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.

该项目目标是开发基于能量的散布估计方法，该方法可以 应用于临床数据，并在具有挑战性的成像上产生准确的定量PET图像 例如低采集计数和/或高计数率下的数据采集等情况。我们的目标是 在当前最先进的散布估计的情况下提高PET成像的准确性 这些技术要么精确度有限，要么表现不佳。在这个建议中，我们发展了散布估计 一种充分利用发射中存在的湮没光子能量信息的方法 PET数据，以及用物理体模获取的简单能量校准。我们实施， 在临床PET扫描仪所有成像的测量数据上优化和评估该算法 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 卡洛模拟以完全实现所提出的算法，因为它将被应用于测量数据， 然后对重建图像中的参数进行优化和评价，以及(Ii)评价 测量数据(模体和患者研究)的方法，然后扩展到HIGH 计数速率数据采集情况。 除了与现有散布估计方法相比，它在低成本情况下的优势之外 收集的计数和/或在高计数率下的数据采集，建议的技术预计将是 速度更快，也不需要传输或CT图像。这项技术的成功演示 可显著扩大定量PET/CT在肿瘤治疗等领域的应用 使用低剂量重复PET扫描进行监测，使用使用低正电子产额的新生物标志物进行成像 放射性核素(如124I、86Y等)，或以高计数率获取数据(如心脏成像或成像 使用124I或86Y)。除了肿瘤学，它还将在心脏研究中提供更好的定量(82Rb， 13NH3，或11C-醋酸酯)。由于所提出的散度估计方法不需要CT图像 可能在PET/MR成像以及一些患者运动的临床研究中有应用-两者 CT图像不可用或受损导致传统的 估计散布的方法。

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