Chest
Volume 137, Issue 4, April 2010, Pages 790-796
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Original Research
Asthma
Diagnostic Performance of an Electronic Nose, Fractional Exhaled Nitric Oxide, and Lung Function Testing in Asthma

https://doi.org/10.1378/chest.09-1836Get rights and content

Background

Analysis of exhaled breath by biosensors discriminates between patients with asthma and healthy subjects. An electronic nose consists of a chemical sensor array for the detection of volatile organic compounds (VOCs) and an algorithm for pattern recognition. We compared the diagnostic performance of a prototype of an electronic nose with lung function tests and fractional exhaled nitric oxide (FENO) in patients with atopic asthma.

Methods

A cross-sectional study was undertaken in 27 patients with intermittent and persistent mild asthma and in 24 healthy subjects. Two procedures for collecting exhaled breath were followed to study the differences between total and alveolar air. Seven patients with asthma and seven healthy subjects participated in a study with mass spectrometry (MS) fingerprinting as an independent technique for assessing between group discrimination. Classification was based on principal component analysis and a feed-forward neural network.

Results

The best results were obtained when the electronic nose analysis was performed on alveolar air. Diagnostic performance for electronic nose, FENO, and lung function testing was 87.5%, 79.2%, and 70.8%, respectively. The combination of electronic nose and FENO had the highest diagnostic performance for asthma (95.8%). MS fingerprints of VOCs could discriminate between patients with asthma and healthy subjects.

Conclusions

The electronic nose has a high diagnostic performance that can be increased when combined with FENO. Large studies are now required to definitively establish the diagnostic performance of the electronic nose. Whether this integrated noninvasive approach will translate into an early diagnosis of asthma has to be clarified.

Trial registration

EUDRACT https://eudralink.emea.europa.eu; Identifier: 2007-000890-51; and clinicaltrials.gov; Identifier: NCT00819676.

Section snippets

Study Subjects

Twenty-seven white patients with intermittent or mild persistent asthma and 24 healthy subjects were studied (Table 1). Among study subjects, seven patients with asthma and seven healthy subjects participated in a study with GC/MS used for MS fingerprinting, an independent technique for assessing between-group discrimination.

Patients with asthma were recruited from the Allergy Outpatient Clinic, Istituto Dermopatico dell'Immacolata, IDI, Rome, Italy. Diagnosis and classification of asthma were

Electronic Nose

The best results were obtained when electronic nose analysis was performed on alveolar air (Tables 2, 3). Diagnostic classification with 95% CIs is shown in Table 4. The diagnostic performance was determined with the test datasets in terms of the number of correct identifications of asthma diagnosis based on current guidelines.11 Diagnostic performance for the electronic nose, FENO, lung function tests, and their combinations is shown in Table 2, Table 3 and is related to the best performances

Discussion

The original aspects of our study are: (1) the comparison between an electronic nose and FENO, in addition to lung function tests; (2) the comparison between total and alveolar exhaled air; (3) the number of study subjects (27 patients with intermittent and persistent mild asthma and 24 healthy controls); (4) the MS fingerprinting based on GC/MS analysis; and (5) the analysis of data based on a neural network that included a training and test analysis performed in two separate datasets for

Acknowledgments

Author contributions: Dr Montuschi: contributed to study planning, study design, measurement of FENO, spirometry, data analysis, data interpretation, and wrote the manuscript.

Dr Santonico: contributed to electronic nose analysis, data interpretation, and mass spectrometry fingerprinting.

Dr Mondino: contributed to recruitment of patients and skin prick testing.

Dr Pennazza: contributed to electronic nose analysis, data interpretation, and mass spectrometry fingerprinting.

Ms Mantini: contributed

References (0)

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Funding/Support: Supported by Merck, Sharp, and Dohme, and Catholic University of the Sacred Heart academic grant 2008-2009.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestpubs.org/site/misc/reprints.xhtml).

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