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作 者:陈玉婷[1] 丁虹[2] 陆锐[1] 黄洪波[2] 刘丽[1]
机构地区:[1]江南大学物联网工程学院,江苏省无锡市214122 [2]江苏省原子医学研究所
出 处:《中华核医学杂志》2011年第5期344-347,共4页Chinese Journal of Nuclear Medicine
基 金:基金项目:中央高校基本科研业务费专项资金(JUSRPl0928)
摘 要:目的基于人工免疫网络提出无需设定初值的示踪剂动力学模型参数估计算法,以提高PET分子影像动力学模型分析方法的可靠性。方法对18F—FDG小鼠PET显像实验中有关数据,用ROI技术获取肝和左心室示踪剂的时间一放射性曲线(TAC),同时经小鼠尾静脉多点采血获取尾静脉血TAC。对动物实验数据进行示踪剂药代动力学建模,设计人工免疫网络算法估计模型参数,并计算小鼠肝葡萄糖代谢率参数Ki。结果获得肝、左心室和尾静脉血TAC。对小动物实验数据建模,应用基于人工免疫网络的药代动力学参数优化方法(PKAIN)求解模型参数,实现无需设定初始值的模型参数估计,并计算3只小鼠K值,平均值分别为0.0024,0.0417和0.0047。PKAIN算法求出对输出模型参数估计的最大加权残差平方和的平均值小于0.0745,标准差最大为0.0084,表明能够获得准确稳定的模型参数。结论人工免疫网络智能计算方法可提高PET分子影像动力学建模方法的可靠性、实用性提供了新型的智能信息处理技术。Objective To develop an accurate, reliable method without the need of initialization in animal PET modeling for estimation of the tracer kinetic parameters based on the artificial immune network. Methods The hepatic and left ventricular time activity curves (TACs) were obtained by drawing ROIs of liver tissue and left ventricle on dynamic 18 F-FDG PET imaging of small mice. Meanwhile, the blood TAC was analyzed by sampling the tail vein blood at different time points after injection. The artificial immune network for parametric optimization of pharmacokinetics (PKAIN) was adapted to estimate the model param- eters and the metabolic rate of glucose (Ki ) was calculated. Results TACs of liver, left ventricle and tail vein blood were obtained. Based on the artificial immune network, Ki in 3 mice was estimated as 0. 0024, 0. 0417 and 0.0047 ,respectively. The average weighted residual sum of squares of the output model genera- ted by PKAIN was less than 0. 0745 with a maximum standard deviation of 0. 0084, which indicated that the proposed PKAIN method can provide accurate and reliable parametric estimation. Conclusion The PKAIN method could provide accurate and reliable tracer kinetic modeling in animal PET imaging without the need of initialization of model parameters.
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