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QModeling:一个用于 PET 动力学分析的多平台、易用且开源的工具箱。

QModeling: a Multiplatform, Easy-to-Use and Open-Source Toolbox for PET Kinetic Analysis.

机构信息

Molecular Imaging Unit, Centro de Investigaciones Médico-Sanitarias, Fundación General de la Universidad de Málaga, Málaga, Spain.

Molecular Imaging and Medical Physics Group, Department of Psychiatry, Radiology and Public Health, Universidade de Compostela, Galicia, Spain.

出版信息

Neuroinformatics. 2019 Jan;17(1):103-114. doi: 10.1007/s12021-018-9384-y.

Abstract

Kinetic modeling is at the basis of most quantification methods for dynamic PET data. Specific software is required for it, and a free and easy-to-use kinetic analysis toolbox can facilitate routine work for clinical research. The relevance of kinetic modeling for neuroimaging encourages its incorporation into image processing pipelines like those of SPM, also providing preprocessing flexibility to match the needs of users. The aim of this work was to develop such a toolbox: QModeling. It implements four widely-used reference-region models: Simplified Reference Tissue Model (SRTM), Simplified Reference Tissue Model 2 (SRTM2), Patlak Reference and Logan Reference. A preliminary validation was also performed: The obtained parameters were compared with the gold standard provided by PMOD, the most commonly-used software in this field. Execution speed was also compared, for time-activity curve (TAC) estimation, model fitting and image generation. QModeling has a simple interface, which guides the user through the analysis: Loading data, obtaining TACs, preprocessing the model for pre-evaluation, generating parametric images and visualizing them. Relative differences between QModeling and PMOD in the parameter values are almost always below 10. The SRTM2 algorithm yields relative differences from 10 to 10 when [Formula: see text] is not fixed, since different, validated methods are used to fit this parameter. The new toolbox works efficiently, with execution times of the same order as those of PMOD. Therefore, QModeling allows applying reference-region models with reliable results in efficient computation times. It is free, flexible, multiplatform, easy-to-use and open-source, and it can be easily expanded with new models.

摘要

动力学建模是动态 PET 数据定量分析方法的基础。它需要特定的软件,而一个免费且易于使用的动力学分析工具箱可以为临床研究的常规工作提供便利。动力学建模在神经影像学中的相关性鼓励将其纳入像 SPM 这样的图像处理管道,同时也为满足用户的需求提供了预处理的灵活性。本工作的目的是开发这样一个工具箱:QModeling。它实现了四个广泛使用的参考区模型:简化参考组织模型(SRTM)、简化参考组织模型 2(SRTM2)、Patlak 参考模型和 Logan 参考模型。还进行了初步验证:获得的参数与 PMOD 提供的金标准进行了比较,PMOD 是该领域最常用的软件。还比较了执行速度,用于估计时间-活性曲线(TAC)、模型拟合和图像生成。QModeling 具有一个简单的界面,它指导用户进行分析:加载数据、获取 TAC、为预评估预处理模型、生成参数图像并对其进行可视化。QModeling 和 PMOD 在参数值上的相对差异几乎总是低于 10。当[公式:见文本]未固定时,SRTM2 算法的相对差异为 10 到 10,因为用于拟合此参数的是不同的、经过验证的方法。新的工具箱工作效率高,执行时间与 PMOD 的执行时间相同。因此,QModeling 允许在高效的计算时间内使用可靠结果的参考区模型。它是免费的、灵活的、跨平台的、易于使用的和开源的,可以轻松地用新模型进行扩展。

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