Light propagation in tissue during fluorescence spectroscopy with single-fiber probes

Fluorescence spectroscopy systems designed for clinical use commonly employ fiberoptic probes to deliver excitation light to a tissue site and collect remitted fluorescence. Although a wide variety of probes have been implemented, there is little known about the influence of probe design on light propagation and the origin of detected signals. In this study, we examined the effect of optical fiber diameter, probe-tissue spacing and numerical aperture on light propagation during fluorescence spectroscopy with a single-fiber probe. A Monte Carlo model was used to simulate light transport in tissue. Two distinct sets of excitation-emission wavelength pairs were studied (337/450 nm and 400/630 nm). Simulation results indicated that increasing fiber diameter or fiber-tissue spacing increased the mean excitation-emission photon pair pathlength and produced a transition from high selectivity for superficial fluorophores to a more homogeneous probing with depth. Increasing numerical aperture caused an increase in signal intensity, but axial emission profiles and pathlengths were not significantly affected for numerical aperture values less than 0.8. Tissue optics mechanisms and implications for probe design are discussed. This study indicates that single-fiber probe parameters can strongly affect fluorescence detection and should be considered in the design of optical diagnostic devices.

I. Introduction

The potential of fluorescence spectroscopy as a tool for minimally invasive detection of precancers and determination of exogenous drug concentration is well established [1], [2]. Medical fluorescence devices frequently incorporate fiberoptic probes for instrument-tissue interfacing, as these components are relatively inexpensive, highly versatile and enable the acquisition of optical data in a wide variety of clinical and laboratory situations. However, the range of designs capable with fiberoptic probes adds complexity to the problem of system optimization.