High Concordance of E-Nose-Derived Breathprints in a Healthy Population: A Cross-Sectional Observational Study

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 8; p. 2610
• Main Authors: Dragonieri, Silvano, Quaranta, Vitaliano Nicola, Portacci, Andrea, Ranieri, Teresa, Carpagnano, Giovanna Elisiana
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 20.04.2025; MDPI
• Subjects: Adolescent; Adult; Aged; Algorithms; Breath tests; Breath Tests - instrumentation; Breath Tests - methods; breathprints; Chronic obstructive pulmonary disease; Cluster Analysis; Clustering; Cross-Sectional Studies; Cyranose 320; Data analysis; Datasets; Electronic Nose; Exhalation - physiology; exhaled breath analysis; Female; Healthy Volunteers; Humans; Humidity; Infectious diseases; Machine learning; Male; Mass spectrometry; Metabolism; Middle Aged; Observational studies; Oral hygiene; Principal Component Analysis; Principal components analysis; Reproducibility; Sample size; Scientific imaging; Sensors; Standardization; VOCs; Volatile organic compounds; Young Adult; United States > US; VOCs; breathprints; diagnostics; Cyranose 320; standardization; electronic nose; exhaled breath analysis
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s25082610

Exhaled breath analysis using electronic noses (e-noses) is a promising non-invasive diagnostic tool. However, a lack of standardized protocols limits clinical implementation. This study evaluates the consistency of breathprints in healthy subjects using the Cyranose 320 e-nose to support standardization efforts. Breath samples from 139 healthy non-smoking subjects (age range 18–65 years) were collected using a standardized protocol. Participants exhaled into a Tedlar bag for immediate analysis with the Cyranose 320. Principal Component Analysis (PCA) was used to reduce data dimensionality, and K-means clustering grouped subjects based on breathprints. PCA identified four principal components explaining 97.15% of variance. K-means clustering revealed two clusters: 1 outlier and 138 subjects with highly similar breathprints. The median distance from the cluster center was 0.21 (IQR: 0.18–0.24), indicating low variability. Box plots confirmed breathprint consistency across subjects. The high consistency of breathprints in healthy subjects supports the feasibility of standardizing e-nose protocols. These findings highlight the potential of e-noses for clinical diagnostics, warranting further research in diverse populations and disease cohorts.