像中的心肌和左心室血池之间的对比度高于门控 SUV 图像。
直接重建可以产生比间接方法噪声更低的参数图像，为灌注 PET 的门控参数成像提供了潜在的应用。
