Abstract
In order to reduce the influence of scattering and absorption on tissue fluorescence spectra, after tissue fluorescence and diffuse reflectance in different tissue optical properties were simulated by the Monte Carlo method, a tissue intrinsic fluorescence recovering algorithm making use of diffuse reflectance spectrum was developed. The empirical parameters in the tissue intrinsic fluorescence recovering algorithm were coded as a particle in the solution domain, the classification performance was defined as the fitness, and then a particle swarm optimization (PSO) algorithm was established for empirical parameters optimization. The skin autofluorescence and diffuse reflectance spectra of 327 subjects were collected in Anhui Provincial Hospital. The skin intrinsic autofluorescence spectra were recovered by using the empirical approach and the integration area of the spectra were calculated as fluorescence intensity. Receiver operating characteristic (ROC) analysis for fluorescence intensity was applied to evaluate the classification performance in type 2 diabetes screening. In addition, a support vector machine (SVM) method was implemented to improve the performance of the classification. The results showed that the sensitivity and specificity were 32% and 76% respectively, and the area under the curve was 0.54 before recovering, while the sensitivity and specificity were 72% and 86% respectively, and the area under the curve was 0.86 after recovering. Furthermore, the sensitivity and specificity increased to 83% and 86% respectively when using linear SVM while 84% and 88%, respectively, when using nonlinear SVM. The results indicate that using the tissue fluorescence spectrum recovery algorithm based on PSO can improve the application of tissue fluorescence spectroscopy effectively.
Highlights
Fluorescence, the re-emission of light by fluorophore that has absorbed a shorter wavelength light, is widely used to investigate biological tissues [1, 2]
Tissue fluorescence spectroscopy is highly sensitive to the microenvironment inside the tissue, and has broad application prospects in cancer tissue detection, photodynamic therapy and other fields
Tissue fluorescence and diffuse reflectance in different tissue optical properties were simulated by Monte Carlo method and tissue intrinsic fluorescence recovering algorithm, making use of a diffuse reflectance measurement taken at the same location, was established
Summary
Fluorescence, the re-emission of light by fluorophore that has absorbed a shorter wavelength light, is widely used to investigate biological tissues [1, 2]. In samples with high scattering or absorption, such as tissue, both the shape and intensity of measured fluorescence spectrum can be heavily distorted, and resulting in the measured fluorescence spectrum may not be proportional to fluorophore concentration [3]. Bradley et al reviewed over 50 different publications that addressed the recovery of intrinsic fluorescence spectrum [4] These studies have used theoretical methods based on physical models of light tissue interactions, including analytical approaches based on diffusion theory [5, 6] as well as computational techniques such as Monte Carlo simulations of photon transport in turbid media [7] or simple empirical approaches [8, 9]. Promising results have been obtained with various methods, far, all available methods have their limitation
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