Expiratory flow rate, breath hold and anatomic dead space influence electronic nose ability to detect lung cancer

BACKGROUND: Electronic noses are composites of nanosensor arrays. Numerous studies showed their potential to detect lung cancer from breath samples by analysing exhaled volatile compound pattern (“breathprint”). Expiratory flow rate, breath hold and inclusion of anatomic dead space may influence the exhaled levels of some volatile compounds; however it has not been fully addressed how these factors affect electronic nose data. Therefore, the aim of the study was to investigate these effects. METHODS: 37 healthy subjects (44 ± 14 years) and 27 patients with lung cancer (60 ± 10 years) participated in the study. After deep inhalation through a volatile organic compound filter, subjects exhaled at two different flow rates (50 ml/sec and 75 ml/sec) into Teflon-coated bags. The effect of breath hold was analysed after 10 seconds of deep inhalation. We also studied the effect of anatomic dead space by excluding this fraction and comparing alveolar air to mixed (alveolar + anatomic dead space) air samples. Exhaled air samples were processed with Cyranose 320 electronic nose. RESULTS: Expiratory flow rate, breath hold and the inclusion of anatomic dead space significantly altered “breathprints” in healthy individuals (p < 0.05), but not in lung cancer (p > 0.05). These factors also influenced the discrimination ability of the electronic nose to detect lung cancer significantly. CONCLUSIONS: We have shown that expiratory flow, breath hold and dead space influence exhaled volatile compound pattern assessed with electronic nose. These findings suggest critical methodological recommendations to standardise sample collections for electronic nose measurements

Modest genetic influence on bronchodilator response:A study in healthy twins

Aim To determine the reasons for large standard deviation of bronchodilator response (BDR) and establish whether there is a potential heritable component in healthy subjects. Methods 67 monozygotic and 42 dizygotic adult twin pairs were assessed for bronchodilator response (% change in FEV1 after inhaling 400 μg salbutamol). Univariate quantitative genetic modeling was performed. Results Multiple regression modeling showed a significant association between BDR and sex and baseline FEV1 (P < 0.05), while no association was found with smoking habits, body mass index, or age. Within pair correlation in monozygotic twins was modest (0.332), but higher than in dizygotic twins (0.258). Age-, sex-, and baseline FEV1- adjusted genetic effect accounted for 14.9% (95% confidence interval, CI 0%-53.1%) of the variance of BDR, shared environmental effect for 18.4% (95% CI 0%-46.8%), and unshared environmental effect for 66.8% (95% CI 46.8%-88.7%). Conclusion Our twin study showed that individual differences in BDR can be mostly explained by unshared environmental effects. In addition, it is the first study to show low, insignificant hereditary influences, independently from sex, age, and baseline FEV1