Quantitative Low-Dose PET Imaging

项目总结 定量PET在临床管理和研究中变得越来越重要，特别是在 预测和评估癌症患者的治疗反应。目前的PET方案包括注射 PET示踪剂，通常会导致患者受到~6-7 mSv的辐射剂量。对于需要多个 重复进行PET扫描以监测治疗反应，以及需要进行两次或以上PET扫描的患者 更多示踪剂(如FDG+Flt)以最佳方式预测治疗反应，减少辐射是至关重要的 PET示踪剂注射的剂量，同时仍保持定量的准确性和图像质量 癌症管理。当减少注射剂量时，由于较少的注射剂量，PET图像将具有更高的噪声 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 以及肺部和腹部的肿瘤，呼吸运动可以显著降低数量 精度不高，因此需要进行运动校正。传统的运动校正使用门控策略 PET数据，导致每个栅极中的噪声显著更高。更先进的方法结合了运动 用于后配准或运动补偿图像重建的图像域矢量估计 所有检测到的事件都不会增加噪音。运动矢量需要从门控PET中导出，这是 在低剂量研究中使用减少的示踪剂注射时，噪音更大，给 准确可靠的逐个体素运动矢量估计。在临床心脏动态PET研究中的应用 示踪剂和其他新的肿瘤学和神经学示踪剂，量化对于低剂量甚至更具挑战性 由于每个动态帧只包含一小部分检测到的事件，因此高图像噪声将 影响图像派生输入函数的确定，并可能导致参数中的偏差和高噪声 图像。在这个项目中，为了减少图像噪声并保持PET的定量精度，我们建议 开发、优化和评估用于低剂量PET数据的多种创新成像方法，以实现 与全剂量正电子发射计算机断层扫描相当的定量准确性。虽然成像技术的发展普遍适用 对于肿瘤学、神经病学和心脏病学中的所有PET示踪剂，因为癌症是 PET，我们将在这个项目中重点研究和优化三种肺癌成像示踪剂 例如：1)18F-FDG作为常规临床示踪剂；2)18F-FMISO用于缺氧 作为人体研究示踪剂的研究，以及3)18F-PD-L1在肿瘤和 其他器官作为最近第一个人类示踪剂。对于每个示踪剂，我们将研究1)静态PET，2)门控和 呼吸运动校正的正电子发射计算机断层扫描和3)动态正电子发射计算机断层扫描。

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.