Department of Biomedical Engineering, University of California, Davis, CA, United States of America.
Department of Radiology, University of California, Davis, Sacramento, CA, United States of America.
Phys Med Biol. 2024 Oct 23;69(21). doi: 10.1088/1361-6560/ad84b5.
. This study presents a universal phantom for positron emission tomography (PET) that allows arbitrary static and dynamic activity distributions of various complexities to be generated using a single PET acquisition.. We collected a high-statistics dataset (with a total of 22.4 × 10prompt coincidences and an event density of 2.75 × 10events mm) by raster-scanning a single plane with aNa point source mounted on a robotic arm in the field-of-view of the uEXPLORER PET/CT scanner. The source position was determined from the reconstructed dynamic frames. Uniquely, true coincidences were separated from scattered and random events based on the distance between their line-of-response and the known source location. Finally, we randomly sampled the dataset to generate the desired activity distributions modeling several different phantoms.. Overall, the target and the reconstructed phantom images had good agreement. The analysis of a simple geometric distribution showed high quantitative accuracy of the phantom, with mean error of <-3.0% relative to the ground truth for activity concentrations ranging from 5.3 to 47.7 kBq ml. The model of a high-resolutionF-fluorodeoxyglucose distribution in the brain illustrates the usefulness of the technique in simulating realistic static neuroimaging studies. A dynamicF-florbetaben study was modeled based on the time-activity curves of a human study and a segmented brain phantom with no coincidences repeating between frames. For all time points, the mean voxel-wise errors ranged from -4.4% to -0.7% in grey matter and from -3.9% to +2.8% in white matter.. The proposed phantom technique is highly flexible and allows modeling of static and dynamic brain PET studies with high quantitative accuracy. It overcomes several key limitations of the existing phantoms and has many promising applications for the purposes of image reconstruction, data correction methods, and system performance evaluation, particularly for new high-performance dedicated brain PET scanners.
. 本研究提出了一种通用的正电子发射断层扫描 (PET) 体模,允许使用单个 PET 采集生成各种复杂度的任意静态和动态活动分布。. 我们使用安装在 uEXPLORER PET/CT 扫描仪视场中的机械臂上的Na 点源对单个平面进行光栅扫描,收集了具有高统计数据的数据集(总共有 22.4 × 10 个prompt 符合事件,事件密度为 2.75 × 10 个事件 mm)。源位置是从重建的动态帧中确定的。独特的是,根据线响应和已知源位置之间的距离,从散射和随机事件中分离出真实符合事件。最后,我们随机抽样数据集以生成模拟几种不同体模的所需活动分布。. 总体而言,目标和重建的体模图像具有很好的一致性。对简单几何分布的分析表明体模具有很高的定量准确性,对于活动浓度范围为 5.3 至 47.7 kBq ml 的情况,相对于真实值的平均误差为 <-3.0%。在大脑中高分辨率 F-氟脱氧葡萄糖分布的模型说明了该技术在模拟现实静态神经成像研究中的有用性。根据人类研究的时间-活性曲线和没有帧间重复符合事件的分段脑体模,模拟了 F-氟苯丙胺的动态研究。对于所有时间点,灰质的平均体素误差范围为 -4.4% 至 -0.7%,白质的平均体素误差范围为 -3.9% 至 +2.8%。. 提出的体模技术具有高度的灵活性,可以对具有高定量准确性的静态和动态脑 PET 研究进行建模。它克服了现有体模的几个关键限制,并为图像重建、数据校正方法和系统性能评估等方面提供了许多有前途的应用,特别是对于新型高性能专用脑 PET 扫描仪。