Li W B, Hoeschen C
Institute of Radiation Protection, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, D-85764 Neuherberg, Germany.
Radiat Prot Dosimetry. 2010 Apr-May;139(1-3):228-31. doi: 10.1093/rpd/ncq064. Epub 2010 Feb 25.
Mathematical models for kinetics of radiopharmaceuticals in humans were developed and are used to estimate the radiation absorbed dose for patients in nuclear medicine by the International Commission on Radiological Protection and the Medical Internal Radiation Dose (MIRD) Committee. However, due to the fact that the residence times used were derived from different subjects, partially even with different ethnic backgrounds, a large variation in the model parameters propagates to a high uncertainty of the dose estimation. In this work, a method was developed for analysing the uncertainty and sensitivity of biokinetic models that are used to calculate the residence times. The biokinetic model of (18)F-FDG (FDG) developed by the MIRD Committee was analysed by this developed method. The sources of uncertainty of all model parameters were evaluated based on the experiments. The Latin hypercube sampling technique was used to sample the parameters for model input. Kinetic modelling of FDG in humans was performed. Sensitivity of model parameters was indicated by combining the model input and output, using regression and partial correlation analysis. The transfer rate parameter of plasma to other tissue fast is the parameter with the greatest influence on the residence time of plasma. Optimisation of biokinetic data acquisition in the clinical practice by exploitation of the sensitivity of model parameters obtained in this study is discussed.
国际放射防护委员会和医学内照射剂量(MIRD)委员会开发了人体放射性药物动力学的数学模型,并用于估算核医学中患者的辐射吸收剂量。然而,由于所使用的停留时间来自不同的受试者,部分受试者甚至具有不同的种族背景,模型参数的巨大差异导致剂量估算的高度不确定性。在这项工作中,开发了一种方法来分析用于计算停留时间的生物动力学模型的不确定性和敏感性。用这种开发的方法分析了MIRD委员会开发的(18)F-FDG(FDG)生物动力学模型。基于实验评估了所有模型参数的不确定性来源。采用拉丁超立方抽样技术对模型输入参数进行抽样。进行了人体FDG的动力学建模。通过回归和偏相关分析,结合模型输入和输出,表明了模型参数的敏感性。血浆向其他组织的快速转移率参数是对血浆停留时间影响最大的参数。讨论了通过利用本研究中获得的模型参数敏感性来优化临床实践中的生物动力学数据采集。