Unmixing Dynamic Fluorescence Diffuse Optical Tomography Images With Independent Component Analysis

Abstract

Dynamic fluorescence diffuse optical tomography (D-FDOT) is important for drug delivery research. However, the low spatial resolution of FDOT and the complex kinetics of drug limit the ability of D-FDOT in resolving metabolic processes of drug throughout whole body of small animals. In this paper, we propose an independent component analysis (ICA)-based method to perform D-FDOT studies. When applied to D-FDOT images, ICA not only generates a set of independent components (ICs) which can illustrate functional structures with different kinetic behaviors, but also provides a set of associated time courses (TCs) which can represent normalized time courses of drug in corresponding functional structures. Further, the drug concentration in specific functional structure at different time points can be recovered by an inverse ICA transformation. To evaluate the performance of the proposed algorithm in the study of drug kinetics at whole-body level, simulation study and phantom experiment are both performed on a full-angle FDOT imaging system with line-shaped excitation pattern. In simulation study, the nanoparticle delivery of indocynaine green (ICG) throughout whole body of a digital mouse is simulated and imaged. In phantom experiment, four tubes containing different ICG concentrations are imaged and used to imitate the uptake and excretion of ICG in organs. The results suggest that we can not only illustrate ICG distributions in different functional structures, but also recover ICG concentrations in specific functional structure at different time points, when ICA is applied to D-FDOT images.