Cumulative input function method for linear compartmental models and spectral analysis in PET.
Cumulative input function method for linear compartmental models and spectral analysis in PET.
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线性房室模型和 PET 光谱分析的累积输入函数方法。
DOI：
10.1038/jcbfm.2010.159
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Jeraj,Robert
中科院分区：
文献类型：
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作者：
Simoncic,Urban;Jeraj,Robert
正电子发射断层扫描（PET）中示踪剂动力学建模常采用房室模型和谱分析。动力学方程中的浓度通常被认为是瞬时的，而PET数据固有地随时间积分，这导致结果的不确定性。一种新的形式主义的动力学分析，使用累积示踪剂浓度，并避免近似的图像导出的输入函数和PET测量与中间帧瞬时值的开发。我们评估了三种常用放射性药物（[11 C]雷氯必利、2′-脱氧-2 ′-[18 F]氟代-d-葡萄糖（FDG）和3′-脱氧-3 ′-[18 F]氟代-胸苷（FLT））的新形式相对于中间框架近似方法的改进。我们发现改进取决于具体情况，并且通常不可忽视。测定[11 C]雷氯必利结合潜力的改进范围为5%至25%。FDG和FLT微参数的估计准确度提高了25%。另一方面，FDG或FLT的宏观参数Ki = K1 k3/（k2+k3）的估计并未显示新方法的显著益处;仅观察到2%的适度改善。对使用新方法的益处的评估远未详尽无遗，但已证明可能有重大改进。因此，我们认为该算法是任何动力学分析软件的必要组成部分。
Compartmental modeling and spectral analysis are often used for tracer kinetic modeling in positron emission tomography (PET). The concentrations in kinetic equations are usually considered to be instantaneous, whereas PET data are inherently integrated over time, which leads to uncertainties in the results. A new formalism for kinetic analysis that uses cumulative tracer concentrations and avoids approximating the image-derived input function and PET measurements with midframe instantanous values was developed. We assessed the improvements of the new formalism over the midframe approximation methods for three commonly used radiopharmaceuticals: [11C]raclopride, 2′-deoxy-2′-[18F]fluoro-d-glucose (FDG), and 3′-deoxy-3′-[18F]fluoro-thymidine (FLT). We found that improvements are case dependent and often not negligible. Improvements for determination of binding potential for [11C]raclopride ranged from 5% to 25%. Improvements in estimation accuracy of FDG and FLT microparameters ranged up to 25%. On the other hand, estimation of macroparameterKi=K1k3/(k2+k3) for FDG or FLT did not show significant benefit with the new method; only modest improvement up to 2% was observed. Assessment of the benefits of using new method is far from being exhaustive, but possibly significant improvement was demonstrated. Therefore, we consider the proposed algorithm a necessary component of any kinetic analysis software.