This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction.

中文翻译：

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使用物理和数学建模对 STIR 库中的飞行时间 PET-MR 扫描仪进行 PET 图像重建

这项工作展示了最先进的集成 PET 和磁共振成像 (PET-MR) 系统的正电子发射断层扫描 (PET) 图像采集过程的计算和物理建模如何产生与制造商相当的图像。GE SIGNA PET/MR 扫描仪由通用电气制造，具有约 390 ps 的飞行时间 (TOF) 能力。所有软件开发都在断层图像重建软件 (STIR: http://stir.sf.net) 库中进行，该库是一种广泛使用的开源软件，用于重建从发射断层扫描仪导出的数据。新的软件开发将集成到 STIR 中，为世界各地的研究人员提供机会来建立和扩展他们的图像重建方法。此外，这项工作特别重要，因为它首次验证了使用 STIR 库对真实扫描仪数据集进行 TOF PET 图像重建。本文介绍了实施独立重建软件包时遇到的方法论、分析和关键问题。获取的 PET 数据通过几种适当的算法进行处理，这些算法是产生准确和精确的定量图像所必需的。这包括患者的数学、物理和解剖学建模以及采集的各个方面的模拟。这些包括使用每个晶体的“单次”率、探测器效率和几何效应对随机巧合进行建模。使用 STIR 的衰减校正模型计算衰减效果。在系统矩阵内对所有这些影响进行建模允许重建 PET 图像，这证明了所管理的放射性药物的代谢吸收。这些实施使用测量的体模和临床数据集进行了验证。使用有序子集期望最大化 (OSEM) 和最近提出的核化期望最大化 (KEM) 算法测试这些进展，该算法将来自 MR 图像的解剖信息合并到 PET 重建中。