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В статье рассматривается возможность мониторинга восстановления после перенесенных респираторных заболеваний методами масс-спектрометрии. В исследовании приняли участие две группы испытуемых: 18 человек, переболевших респираторной вирусной инфекцией, и 31 здоровый доброволец в хорошей физической форме. В исследовании использовалась неинвазивная масс-спектрометрическая методика контроля газового состава выдыхаемого воздуха. Результаты эксперимента показывают эффективность методики: выявленные различия в масс-спектрах здоровых людей и испытуемых, перенесших респираторную вирусную инфекцию, позволяют использовать методику для поиска маркеров патологий., This article considers the possibility of monitoring recovery after respiratory diseases by mass spectrometric methods. Two groups of test subjects took part in the study: 18 individuals who had had a respiratory viral infection and 31 healthy volunteers in good physical condition. A noninvasive mass spectrometric method of controlling the gas composition of exhaled air was used in the study. The results of the experiment demonstrate the effectiveness of the technique: the differences detected in the mass spectra of healthy people and subjects who had a respiratory viral infection allow the technique to be used to search for pathology markers.

A Raman spectrometer for gaseous media with a detection limit at a level of 100 ppb is developed. The results of its experimental approval on exhaled air samples from healthy people confirmed the possibility of monitoring the concentrations of a number of hydrocarbon compounds and 13CO2. The ways of further development of this analytical method are outlined.

Funding Acknowledgements Type of funding sources: None. Background. Myocardial infarction is one of the main causes of mortality and disability. The standard diagnosis of myocardial infarction is associated with cardiospecific enzymes blood sampling. At the same time, it is of interest to search for new non-invasive myocardial necrosis markers, and there are few data in the periodicals on exhaled metabolites in myocardial infarction patients. Purpose. Detecting specific molecules or their combination for ST-segment elevation myocardial infarction patients in exhaled air by analyzing the spectroscopic characteristics of exhaled air samples. Methods. The target group included 17 patients. The control group included 18 healthy volunteers. Inclusion criteria for the target group: primary STEMI; admission within 12 hours from the onset of STEMI; age 18 and older. All patients underwent standard diagnostics of AMI, including determination of CPK, CPK-MB, troponin. Exclusion criteria: acute illness, or exacerbation of chronic, major surgery 1 month before myocardial infarction; severe lung pathology; congestive heart failure III, IV NYHA class; impossibility of air sampling due to various reasons. In parallel, on the 1st day of hospitalization, as early as possible, air samples were taken on fasting. To do this, the patient three times calmly, until the lungs are completely empty, exhales into the surrounding space, at the end of the third exhalation - into a one-off air intake, which then was closed hermetically. The absorption spectra of samples of exhaled air were determined using the method of laser optical-acoustic spectroscopy and using a system for terahertz spectroscopy with time resolution. A comparative analysis of the spectra of samples of exhaled air for the 1st and 2nd ranges was carried out. The obtained spectra of exhaled air samples were analyzed using the principal component analysis. Statistical data processing was carried out by the STATISTICA 10.0. Results. Absorption spectra of exhaled air samples were obtained in two ranges - infrared (range 1, wavelength: 2.5-10 μm - using the method of laser optical-acoustic spectroscopy) and terahertz (range 2, frequency: 0.3-2 THz - s using a terahertz time-resolved spectroscopy system). A comparative spectra analysis of exhaled air samples for the 1st and 2nd ranges was carried out. It is shown that in the Principal Component space of the vector set of signs for the spectra of exhaled air samples in ranges 1 and 2, corresponding to healthy patients and patients with primary myocardial infarction, it is possible to perform a visual separation. Conclusion. With the help of optical-acoustic and terahertz spectroscopy, a specific combination of substances in the exhaled air for patients with ST-segment elevation myocardial infarction was found.

Conventional acute myocardial infarction (AMI) diagnosis is quite accurate and has proved its effectiveness. However, despite this, discovering more operative methods of this disease detection is underway. From this point of view, the application of exhaled air analysis for a similar diagnosis is valuable. The aim of the paper is to research effective machine learning algorithms for the predictive model for AMI diagnosis constructing, using exhaled air spectral data. The target group included 30 patients with primary myocardial infarction. The control group included 42 healthy volunteers. The ‘LaserBreeze’ laser gas analyzer (Special Technologies Ltd, Russia), based on the dual-channel resonant photoacoustic detector cell and optical parametric oscillator as the laser source, had been used. The pattern recognition approach was applied in the same manner for the set of extracted concentrations of AMI volatile markers and the set of absorption coefficients in a most informative spectral range 2.900 ± 0.125 µm. The created predictive model based on the set of absorption coefficients provided 0.86 of the mean values of both the sensitivity and specificity when linear support vector machine (SVM) combined with principal component analysis was used. The created predictive model based on using six volatile AMI markers (C5H12, N2O, NO2, C2H4, CO, CO2) provided 0.82 and 0.93 of the mean values of the sensitivity and specificity, respectively, when linear SVM was used.

Control over volatile products of metabolic processes in human body in exhaled air is a promising method for noninvasive medical diagnostics. The mid-IR range (2 – 12 mm) is of great interest for diagnostic applications of the exhaled air spectral analysis. Laser optoacoustic spectroscopy is quite attractive for detecting a large set of gaseous substances; however, high-power sources of tunable radiation are required to increase the method sensitivity. We consider the possibility of using a parametric light generator based on a BaGa4Se7 crystal as a broadband tunable mid-IR laser source for laser optoacoustic spectroscopy.

Myocardial infarction (MI) causes partial or complete necrosis of the heart muscle. It means that muscle cells are wiped, and the contractility of the heart decreases. Today, for the MI diagnosis is based on the ECG recording or specific biomarkers identifying in the patient's blood, the most specific of which are: creatine phosphokinase (CPK), CPK-MB, fatty acids binding protein (H-FABP), myoglobin troponin-I, and troponin-T. Additionally to these biomarkers in the MI patients’ blood, there are many other products of metabolism in damaged muscles, which are excreted from the body human body, including through exhaled air. The results of MI patients’ exhaled air analysis using photoacoustic laser spectroscopy and data mining are presented.

Цель исследования. Изучить влияние курения на воздух, выдыхаемый больными хронической обструктивной болезнью легких (ХОБЛ) и бронхиальной астмой (БА), с применением оптико-акустической спектроскопии. Материалы и методы. Проведен анализ спектров поглощения выдыхаемого воздуха (СПВВ) у здоровых добровольцев и больных ХОБЛ и БА с помощью лазерного оптико-акустического газоанализатора ILPA-1 на основе CO2-лазера. Для оценки результатов использовали методику, основанную на вычислении интегральной оценки (ИО) состояния объекта. Результаты. Сравнение ИО СПВВ больных ХОБЛ и некурящих здоровых лиц показало, что в диапазоне длин волн, соответствующем ветви 10R генерации CO2-лазера, регистрируются спектры соединений, образование которых связано с курением. Кроме того, получены данные об отличии выдыхаемого воздуха больных БА от выдыхаемого воздуха как курящих, так и некурящих здоровых лиц. На основе расчетов получены пороговые значения ИО СПВВ в диапазоне длин волн, соответствующем ветви 10P генерации CO2-лазера, которые позволяют отличать некурящих здоровых лиц от больных БА и ХОБЛ в 94 и 89% случаев соответственно. Заключение. Подтверждено, что курение существенно влияет на состав воздуха, выдыхаемого здоровыми лицами. Показано, что использование референтной группы, сформированной из некурящих здоровых лиц, позволяет повысить точность при выявлении ХОБЛ и БА методом оптико-акустической спектроскопии. При дальнейшей разработке данного направления открываются перспективы получения нового метода для диагностики ХОБЛ и БА.

Цель исследования. Изучить влияние курения на воздух, выдыхаемый больными хронической обструктивной болезнью легких (ХОБЛ) и бронхиальной астмой (БА), с применением оптико-акустической спектроскопии. Материалы и методы. Проведен анализ спектров поглощения выдыхаемого воздуха (СПВВ) у здоровых добровольцев и больных ХОБЛ и БА с помощью лазерного оптико-акустического газоанализатора ILPA-1 на основе CO2-лазера. Для оценки результатов использовали методику, основанную на вычислении интегральной оценки (ИО) состояния объекта. Результаты. Сравнение ИО СПВВ больных ХОБЛ и некурящих здоровых лиц показало, что в диапазоне длин волн, соответствующем ветви 10R генерации CO2-лазера, регистрируются спектры соединений, образование которых связано с курением. Кроме того, получены данные об отличии выдыхаемого воздуха больных БА от выдыхаемого воздуха как курящих, так и некурящих здоровых лиц. На основе расчетов получены пороговые значения ИО СПВВ в диапазоне длин волн, соответствующем ветви 10P генерации CO2-лазера, которые позволяют отличать некурящих здоровых лиц от больных БА и ХОБЛ в 94 и 89% случаев соответственно. Заключение. Подтверждено, что курение существенно влияет на состав воздуха, выдыхаемого здоровыми лицами. Показано, что использование референтной группы, сформированной из некурящих здоровых лиц, позволяет повысить точность при выявлении ХОБЛ и БА методом оптико-акустической спектроскопии. При дальнейшей разработке данного направления открываются перспективы получения нового метода для диагностики ХОБЛ и БА.

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.

The results of measuring of biomarkers in breath air of patients with broncho-pulmonary diseases using wide-band frequency tuning IR laser photo-acoustic spectroscopy and the methods of data mining are presented. We will discuss experimental equipment and various methods of intellectual analysis of the experimental spectra in context of above task. The work was carried out with partial financial support of the FCPIR contract No 14.578.21.0082 (ID RFMEFI57814X0082).

Technique of exhaled breath sampling is discussed. The procedure of wavelength auto-calibration is proposed and tested. Comparison of the experimental data with the model absorption spectra of 5% CO2 is conducted. The classification results of three study groups obtained by using support vector machine and principal component analysis methods are presented.

The results of numerical simulation of application principal component analysis to absorption spectra of breath air of patients with pulmonary diseases are presented. Various methods of experimental data preprocessing are analyzed.

Canonical correlation analysis is adapted to the problem of determining the concentration of molecular components contained in samples of exhaled air. To solve this problem dealt with model spectra in form of linear combination of the absorption spectra of molecular components with unknown coefficients. The absorption spectra were calculated on the basis of databases HITRAN, HITEMP, GEISA. Application of canonical correlation analysis allows us to represent the spectrum of the mixture in the form of a vector whose coordinates are the proportion of the individual components in the mixture.

We consider the problem of finding concentrations of molecular gases in the models of exhaled air samples in terms of their absorption spectra. We introduce model spectra describing the exhaled air samples as linear combinations of the absorption spectra of individual molecular gases with given coefficients. The absorption spectra are calculated on the basis of the database HITRAN. The concentrations are determined using Principal Component Analysis and Canonical Correlation Analysis.

The possibility of the inverse spectroscopic problem solution for multicomponent gas mixtures based on the use of principal component analysis is discussed. The analysis revealed usefulness of principal component analysis to estimate the parameters of the components in a case of investigation of exhaled air samples from various groups of patients.

The comparison results of different mother wavelets used for de-noising of model and experimental data which were presented by profiles of absorption spectra of exhaled air are presented. The impact of wavelets de-noising on classification quality made by principal component analysis are also discussed.

Для аппаратного комплекса, включающего измеритель концентрации углекислого газа и кислорода в выдыхаемом воздухе, разработана программная оболочка. В результате врачу-исследователю предоставляется возможность наблюдения в реальном масштабе динамики потребления кислорода и выделения углекислого газа, анализа и хранения полученных зависимостей. Программное обеспечение протестировано в среде MS Windows 98/2000/XP.