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， 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 例如低收集计数和/或在高计数率下的数据采集的情况。目标是 在当前最先进的散射估计 这些技术在准确性方面受到限制或表现不佳。在这个建议中，我们发展了散布估计， 充分利用发射中存在的湮灭光子能量信息的方法 PET数据以及使用物理体模采集的简单能量校准。我们实施， 在所有成像过程中，根据临床PET扫描仪的测量数据优化并评估该算法 协议.我们的最终目标是在临床PET/CT上实现它，并评估其对真实的患者数据的影响。 建议的工作将通过以下具体目标来完成：（i）使用现实的Monte 卡洛模拟，以充分实现所提出的算法，因为它将被应用到测量数据， 然后在重建图像中进行参数优化和评估，以及（ii）评估 测量数据（体模和患者研究）的方法，然后将其扩展到高 计数率数据采集情况。 除了其在低信噪比的情况下优于现有的散射估计方法之外， 收集的计数和/或以高计数率的数据采集，预计所提出的技术将 更快，也不需要透射或CT图像。这项技术的成功示范 可以显著扩展定量PET/CT在肿瘤学领域的应用， 使用低剂量重复PET扫描进行监测，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124 I、86 Y等），或以高计数率采集数据（如在心脏成像或成像中 124 I或86 Y）。除了肿瘤学，它还将提供心脏研究中改进的定量（82 Rb， 13 NH3或11 C-乙酸盐）。由于所提出的散射估计方法不需要CT图像， 可应用于PET/MR成像以及具有一些患者运动的临床研究-两者 CT图像不可用或受损导致传统方法中的错误的情况， 估计散射的方法。

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