Influence of the emission–reception geometry in laser-induced fluorescence spectra from turbid media

Abstract

Routine clinical detection of precancerous lesions by laser-inducedautofluorescence was recently demonstrated in several medicalfields. This technique is based on the analysis of complex spectrawith overlapping broad structures. However, in biological tissues, scattering and absorption are wavelength dependent, and the observedfluorescence signals are distorted when the illumination and detectiongeometry varies, making comparison of results from different groupsdifficult. We study this phenomenon experimentally in human tissuein a simple experiment: A fiber is used for the excitation and anidentical fiber is used for reception of the signal; both fibers aremaintained in contact with the tissue. We study the distortion ofthe spectra as a function of the distance between the twofibers. For correction of the spectra we show that it is possibleto use a fast and accurate ab initio Monte Carlo simulationwhen the spectral variations of the optical properties of the mediumare known. The main advantage of this simulation is itsapplicability even for complex boundary conditions or when the sampleconsists of several layers.

Modeling of spectral changes for depth localization of fluorescent inclusion

“…The demonstrated method relies on spectral changes in the fluorescence as it propagates through the tissue. The characteristics of the detected fluorescence light depend on many different factors, for example, the optical properties of the tissue, the depth of the fluorescent inclusion, and the detection geometry [12][13][14][15][16][17][18]. Studies to determine the depth of a luminescent source embedded in a liquid phantom have been performed previously [19,20].…”

Investigation of fiber‐optic probe designs for optical spectroscopic diagnosis of epithelial pre‐cancers

“…The geometry of the illumination and collection system is an important component of tissue fluorescence spectroscopy and fiber-optic probes are most commonly used for this purpose (1,(9)(10)(11)(12)(13)(14)(15). The geometry of the illumination and collection fibers on the tissue surface, the optical properties (absorption and scattering) and the fluorescence efficiency of the tissue through which the light propagates, define the optical sensing depth (1,13,14,16).…”

Accelerated Monte Carlo models to simulate fluorescence spectra from layered tissues

“…28 A similar approach was used by Avrillier et al for steady-state problems. 23 We can describe the absorption probability of the excitation light by using the quantity A(r, t, z), defined as the probability per unit volume and time for an excitation photon to be absorbed at a radial distance r, a depth z, and a delay t from the injection point. This quantity can be calculated from one single Monte Carlo simulation based on the optical properties for the excitation wavelength.…”

“…The aim of this study is to develop efficient fluorescence Monte Carlo models, thereby making the Monte Carlo technique more feasible for applications within fluorescence spectroscopy of turbid media such as tissues. We consider not only steady-state fluorescence 22,23 but also the dimension of time, enabling simulations of timeresolved fluorescence. Furthermore, the advantages and the limitations of the accelerated models are evaluated by rigorous comparison with the well-tested conventional Monte Carlo approach in terms of accuracy and computation time required to achieve a predefined signal-to-noise ratio.…”