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作 者:张雁琦 张丽敏[1,2] 赵志超 马文娟 高峰[1,2] Zhang Yanqi;Zhang Limin;Zhao Zhichao;Ma Wenjuan;Gao Feng(School of Precision Instrument and Opto-Electronics Engineering,Tianjin University,Tianjin 300072,China;Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments,Tianjin 300072,China;Cancer Institute and Hospital,Tianjin Medical University,Tianjin 300060,China)
机构地区:[1]天津大学精密仪器与光电子工程学院,天津300072 [2]天津市生物医学检测技术与仪器重点实验室,天津300072 [3]天津医科大学肿瘤医院,天津300060
出 处:《中国激光》2020年第9期271-279,共9页Chinese Journal of Lasers
基 金:国家自然科学基金(81671728,81771880,81871396,81971656);天津市自然科学基金(18JCYBJC29400,19JCYBJC28600,19JCYBJC29100)。
摘 要:基于动态扩散荧光层析成像(DFT)的荧光剂药代动力学参数(渗透率等),可为判断不同生物组织体的生理过程和病理信息提供参考。自适应扩展卡尔曼滤波(AEKF)作为一种动态分析方法,具有精确的建模和多参数在线估计等优势。基于DFT系统对吲哚菁绿(ICG)在健康小鼠肝脏和荷瘤小鼠皮下移植瘤组织中的代谢过程进行了测量,然后采用DFT重建技术获得了ICG的时间序列荧光层析图像,在此基础上结合二室模型和AEKF方法得到了ICG的时间序列渗透率参数层析图像。对比两种实验结果可知,肿瘤中ICG的渗透率参数Kpe、Kep均较健康小鼠肝脏中的小。时间序列荧光层析图像显示,AEKF方法能有效获得复杂生物体实时、稳定的ICG药代动力学参数。The fluorescence pharmacokinetic parameters(permeability, etc.) based on dynamic diffuse fluorescence tomography(DFT) can provide reference for studying the dynamic physiological process and pathological information of different biological tissues. The adaptive extended Kalman filter(AEKF)(a method for dynamic analysis) has many advantages, such as precise modeling and multi-parameter online estimation. In this work, the metabolic process of indocyanine green(ICG) in healthy mice liver and tumor-burdened mice subcutaneous transplanted tumor tissue was measured using the dynamic DFT system. Then, we obtained the time-series fluorescence yield images of ICG by DFT method. On this basis, the time-series permeability images of ICG were reconstructed by the AEKF method based on a two-compartment model. The two experimental results verify that the permeability parameters Kpe and Kep of ICG in the tumor are less than that in the liver. Furthermore, the time-series permeability images of ICG also demonstrate that the AEKF method can effectively obtain the real-time and stable ICG pharmacokinetic parameters of complex organisms.
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