Simultaneous Multi-Tracer Positron Emission Tomography for Interrogating Molecular Pathways of Neurological Disorders

同步多示踪剂正电子发射断层扫描用于探查神经系统疾病的分子通路

• 批准号: 10607431
• 负责人: Jackson West Foster
• 金额: $ 5.72万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-23 至 2026-03-22
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10607431
• 关键词: 3-Dimensional; Algorithms; Alzheimer' s Disease; Amyloid beta-Protein; Biological; Biological Markers; Biological Process; Biology; Compensation; Computational algorithm; Consumption; DNA; Data; Detection; Diagnosis; Disease; Dose; Electrons; Elements; Event; Gamma Rays; Geometry; Image; Joints; Label; Malignant Neoplasms; Maximum Likelihood Estimate; Measures; Medical Imaging; Methods; Molecular; Nerve Degeneration; Pathway interactions; Patients; Photons; Positioning Attribute; Positron; Positron-Emission Tomography; Probability; Proliferating; Radioisotopes; Scanning; Solid; System; Techniques; Testing; Time; Tissues; Tracer; Visualization; accurate diagnosis; deep learning; design and construction; detection platform; detector; glucose uptake; imaging modality; improved; in vivo; innovation; nervous system disorder; neuroinflammation; photon-counting detector; potential biomarker; radiotracer; receptor density; response; signal processing; statistics; tau Proteins; two-photon

Project Summary/Abstract Positron emission tomography (PET) is a method of medical imaging that employs positron emitting radionuclides attached to probe molecules (tracers) for non-invasively interrogating biological processes in vivo. Each radionuclide decay emits a positron, which then combines with an electron and creates two oppositely directed, colinear 511 keV annihilation photons. These annihilation photons are detected in opposing elements of a photon detector ring forming lines of response (LOR) along which each positron emission originated. After collecting millions of such photon pair events and positioning them along system LORs, an image can be reconstructed to visualize and quantify the 3D distribution of tracer probe molecules within the body. Up to now, PET systems detect only one tracer per study. However, more complete understanding of the disease biology often requires the study of multiple biological processes simultaneously. Alzheimer’s Disease specifically is characterized by presence of neuroinflammation, β-amyloid, phosphor-τ, and neurodegeneration. This project aims to enable simultaneous imaging of multiple tracers by strategically choosing at least one PET tracer that emits gamma photons in cascade with their positron. These gamma photons can be differentiated from annihilation photons through their higher energy measured by the photon detector. Thus, LORs can be associated with this positron + gamma tracer when a high energy photon arrives nearly the same time as a pair of 511 keV photons. Challenges associated with using prompt gamma emitters come from the lower probability of detecting both the annihilation photons and gamma photon within the appropriate timing and energy windows. Another challenge associated with using multiple tracers is misclassification of events among tracers due to missed, tissue scattered, or random photons detected. Low detection efficiency and misclassification will reduce image quality and accuracy of the associated multi-tracer images; thus, methods must be developed to mitigate these issues. This project proposes to develop and characterize a position-sensitive endcap detector that will cover the open end of an existing PET ring system to increase the detection efficiency for 3-photon events through increasing the solid angle coverage of the system photon detectors. Signal processing algorithms will also be employed using multiple temporal and energy windows to mitigate misclassification of photons coming from the two emitters in addition to compensating for sensitivity differences between two- and three-photon emitters. These techniques will include use of delayed time windows to estimate the different random coincidence rates and joint maximum likelihood estimation of coincidence events based on system geometry. We will also use deep learning to improve the image quality of the low dose images and to accurately separate the images obtained. Through these techniques, this project aims to develop the first system capable of simultaneous multi-tracer PET imaging.

项目摘要/摘要 正电子发射断层扫描（PET）是一种医学成像的方法，员工阳性排放 与探针分子（示踪剂）相连的放射性cli虫，用于在体内非侵入性询问的生物过程。 每个放射线衰减都会发出阳性，然后与一个电子结合，并产生两个相对的 指导，Colinear 511 Kev歼灭照片。这些歼灭照片在相反的元素中检测到 光子检测器环形成响应线（LOR）的线，每个正电子发射起源。后 收集数百万此类光子对事件并沿着系统LORS定位，图像可以是 重建以可视化和量化体内示踪探针分子的3D分布。到目前为止， 宠物系统每项研究仅检测一个示踪剂。但是，对疾病生物学的更全面了解 通常需要特别需要简单地研究阿尔茨海默氏病。 其特征是存在神经炎症，β-淀粉样蛋白，磷酸 - τ和神经变性的特征。这个项目 旨在通过策略性地选择至少一个宠物示踪剂来实现多个示踪剂的简单成像 将伽玛的照片放在级联的正面上。这些伽马照片可以与 通过光子检测器测量的较高能量的歼灭照片。那可以是 当高能量光子与一对几乎相同的时间时，与此正电子 +伽马示踪剂相关 511 Kev Photosons。 与使用及时伽玛发射器相关的挑战来自检测两者的较低概率 在适当的时机和能量窗口内歼灭照片和伽马光子。另一个挑战 与使用多个示踪剂有关的是由于错过的组织而导致的示踪剂事件的错图 检测到的分散或随机照片。低检测效率和错误分类将降低图像质量 相关的多跟踪图像的准确性；因此，必须开发方法来减轻这些问题。 该项目的提议要开发和表征对位置敏感的端盖检测器，该检测器将涵盖公开 现有的宠物环系统的结束，以提高3光孔事件的检测效率 系统光子检测器的实体角度覆盖率。信号处理算法也将被录用 使用多个临时和能量窗口来减轻对两者的照片的错误分类 发射器除了补偿两光子和三光子发射器之间的敏感性差异。这些 技术将包括使用延迟的时间窗口来估计不同的随机巧合率和关节 基于系统几何形状的重合事件的最大似然估计。我们还将使用深度学习 为了提高低剂量图像的图像质量，并准确分开所获得的图像。通过 这些技术，该项目旨在开发第一个能够简单的多跟踪宠物成像的系统。