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Parameter estimation using the impulse response function for high affinity neuroreceptor ligands in PET

机译:使用脉冲响应函数对PET中高亲和力神经受体配体进行参数估计

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A tool for the complex task of multiparameter estimates from positron emission tomography (PET) and single photon emission computed tomography (SPECT) data, based on models of high affinity neuroreceptors ligands is presented. A simplified kinetic model of high affinity ligands and the mathematical background for the estimation of an impulse response function (IRF) from measured time activity curves are discussed. The advantages of this approach are that there is a straightforward relationship between the rate constants and the shape of the theoretical IRF, allowing a simplified parameter estimation process that in some cases will only yield one solution. Additionally, the estimated IRF allows a qualitative assessment of reliability of the estimates for each parameter and also an intuitive method of selectively weighting the data. Results based on simulated and measured N-methy-spiperone (NMSP) studies show that the IRF method is robust and also is a useful tool in conjunction with a standard three-parameter estimation algorithm.
机译:提出了一种基于高亲和力神经受体配体模型的,用于从正电子发射断层扫描(PET)和单光子发射计算机断层扫描(SPECT)数据进行多参数估计的复杂任务的工具。讨论了高亲和力配体的简化动力学模型和从测得的时间活动曲线估算脉冲响应函数(IRF)的数学背景。这种方法的优势在于,速率常数与理论IRF的形状之间存在直接的关系,从而简化了参数估计过程,在某些情况下只能得出一个解。另外,估计的IRF允许对每个参数的估计的可靠性进行定性评估,并且还可以提供一种选择性地对数据加权的直观方法。基于模拟和测量的N-甲基-甲基-哌隆酮(NMSP)研究的结果表明,IRF方法是鲁棒的,并且与标准的三参数估计算法结合使用也是一种有用的工具。

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