Data Driven Background Estimation in PET Using Event Energy Information

使用事件能量信息进行 PET 中数据驱动的背景估计

• 批准号: 10644161
• 负责人: Suleman Surti
• 金额: $ 57.86万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10644161
• 关键词: 90Y; Algorithms; Archives; Area; Beds; Biological Markers; Brain; Breast; Calibration; Cancer Patient; Cardiac; Clinical; Clinical Data; Clinical Research; Data; Development; Disadvantaged; Disease; Distributional Activity; Dose; Environment; Estimation Techniques; Evaluation; Event; Geometry; Goals; Image; Isotopes; Knowledge; Magnetic Resonance Imaging; Maps; Measurement; Measures; Methodology; Methods; Modeling; Molecular Target; Monitor; Monte Carlo Method; Motion; Oncology; Organ; PET/CT scan; Patient imaging; Patients; Performance; Photons; Play; Positron; Positron-Emission Tomography; Protocols documentation; Radioisotopes; Resources; Role; Scanning; Shapes; Tail; Techniques; Testing; Tracer; Work; X-Ray Computed Tomography; attenuation; base; breast scanner; clinical imaging; data acquisition; fluorodeoxyglucose; heart imaging; image reconstruction; imaging biomarker; improved; precision medicine; precision oncology; prototype; quantitative imaging; simulation; spectral energy; targeted cancer therapy; targeted treatment; transmission process; treatment response; tumor; uptake

The objective of this project is to develop methodology for energy-based background estimation that can be applied to clinical data and produce accurate quantitative PET images over challenging imaging situations such as low collected counts, high multiple scatter, and prompt gamma contamination when imaging non-standard PET isotopes. 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 a data driven scatter estimation methodology that makes full use of the annihilation photon energy information present to estimate scatter. This method is also extended to provide correction for bias arising from prompt gammas present in data collected form some non-standard PET isotopes. We implement, optimize, and evaluate this algorithm on measured data from a clinical PET scanner for standard and non-standard isotopes, and subsequently apply the methodology to organ- specific scanners (brain and breast). The proposed work will be accomplished through the following specific aims: (i) optimization and evaluation of the EB method for scatter estimation, (ii) extension of the EB methodology to correct for prompt gamma contamination present in data acquired from non-standard PET isotopes, and (iii) application of the EB methodology to dedicated brain and breast PET scanner geometries. In addition to its advantages over existing scatter estimation methodology in situations with low collected counts and/or data with higher level of multiple scatter, the proposed technique is expected to be faster, does not require knowledge of activity distribution outside the imaging field-of-view, and 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背景估计方法，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、高多重散射和快速伽马污染等情况 非标准 PET 同位素成像。目标是提高 PET 成像在某些情况下的准确性 当前最先进的散射估计技术的准确性有限或性能不佳。在这个 建议，我们开发了一种数据驱动的散射估计方法，充分利用湮没 提供光子能量信息来估计散射。该方法还可以扩展为提供 修正从某些非标准 PET 收集的数据中存在的即时伽玛所产生的偏差 同位素。我们根据临床 PET 测量数据实施、优化和评估该算法 标准和非标准同位素扫描仪，然后将该方法应用于器官 特定扫描仪（大脑和乳房）。 拟议的工作将通过以下具体目标来完成：（i）优化和 评估用于散布估计的 EB 方法，(ii) 扩展 EB 方法以校正 从非标准 PET 同位素获取的数据中存在即时伽玛污染，以及 (iii) 将 EB 方法应用于专用的大脑和乳房 PET 扫描仪几何形状。 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， 收集的计数和/或具有更高水平的多重散射的数据，所提出的技术预计 速度更快，不需要了解成像视野之外的活动分布，并且不需要 不需要透射或 CT 图像。这项技术的成功示范可能会显着 扩大定量 PET/CT 在肿瘤学领域的应用，例如低剂量的治疗监测 剂量重复 PET 扫描，使用低正电子产放射性核素（例如 124I、 86Y 等），或以高计数率采集数据（如心脏成像或使用 124I 或 86Y 成像）。超过 除了肿瘤学之外，它还将改进心脏研究中的定量（82Rb、13NH3 或 11C-醋酸盐）。 由于所提出的散射估计方法不需要 CT 图像，因此它可能在以下领域有应用： PET/MR 成像以及涉及某些患者运动的临床研究 – 这两种情况都需要 CT 图像要么不可用，要么被破坏，导致传统的估计方式出现错误 分散。