Quantitative Low-Dose PET Imaging

项目摘要 定量PET在临床管理和研究中变得越来越重要，特别是对于 预测和评估癌症患者对治疗的反应。目前的PET方案涉及注射 PET示踪剂通常对患者产生约6-7 mSv辐射剂量。对于需要多个 重复PET扫描以监测对治疗的反应，对于需要PET扫描的患者， 更多的示踪剂（例如，FDG + FLT）以最佳地预测对治疗的反应，减少辐射是至关重要的。 剂量从PET示踪剂注射，同时仍然保持定量精度和图像质量， 癌症管理当减少注射剂量时，PET图像将由于较少的 检测到的计数，这将随后在定量测量中引入误差。用于移动器官 以及诸如肺和腹部中的那些肿瘤，呼吸运动可以实质上降低定量 精度，因此需要运动校正。传统的运动校正使用门控策略， PET数据，导致每个门中的噪声显著更高。更先进的方法包括运动 用于后配准或运动补偿图像重建的图像域中的矢量估计， 所有检测到的事件都不会增加噪声。运动矢量需要从门控PET导出，其是 当在低剂量研究中使用减少的示踪剂注射时，噪音甚至更大， 精确和可靠的逐体素运动矢量估计。在临床心脏动态PET研究中， 示踪剂和其他新的肿瘤学和神经学示踪剂，定量对于低剂量 PET作为每个动态帧仅包含检测到的事件的一小部分，因此高图像噪声将 影响图像导出的输入函数的确定，并且可能导致参数化中的偏差和高噪声。 图像.在这个项目中，为了减少图像噪声并保持PET的定量准确性，我们建议 开发、优化和评估低剂量PET数据的多种创新成像方法， 与全剂量PET相当的定量准确性。虽然成像技术的发展通常适用于 肿瘤学、神经病学和心脏病学中的所有PET示踪剂，因为癌症是 PET，我们将集中我们的调查和优化在这个项目上的三个肺癌成像示踪剂， 不同的临床采用阶段为例：1）18F-FDG作为常规临床示踪剂，2）18F-FMISO用于缺氧 作为人类研究的示踪剂的研究，以及3）18F-PD-L1，其特异性结合肿瘤中的人PD-L1， 其他器官作为近期首次人体示踪剂。对于每种示踪剂，我们将研究1）静态PET，2）门控和 呼吸运动校正PET，和3）动态PET。

Project summary Quantitative PET has become increasingly important in clinical management and research, in particular for predicting and assessing response to therapy for cancer patients. Current PET protocols involve injection of PET tracers that typically result in ~6-7 mSv radiation dose to patients. For patients who require multiple repeated PET scans to monitor the response to therapy, and for patients who need PET scans with two or more tracers (e.g., FDG + FLT) to optimally predict response to therapy, it is critical to reduce the radiation dose from the PET tracer injection, while still maintaining the quantitative accuracy and image quality for cancer management. When reducing injection dose, the PET images will have higher noise due to fewer detected counts, which will subsequently introduce errors in quantitative measurements. For moving organs and tumors such as those in the lung and abdomen, respiratory motion can substantially degrade quantitative accuracy, so motion correction is required. Conventional motion correction uses a gating strategy that rebins the PET data, resulting in substantially higher noise in each gate. More advanced methods incorporate motion vector estimation in the image domain for post-registration or motion compensated image reconstruction using all detected events without increasing noise. The motion vectors need to be derived from gated PET, which are even noisier when using a reduced tracer injection in low-dose studies, imposing substantial challenges for accurate and reliable voxel-by-voxel motion vector estimation. In dynamic PET studies with clinical cardiac tracers and other novel oncology and neurology tracers, quantification is even more challenging for low-dose PET as each dynamic frame only contains a small fraction of detected events so the high image noise will affect the determination of image-derived input functions and can lead to bias and high noise in parametric images. In this project, to reduce image noise and maintain quantitative accuracy in PET, we propose to develop, optimize, and evaluate multiple innovative imaging methods for low-dose PET data to achieve comparable quantitative accuracy as full-dose PET. While the imaging developments are generally applicable to all PET tracers in oncology, neurology, and cardiology, since cancer is the primary clinical application of PET, we will focus our investigation and optimization in this project on three lung cancer imaging tracers at different clinical adoption stages as examples: 1) 18F-FDG as a routine clinical tracer, 2) 18F-FMISO for hypoxia studies as a tracer for human research, and 3) 18F-PD-L1 that specifically binds to human PD-L1 in tumors and other organs as a recent first-in-human tracer. For each tracer, we will investigate 1) static PET, 2) gated and respiratory motion corrected PET, and 3) dynamic PET.