· · · Repository hosted by TU Delft Library

Abstract: An overview of the scientific literature in the medical field tells us that a large part of electronic nose applications is devoted to breath analysis. A network based study can help testing thevalidity of this strategy when using many different devices based on identical or different technologies, in view of a use in real clinical practice. The first step is the instrument calibration using aset of key-compounds. In this work a gas sensor array based on Quartz Micro Balance (QMB) transducers functionalized with metallo-porphyrins (ROTV e-nose), and a Cyranose are used simultaneously in a calibration experiment with three ad hoc selected compounds: ethanol, hexane and ethyl acetate, at concentration levels around 1 ppm. Thesetests have demonstrated that LODs down to tens of ppb are possible.Moreover, a mapping between the two instruments has been performed through the calculation of a model based on Cyranose data, and applied to the ROTV e-nose data, for the prediction of compound concentrations. This test has shown a good ability in concentrations prediction, with an error lower than 10 ppb.

Background Eosinophilic inflammation in COPD is predictive for response to inhaled steroids. We hypothesized that inflammatory subtype in mild and moderately severe COPD can be assessed by exhaled breathmetabolomics. Methods Standardized sampling of exhaled compounds wasperformed using gas-chromatography and mass-spectrometry (GC-MS) and electronic nose (eNose) in 28 COPD patients (12/16 GOLD I/II). Differential cell counts, eosinophilic cationic protein and myeloperoxidase were measured in induced sputum. Relationships between compounds, eNose breathprints and sputum inflammatory markers were analyzedand ROC curves were constructed. Results Exhaled compounds were highly associated with sputum cell counts (9 compounds with eosinophils,20 with neutrophils:,p<0.01). Only two compounds (phenol, alkylatedbenzene) overlapped between eosinophilic and neutrophilic profiles.GC-MS and eNose breathprints were also associated with markers of inflammatory activity, in GOLD stage I (ECP: 19 compounds, p<0.01; eNose breathprint r=0.84, p=0.002) (MPO: 4 compounds p<0.01; eNose r=0.72, p=0.008). ROC analysis for eNose showed high sensitivity and specificity for inflammatory activity in mild COPD (ECP: AUC=1.00) (MPO: AUC=0.96). Conclusions Exhaled molecular profiles are closely associated with the type and activity of airways inflammation in mildand moderate COPD. This suggests that breath analysis can potentially be used for assessment and monitoring of airways inflammation inCOPD.

Introduction It has been postulated that the pathophysiology and clinical presentation of ALI based on pulmonary and non-pulmonary etiology represent different phenotypes1. Until now, little biological evidence on the molecular level has been presented to support this hypothesis. Exhaled air contains volatile organic compounds (VOCs), metabolites of systemic or respiratory origin. Exhaled air metabolites may differ between diseases2. Molecular profiling of exhaled air of intubated and mechanically ventilated ALI patients using an electronic nose might serve as a tool to phenotype patients rapidly and non-invasively. Hypothesis We hypothesized that exhaled breath profiles differ between patients with pulmonary and non-pulmonary ALI.Methods This study represented an interim analysis in a longitudinal diagnostic cohort of intubated and mechanically ventilated ICU patients admitted to the Academic Medical Center, Amsterdam. Patientswith chronic pulmonary diseases were excluded. Consecutive patientswith ALI according to international consensus criteria3 were included. Exhaled breath was sampled by a Cyranose 320, an electronic nose,for 60 seconds using a t-connector placed distal of the endotracheal tube, but proximal to the heat-moist exchanger. The electronic nose contains 32 polymer sensors, which change electrical resistance when bound by volatile organic compounds (VOCs) resulting in a unique“breathprint”. Sensor data are analyzed by principal component (PC)analysis. One-way ANOVA is used to compare groups and ROC-analysis was used to examine diagnostic values. Results 16 patients with ALI at admission were included. ALI was caused by a pulmonary insult in 7 patients (3 pneumonia, 2 aspiration, 1 contusion and 1 drowning)whereas 9 patients had a non-pulmonary (7 sepsis, 2 pancreatitis) and 5 patients had a combined cause for ALI. P/F-ratio, pressures andtidal volumes were not different between patient categories. PC4 was significantly different between patients with pulmonary and non-pulmonary ALI (p = 0.009) (figure 1). ROC-analysis showed good discrimination (AUC 0.84). Conclusions Exhaled breath profiles obtainedby an electronic nose discriminate between patients with pulmonary and non-pulmonary ALI. Implications This indicates that metabolicpathways are differentially expressed between pulmonary and non-pulmonary acute lung injury. These pathways will be delineated using gas-chromatography and mass-spectrometry by separating, identifying andquantifying the discriminating VOCs.