LaserBreeze gas analyzer for noninvasive diagnostics of air exhaled by patients

Karapuzikov, Alexey A.; Sherstov, I. V.; Kolker, D. B.; Karapuzikov, A. I.; Kistenev, Yury V.; Kuzmin, Dmitry A.; Shtyrov, M. Yu.; Dukhovnikova, N. Yu.; Zenov, K. G.; Boyko, Аndrey А.; Старикова, М. К.; Tikhonyuk, I. I.; Мирошниченко, И. Б.; Miroshnichenko, Maksim B.; Myakishev, Yu. B.; Lokonov, V. N.

doi:10.3103/s1541308x14030054

Cited by 30 publications

(11 citation statements)

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“…This study included 18 lung cancer patients, 21 patients with pneumonia, 22 patients with chronic obstructive pulmonary disease, and 39 healthy nonsmoking volunteers [ 125 ]. The PAS LaserBreeze gas analyzer uses a wavelength range of 2.5–10.7 μm [ 126 ], and the laser source includes two automatically switched OPOs pumped by Nd:YLF laser. The experimental data analysis was carried out using a support vector machine (SVM) which is a differential classification predictive machine learning.…”

Section: Applicationsmentioning

confidence: 99%

Types of spectroscopy and microscopy techniques for cancer diagnosis: a review

et al. 2022

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Cancer is a life-threatening disease that has claimed the lives of many people worldwide. With the current diagnostic methods, it is hard to determine cancer at an early stage, due to its versatile nature and lack of genomic biomarkers. The rapid development of biophotonics has emerged as a potential tool in cancer detection and diagnosis. Using the fluorescence, scattering, and absorption characteristics of cells and tissues, it is possible to detect cancer at an early stage. The diagnostic techniques addressed in this review are highly sensitive to the chemical and morphological changes in the cell and tissue during disease progression. These changes alter the fluorescence signal of the cell/tissue and are detected using spectroscopy and microscopy techniques including confocal and two-photon fluorescence (TPF). Further, second harmonic generation (SHG) microscopy reveals the morphological changes that occurred in non-centrosymmetric structures in the tissue, such as collagen. Again, Raman spectroscopy is a non-destructive method that provides a fingerprinting technique to differentiate benign and malignant tissue based on Raman signal. Photoacoustic microscopy and spectroscopy of tissue allow molecule-specific detection with high spatial resolution and penetration depth. In addition, terahertz spectroscopic studies reveal the variation of tissue water content during disease progression. In this review, we address the applications of spectroscopic and microscopic techniques for cancer detection based on the optical properties of the tissue. The discussed state-of-the-art techniques successfully determines malignancy to its rapid diagnosis.

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Section: Applicationsmentioning

confidence: 99%

Types of spectroscopy and microscopy techniques for cancer diagnosis: a review

et al. 2022

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“…We developed the LaserBreeze gas analyzer based on an LPAS method and OPO with a tuning range from 2.5 to 10.7 μm. 23 The experimental set-up of the LaserBreeze gas analyzer is shown in Fig. 1.…”

Section: Technical Backgroundmentioning

confidence: 99%

Exhaled air analysis using wideband wave number tuning range infrared laser photoacoustic spectroscopy

et al. 2017

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The infrared laser photoacoustic spectroscopy (LPAS) and the pattern-recognition-based approach for noninvasive express diagnostics of pulmonary diseases on the basis of absorption spectra analysis of the patient’s exhaled air are presented. The study involved lung cancer patients ( N = 9 ), patients with chronic obstructive pulmonary disease ( N = 12 ), and a control group of healthy, nonsmoking volunteers ( N = 11 ). The analysis of the measured absorption spectra was based at first on reduction of the dimension of the feature space using principal component analysis; thereafter, the dichotomous classification was carried out using the support vector machine. The gas chromatography–mass spectrometry method (GC–MS) was used as the reference. The estimated mean value of the sensitivity of exhaled air sample analysis by the LPAS in dichotomous classification was not less than 90% and specificity was not less than 69%; the analogous results of analysis by GC–MS were 68% and 60%, respectively. Also, the approach to differential diagnostics based on the set of SVM classifiers usage is presented.

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“…Registration of spectral characteristics of exhaled air probes (EAPs) was carried out using the LaserBreeze gas analyzer based on an LPAS method and OPO with a tuning range of 2.5-10.7 lm. The parameters of LaserBreeze gas analyzer are presented in [6].…”

Section: The Experimental Basementioning

confidence: 99%

Development of Classification Rules for a Screening Diagnostics of Lung Cancer Patients Based on the Spectral Analysis of Metabolic Profiles in the Exhaled Air

Borisov

Kistenev

Kuzmin

et al. 2017

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

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The pattern recognition technique was used for the development of classification rules for a screening diagnostics of lung cancer (LC) patients, based on the spectral analysis of metabolic profiles in the exhaled air, measured by the IR laser photoacoustic spectroscopy (LPAS). The study involved LC, chronic obstructive pulmonary disease, pneumonia patients, and healthy volunteers. The analysis of the measured spectra of exhaled air samples was based first on reduction of the dimension of the feature space using principal component analysis (PCA); thereafter the dichotomous classification was carried out using the support vector machine (SVM). The approaches to differential diagnostics based on the set of SVM classifiers usage are presented.

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LaserBreeze gas analyzer for noninvasive diagnostics of air exhaled by patients

Cited by 30 publications

References 2 publications

Types of spectroscopy and microscopy techniques for cancer diagnosis: a review

Types of spectroscopy and microscopy techniques for cancer diagnosis: a review

Exhaled air analysis using wideband wave number tuning range infrared laser photoacoustic spectroscopy

Development of Classification Rules for a Screening Diagnostics of Lung Cancer Patients Based on the Spectral Analysis of Metabolic Profiles in the Exhaled Air

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