GPU-based SPECT Reconstruction Using Reverse Monte Carlo Simulations

项目总结/摘要 对放射性药物缀合物的应用的兴趣在过去几年中显著增加， 治疗各种癌症。这些缀合物由靶向癌细胞的螯合剂组成， 放射性核素利用电离辐射的细胞毒性。需要进行辐射剂量测定， 这些治疗的剂量、疗效和安全性，以及活性生物分布的3D定量成像 是进行剂量测定的最佳工具。对于大多数使用的放射性核素（非正电子发射体），SPECT 需要成像用于患者特异性剂量测定。然而，多种物理因素影响SPECT图像质量， 例如SPECT扫描中的衰减、散射或响应准直器-检测器系统。以考虑 由于蒙特卡罗技术在描述物理过程方面具有显著的准确性，因此可以使用蒙特卡罗技术 与电离辐射的传输有关。特别地，从所采集的图像进行3D SPECT重建是可行的。 可以通过向后传输在伽马照相机中探测到的光子 投影，虽然许多光子被光子传输需要特别优化的架构， 模拟该项目将开发一种新的反向蒙特卡罗软件，用于SPECT重建， 在GPU中加速模拟。首先，只选择相关的反向物理过程 并使用用于辐射输运的良好表征的TOPAS蒙特卡罗代码的逆过程建模。 然后，将准直器-检测器系统的特定属性集成到我们的代码中，以确定角度 检测到的光子的分布。最后，这些开发将集成到一个基于GPU的平台中 并与NCI癌症研究计划的信息学技术共享，以获得具体的 商业SPECT扫描。

Project Summary/Abstract Interest in applications of radiopharmaceutical conjugates has notably increased in the last few years for the treatment of a variety of cancers. These conjugates are composed of chelators to target cancer cells and radionuclides to employ the cytotoxicity of ionizing radiation. Radiation dosimetry is required to determine the dosages, efficacy, and safety of these treatments, and 3D quantitative imaging of the biodistribution of activity represents the best tool to perform dosimetry. For most radionuclides employed (non-positron-emitters), SPECT imaging is needed for patient-specific dosimetry. However, multiple physical factors affect SPECT image quality, such as attenuation, scattering, or the response collimator-detector system in SPECT scans. To account for them, Monte Carlo techniques can be used due to their remarkable accuracy in representing physical processes relevant to the transport of ionizing radiation. In particular, 3D SPECT reconstruction from the acquired bidimensional projections may be obtained by transporting backward the photons detected in the gamma camera projections, although many photons to be reversely transported require specially optimized architecture and simulations. This project will develop a new reverse Monte Carlo software for SPECT reconstruction, built from scratch in the GPU to speed up simulations. First, only the relevant reverse physical processes will be selected and modeled using inverse processes of the well-characterized TOPAS Monte Carlo code for radiation transport. Then, specific properties of collimator-detector systems will be integrated into our code to determine the angular distributions for the photons detected. Finally, these developments will be integrated into a GPU-based platform and shared with the Informatics Technology for Cancer Research program at NCI for further results of specific commercial SPECT scans from the research community.