Effects of statistical noise on graphic analysis of PET neuroreceptor studies.
Effects of statistical noise on graphic analysis of PET neuroreceptor studies.
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发表时间：
2000-12
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通讯作者：
M. Slifstein;M. Laruelle
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作者：
M. Slifstein;M. Laruelle
由于计算简单，Logan等人提出的图解法经常用于分析PET脑区测量的可逆放射性示踪剂的时间-活性曲线。图形方法使用数据到具有渐近线性关系的变量的非线性变换。与未转换数据的房室分析相比，图形方法能够推导出区域分布体积，无需对基础房室配置进行假设。在这篇文章中，我们描述了与这种非线性变换方法相关的统计偏差。方法采用理论分析、Monte Carlo模拟和PET数据统计分析等方法对图解法进行偏倚检验。结果平均零噪声与图形分析数据时分布体积的低估有关，而当用非线性回归和房室分析分析相同的数据时，这种影响不会发生。此外，这种效应取决于分布体积的大小，因此在具有高受体密度的区域中的偏差比具有低受体密度或没有受体的区域（参考区域）更明显。结论这些结果表明，传统的动力学分析的未转换的数据是不敏感的平均零噪声比图形分析的非线性转换的数据。
UNLABELLED Because of its computational simplicity, the graphic method introduced by Logan et al. is frequently used to analyze time-activity curves of reversible radiotracers measured in brain regions with PET. The graphic method uses a nonlinear transformation of data to variables that have an asymptotically linear relationship. Compared with compartmental analysis of untransformed data, the graphic method enables derivation of regional distribution volumes that are free from assumptions about the underlying compartmental configuration. In this article, we describe statistical bias associated with this nonlinear transformation method. METHODS Theoretic analysis, Monte Carlo simulation, and statistical analysis of PET data were used to test the graphic method for bias. RESULTS Mean zero noise is associated with underestimation of distribution volumes when data are analyzed with graphic analysis, whereas this effect does not occur when the same data are analyzed by nonlinear regression and compartmental analysis. Moreover, this effect depends on the magnitude of the distribution volume, so that the bias is more pronounced in regions with high receptor density than regions with low receptor density or no receptors (region of reference). CONCLUSION These results indicate that conventional kinetic analysis of untransformed data is less sensitive to mean zero noise than is graphic analysis of nonlinearly transformed data.