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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.
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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
Data Driven Background Estimation in PET Using Event Energy Information
  • 批准号:
    10644161
  • 项目类别:
  • 资助金额:
    $57.86万
  • 财政年份:
    2022
  • 负责人:
    Suleman Surti
  • 依托单位:
Optimization of Clinical and Research PET Imaging
  • 批准号:
    10322759
  • 项目类别:
  • 资助金额:
    $49.55万
  • 财政年份:
    2020
  • 负责人:
    Suleman Surti
  • 依托单位:
Optimization of Clinical and Research PET Imaging
  • 批准号:
    10580601
  • 项目类别:
  • 资助金额:
    $49.55万
  • 财政年份:
    2020
  • 负责人:
    Suleman Surti
  • 依托单位:
High Performance, Quantitative Breast PET Scanner Integrated with Tomosynthesis
  • 批准号:
    9896791
  • 项目类别:
  • 资助金额:
    $58.26万
  • 财政年份:
    2016
  • 负责人:
    Suleman Surti
  • 依托单位:
国内基金
海外基金
层出镰刀菌氮代谢调控因子AreA 介导伏马菌素 FB1 生物合成的作用机理
  • 批准号:
    2021JJ40433
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2021
  • 负责人:
    孙磊
  • 依托单位:
寄主诱导梢腐病菌AreA和CYP51基因沉默增强甘蔗抗病性机制解析
  • 批准号:
    32001603
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    段真珍
  • 依托单位:
AREA国际经济模型的移植.改进和应用
  • 批准号:
    18870435
  • 项目类别:
    面上项目
  • 资助金额:
    2.0万元
  • 批准年份:
    1988
  • 负责人:
    史树中
  • 依托单位: