Shuke N
Department of Nuclear Medicine, Kanazawa University School of Medicine.
Kaku Igaku. 1991 Apr;28(4):381-90.
In hepatobiliary scintigraphy, kinetic model analysis, which provides kinetic parameters like hepatic extraction or excretion rate, have been done for quantitative evaluation of liver function. In this analysis, unknown model parameters are usually determined using nonlinear least square regression method (NLS method) where iterative calculation and initial estimate for unknown parameters are required. As a simple alternative to NLS method, direct integral linear least square regression method (DILS method), which can determine model parameters by a simple calculation without initial estimate, is proposed, and tested the applicability to analysis of hepatobiliary scintigraphy. In order to see whether DILS method could determine model parameters as good as NLS method, or to determine appropriate weight for DILS method, simulated theoretical data based on prefixed parameters were fitted to 1 compartment model using both DILS method with various weightings and NLS method. The obtained parameter values were then compared with prefixed values which were used for data generation. The effect of various weights on the error of parameter estimate was examined, and inverse of time was found to be the best weight to make the error minimum. When used this weight, DILS method could give close parameter values to those obtained by NLS method and both parameter values were very close to prefixed values. With appropriate weighting, the DILS method could provide reliable parameter estimate which is relatively insensitive to the data noise. In conclusion, the DILS method could be used as a simple alternative to NLS method, providing reliable parameter estimate.
在肝胆闪烁扫描术中,为了对肝功能进行定量评估,已经开展了动力学模型分析,该分析可提供诸如肝脏摄取或排泄率等动力学参数。在这种分析中,未知模型参数通常使用非线性最小二乘法(NLS法)来确定,其中需要对未知参数进行迭代计算和初始估计。作为NLS法的一种简单替代方法,提出了直接积分线性最小二乘法(DILS法),该方法无需初始估计即可通过简单计算确定模型参数,并测试了其在肝胆闪烁扫描术分析中的适用性。为了了解DILS法是否能像NLS法一样准确地确定模型参数,或者确定DILS法的合适权重,使用具有不同权重的DILS法和NLS法将基于预先设定参数的模拟理论数据拟合到单室模型中。然后将获得的参数值与用于数据生成的预先设定值进行比较。研究了不同权重对参数估计误差的影响,发现时间的倒数是使误差最小的最佳权重。当使用此权重时,DILS法可以给出与NLS法获得的参数值相近的参数值,并且两个参数值都非常接近预先设定值。通过适当加权,DILS法可以提供对数据噪声相对不敏感的可靠参数估计。总之,DILS法可以作为NLS法的一种简单替代方法,提供可靠的参数估计。