Exhaled Volatile Organic Compounds Research Articles

Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry

BackgroundProton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF). ObjectiveTo detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS. Methods102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z). ResultsPTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing. ConclusionPTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Identification of exhaled volatile organic compounds that characterize asthma phenotypes: A J-VOCSA study

BackgroundAsthma is characterized by phenotypes of different clinical, demographic, and pathological characteristics. Identifying the profile of exhaled volatile organic compounds (VOCs) in asthma phenotypes may facilitate establishing biomarkers and understanding asthma background pathogenesis. This study aimed to identify exhaled VOCs that characterize severe asthma phenotypes among patients with asthma. MethodsThis was a multicenter cross-sectional study of patients with severe asthma in Japan. Clinical data were obtained from medical records, and questionnaires were collected. Exhaled breath was sampled and subjected to thermal desorption gas chromatography-mass spectrometry (GC/MS). ResultsUsing the decision tree established in the previous nationwide asthma cohort study, 245 patients with asthma were divided into five phenotypes and subjected to exhaled VOC analysis with 50 healthy controls (HCs). GC/MS detected 243 VOCs in exhaled breath samples, and 142 frequently detected VOCs (50% of all samples) were used for statistical analyses. Cluster analysis assigning the groups with similar VOC profile patterns showed the highest similarities between phenotypes 3 and 4 (early-onset asthma phenotypes), followed by the similarities between phenotypes 1 and 2 (late-onset asthma phenotypes). Comparisons between phenotypes 1–5 and HC revealed 19 VOCs, in which only methanesulfonic anhydride showed p < 0.05 adjusted by false discovery rate (FDR). Comparison of these phenotypes yielded several VOCs showing different trends (p < 0.05); however, no VOCs showed p < 0.05 adjusted by FDR. ConclusionsExhaled VOC profiles may be useful for distinguishing asthma and asthma phenotypes; however, these findings need to be validated, and their pathological roles should be clarified.

Detection of Clostridioides difficile infection by assessment of exhaled breath volatile organic compounds

Clostridioides difficile infection (CDI) is the leading cause of hospital-acquired infective diarrhea. Current methods for diagnosing CDI have limitations; enzyme immunoassays for toxin have low sensitivity and Clostridioides difficile polymerase chain reaction cannot differentiate infection from colonization. An ideal diagnostic test that incorporates microbial factors, host factors, and host-microbe interaction might characterize true infection. Assessing volatile organic compounds (VOCs) in exhaled breath may be a useful test for identifying CDI. To identify a wide selection of VOCs in exhaled breath, we used thermal desorption-gas chromatography-mass spectrometry to study breath samples from 17 patients with CDI. Age- and sex-matched patients with diarrhea and negative C.difficile testing (no CDI) were used as controls. Of the 65 VOCs tested, 9 were used to build a quadratic discriminant model that showed a final cross-validated accuracy of 74%, a sensitivity of 71%, a specificity of 76%, and a receiver operating characteristic area under the curve of 0.72. If these findings are proven by larger studies, breath VOC analysis may be a helpful adjunctive diagnostic test for CDI.

Identification of breath volatile organic compounds to distinguish pancreatic adenocarcinoma, pancreatic cystic neoplasm, and patients without pancreatic lesions.

Volatile organic compounds (VOCs) are a promising potential biomarker that may be able to identify the presence of cancers. To identify exhaled breath VOCs that distinguish pancreatic ductal adenocarcinoma (PDAC) from intraductal papillary mucinous neoplasm (IPMN) and healthy volunteers. We collected exhaled breath from histologically proven PDAC patients, radiological diagnosis IPMN, and healthy volunteers using the ReCIVA® device between 10/2021-11/2022. VOCs were identified by thermal desorption-gas chromatography/field-asymmetric ion mobility spectrometry and compared between groups. A total of 156 participants (44% male, mean age 62.6 ± 10.6) were enrolled (54 PDAC, 42 IPMN, and 60 controls). Among the nine VOCs identified, two VOCs that showed differences between groups were dimethyl sulfide [0.73 vs 0.74 vs 0.94 arbitrary units (AU), respectively; P = 0.008] and acetone dimers (3.95 vs 4.49 vs 5.19 AU, respectively; P < 0.001). After adjusting for the imbalance parameters, PDAC showed higher dimethyl sulfide levels than the control and IPMN groups, with adjusted odds ratio (aOR) of 6.98 (95%CI: 1.15-42.17) and 4.56 (1.03-20.20), respectively (P < 0.05 both). Acetone dimer levels were also higher in PDAC compared to controls and IPMN (aOR: 5.12 (1.80-14.57) and aOR: 3.35 (1.47-7.63), respectively (P < 0.05 both). Acetone dimer, but not dimethyl sulfide, performed better than CA19-9 in PDAC diagnosis (AUROC 0.910 vs 0.796). The AUROC of acetone dimer increased to 0.936 when combined with CA19-9, which was better than CA19-9 alone (P < 0.05). Dimethyl sulfide and acetone dimer are VOCs that potentially distinguish PDAC from IPMN and healthy participants. Additional prospective studies are required to validate these findings.

Disease diagnosis and severity classification in pulmonary fibrosis using carbonyl volatile organic compounds in exhaled breath

BackgroundPathophysiological conditions underlying pulmonary fibrosis remain poorly understood. Exhaled breath volatile organic compounds (VOCs) have shown promise for lung disease diagnosis and classification. In particular, carbonyls are a byproduct of oxidative stress, associated with fibrosis in the lungs. To explore the potential of exhaled carbonyl VOCs to reflect underlying pathophysiological conditions in pulmonary fibrosis, this proof-of-concept study tested the hypothesis that volatile and low abundance carbonyl compounds could be linked to diagnosis and associated disease severity. MethodsExhaled breath samples were collected from outpatients with a diagnosis of Idiopathic Pulmonary Fibrosis (IPF) or Connective Tissue related Interstitial Lung Disease (CTD-ILD) with stable lung function for 3 months before enrollment, as measured by pulmonary function testing (PFT) DLCO (%), FVC (%) and FEV1 (%). A novel microreactor was used to capture carbonyl compounds in the breath as direct output products. A machine learning workflow was implemented with the captured carbonyl compounds as input features for classification of diagnosis and disease severity based on PFT (DLCO and FVC normal/mild vs. moderate/severe; FEV1 normal/mild/moderate vs. moderately severe/severe). ResultsThe proposed approach classified diagnosis with AUROC=0.877 ± 0.047 in the validation subsets. The AUROC was 0.820 ± 0.064, 0.898 ± 0.040, and 0.873 ± 0.051 for disease severity based on DLCO, FEV1, and FVC measurements, respectively. Eleven key carbonyl VOCs were identified with the potential to differentiate diagnosis and to classify severity. ConclusionsExhaled breath carbonyl compounds can be linked to pulmonary function and fibrotic ILD diagnosis, moving towards improved pathophysiological understanding of pulmonary fibrosis.

A LA-BTC MOF as a sensor element of an electronic nose for selective adsorption of biomarkers of diseases: Molecular dynamics simulations of adsorption

The advanced non-invasive diagnostic method is an analysis of exhaled volatile organic compounds (VOCs), which are regarded as biomarkers of various diseases. A gravimetric-type electronic nose (e-nose) has shown great promise in exhaled VOC-pattern identification, and its efficiency is determined by the adsorption capacity of the sensing materials towards a specific VOC. The present study employed molecular dynamics (MD) calculations with the OPLS all-atom force field to investigate the adsorption of an isolated molecule of volatile fatty acids, acetone, ethanol, methanol, acetic aldehyde, neopentane, and ethane in a unit cell of the lanthanum-based metal-organic framework (La-BTC MOF), which was proposed as a potential sensing material for the gravimetric-type e-nose. The adsorption potential determined as a change in the potential energy, ΔEp, of the total simulation system upon the penetration of a single molecule into a unit pore of La-BTC MOF was calculated for all the targeted VOCs and water to be 1.56–10.78 kJ·mol−1, following the order: ethane < neopentane < acetic aldehyde < ethanol < methanol < water < acetone < butanoic acid < caproic acid. Therefore, the biomarkers with ΔEp > ΔEp(water) ∼ 7.3 kJ/mol can be captured from the exhaled breath. According to the MD calculations, an oxygen-containing biomarker molecule in the adsorbed state was oriented by its oxygen atom towards the La3+ cation, so that the O---La3+ distance of 0.28–0.32 nm was the shortest among those for other constituent atoms. Thus, the strong electrostatic interactions between the oxygen atoms of the adsorbate molecules and the La3+ cation of the adsorbent were most responsible for the capture of the oxygen-containing biomarkers by the La-BTC MOF. The competing adsorption effect between water and oxygen-containing biomarker molecules was examined in dependence on the water content and the way the water molecules were introduced into the simulation system.

Exhaled VOC Biomarkers from Rats Injected with PMs from Thirty-One Major Cities in China.

Particulate matter (PMs) of different origins can cause diverse health effects. Here, a homemade box was used to facilitate real-time measurements of breath-borne volatile organic compounds (VOCs) by gas chromatography-ion mobility spectrometry. We have tracked exhaled VOC changes in 228 Wistar rats that were injected with water-soluble PM suspension filtrates (after 0.45 μm) from 31 China cities for 1 h to up to 1-6 days during the experiments. Rats exposed to the filtrates exhibited significant changes in breath-borne VOCs within hours, featuring dynamic fluctuations in the levels of acetone, butan-2-one, heptan-2-one-M, acetic acid-M, and ethanol. Subsequently, on the fifth to sixth day after the injection, there was a notable increase in the proportion of aldehydes (including hexanal-M, hexanal-D, pentanal, heptanal-M, and (E)-2-hexenal). The 10 dynamic VOC fingerprint patterns mentioned earlier showcased the capability to indirectly differentiate urban PM toxicity and categorize the 31 cities into four distinct groups based on their health effects. This study provides valuable insights into the mechanisms of exhaled VOCs and underscores their critical role as biomarkers for differentiating the toxicity of different PMs and detecting the early signs of potential diseases. The results from this work also provide a scientific basis for city-specific air pollution control and policy development.

A feasibility study on exhaled breath analysis using UV spectroscopy to detect COVID-19

A 23-subject feasibility study is reported to assess how UV absorbance measurements on exhaled breath samples collected from silicon microreactors can be used to detect COVID-19. The silicon microreactor technology chemoselectively preconcentrates exhaled carbonyl volatile organic compounds and subsequent methanol elution provides samples for analysis. The underlying scientific rationale that viral infection will induce an increase in exhaled carbonyls appears to be supported by the results of the feasibility study. The data indicate statistically significant differences in measured UV absorbance values between healthy and symptomatic COVID-19 positive subjects in the wavelength range from 235 nm to 305 nm. Factors such as subject age were noted as potential confounding variables.

Machine-learning-assisted sensor array for detecting COVID-19 through simulated exhaled air

Reverse transcription polymerase chain reaction (RT-PCR), the primary test for COVID-19, requires complicated sample collection and several hours to obtain results. Breath test for exhaled volatile organic compounds (VOCs) has gained substantial research attention as a simple non-invasive and fast screening method. However, a unique VOC fingerprint as a potential prognostic biomarker is still unavailable. Accordingly, this study prepared simulated VOC gases to test the classification performance of a sensing system. The simulated VOC gases were selected according to the actual composition of the exhaled breath of patients with acute respiratory diseases, including COVID-19. Two sets of metal oxide sensor arrays, comprising eight commercial sensors and eight Advanced Institute of Science and Technology (AIST) laboratory-made sensors, were prepared to test their sensing ability for the simulated gases. The principal component analysis (PCA) results revealed that the AIST sensors had better sensing ability than the commercial sensors. Moreover, the recursive feature elimination cross-validation (RFECV) of random forest (RF) further confirmed the superiority of the AIST sensors over the commercial sensors. An artificial neural network (ANN) with excellent prediction performance for gas concentration was developed. This study provides a promising method for rapidly screening respiratory diseases.

Exhaled Breath Analysis Using Selected Ion Flow Tube Mass Spectrometry and Disease Severity in Heart Failure.

Exhaled breath volatile organic compounds (VOCs) are elevated in heart failure (HF). The ability of VOCs to predict long term cardiovascular mortality and morbidity has not been independently verified. In 55 patients admitted with acute decompensated heart failure (ADHF), we measured exhaled breath acetone and pentane levels upon admission and after 48 h of diuresis. In a separate cohort of 51 cardiac patients undergoing cardiopulmonary exercise testing (CPET), we measured exhaled breath acetone and pentane levels before and at peak exercise. In the ADHF cohort, admission acetone levels correlated with lower left ventricular ejection fraction (LVEF, r = -0.297, p = 0.035). Greater weight loss with diuretic therapy correlated with a greater reduction in both acetone levels (r = -0.398, p = 0.003) and pentane levels (r = -0.309, p = 0.021). In patients with above-median weight loss (≥4.5 kg), patients demonstrated significantly greater percentage reduction in acetone (59% reduction vs. 7% increase, p < 0.001) and pentane (23% reduction vs. 2% reduction, p = 0.008). In the CPET cohort, admission acetone and pentane levels correlated with higher VE/VCO2 (r = 0.39, p = 0.005), (r = 0.035, p = 0.014). However, there were no significant correlations between baseline or peak exercise acetone and pentane levels and peak VO2. In longitudinal follow-up with a median duration of 33 months, patients with elevated exhaled acetone and pentane levels experienced higher composite adverse events of death, ventricular assist device implantation, or orthotopic heart transplantation. In patients admitted with ADHF, higher exhaled breath acetone levels are associated with lower LVEF and poorer outcomes, and greater reductions in exhaled breath acetone and pentane tracked with greater weight loss. Exhaled acetone and pentane may be novel biomarkers in heart failure worthy of future investigation.

Alteration of the Exhaled Volatile Organic Compound Pattern in Colorectal Cancer Patients after Intentional Curative Surgery-A Prospective Pilot Study.

As current follow-up modalities for colorectal carcinoma (CRC) have restricted sensitivity, novel diagnostic tools are needed. The presence of CRC changes the endogenous metabolism, resulting in the release of a specific volatile organic compounds (VOC) pattern that can be detected with an electronic nose or AeonoseTM. To evaluate the use of an electronic nose in the follow-up of CRC, we studied the effect of curative surgery on the VOC pattern recognition using AeonoseTM. A prospective cohort study was performed, in which 47 patients diagnosed with CRC were included, all of whom underwent curative surgical resection. Breath testing was performed before and after surgery using the AeonoseTM. A machine learning model was developed by discerning between the 94 pre-and postoperative breath samples. The training model differentiated between the pre-and postoperative CRC breath samples with a sensitivity and specificity of 0.78 (95%CI 0.61-0.90) and 0.73 (95%CI 0.56-0.86), respectively, with an accuracy of 0.76 (95%CI 0.66-0.85), and an area under the curve of 0.79 (95%CI 0.68-0.89). The internal validation of the test set resulted in an accuracy of 0.75 (95%CI 0.51-0.91) and AUC of 0.82 (95%CI 0.61-1). In conclusion, our results suggest that the VOC pattern of CRC patients is altered by curative surgery in a short period, indicating that the exhaled VOCs might be closely related to the presence of CRC. However, to use AeonoseTM as a potential diagnostic tool in the clinical follow-up of CRC patients, the performance of the models needs to be improved through further large-scale prospective research.

Construction of High-Active SERS Cavities in a TiO2 Nanochannels-Based Membrane: A Selective Device for Identifying Volatile Aldehyde Biomarkers.

The accurate, sensitive, and selective on-site screening of volatile aldehyde biomarkers for lung cancer is of utmost significance for preclinical cancer diagnosis and treatment. Applying surface-enhanced Raman scattering (SERS) for gas sensing remains difficult due to the small Raman cross section of most gaseous molecules and interference from other components in exhaled breath. Using an Au asymmetrically coated TiO2 nanochannel membrane (Au/TiO2 NM) as the substrate, a ZIF-8-covered Au/TiO2 NM SERS sensing substrate is designed for the detection of exhaled volatile organic compounds (VOCs). Au/TiO2 NM provides uniformly amplified Raman signals for trace measurements in this design. Importantly, the interfacial nanocavities between Au nanoparticles (NPs) and metal-organic frameworks (MOFs) served as gaseous confinement cavities, which is the key to enhancing the capture and adsorption ability toward gaseous analytes. Both ends of the membrane are left open, allowing gas molecules to pass through. This facilitates the diffusion of gaseous molecules and efficient capture of the target analyte. Using benzaldehyde as a typical gas marker model of lung cancer, the Schiff base reaction with a Raman-active probe molecule 4-aminothiophene (4-ATP) pregrafted on Au NPs enabled trace and multicomponent detection. Moreover, the combination of machine learning (ML) and Raman spectroscopy eliminates subjective assessments of gaseous aldehyde species with the use of a single feature peak, allowing for more accurate identification. This membrane sensing device offers a promising design for the development of a desktop SERS analysis system for lung cancer point-of-care testing (POCT).

Food and lifestyle impact on breath VOCs using portable mass spectrometer—pilot study across European countries

In the modern world, many people are changing old dietary and lifestyle habits to improve the quality of their living—to treat or just prevent possible diseases. The main goal of this pilot study was to assess the food and lifestyle impact on exhaled breath volatile organic compounds (VOCs) in various population groups. It was done by employing a recently validated portable membrane-inlet mass spectrometer—MIMS. Thus, the obtained results would also represent the additional confirmation for the employment of the new instrument in the breath analysis. The pilot study involved 151 participants across Europe, including people with overweight, obesity, type 2 diabetes mellitus, cardiovascular disease, people with poor-quality diet and professional athletes. Exhaled breath acetone, ethanol, isoprene, and n-pentane levels were determined in samples before the meal, and 120 min after the meal. Obtained basal ppbv values were mainly in accordance with previously reported, which confirms that MIMS instrument can be used in the breath analysis. Combining the quantified levels along with the information about the participants’ lifestyle habits collected via questionnaire, an assessment of the food and lifestyle impact was obtained. Notable alteration in examined VOC levels upon meal consumption was detected in more than 70% of all participants, with exception for isoprene, which was affected in about half of participants. Lifestyle parameters impact was examined using statistical analysis of variance (ANOVA) on ranks test. Statistically significant differences in basal breath VOC levels were observed among all examined population groups. Also, n-pentane and ethanol levels significantly differed in people of different ages, as well as acetone levels in people with different physical activity habits. These findings are promising for further, more focused research using MIMS technique in breath analysis.

Effect of Food Intake on Exhaled Volatile Organic Compounds Profile Analyzed by an Electronic Nose.

Exhaled breath analysis using an e-nose is a groundbreaking tool for exhaled volatile organic compound (VOC) analysis, which has already shown its applicability in several respiratory and systemic diseases. It is still unclear whether food intake can be considered a confounder when analyzing the VOC-profile. We aimed to assess whether an e-nose can discriminate exhaled breath before and after predefined food intake at different time periods. We enrolled 28 healthy non-smoking adults and collected their exhaled breath as follows: (a) before food intake, (b) within 5 min after food consumption, (c) within 1 h after eating, and (d) within 2 h after eating. Exhaled breath was collected by a formerly validated method and analyzed by an e-nose (Cyranose 320). By principal component analysis, significant variations in the exhaled VOC-profile were shown for principal component 1 (capturing 63.4% of total variance) when comparing baseline vs. 5 min and vs. 1 h after food intake (both p < 0.05). No significance was shown in the comparison between baseline and 2 h after food intake. Therefore, the exhaled VOC-profile seems to be influenced by very recent food intake. Interestingly, two hours might be sufficient to avoid food induced alterations of exhaled VOC-spectrum when sampling for research protocols.

Changes in exhaled volatile organic compounds following indirect bronchial challenge in suspected asthma

BackgroundInhaled mannitol provokes bronchoconstriction via mediators released during osmotic degranulation of inflammatory cells, and, hence represents a useful diagnostic test for asthma and model for acute attacks. We hypothesised that...

Exhaled volatile organic compounds associated with risk factors for obstructive pulmonary diseases: a systematic review.

Asthma and COPD are among the most common respiratory diseases. To improve the early detection of exacerbations and the clinical course of asthma and COPD new biomarkers are needed. The development of noninvasive metabolomics of exhaled air into a point-of-care tool is an appealing option. However, risk factors for obstructive pulmonary diseases can potentially introduce confounding markers due to altered volatile organic compound (VOC) patterns being linked to these risk factors instead of the disease. We conducted a systematic review and presented a comprehensive list of VOCs associated with these risk factors. A PRISMA-oriented systematic search was conducted across PubMed, Embase and Cochrane Libraries between 2000 and 2022. Full-length studies evaluating VOCs in exhaled breath were included. A narrative synthesis of the data was conducted, and the Newcastle-Ottawa Scale was used to assess the quality of included studies. The search yielded 2209 records and, based on the inclusion/exclusion criteria, 24 articles were included in the qualitative synthesis. In total, 232 individual VOCs associated with risk factors for obstructive pulmonary diseases were found; 58 compounds were reported more than once and 12 were reported as potential markers of asthma and/or COPD in other studies. Critical appraisal found that the identified studies were methodologically heterogeneous and had a variable risk of bias. We identified a series of exhaled VOCs associated with risk factors for asthma and/or COPD. Identification of these VOCs is necessary for the further development of exhaled metabolites-based point-of-care tests in these obstructive pulmonary diseases.

P200 Exhaled breath proton mass spectrometry in adult patients with cystic fibrosis

Proton-transfer reaction mass spectrometry (PTR-MS) is a promising tool for a rapid on-line determination of exhaled volatile organic compounds (eVOCs) profiles inpatients with different respiratory diseases.

Impact of breast density on classification of infrared spectroscopy for breath-based breast cancer screening.

e13558 Background: While mammography is currently the standard of care for breast cancer screening, dense breast tissue can significantly degrade results. Alternatively, infrared spectroscopy analysis of breath offers a highly sensitive method for identifying exhaled volatile organic compounds (VOCs), which may circumvent issues with breast density. Methods: Alveolar breath samples were collected onto Tenax TA sorbent tubes using a SohnoXB™ breath sampler. Using four desorb temperatures (75, 150, 225 and 300°C), absorption spectra were measured by infrared cavity ring-down spectroscopy (IR-CRDS), a technique for measuring absorption coefficients due to VOCs in exhaled breath. Missing values in the absorption spectra were backfilled using interpolation, and the spectrum was min-max normalized and quadratic detrended. First and second derivatives of the preprocessed absorption spectra were used as features for a support vector machine machine-learning model. Features were ranked based on minimum redundancy maximum relevance (mRMR). The top 20 ranked features were selected to limit the potential for overfitting and then optimized. Model performance was validated using non-nested leave-one-out cross-validation (LOOCV) and nested LOOCV to provide optimistic and pessimistic results, respectively. Results: Absorption spectra from 111 participants (71 positive, 40 control) were used. Of the positive subjects, 30 had low- and 31 had high-density breast tissue (measures missing for 10). Model performance is outlined. A subgroup analysis compared model performance for subjects with low- and high-density breast tissue for both non-nested and nested LOOCV models. Breast density data was not captured for control subjects thus they were not included in the subgroup analysis. Fisher’s exact test was performed to assess for significant difference between model performance for those with low- vs high-density breast tissue, resulting in a p-value of 1.00. Conclusions: Our results suggest that the classification of alveolar breath using IR-CRDS is a promising technique for the detection of breast cancer that is independent of breast density. Breath analysis may therefore become a new alternative or corroborative to mammography to support clinical decision-making. [Table: see text]

P203 Volatile organic compounds in adults with cystic fibrosis by real-time proton-transfer reaction mass spectrometry

To study of exhaled volatile organic compounds (eVOCs) as diagnostic markers, assessment of the progression of respiratory diseases is becoming more widespread. Due to its noninvasive character, detection of eVOCs with a using real-time proton mass spectrometry of exhaled air (PTR-MS) in patients with cystic fibrosis (CF) seems to be particularly attractive.