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Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

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用于比较排放断层扫描中的数据驱动门关算法的方法.

M P Reymann^1,2,3, A H Vija⁴, A Maier¹

¹Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Physics in medicine and biology

|August 24, 2023

概括

单光子发射计算机断层扫描 (SPECT) 的数据驱动门 (DDG) 方法需要仔细评估心肌输液成像 (MPI) 以外. 幻影模拟显示,视角,物体大小和对比度显著影响DDG准确性.

关键词:

蒙托卡洛模拟的模拟斯佩克特 (Spectre) 是一个运动场.数据驱动的网关是数据驱动的网关.排放断层扫描是一种排放断层扫描.呼吸运动是呼吸的运动.

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科学领域:

医疗成像医学成像
计算成像技术的成像
核医学是一种核医学.

背景情况:

数据驱动的门关 (DDG) 算法用于单光子发射计算机断层扫描 (SPECT) 和心肌输液成像 (MPI).
对于其他SPECT采集类型的DDG方法的性能和局限性在很大程度上仍然没有特征.
了解这些限制对于扩展DDG应用程序至关重要.

研究的目的:

在与SPECT成像相关的各种模拟条件下,全面评估数据驱动门关 (DDG) 算法.
确定影响DDG方法准确性和可靠性的关键因素.
为评估超越SPECT MPI的DDG算法性能提供一个框架.

主要方法:

开发了一套全面的幻影模拟套件,包括运动工件,不同的视角,物体大小,对比度水平和计数统计数据.
使用蒙特卡洛模拟来生成现实的SPECT数据.
使用衍生指标对DDG算法的定量评估,特别是光中心 (COL) 和Laplacian Eigenmaps,使用衍生指标.

主要成果:

DDG的准确性明显受到采集参数的影响,包括视角,物体大小,计数速率密度和对比度.
从模拟数据中成功提取呼吸运动与特征对比度,信号噪声比率和整体数据噪声有很强的相关性.
与外部参考信号的平均相关性不足以描述DDG方法的性能.

结论:

对于DDG方法的表征,需要更详细的,逐一的视图评估,而不是仅仅依赖于平均性能指标.
这里介绍的模拟和定量指标可以识别当前DDG算法的陷和局限性.
这项工作有助于将DDG应用扩展到MPI以外的多种SPECT成像模式.