Differentiation of aspirated nasal air from room air using analysis with a differential mobility spectrometry-based electronic nose: a proof-of-concept study. (2nd December 2021)

• Record Type: Journal Article
• Authors: Virtanen, Jussi; Anttalainen, Anna; Ormiskangas, Jaakko; Karjalainen, Markus; Kontunen, Anton; Rautiainen, Markus; Oksala, Niku; Kivekäs, Ilkka; Roine, Antti
• Is Part Of: Journal of breath research. Volume 16:Number 1(2022)
• Publication Date: 2021-12-02
• Subjects: electronic nose -- eNose -- nasal air -- differential mobility spectrometry -- DMS; Volatile organic compounds -- Analysis -- Periodicals; Clinical chemistry -- Periodicals; Bad breath -- Periodicals; Bad breath -- Treatment -- Periodicals; Bad breath -- Diagnosis -- Periodicals; 616.0756
• DOI: 10.1088/1752-7163/ac3b39
• Languages: English
• ISSNs: 1752-7155

Abstract

Abstract: Over the last few decades, breath analysis using electronic nose (eNose) technology has become a topic of intense research, as it is both non-invasive and painless, and is suitable for point-of-care use. To date, however, only a few studies have examined nasal air. As the air in the oral cavity and the lungs differs from the air in the nasal cavity, it is unknown whether aspirated nasal air could be exploited with eNose technology. Compared to traditional eNoses, differential mobility spectrometry uses an alternating electrical field to discriminate the different molecules of gas mixtures, providing analogous information. This study reports the collection of nasal air by aspiration and the subsequent analysis of the collected air using a differential mobility spectrometer. We collected nasal air from ten volunteers into breath collecting bags and compared them to bags of room air and the air aspirated through the device. Distance and dissimilarity metrics between the sample types were calculated and statistical significance evaluated with Kolmogorov-Smirnov test. After leave-one-day-out cross-validation, a shrinkage linear discriminant classifier was able to correctly classify 100% of the samples. The nasal air differed ( p < 0.05) from the other sample types. The results show the feasibility of collecting nasal air by aspiration and subsequent analysis using differential mobility spectrometry, and thus increases the potential of the method to be used in disease detection studies.