Department of Radiology, Perelman School of Medicine, University of Pennsylvania, United States of America.
Phys Med Biol. 2022 Apr 21;67(9). doi: 10.1088/1361-6560/ac62fc.
Scattered events add bias in the reconstructed positron emission tomography (PET) images. Our objective is the accurate estimation of the scatter distribution, required for an effective scatter correction.In this paper, we propose a practical energy-based (EB) scatter estimation method that uses the marked difference between the energy distribution of the non-scattered and scattered events in the presence of randoms. In contrast to previous EB methods, we model the unscattered events using data obtained from measured point sources.We demonstrate feasibility using Monte Carlo simulated as well as experimental data acquired on the long axial field-of-view (FOV) PennPET EXPLORER scanner. Simulations show that the EB scatter estimated sinograms, for all phantoms, are in excellent agreement with the ground truth scatter distribution, known from the simulated data. Using the standard NEMA image quality (IQ) phantom we find that both the EB and single scatter simulation (SSS) provide good contrast recovery values. However, the EB correction gives better lung residuals.Application of the EB method on measured data showed, that the proposed method can be successfully translated to real-world PET scanners. When applied to a 20 cm diameter ×20 cm long cylindrical phantom the EB and SSS algorithms demonstrated very similar performance. However, on a larger 35 cm × 30 cm long cylinder the EB can better account for increased multiple scattering and out-of-FOV activity, providing more uniform images with 12%-36% reduced background variability. In typical PET ring sizes, the EB estimation can be performed in a matter of a few seconds compared to the several minutes needed for SSS, leading to efficiency advantages over the SSS implementation. as well.
散射事件会给重建的正电子发射断层扫描（PET）图像带来偏差。我们的目标是准确估计散射分布，这是进行有效散射校正所必需的。在本文中，我们提出了一种实用的基于能量（EB）的散射估计方法，该方法利用随机事件存在时非散射和散射事件能量分布之间的明显差异。与之前的 EB 方法不同，我们使用从测量点源获得的数据来模拟未散射事件。我们使用在长轴向视野（FOV）PennPET EXPLORER 扫描仪上获得的蒙特卡罗模拟和实验数据证明了该方法的可行性。模拟结果表明，对于所有体模，EB 估计的散射正弦图与从模拟数据中已知的真实散射分布非常吻合。使用标准的 NEMA 图像质量（IQ）体模，我们发现 EB 和单散射模拟（SSS）都能提供良好的对比度恢复值。然而，EB 校正能提供更好的肺部残差。在实测数据上的应用表明，所提出的方法可以成功地应用于实际的 PET 扫描仪。当应用于直径为 20cm、长为 20cm 的圆柱形体模时，EB 和 SSS 算法表现出非常相似的性能。然而，在更大的 35cm×30cm 长的圆柱体上，EB 可以更好地考虑增加的多次散射和视野外活动，提供更均匀的图像，背景变化减少 12%-36%。在典型的 PET 环尺寸下，EB 估计可以在几秒钟内完成，而 SSS 需要几分钟，因此在效率方面优于 SSS 实现。
