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1.
Sci Rep ; 14(1): 7430, 2024 Mar 28.
Article in English | MEDLINE | ID: mdl-38548800

ABSTRACT

A fiber probe has been developed that enables simultaneous acquisition of mid-infrared (MIR) and Raman spectra in the region of 3100-2600 cm-1. Multimodal measurement is based on a proposed ZrO2 crystal design at the tip of an attenuated total reflection (ATR) probe. Mid-infrared ATR spectra are obtained through a pair of chalcogenide infrared (CIR) fibers mounted at the base of the crystal. The probe enables both excitation and acquisition of a weak Raman signal from a portion of the sample in front of the crystal using an additional pair of silica fibers located in a plane perpendicular to the CIR fibers. The advantages of combining MIR and Raman spectra in a single probe have been discussed.

2.
Analyst ; 148(17): 4116-4126, 2023 Aug 21.
Article in English | MEDLINE | ID: mdl-37493462

ABSTRACT

Patients with oral cavity cancer are almost always treated with surgery. The goal is to remove the tumor with a margin of more than 5 mm of surrounding healthy tissue. Unfortunately, this is only achieved in about 15% to 26% of cases. Intraoperative assessment of tumor resection margins (IOARM) can dramatically improve surgical results. However, current methods are laborious, subjective, and logistically demanding. This hinders broad adoption of IOARM, to the detriment of patients. Here we present the development and validation of a high-wavenumber Raman spectroscopic technology, for quick and objective intraoperative measurement of resection margins on fresh specimens. It employs a thin fiber-optic needle probe, which is inserted into the tissue, to measure the distance between a resection surface and the tumor. A tissue classification model was developed to discriminate oral cavity squamous cell carcinoma (OCSCC) from healthy oral tissue, with a sensitivity of 0.85 and a specificity of 0.92. The tissue classification model was then used to develop a margin length prediction model, showing a mean difference between margin length predicted by Raman spectroscopy and histopathology of -0.17 mm.


Subject(s)
Mouth Neoplasms , Spectrum Analysis, Raman , Mouth Neoplasms/diagnosis , Mouth Neoplasms/surgery , Margins of Excision , Intraoperative Period , Spectrum Analysis, Raman/instrumentation , Carcinoma, Squamous Cell/diagnosis , Carcinoma, Squamous Cell/surgery , Humans
3.
Sci Rep ; 12(1): 16436, 2022 09 30.
Article in English | MEDLINE | ID: mdl-36180775

ABSTRACT

The worldwide increase of antimicrobial resistance (AMR) is a serious threat to human health. To avert the spread of AMR, fast reliable diagnostics tools that facilitate optimal antibiotic stewardship are an unmet need. In this regard, Raman spectroscopy promises rapid label- and culture-free identification and antimicrobial susceptibility testing (AST) in a single step. However, even though many Raman-based bacteria-identification and AST studies have demonstrated impressive results, some shortcomings must be addressed. To bridge the gap between proof-of-concept studies and clinical application, we have developed machine learning techniques in combination with a novel data-augmentation algorithm, for fast identification of minimally prepared bacteria phenotypes and the distinctions of methicillin-resistant (MR) from methicillin-susceptible (MS) bacteria. For this we have implemented a spectral transformer model for hyper-spectral Raman images of bacteria. We show that our model outperforms the standard convolutional neural network models on a multitude of classification problems, both in terms of accuracy and in terms of training time. We attain more than 96% classification accuracy on a dataset consisting of 15 different classes and 95.6% classification accuracy for six MR-MS bacteria species. More importantly, our results are obtained using only fast and easy-to-produce training and test data.


Subject(s)
Anti-Infective Agents , Spectrum Analysis, Raman , Bacteria , Humans , Machine Learning , Methicillin , Phenotype , Spectrum Analysis, Raman/methods
4.
Biomed Opt Express ; 13(2): 744-760, 2022 Feb 01.
Article in English | MEDLINE | ID: mdl-35284181

ABSTRACT

Pyrometry is widely used in science, medicine, and industry to measure the surface temperature of objects in a non-contact way. IR fibers are an ideal solution for the flexible delivery of thermal radiation emitted from objects inside a complex structure like internal organs inside the human body. Silver halide polycrystalline infrared fibers (PIR) are transparent in a spectral range of 3 - 18 µm, matching perfectly with the spectra of black body radiation for temperatures ranging from 20°C to 200°C. These fibers are non-toxic and allow small bending radii. They could become critical components in pyrometric systems for temperature-controlled laser surgeries. Here we discuss the ability of the PIR fibers for simultaneous laser power delivery and real-time temperature monitoring in laser surgery applications and demonstrate two different setups for this purpose.

5.
Anal Chem ; 93(15): 6013-6018, 2021 04 20.
Article in English | MEDLINE | ID: mdl-33821623

ABSTRACT

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.

6.
Sensors (Basel) ; 20(22)2020 Nov 23.
Article in English | MEDLINE | ID: mdl-33238646

ABSTRACT

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.


Subject(s)
Colorectal Neoplasms/diagnostic imaging , Spectrophotometry, Infrared , Stomach Neoplasms/diagnostic imaging , Humans
7.
Opt Express ; 28(19): 27940-27950, 2020 Sep 14.
Article in English | MEDLINE | ID: mdl-32988076

ABSTRACT

Limited operating bandwidth originated from strong absorption of glass materials in the infrared (IR) spectral region has hindered the potential applications of microstructured optical waveguide (MOW)-based sensors. Here, we demonstrate multimode waveguide regime up to 6.5 µm for the hollow-core (HC) MOWs drawn from borosilicate soft glass. Effective light guidance in central HC (diameter ∼240 µm) was observed from 0.4 to 6.5 µm despite high waveguide losses (0.4 and 1 dB/cm in near- and mid-IR, respectively). Additional optimization of the waveguide structure can potentially extend its operating range and decrease transmission losses, offering an attractive alternative to tellurite and chalcogenide-based fibers. Featuring the transparency in mid-IR, HC MOWs are promising candidates for the creation of MOW-based sensors for chemical and biomedical applications.

8.
Sensors (Basel) ; 17(11)2017 Nov 05.
Article in English | MEDLINE | ID: mdl-29113084

ABSTRACT

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.


Subject(s)
Spectrophotometry, Infrared , Multivariate Analysis
9.
Sensors (Basel) ; 17(8)2017 Aug 19.
Article in English | MEDLINE | ID: mdl-28825612

ABSTRACT

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.


Subject(s)
Least-Squares Analysis , Discriminant Analysis , Humans , Kidney Neoplasms , Principal Component Analysis , Spectroscopy, Near-Infrared
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