In this paper, we develop a method of forming pharmacokinetic-rate images of indocyanine green (ICG) and apply our method to in vivo data obtained from three patients with breast tumors. To form pharmacokinetic-rate images, we first obtain a sequence of ICG concentration images using the differential diffuse optical tomography technique. We next employ a two-compartment model composed of plasma, and extracellular-extravascular space (EES), and estimate the pharmacokinetic rates and concentrations in each compartment using the extended Kalman filtering framework. The pharmacokinetic-rate images of the three patient show that the rates from the tumor region and outside the tumor region are statistically different. Additionally, the ICG concentrations in plasma, and the EES compartments are higher around the tumor region agreeing with the hypothesis that around the tumor region ICG may act as a diffusible extravascular flow in compromised capillary of cancer vessels. Our study indicates that the pharmacokinetic-rate images may provide superior information than single set of pharmacokinetic rates estimated from the entire breast tissue for breast cancer diagnosis.
Compartmental modeling of indocyanine green (ICG) pharmacokinetics, as measured by near infrared (NIR) techniques, has the potential to provide diagnostic information for tumor differentiation. In this paper, we present three different compartmental models to model the pharmacokinetics of ICG in cancerous tumors. We introduce a systematic and robust approach to model and analyze ICG pharmacokinetics based on the extended Kalman filtering (EKF) framework. The proposed EKF framework 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, the recursive nature of the Kalman filter estimator potentially allows real-time monitoring of time varying pharmacokinetic rates and concentration changes in different compartments. Additionally, we introduce an information theoretic criteria for the best compartmental model order selection, and residual analysis for the statistical validation of the estimates. We tested our approach using the ICG concentration data acquired from four Fischer rats carrying adenocarcinoma tumor cells. Our study indicates that, in addition to the pharmacokinetic rates, the EKF model may provide parameters that may be useful for tumor differentiation.
Abstract-In this paper, we present a new method to form pharmacokinetic-rate images of optical fluorophores directly from near infra-red (NIR) boundary measurements. We first derive a mapping from spatially resolved pharmacokinetic rates to NIR boundary measurements by combining compartmental modeling with a diffusion based NIR photon propagation model. We express this mapping as a state-space equation. Next, we introduce a spatio-temporal prior model for the pharmacokinetic-rate images and combine it with the state-space equation. We address the image formation problem using the extended Kalman filtering framework. We analyze the computational complexity of the resulting algorithms and evaluate their performance in numerical simulations. An important feature of our approach is that the reconstruction of fluorescence concentrations and compartmental modeling are combined into a single step 1) to take advantage of the inherent temporal correlations in dynamic NIR measurements, and 2) to incorporate spatio-temporal a priori information on pharmacokinetic-rate images. Simulation results show that the resulting algorithms are more robust and lead to higher signal-to-noise ratio as compared to existing approaches where the reconstruction of concentrations and compartmental modeling are treated separately. Additionally, we reconstructed pharmacokinetic-rate images using in vivo data obtained from three patients with breast tumors. The reconstruction results show that the pharmacokinetic rates of indocyanine green are higher inside the tumor region as compared to the surrounding tissue.
In this work, we present spatially resolved pharmacokinetic rate images of indocyanine green (ICG) obtained from three breast cancer patients using near infrared imaging methods. We used a two-compartment model, namely, plasma and extracellular extravascular (EES), to model ICG kinetics around the tumor region. We introduced extended Kalman filtering (EKF) framework to estimate the ICG pharmacokinetic rate images. The EKF framework allows simultaneous estimation of pharmacokinetic rates and the ICG concentrations in each compartment. Based on the pharmacokinetic rate images, we observed that the rates from inside and outside the tumor region are statistically different with a p-value of 0.0001 for each patient. Additionally, we observed that the ICG concentrations in plasma and the EES compartments are higher around the tumors agreeing with the hypothesis that ICG may act as a diffusible extravascular flow in leaky capillary of cancer vessels. Our study shows that spatially resolved pharmacokinetic rate images can be potentially useful for breast cancer screening and diagnosis.
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