Fiber Probe for Simultaneous Mid-Infrared and Fluorescence Spectroscopic Analysis.

A multispectral fiber optic probe has been developed that enables simultaneous analysis of various liquid and solid samples using attenuated total reflection mid-infrared spectroscopy and fluorimetry. The probe design was optimized using ray-tracing simulation of the light propagation. Technical evaluation of the probe has confirmed its output signal quality that was comparable to that of respective probes for single methods. The capability of the probe to deliver complementary chemical information from the same measurement point has been illustrated using model samples of biological tissue. Qualitative analysis of the biological tissue is one of the most important applications of the developed multispectral probe.

Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting.

In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (tris-(2,2'-bipyridyl) dichlororuthenium(II) (Ru(bpy)32+), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid). The fluorescence spectra were obtained within 400-600 nm and treated by principal component analysis (PCA). No fluorophore allowed for the discrimination of all samples. To evaluate the discrimination performance of fluorophores, we introduced crossing number (CrN) calculated as the number of mutual intersections of confidence ellipses in the PCA scores plots, and relative position (RP) characterized by the pairwise mutual location of group centers and their most distant points. CrN and RP parameters correlated with each other, with total sensitivity (TS) calculated by Mahalanobis distances, and with the overall rating based on all metrics, with coefficients of correlation over 0.7. Most of the considered parameters gave the first place in the discrimination performance to Ru(bpy)32+ fluorophore.

Synergy Effect of Combined Near and Mid-Infrared Fibre Spectroscopy for Diagnostics of Abdominal Cancer.

Cancers of the abdominal cavity comprise one of the most prevalent forms of cancers, with the highest contribution from colon and rectal cancers (12% of the human population), followed by stomach cancers (4%). Surgery, as the preferred choice of treatment, includes the selection of adequate resection margins to avoid local recurrences due to minimal residual disease. The presence of functionally vital structures can complicate the choice of resection margins. Spectral analysis of tissue samples in combination with chemometric models constitutes a promising approach for more efficient and precise tumour margin identification. Additionally, this technique provides a real-time tumour identification approach not only for intraoperative application but also during endoscopic diagnosis of tumours in hollow organs. The combination of near-infrared and mid-infrared spectroscopy has advantages compared to individual methods for the clinical implementation of this technique as a diagnostic tool.

Development and Testing of an LED-Based Near-Infrared Sensor for Human Kidney Tumor Diagnostics.

Optical spectroscopy is increasingly used for cancer diagnostics. Tumor detection feasibility in human kidney samples using mid- and near-infrared (NIR) spectroscopy, fluorescence spectroscopy, and Raman spectroscopy has been reported (Artyushenko et al., Spectral fiber sensors for cancer diagnostics in vitro. In Proceedings of the European Conference on Biomedical Optics, Munich, Germany, 21-25 June 2015). In the present work, a simplification of the NIR spectroscopic analysis for cancer diagnostics was studied. The conventional high-resolution NIR spectroscopic method of kidney tumor diagnostics was replaced by a compact optical sensing device constructively represented by a set of four light-emitting diodes (LEDs) at selected wavelengths and one detecting photodiode. Two sensor prototypes were tested using 14 in vitro clinical samples of 7 different patients. Statistical data evaluation using principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) confirmed the general applicability of the LED-based sensing approach to kidney tumor detection. An additional validation of the results was performed by means of sample permutation.

Synergy Effect of Combining Fluorescence and Mid Infrared Fiber Spectroscopy for Kidney Tumor Diagnostics.

Matching pairs of tumor and non-tumor kidney tissue samples of four patients were investigated ex vivo using a combination of two methods, attenuated total reflection mid infrared spectroscopy and fluorescence spectroscopy, through respectively prepared and adjusted fiber probes. In order to increase the data information content, the measurements on tissue samples in both methods were performed in the same 31 preselected positions. Multivariate data analysis revealed a synergic effect of combining the two methods for the diagnostics of kidney tumor compared to individual techniques.

Reference-free spectroscopic determination of fat and protein in milk in the visible and near infrared region below 1000nm using spatially resolved diffuse reflectance fiber probe.

New technique of diffuse reflectance spectroscopic analysis of milk fat and total protein content in the visible (Vis) and adjacent near infrared (NIR) region (400-995nm) has been developed and tested. Sample analysis was performed through a probe having eight 200-µm fiber channels forming a linear array. One of the end fibers was used for the illumination and other seven - for the spectroscopic detection of diffusely reflected light. One of the detection channels was used as a reference to normalize the spectra and to convert them into absorbance-equivalent units. The method has been tested experimentally using a designed sample set prepared from industrial raw milk standards with widely varying fat and protein content. To increase the modelling robustness all milk samples were measured in three different homogenization degrees. Comprehensive data analysis has shown the advantage of combining both spectral and spatial resolution in the same measurement and revealed the most relevant channels and wavelength regions. The modelling accuracy was further improved using joint variable selection and preprocessing optimization method based on the genetic algorithm. The root mean-square errors of different validation methods were below 0.10% for fat and below 0.08% for total protein content. Based on the present experimental data, it was computationally shown that the full-spectrum analysis in this method can be replaced by a sensor measurement at several specific wavelengths, for instance, using light-emitting diodes (LEDs) for illumination. Two optimal sensor configurations have been suggested: with nine LEDs for the analysis of fat and seven - for protein content. Both simulated sensors exhibit nearly the same component determination accuracy as corresponding full-spectrum analysis.