An electronic nose in the discrimination of patients with asthma and controls

Background Exhaled breath contains thousands of volatile organic compounds (VOCs) that could serve as biomarkers of lung disease. Electronic noses can distinguish VOC mixtures by pattern recognition. Objective We hypothesized that an electronic nose can discriminate exhaled air of patients with asth...

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Bibliographic Details
Published in:Journal of allergy and clinical immunology 2007-10, Vol.120 (4), p.856-862
Main Authors: Dragonieri, Silvano, MD, Schot, Robert, BEng, Mertens, Bart J.A., PhD, Le Cessie, Saskia, PhD, Gauw, Stefanie A., BN, Spanevello, Antonio, MD, Resta, Onofrio, MD, Willard, Nico P., PhD, Vink, Teunis J., PhD, Rabe, Klaus F., MD, PhD, Bel, Elisabeth H., MD, PhD, Sterk, Peter J., MD, PhD
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Allergy and Immunology
Asthma
Asthma - diagnosis
Asthma mild
asthma severe
Biological and medical sciences
biomarkers
Biosensing Techniques - instrumentation
Breath Tests - instrumentation
Case-Control Studies
Cross-Sectional Studies
diagnosis
Discrimination
Disease
electronic nose
exhaled breath
Fundamental and applied biological sciences. Psychology
Fundamental immunology
Gas Chromatography-Mass Spectrometry
Humans
Hypotheses
Immunopathology
Lung cancer
Medical sciences
Methods
Middle Aged
Nitric oxide
Nose
Organic Chemicals - analysis
Pattern recognition systems
Sarcoidosis. Granulomatous diseases of unproved etiology. Connective tissue diseases. Elastic tissue diseases. Vasculitis
Sensors
Studies
VOCs
Volatile organic compounds
Volatilization
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Summary:Background Exhaled breath contains thousands of volatile organic compounds (VOCs) that could serve as biomarkers of lung disease. Electronic noses can distinguish VOC mixtures by pattern recognition. Objective We hypothesized that an electronic nose can discriminate exhaled air of patients with asthma from healthy controls, and between patients with different disease severities. Methods Ten young patients with mild asthma (25.1 ± 5.9 years; FEV1 , 99.9 ± 7.7% predicted), 10 young controls (26.8 ± 6.4 years; FEV1 , 101.9 ± 10.3), 10 older patients with severe asthma (49.5 ± 12.0 years; FEV1 , 62.3 ± 23.6), and 10 older controls (57.3 ± 7.1 years; FEV1 , 108.3 ± 14.7) joined a cross-sectional study with duplicate sampling of exhaled breath with an interval of 2 to 5 minutes. Subjects inspired VOC-filtered air by tidal breathing for 5 minutes, and a single expiratory vital capacity was collected into a Tedlar bag that was sampled by electronic nose (Cyranose 320) within 10 minutes. Smellprints were analyzed by linear discriminant analysis on principal component reduction. Cross-validation values (CVVs) were calculated. Results Smellprints of patients with mild asthma were fully separated from young controls (CVV, 100%; Mahalanobis distance [M-distance], 5.32), and patients with severe asthma could be distinguished from old controls (CVV, 90%; M-distance, 2.77). Patients with mild and severe asthma could be less well discriminated (CVV, 65%; M-distance, 1.23), whereas the 2 control groups were indistinguishable (CVV, 50%; M-distance, 1.56). The duplicate samples replicated these results. Conclusion An electronic nose can discriminate exhaled breath of patients with asthma from controls but is less accurate in distinguishing asthma severities. Clinical implication These findings warrant validation of electronic noses in diagnosing newly presented patients with asthma.
ISSN:0091-6749
1097-6825
DOI:10.1016/j.jaci.2007.05.043