Extended Kalman Filtering for the Modeling and Analysis of ICG Pharmacokinetics using NIR Optical Methods
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چکیده
A number of studies indicate that compartmental modeling of indocyanine green (ICG) pharmacokinetics, as measured by near infrared (NIR) techniques, may provide diagnostic information for tumor differentiation. However, compartmental parameter estimation is a highly non-linear problem with limited data available in a clinical setting. Furthermore, pharmacokinetic parameter estimates show statistical variation from one data set to another. Thus, a systematic and robust approach is needed to model, estimate and quantify ICG pharmacokinetic parameters. In this paper, we propose to model ICG pharmacokinetics in extended Kalman filtering (EKF) framework. EKF effectively models multiple-compartment and multiple-measurement systems in the presence of measurement noise and uncertainties in model dynamics. It provides simultaneous estimation of pharmacokinetic parameters and ICG concentrations in each compartment. Moreover, recursive nature of the Kalman filter estimator potentially allows real time monitoring of time varying pharmacokinetic rates and concentration changes in different compartments. We tested our approach using the ICG concentration data acquired from four Fischer rats carrying adenocarcinoma tumor cells. Our study indicates that EKF model may provide additional parameters that may be useful for tumor differentiation.
منابع مشابه
Extended Kalman Filtering for the Modeling and Estimation of ICG Pharmacokinetics in Cancerous Tumors using NIR Measurements
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تاریخ انتشار 2005