Related Experiment Video For Breath analysis
Updated: Aug 8, 2026
Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry
Published on: March 9, 2018
Real-time breath metabolomic profiling reveals a volatile signature associated with lung cancer
Kai Fricke1, Jonas Herth1, Diego M Baur1
1Faculty of Medicine, University of Zurich, Switzerland; Department of Pulmonology, University Hospital Zurich, Switzerland.
Background:
Real-time breath metabolomic profiling may detect lung cancer-associated breath features, but exploratory case-control findings require cautious interpretation because small cohorts are susceptible to overfitting and may not reflect real-world diagnostic performance.
Methods:
In this single-centre matched case-control study, adults undergoing bronchoscopy for suspected lung cancer provided real-time whole-breath samples before bronchoscopy. In confirmed malignancy, bronchoscopic airway samples were collected under general anaesthesia to evaluate whole-breath concordance. Controls were matched by age, sex and smoking history. Machine-learning analyses used nested participant-level cross-validation.
Results:
Seventy-six participants were included: 38 in the malignancy cohort, comprising 37 primary lung cancers and one thymic sarcomatoid carcinoma, and 38 matched controls. Most cancers were stage III-IV. Feature selection identified 23 breath VOC features contributing to separation between lung cancer and controls. Twenty-two features were also detected in paired airway samples; feature-level correlations provided partial whole-breath-airway concordance, and formal equivalence testing showed no systematic ipsilateral-contralateral airway differences. Stage-related analyses were exploratory because only 13 malignancy cases had stage I-II disease. Within this enriched cohort, participant-level out-of-fold analysis showed exploratory signal separation using the primary 23-feature Elastic Net model (AUC 0.865, 95% bootstrap CI 0.769-0.938), but this estimate should not be interpreted as real-world diagnostic accuracy.
Conclusions:
Real-time breath profiling identified a lung cancer-associated breath feature pattern in this exploratory matched case-control cohort. The findings support prospective multicentre validation with locked algorithms before clinical diagnostic performance can be inferred in lower-prevalence indeterminate nodule and screening populations.
Trial Registration:
NCT02781857 (25/May/2016).
