课题基金 / 基金详情

项目摘要

项目成果

JINYI QI的其他基金

相关文献

中文摘要
翻译
项目摘要/摘要 正电子发射断层扫描(PET)是一种广泛应用于肿瘤学的高灵敏度分子成像手段, 神经学和心脏病学,有能力通过观察活体内分子水平的活动 用正电子发射器注入特定的放射性示踪剂。最近有研究表明,人的生命周期 正电子是一对电子和正电子形成的亚稳状态,它对微环境很敏感。 对周围组织的影响,如氧分压。这些信息对癌症分期和 治疗计划。然而,目前还没有一种实用的方法来对正电子寿命进行成像。 由于有限的光子探测灵敏度和缺乏合适的图像,与PET的空间分辨率相匹配 重建法。这一建议通过开发基于统计的图像来解决这些问题 正电子寿命成像(PLI)的重建方法及其与新发展的全电子寿命成像的结合 加州大学戴维斯分校的身体探索者PET扫描仪。我们将使用该方法来演示该方法的有效性 在探索者扫描仪上进行幻影实验。PLI的优势在于寿命测量 与示踪剂浓度无关,可与标准PET成像一起使用。这个 PLI和PET的结合将为当前的PET成像增加另一个维度,并提供有用的信息 以了解组织的微环境,以研究各种人类疾病。
英文摘要
Project Summary/Abstract Positron emission tomography (PET) is a high-sensitivity molecular imaging modality widely used in oncology, neurology, and cardiology, with the ability to observe molecular-level activities inside a living body through the injection of specific radioactive tracers with positron emitters. Recently it has been shown that the lifetime of positronium, a metastable state formed by a pair of electron and positron, is sensitive to the microenvironment of the surrounding tissue, such as oxygen pressure. Such information is valuable for cancer staging and treatment planning. However, currently there is no practical method to imaging the positronium lifetime at a spatial resolution matching that of PET due to the limited photon detection sensitivity and lack of proper image reconstruction method. This proposal addresses these problems by developing a statistically based image reconstruction method for positronium lifetime imaging (PLI) and combining it with the newly developed total- body EXPLORER PET scanner at UC Davis. We will demonstrate the effectiveness of the method using phantom experiments on the EXPLORER scanner. The advantage of the PLI is that the lifetime measurement is independent of the tracer concentration and can be used together with standard PET imaging. The combination of PLI and PET will add another dimension to current PET imaging and provide useful information for understanding the microenvironment of the tissue for studying various human diseases.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
TRD3: Data Analytics and Intelligent Systems (AI-ML-DL-Visualization)
TRD3: Data Analytics and Intelligent Systems (AI-ML-DL-Visualization)
Positronium lifetime imaging using TOF PET
Synergistic integration of deep learning and regularized image reconstruction for positron emission tomography