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Background: Patients with COPD are at high risk of lung cancer developing, but no validated predictive biomarkers have been reported to identify these patients. Molecular profiling of exhaled breath by electronic nose (eNose) technology may qualify for early detection of lung cancer in patients with COPD., Research Question: Can eNose technology be used for prospective detection of early lung cancer in patients with COPD?, Study Design and Methods: BreathCloud is a real-world multicenter prospective follow-up study using diagnostic and monitoring visits in day-to-day clinical care of patients with a standardized diagnosis of asthma, COPD, or lung cancer. Breath profiles were collected at inclusion in duplicate by a metal-oxide semiconductor eNose positioned at the rear end of a pneumotachograph (SpiroNose; Breathomix). All patients with COPD were managed according to standard clinical care, and the incidence of clinically diagnosed lung cancer was prospectively monitored for 2 years. Data analysis involved advanced signal processing, ambient air correction, and statistics based on principal component (PC) analysis, linear discriminant analysis, and receiver operating characteristic analysis., Results: Exhaled breath data from 682 patients with COPD and 211 patients with lung cancer were available. Thirty-seven patients with COPD (5.4%) demonstrated clinically manifest lung cancer within 2 years after inclusion. Principal components 1, 2, and 3 were significantly different between patients with COPD and those with lung cancer in both training and validation sets with areas under the receiver operating characteristic curve of 0.89 (95% CI, 0.83-0.95) and 0.86 (95% CI, 0.81-0.89). The same three PCs showed significant differences (P < .01) at baseline between patients with COPD who did and did not subsequently demonstrate lung cancer within 2 years, with a cross-validation value of 87% and an area under the receiver operating characteristic curve of 0.90 (95% CI, 0.84-0.95)., Interpretation: Exhaled breath analysis by eNose identified patients with COPD in whom lung cancer became clinically manifest within 2 years after inclusion. These results show that eNose assessment may detect early stages of lung cancer in patients with COPD., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Pseudomonas aeruginosa (PA) is an important respiratory pathogen for cystic fibrosis (CF) patients. Routine microbiology surveillance is time-consuming, and is best performed on expectorated sputum. As alternative, volatile organic compounds (VOCs) may be indicative of PA colonisation. In this study, we aimed to identify VOCs associated with PA in literature and perform targeted exhaled breath analysis to recognize PA positive CF patients non-invasively., Methods: This study consisted of 1) a literature review to select VOCs of interest, and 2) a cross-sectional CF study. Definitions used: A) PA positive, PA culture at visit/chronically; B) PA free, no PA culture in ≥12 months. Exhaled VOCs were identified via quadrupole MS. The primary endpoint was the area under the receiver operating characteristics curve (AUROCC) of individual VOCs as well as combined VOCs against PA culture., Results: 241 VOCs were identified in literature, of which 56 were further evaluated, and 13 could be detected in exhaled breath in our cohort. Exhaled breath of 25 pediatric and 28 adult CF patients, PA positive (n=16) and free (n=28) was available. 3/13 VOCs were significantly (p<0.05) different between PA groups in children; none were in adults. Notably, a composite model based on 5 or 1 VOC(s) showed an AUROCC of 0.86 (CI 0.71-1.0) and 0.87 (CI 0.72-1.0) for adults and children, respectively., Conclusions: Targeted VOC analysis appears to discriminate children and adults with and without PA positive cultures with clinically acceptable sensitivity values., Competing Interests: Declaration of Competing Interests AHM and PB are supported by an innovation grant from Vertex Pharmaceuticals B.V. PJS is scientific advisor and has a formally inconsiderable interest in the SME Breathomix AHM reports grants and personal fees from GSK, Boehringer Ingelheim, and AstraZeneca, and grants from Chiesi, outside the submitted work., (Copyright © 2021. Published by Elsevier B.V.)

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver-operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66-0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43-0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49-0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50-0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.

Introduction: Asthma is a heterogeneous condition, characterised by chronic inflammation of the airways, typically managed with inhaled bronchodilators and corticosteroids. In the case of uncontrolled asthma, oral corticosteroids (OCSs) are often prescribed. Good adherence and inhalation technique are associated with improved outcomes; however, it is difficult to monitor appropriate drug intake and effectiveness in individual patients. Exhaled breath contains thousands of volatile organic compounds (VOCs) that reflect changes in the body's chemistry and may be useful for monitoring drug pharmacokinetics/pharmacodynamics. We aimed to investigate the association of exhaled VOCs in severe asthma patients from the U-BIOPRED cohort (by gas chromatography coupled with time-of-flight mass spectrometry) with urinary levels of salbutamol and OCSs (by liquid chromatography coupled with high-resolution mass spectrometry)., Methods: Samples were collected at baseline and after 12-18 months of follow-up. Statistical analysis was based on univariate and multivariate modelling, followed by area under the receiver operating characteristic curve (AUC) calculation. Results were verified through longitudinal replication and independent validation., Results: Data were available for 78 patients (baseline n=48, replication n=30 and validation n=30). Baseline AUC values were 82.1% (95% CI 70.4-93.9%) for salbutamol and 78.8% (95% CI 65.8-91.8%) for OCS. These outcomes could be adequately replicated and validated. Additional regression analysis between qualified exhaled VOCs and urinary concentrations of salbutamol and prednisone showed statistically significant correlations (p<0.01)., Conclusion: We have linked exhaled VOCs to urinary detection of salbutamol and OCSs. This merits further development of breathomics into a point-of-care tool for therapeutic drug monitoring., Competing Interests: Conflict of interest: P. Brinkman has nothing to disclose. Conflict of interest: W.M. Ahmed has nothing to disclose. Conflict of interest: C. Gómez has nothing to disclose. Conflict of interest: H.H. Knobel has a patent “Inline drying of breath sample” pending. Conflict of interest: H. Weda has nothing to disclose. Conflict of interest: T.J. Vink has nothing to disclose. Conflict of interest: T.M. Nijsen has nothing to disclose. Conflict of interest: C.E. Wheelock has nothing to disclose. Conflict of interest: S-E. Dahlén has participated in advisory boards for AstraZeneca, GSK, Merck, Novartis, Sanofi and Teva, outside the submitted work. Conflict of interest: P. Montuschi has nothing to disclose. Conflict of interest: R.G. Knowles is director of Knowles Consulting Ltd, outside the submitted work. Conflict of interest: S.J. Vijverberg has nothing to disclose. Conflict of interest: A.H. Maitland-van der Zee reports grants from Boehringer Ingelheim, personal fees for advisory board work from AstraZeneca, and personal fees for travel to meetings from Chiesi, outside the submitted work. Conflict of interest: P.J. Sterk reports grants (paid to institution) from Innovative Medicines Initiative covered by the European Union and the European Federation of Pharmaceutical Industries and Associations, during the conduct of the study; and reports a 4% interest and is a scientific advisor for Breathomix BV, outside the submitted work. Conflict of interest: S.J. Fowler reports personal fees for lectures and nonfinancial support to attend conferences from AstraZeneca, grants and personal fees for lectures from Boehringer Ingelheim, personal fees for lectures from Novartis, Teva and Chiesi, outside the submitted work., (Copyright ©ERS 2020.)

Many patients with chronic obstructive lung disease (COPD) experience exacerbations. The diagnosis of an exacerbation is solely based on symptoms. We hypothesized that exhaled breath profiles, measured by Gas Chromatography-Mass Spectrometry (GC-MS) or electronic nose (eNose), are different between stable disease and exacerbations and may have the potential to serve as biomarkers for COPD exacerbations. In this prospective follow-up study, breath samples were taken during stable COPD, during a subsequent exacerbation and after recovery. Samples were analyzed by GC-MS and eNose. CCQ symptom scores were associated with univariate outcomes of GC-MS and eNose using analysis of covariance (ANCOVA). After multivariate modeling by Principal Component Analysis (PCA), paired student t -tests were performed. Sixty-eight patients were included, 31 had an exacerbation and 16 patients had breath sampled at all three time points. Significant differences were found in breathprints taken during exacerbation as compared to baseline and recovery for both GC-MS and eNose. Breath profiles obtained by GC-MS as well as by eNose showed a correct classification of 71% (10/14) for baseline vs exacerbation and of 78% (11/14) for exacerbation vs recovery. These results provide proof of principle that exhaled breath can serve as a noninvasive biomarker for the diagnosis of COPD exacerbations.

Volatile organic compounds (VOCs) in exhaled breath may identify the presence of invasive pulmonary aspergillosis. We aimed to detect VOC profiles emitted by in vitro cultured, clinical Aspergillus isolates using gas chromatography-mass spectrometry (GC-MS). Three clinical Aspergillus isolates and a reference strain were cultured while conidiation was prevented. Headspace samples were analyzed using a standardized method. Breath samples of patients from which the cultures were obtained were checked for the presence of the VOCs found in vitro. Each Aspergillus isolate produced a distinct VOC profile. These profiles could not be confirmed in exhaled breath in vivo., (© The Author 2017. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Asthma is the most common chronic disease in children, and is characterized by airway inflammation, bronchial hyperresponsiveness, and airflow obstruction. Asthma diagnosis, phenotyping, and monitoring are still challenging with currently available methods, such as spirometry, F E NO or sputum analysis. The analysis of volatile organic compounds (VOCs) in exhaled breath could be an interesting non-invasive approach, but has not yet reached clinical practice. This review describes the current status of breath analysis in the diagnosis and monitoring of pediatric asthma. Furthermore, features of an ideal breath test, different breath analysis techniques, and important methodological issues are discussed. Although only a (small) number of studies have been performed in pediatric asthma, of which the majority is focusing on asthma diagnosis, these studies show moderate to good prediction accuracy (80-100%, with models including 6-28 VOCs), thereby qualifying breathomics for future application. However, standardization of procedures, longitudinal studies, as well as external validation are needed in order to further develop breathomics into clinical tools. Such a non-invasive tool may be the next step toward stratified and personalized medicine in pediatric respiratory disease., (© 2017 Wiley Periodicals, Inc.)

Background: Asthma is a chronic inflammatory airway disease, associated with episodes of exacerbations. Therapy with inhaled corticosteroids (ICS) targets airway inflammation, which aims to maintain and restore asthma control. Clinical features are only modestly associated with airways inflammation. Therefore, we hypothesized that exhaled volatile metabolites identify longitudinal changes between clinically stable episodes and loss of asthma control., Objectives: To determine whether exhaled volatile organic compounds (VOCs) as measured by gas-chromatography/mass-spectrometry (GC/MS) and electronic nose (eNose) technology discriminate between clinically stable and unstable episodes of asthma., Methods: Twenty-three patients with (partly) controlled mild to moderate persistent asthma using ICS were included in this prospective steroid withdrawal study. Exhaled metabolites were measured at baseline, during loss of control and after recovery. Standardized sampling of exhaled air was performed, after which samples were analysed by GC/MS and eNose. Univariate analysis of covariance (ANCOVA), followed by multivariate principal component analysis (PCA) was used to reduce data dimensionality. Next paired t tests were utilized to analyse within-subject breath profile differences at the different time-points. Finally, associations between exhaled metabolites and sputum inflammation markers were examined., Results: Breath profiles by eNose showed 95% (21/22) correct classification for baseline vs loss of control and 86% (19/22) for loss of control vs recovery. Breath profiles using GC/MS showed accuracies of 68% (14/22) and 77% (17/22) for baseline vs loss of control and loss of control vs recovery, respectively. Significant associations between exhaled metabolites captured by GC/MS and sputum eosinophils were found (Pearson r≥.46, P<.01)., Conclusions & Clinical Relevance: Loss of asthma control can be discriminated from clinically stable episodes by longitudinal monitoring of exhaled metabolites measured by GC/MS and particularly eNose. Part of the uncovered biomarkers was associated with sputum eosinophils. These findings provide proof of principle for monitoring and identification of loss of asthma control by breathomics., (© 2017 John Wiley & Sons Ltd.)

Breath tests cover the fraction of nitric oxide in expired gas ( F ), volatile organic compounds (VOCs), variables in exhaled breath condensate (EBC) and other measurements. For EBC and for eNO ), volatile organic compounds (VOCs), variables in exhaled breath condensate (EBC) and other measurements. For EBC and for F eNO , official recommendations for standardised procedures are more than 10 years old and there is none for exhaled VOCs and particles. The aim of this document is to provide technical standards and recommendations for sample collection and analytic approaches and to highlight future research priorities in the field. For EBC and F eNO , new developments and advances in technology have been evaluated in the current document. This report is not intended to provide clinical guidance on disease diagnosis and management.Clinicians and researchers with expertise in exhaled biomarkers were invited to participate. Published studies regarding methodology of breath tests were selected, discussed and evaluated in a consensus-based manner by the Task Force members.Recommendations for standardisation of sampling, analysing and reporting of data and suggestions for research to cover gaps in the evidence have been created and summarised.Application of breath biomarker measurement in a standardised manner will provide comparable results, thereby facilitating the potential use of these biomarkers in clinical practice., Competing Interests: Conflict of interest: T. Tonia acts as a methodologist for the European Respiratory Society. Further disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2017.)

Background: The diagnosis of ventilator-associated pneumonia (VAP) remains time-consuming and costly, the clinical tools lack specificity and a bedside test to exclude infection in suspected patients is unavailable. Breath contains hundreds to thousands of volatile organic compounds (VOCs) that result from host and microbial metabolism as well as the environment. The present study aims to use breath VOC analysis to develop a model that can discriminate between patients who have positive cultures and who have negative cultures with a high sensitivity., Methods/design: The Molecular Analysis of Exhaled Breath as Diagnostic Test for Ventilator-Associated Pneumonia (BreathDx) study is a multicentre observational study. Breath and bronchial lavage samples will be collected from 100 and 53 intubated and ventilated patients suspected of VAP. Breath will be analysed using Thermal Desorption - Gas Chromatography - Mass Spectrometry (TD-GC-MS). The primary endpoint is the accuracy of cross-validated prediction for positive respiratory cultures in patients that are suspected of VAP, with a sensitivity of at least 99% (high negative predictive value)., Discussion: To our knowledge, BreathDx is the first study powered to investigate whether molecular analysis of breath can be used to classify suspected VAP patients with and without positive microbiological cultures with 99% sensitivity., Trial Registration: UKCRN ID number 19086, registered May 2015; as well as registration at www.trialregister.nl under the acronym 'BreathDx' with trial ID number NTR 6114 (retrospectively registered on 28 October 2016).

Exhaled breath contains thousands of volatile organic compounds that reflect the metabolic process occurring in the host both locally in the airways and systemically. They also arise from the environment and airway microbiome. Comprehensive analysis of breath volatile organic compounds (breathomics) provides opportunities for noninvasive biomarker discovery and novel mechanistic insights. Applications in patients with obstructive lung diseases, such as asthma and chronic obstructive pulmonary disease, include not only diagnostics (especially in children and other challenging diagnostic areas) but also identification of clinical treatable traits, such as airway eosinophilia and risk of infection/exacerbation, that are not specific to diagnostic labels. Although many aspects of breath sampling and analysis are challenging, proof-of-concept studies with mass spectrometry and electronic nose technologies have provided independent studies with moderate-to-good diagnostic and phenotypic accuracies. The present review evaluates the data obtained by using breathomics in (1) predicting the inception of asthma or chronic obstructive pulmonary disease, (2) inflammatory phenotyping, (3) exacerbation prediction, and (4) treatment stratification. The current findings merit the current efforts of large multicenter studies using standardized sampling, shared analytic methods, and databases, including external validation cohorts. This will position this noninvasive technology in the clinical assessment and monitoring of chronic airways diseases., (Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Objective: To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls., Methods: In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored., Results: Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60-0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61-0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55-0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups., Conclusions: Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.

Medical diagnosis and phenotyping increasingly incorporate information from complex biological samples. This has promoted the development and clinical application of non-invasive metabolomics in exhaled air (breathomics). In respiratory medicine, expired volatile organic compounds (VOCs) are associated with inflammatory, oxidative, microbial, and neoplastic processes. After recent proof of concept studies demonstrating moderate to good diagnostic accuracies, the latest efforts in breathomics are focused on optimization of sensor technologies and analytical algorithms, as well as on independent validation of clinical classification and prediction. Current research strategies are revealing the underlying pathophysiological pathways as well as clinically-acceptable levels of diagnostic accuracy. Implementing recent guidelines on validating molecular signatures in medicine will enhance the clinical potential of breathomics and the development of point-of-care technologies., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Exhaled breath contains volatile organic compounds (VOCs) that are associated with respiratory pathophysiology. We hypothesized that hyperbaric oxygen exposure (hyperoxia) generates a distinguishable VOC pattern. This study aimed to test this hypothesis in oxygen-breathing divers. VOCs in exhaled breath were measured in 10 male divers before and 4h after diving to 9msw (190kPa) for 1h. During the dive they breathed 100% oxygen or air in randomized order. VOCs were determined using two-dimensional gas chromatography with time-of-flight mass spectrometry. Compared to air dives, after oxygen dives there was a significant increase in five VOCs (predominately methyl alkanes). Furthermore, a strong, positive correlation was found between increments in 2,4-dimethyl-hexane and those of 4-ethyl-5-methyl-nonane. Although non-submerged hyperoxia studies on VOCs have been performed, the present study is the first to demonstrate changes in exhaled molecular profiles after submerged oxygen diving. The pathophysiological background might be attributed to either a lipid peroxidation-induced pathway, an inflammatory pathway, or to both., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background: In critically ill patients, glucose control with insulin mandates time- and blood-consuming glucose monitoring. Blood glucose level fluctuations are accompanied by metabolomic changes that alter the composition of volatile organic compounds (VOC), which are detectable in exhaled breath. This review systematically summarizes the available data on the ability of changes in VOC composition to predict blood glucose levels and changes in blood glucose levels., Methods: A systematic search was performed in PubMed. Studies were included when an association between blood glucose levels and VOCs in exhaled air was investigated, using a technique that allows for separation, quantification and identification of individual VOCs. Only studies on humans were included., Results: Nine studies were included out of 1041 identified in the search. Authors of seven studies observed a significant correlation between blood glucose levels and selected VOCs in exhaled air. Authors of two studies did not observe a strong correlation. Blood glucose levels were associated with the following VOCs: ketone bodies (e.g., acetone), VOCs produced by gut flora (e.g., ethanol, methanol, and propane), exogenous compounds (e.g., ethyl benzene, o-xylene, and m/p-xylene) and markers of oxidative stress (e.g., methyl nitrate, 2-pentyl nitrate, and CO)., Conclusion: There is a relation between blood glucose levels and VOC composition in exhaled air. These results warrant clinical validation of exhaled breath analysis to monitor blood glucose levels.

Volatile organic compounds (VOCs) in breath may serve as biomarkers of pulmonary infection or inflammation. We developed and validated a new breath sampling method for VOC analysis in ventilated patients. Breath was collected from the ventilatory circuit using cheap disposables. VOCs were identified by gas-chromatography and mass-spectrometry (GC-MS) at various minute volumes during ventilation of an artificial lung (in vitro) and ventilated patients (in vivo). Sixty-four VOCs emendated from the ventilator and tubing. Their concentrations had an inverse correlation with minute volume in in vitro experiments (median correlation coefficient: -0.61 [25-75th percentile: -0.66 to -0.43]). Forty-four of these "ventilator-associated VOCs" were also observed in vivo, without correlations with minute volume. In vivo experiments showed that only positive end-expiratory pressure influenced the concentration of breath VOCs. The sampling method was highly reproducible (median intra-class correlation 0.95 [25-75th percentile: 0.87-0.97]). In conclusion, a novel, simple and repeatable sampling method was developed and validated for capturing exhaled VOCs in ventilated patients, which could allow for large-scale breath analysis in clinical studies., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Exhaled air contains many volatile organic compounds (VOCs) that are the result of normal and disease-associated metabolic processes anywhere in the body. Different omics techniques can assess the pattern of these VOCs. One such omics technique suitable for breath analysis is represented by electronic noses (eNoses), providing fingerprints of the exhaled VOCs, called breathprints. Breathprints have been shown to be altered in different disease states, including in asthma and COPD. This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases. Furthermore, important methodological issues including breath sampling, modulating factors and incompatibility between eNoses are raised and discussed. Next steps towards clinical application of electronic noses are provided, including further validation in suspected disease, assessment of the influence of different comorbidities, the value in longitudinal monitoring of patients with asthma and COPD and the possibility to predict treatment responses. Eventually, a Breath Cloud may be constructed, a large database containing disease-specific breathprints. When collaborative efforts are put into optimization of this technique, it can provide a rapid and non-invasive first line diagnostic test., (© 2012 John Wiley & Sons Ltd.)

Ideally, invading bacteria are detected as early as possible in critically ill patients: the strain of morbific pathogens is identified rapidly, and antimicrobial sensitivity is known well before the start of new antimicrobial therapy. Bacteria have a distinct metabolism, part of which results in the production of bacteria-specific volatile organic compounds (VOCs), which might be used for diagnostic purposes. Volatile metabolites can be investigated directly in exhaled air, allowing for noninvasive monitoring. The aim of this review is to provide an overview of VOCs produced by the six most abundant and pathogenic bacteria in sepsis, including Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli. Such VOCs could be used as biological markers in the diagnostic approach of critically ill patients. A systematic review of existing literature revealed 31 articles. All six bacteria of interest produce isopentanol, formaldehyde, methyl mercaptan, and trimethylamine. Since humans do not produce these VOCs, they could serve as biological markers for presence of these pathogens. The following volatile biomarkers were found for identification of specific strains: isovaleric acid and 2-methyl-butanal for Staphylococcus aureus; 1-undecene, 2,4-dimethyl-1-heptane, 2-butanone, 4-methyl-quinazoline, hydrogen cyanide, and methyl thiocyanide for Pseudomonas aeruginosa; and methanol, pentanol, ethyl acetate, and indole for Escherichia coli. Notably, several factors that may effect VOC production were not controlled for, including used culture media, bacterial growth phase, and genomic variation within bacterial strains. In conclusion, VOCs produced by bacteria may serve as biological markers for their presence. Goal-targeted studies should be performed to identify potential sets of volatile biological markers and evaluate the diagnostic accuracy of these markers in critically ill patients.

Although the high mortality rate of pulmonary invasive aspergillosis (IA) in patients with prolonged chemotherapy-induced neutropenia (PCIN) can be reduced by timely diagnosis, a diagnostic test that reliably detects IA at an early stage is lacking. We hypothesized that an electronic nose (eNose) could fulfill this need. An eNose can discriminate various lung diseases through the analysis of exhaled volatile organic compounds (VOCs). An eNose is cheap and noninvasive and yields results within minutes. In a single-center prospective cohort study, we included patients who were treated with chemotherapy expected to result in PCIN. Based on standardized indications, a full diagnostic workup was performed to confirm invasive aspergillosis or to rule it out. Patients with no aspergillosis were considered controls, and patients with probable or proven aspergillosis were considered index cases. Exhaled breath was examined with a Cyranose 320 (Smith Detections, Pasadena, CA). The resulting data were analyzed using principal component reduction. The primary endpoint was cross-validated diagnostic accuracy, defined as the percentage of patients correctly classified using the leave-one-out method. Accuracy was validated by 100,000 random classifications. We included 46 subjects who underwent 16 diagnostic workups, resulting in 6 cases and 5 controls. The cross-validated accuracy of the eNose in diagnosing IA was 90.9% (P = 0.022; sensitivity, 100%; specificity, 83.3%). Receiver operating characteristic analysis showed an area under the curve of 0.93. These preliminary data indicate that PCIN patients with IA have a distinct exhaled VOC profile that can be detected with eNose technology. The diagnostic accuracy of the eNose for invasive aspergillosis warrants validation.

Molecular profiling of exhaled volatile organic compounds (VOC) by electronic nose technology provides breathprints that discriminate between patients with different inflammatory airway diseases, such as asthma and COPD. However, it is unknown whether this is determined by differences in airway caliber. We hypothesized that breathprints obtained by electronic nose are independent of acute changes in airway caliber in asthma. Ten patients with stable asthma underwent methacholine provocation (Visit 1) and sham challenge with isotonic saline (Visit 2). At Visit 1, exhaled air was repetitively collected pre-challenge, after reaching the provocative concentration (PC(20)) causing 20% fall in forced expiratory volume in 1 second (FEV(1)) and after subsequent salbutamol inhalation. At Visit 2, breath was collected pre-challenge, post-saline and post-salbutamol. At each occasion, an expiratory vital capacity was collected after 5 min of tidal breathing through an inspiratory VOC-filter in a Tedlar bag and sampled by electronic nose (Cyranose 320). Breathprints were analyzed with principal component analysis and individual factors were compared with mixed model analysis followed by pairwise comparisons. Inhalation of methacholine led to a 30.8 ± 3.3% fall in FEV(1) and was followed by a significant change in breathprint (p = 0.04). Saline inhalation did not induce a significant change in FEV(1), but altered the breathprint (p = 0.01). However, the breathprint obtained after the methacholine provocation was not significantly different from that after saline challenge (p = 0.27). The molecular profile of exhaled air in patients with asthma is altered by nebulized aerosols, but is not affected by acute changes in airway caliber. Our data demonstrate that breathprints by electronic nose are not confounded by the level of airway obstruction.

Background: Exhaled breath contains thousands of gaseous volatile organic compounds (VOCs) that may be used as non-invasive markers of lung disease. The electronic nose analyzes VOCs by composite nano-sensor arrays with learning algorithms. It has been shown that an electronic nose can distinguish the VOCs pattern in exhaled breath of lung cancer patients from healthy controls. We hypothesized that an electronic nose can discriminate patients with lung cancer from COPD patients and healthy controls by analyzing the VOC-profile in exhaled breath., Methods: 30 subjects participated in a cross-sectional study: 10 patients with non-small cell lung cancer (NSCLC, [age 66.4+/-9.0, FEV(1) 86.3+/-20.7]), 10 patients with COPD (age 61.4+/-5.5, FEV(1) 70.0+/-14.8) and 10 healthy controls (age 58.3+/-8.1, FEV(1) 108.9+/-14.6). After 5 min tidal breathing through a non-rebreathing valve with inspiratory VOC-filter, subjects performed a single vital capacity maneuver to collect dried exhaled air into a Tedlar bag. The bag was connected to the electronic nose (Cyranose 320) within 10 min, with VOC-filtered room air as baseline. The smellprints were analyzed by onboard statistical software., Results: Smellprints from NSCLC patients clustered distinctly from those of COPD subjects (cross validation value [CVV]: 85%; M-distance: 3.73). NSCLC patients could also be discriminated from healthy controls in duplicate measurements (CVV: 90% and 80%, respectively; M-distance: 2.96 and 2.26)., Conclusion: VOC-patterns of exhaled breath discriminates patients with lung cancer from COPD patients as well as healthy controls. The electronic nose may qualify as a non-invasive diagnostic tool for lung cancer in the future.