title: Exhaled air analysis using wideband wave number tuning range infrared laser photoacoustic spectroscopy.
abstract: 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.
authors.affiliation: National Research Tomsk State University, 36 Lenin Avenue, Tomsk 634050, RussiabSiberian State Medical University, 2 Moscovsky Trakt, Tomsk 634050, Russia.
authors.forename: Yury V
authors.initials: YV
authors.lastname: Kistenev
authors.affiliation: National Research Tomsk State University, 36 Lenin Avenue, Tomsk 634050, RussiabSiberian State Medical University, 2 Moscovsky Trakt, Tomsk 634050, Russia.
authors.forename: Alexey V
authors.initials: AV
authors.lastname: Borisov
authors.affiliation: National Research Tomsk State University, 36 Lenin Avenue, Tomsk 634050, RussiabSiberian State Medical University, 2 Moscovsky Trakt, Tomsk 634050, Russia.
authors.forename: Dmitry A
authors.initials: DA
authors.lastname: Kuzmin
authors.affiliation: National Research Tomsk State University, 36 Lenin Avenue, Tomsk 634050, Russia.
authors.forename: Olga V
authors.initials: OV
authors.lastname: Penkova
authors.affiliation: Special Technologies, Ltd., 1/3 Zelenaya Gorka, Novosibirsk 630060, Russia.
authors.forename: Nadezhda Y
authors.initials: NY
authors.lastname: Kostyukova
authors.affiliation: Special Technologies, Ltd., 1/3 Zelenaya Gorka, Novosibirsk 630060, Russia.
authors.forename: Alexey A
authors.initials: AA
authors.lastname: Karapuzikov
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001944:Breath Tests / Q000295:instrumentation / Q000379:methods*; D016022:Case-Control Studies; D045853:Exhalation; D008401:Gas Chromatography-Mass Spectrometry; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis*; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D061088:Photoacoustic Techniques / Q000295:instrumentation / Q000379:methods*; D025341:Principal Component Analysis; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis*; D012680:Sensitivity and Specificity; D060388:Support Vector Machine