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Fiber optic spectroscopy label-free composition analysis makes it the best tool for reaction monitoring in Process Analytical Technologies (PAT) and chemical analysis of bio tissues for medical diagnostics in-citu and in-vivo. Biological samples and modern chemicals are complex substances, which composition analysis requires combining several spectroscopic techniques. Fiber optics probes provide compact, flexible, robust, and cost-effective solutions to merge different optical modalities in one tool for sample analysis at the same point. This spatial synchronization of the analysis is critical for heterogeneous samples. Recent advances in optical fiber manufacturing significantly expand the wavelength range of the analysis from 0,3-2µm range with Silica fibers towards middle IR (with chalcogenide, AgCl:AgBr Polycrystalline PIR fibers, and Ag/AgI hollow glass waveguides covering together 1-20 µm range).
We were able to fuse all 4 key spectroscopic methods (Fluorescence, NIR, MIR, and Raman) in compact fiber probes. In preliminary studies of tissue samples we showed that a combination of fluorescence with NIR or ATR-IR spectroscopy results in much better accuracy of the tumor margin detection than each of the individual methods separately. This synergy is explained by the capability of different light modalities to deliver complementary chemical information. We are using information from fluorescence background subtracted from Raman spectra to enhance the accuracy of the analysis. This concept, combined with advanced chemometrics data analysis, enables the development of customized spectral fiber sensors based only on several wavelengths or wavelength regions. Our recent experiments have shown the possibility of combining mid-IR ATR absorption and Raman spectroscopy in one compact fiber-optic probe. Thus it is possible to obtain an extended optical spectrum of molecular vibrations from the same point of a complex sample. These advances turn fiber-optic multispectral probes into the universal tool for applications that require in vivo analysis or real-time process monitoring.
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