Energy-Based Scatter Estimation Algorithm for Accurate Quantitative PET Imaging

用于精确定量 PET 成像的基于能量的散射估计算法

• 批准号: 9975773
• 负责人: Suleman Surti
• 金额: $ 19.39万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-10 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9975773
• 关键词: Algorithms; Area; Biologic Characteristic; Biological Markers; Calibration; Cancer Patient; Cardiac; Clinical; Clinical Data; Clinical Research; Data; Disadvantaged; Disease; Distributional Activity; Dose; Environment; Estimation Techniques; Evaluation; Event; Future; Goals; Healthcare; Image; Light; Magnetic Resonance Imaging; Maps; Measurement; Measures; Methodology; Methods; Modernization; Molecular Target; Monitor; Monte Carlo Method; Motion; Noise; Oncology; PET/CT scan; Patient imaging; Patients; Performance; Photons; Play; Positron; Positron-Emission Tomography; Protocols documentation; Radioisotopes; Resolution; Resources; Role; Scanning; Shapes; Techniques; Testing; Tracer; Translating; Work; X-Ray Computed Tomography; attenuation; base; clinical imaging; data acquisition; detector; fluorodeoxyglucose; heart imaging; image reconstruction; imaging biomarker; improved; individualized medicine; personalized medicine; precision medicine; precision oncology; response; simulation; spectral energy; targeted treatment; transmission process; tumor; uptake

The objective of this project is to develop methodology for energy-based scatter estimation that can be applied to clinical data and produce accurate quantitative PET images over challenging imaging situations such as low collected counts and/or data acquisition at high count-rates. The goal is to enhance the accuracy of PET imaging in situations where current state-of-art scatter estimation techniques are limited in accuracy or perform poorly. In this proposal, we develop scatter estimation methodology that makes full use of the annihilation photon energy information present in the emission PET data together with a simple energy calibration acquired with a physical phantom. We implement, optimize, and evaluate this algorithm on measured data from a clinical PET scanner over all imaging protocols. Our final goal is to implement it on clinical PET/CT and evaluate its impact on real patient data. The proposed work will be accomplished through the following specific aims: (i) Using realistic Monte Carlo simulations to fully implement the proposed algorithm as it will be applied to measured data, followed by parameter optimization and evaluation in reconstructed images, and (ii) evaluating the methodology on measured data (phantoms as well as patient studies) followed by its extension to high count-rate data acquisition situations. In addition to its advantages over existing scatter estimation methodology in situations with low collected counts and/or data acquisition at high count-rates, the proposed technique is expected to be faster and also does not require a transmission or CT image. Successful demonstration of this technique may significantly expand the application of quantitative PET/CT in oncology areas such as treatment monitoring with low-dose repeat PET scans, imaging with new biomarkers that use low positron yield radionuclides (e.g. 124I, 86Y, etc.), or acquiring data at high count-rates (as in cardiac imaging or imaging with 124I or 86Y). Beyond oncology, it will also provide improved quantitation in cardiac studies (82Rb, 13NH3, or 11C-actetate). Since, the proposed scatter estimation method does not require a CT image it may have an application in PET/MR imaging as well as clinical studies with some patient motion – both situations where the CT image is either not available or is compromised leading to errors in the traditional way of estimating scatter.

该项目的目标是开发基于能量的散射估计方法，该方法可以 应用于临床数据并在具有挑战性的成像中生成准确的定量 PET 图像 诸如低收集计数和/或高计数率数据采集的情况。目标是 在当前最先进的散射估计情况下提高 PET 成像的准确性 技术的准确性有限或表现不佳。在这个提案中，我们开发了散点估计 充分利用发射中存在的湮灭光子能量信息的方法 PET 数据以及通过物理体模获取的简单能量校准。我们实施， 根据临床 PET 扫描仪的所有成像测量数据优化和评估该算法 协议。我们的最终目标是将其应用于临床 PET/CT 并评估其对真实患者数据的影响。 拟议的工作将通过以下具体目标来完成： (i) 使用现实的蒙特 卡洛模拟完全实现所提出的算法，因为它将应用于测量数据， 其次是重建图像中的参数优化和评估，以及（ii）评估 测量数据（模型以及患者研究）的方法，然后扩展到高 计数率数据采集情况。 除了在低散射估计情况下它比现有的散射估计方法具有优势之外， 以高计数率收集计数和/或数据采集，所提出的技术预计是 速度更快，也不需要传输或 CT 图像。该技术的成功示范 可能会显着扩展定量 PET/CT 在治疗等肿瘤学领域的应用 通过低剂量重复 PET 扫描进行监测，使用低正电子产率的新生物标志物进行成像 放射性核素（例如 124I、86Y 等），或以高计数率采集数据（如心脏成像或成像） 与 124I 或 86Y）。除了肿瘤学之外，它还将在心脏研究中提供改进的定量（82Rb、 13NH3，或11C-乙酸盐）。由于所提出的散射估计方法不需要 CT 图像，因此 可能在 PET/MR 成像以及一些患者运动的临床研究中得到应用 – 两者 CT 图像不可用或受到损害导致传统方法出现错误的情况 估计分散度的方法。

项目成果

TOF-PET Image Reconstruction With Multiple Timing Kernels Applied on Cherenkov Radiation in BGO.

• DOI: 10.1109/trpms.2020.3048642
• 发表时间: 2020-09
• 期刊: IEEE transactions on radiation and plasma medical sciences
• 影响因子: 4.4
• 作者: Efthimiou N;Kratochwil N;Gundacker S;Polesel A;Salomoni M;Auffray E;Pizzichemi M
• 通讯作者: Pizzichemi M