Analysis of Raman spectra using the Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) method

Abstract

In recent years, optical methods such as Raman spectroscopy have been increasingly used to diagnose various diseases. Raman spectra of biological tissues are specific and can be used for successful differentiation of pathologies. However, despite the advances in the development of equipment for Raman scattering spectroscopy and probe designs allowing their implementation in clinical applications, the analysis of the recorded spectra is difficult due to the fact that the spectra contain an extremely large amount of information about all substances that make up the tissue. It makes us look for new methods to analyze Raman spectra.
The main purpose of the research is to study the possibilities of applying the Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) method (which is widely used for the reconstruction of the concentration profiles in chemicals analysis) for the analysis of Raman spectra and evaluate the effect of noise in the Raman spectra on the analysis result.
We used the experimental Raman spectra of pure amino acids and mathematically simulated amino acid mixtures in our study. The experimental Raman spectra are recorded using a portable spectroscopic setup (785±0.1 nm central wavelength). The concentrations of amino acids in the mixtures are chosen so that the mixtures correspond to real plasma free amino acid (PFAA) profiles of blood plasma samples studied by other researchers. Noise with different signal-to-noise ratios (SNR) was artificially added to both the experimental spectra of pure amino acids and the mixture spectra.
Using the MCR-ALS method, unmixing the amino acid mixture Raman spectra into components was performed. Obtained concentration values for each amino acid have been compared with the corresponding true values. The results indicate that using the method makes it possible to successfully estimate the amino acid concentrations in the mixture. The accuracy of the reconstruction of amino acids is negatively affected by noise and strong background fluorescence in the spectra. However, using the basis spectra in MCR-ALS analysis allows us to reduce this effect. The findings suggest that this approach could be useful for analysis of Raman spectra. Our future research will be devoted to experiments on real mixtures of amino acids and biological tissues.


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Speaker

Irina Matveeva
Samara National Research University
Russia

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