Analysis Of Breath Volatile Organic Compounds Research Articles

Volatile organic compounds: A promising new frontier for cancer screening

The late onset of cancer symptoms can cause a significant delay in diagnosis, impacting patients’ prognosis and quality of life, thus prompting a need for alternative screening and detection methods. Neoplastic processes cause distinct and immediate changes to the body’s metabolism, creating unique patterns in the volatile organic compounds (VOCs) produced and released through exhaled breath. For this reason, VOC profiles have emerged as diagnostic indicators for several types of malignancies, facilitating early cancer detection. Both non-invasive and accessible, the analysis of breath VOCs for cancer screening and detection has gained recognition as a new frontier in cancer diagnostics. Using exhaled breath instead of gold-standard cancer detection and screening tools that are traditionally invasive and uncomfortable for the patient could be revolutionary in improving patient compliance. Further, compared to the gold-standard tools, breath testing is relatively inexpensive, and the method of analysis, storage, and transporting the samples is simplified. Several studies have demonstrated the accuracy of VOC analysis in detecting various types of cancer, including breast cancer, colon cancer, prostate cancer, gastric cancer, and melanoma. This article summarizes the evidence supporting VOC analysis for cancer screening and detection. It reviews the clinical utility, current limitations, and necessity for standardization across all VOC screening tools to ensure the standardization and reliability of measurements. The evidence supporting breath tests to detect cancer accurately is strong, demonstrating that VOC sampling improves patient outcomes and decreases the global burden of malignant conditions by detecting cancer earlier.

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.

Metabolic insights at the finish line: deciphering physiological changes in ultramarathon runners through breath VOC analysis

Exhaustive exercise can induce unique physiological responses in the lungs and other parts of the human body. The volatile organic compounds (VOCs) in exhaled breath are ideal for studying the effects of exhaustive exercise on the lungs due to the proximity of the breath matrix to the respiratory tract. As breath VOCs can originate from the bloodstream, changes in abundance should also indicate broader physiological effects of exhaustive exercise on the body. Currently, there is limited published data on the effects of exhaustive exercise on breath VOCs. Breath has great potential for biomarker analysis as it can be collected non-invasively, and capture real-time metabolic changes to better understand the effects of exhaustive exercise. In this study, we collected breath samples from a small group of elite runners participating in the 2019 Ultra-Trail du Mont Blanc ultra-marathon. The final analysis included matched paired samples collected before and after the race from 24 subjects. All 48 samples were analyzed using the Breath Biopsy Platform with GC-Orbitrap™ via thermal desorption gas chromatography-mass spectrometry. The Wilcoxon signed-rank test was used to determine whether VOC abundances differed between pre- and post-race breath samples (adjusted P-value < .05). We identified a total of 793 VOCs in the breath samples of elite runners. Of these, 63 showed significant differences between pre- and post-race samples after correction for multiple testing (12 decreased, 51 increased). The specific VOCs identified suggest the involvement of fatty acid oxidation, inflammation, and possible altered gut microbiome activity in response to exhaustive exercise. This study demonstrates significant changes in VOC abundance resulting from exhaustive exercise. Further investigation of VOC changes along with other physiological measurements can help improve our understanding of the effect of exhaustive exercise on the body and subsequent differences in VOCs in exhaled breath.

Machine Learning-Assisted Janus Colorimetric Face Mask for Breath Ammonia Analysis.

Artificial olfactory systems have been widely used in medical fields such as in the analysis of volatile organic compounds (VOCs) in human exhaled breath. However, there is still an urgent demand for a portable, accurate breath VOC analysis system for the healthcare industry. In this work, we proposed a Janus colorimetric face mask (JCFM) for the comfortable evaluation of breath ammonia levels by combining the machine learning K-nearest neighbor (K-NN) algorithm. Such a Janus fabric is designed for the unidirectional penetration of exhaled moisture, which can reduce stickiness and ensure facial dryness and comfort. Four different pH indicators on the colorimetric array serve as recognition elements that cross-react with ammonia, capturing the optical fingerprint information on breath ammonia by mimicking the sophisticated olfactory structure of mammals. The Euclidean distance (ED) is used to quantitatively describe the ammonia concentration between 1 ppm and 10 ppm, indicating that there is a linear relationship between the ammonia concentration and the ED response (R2 = 0.988). The K-NN algorithm based on RGB response features aids in the analysis of the target ammonia level and achieves a prediction accuracy of 96%. This study integrates colorimetry, Janus design, and machine learning to present a wearable and portable sensing system for breath ammonia analysis.

P235 Patients with inflammatory ileal pouch anal anastomosis (IPAA) disorders are characterized by a distinct breath volatile organic compounds (VOC) metabolome profile

Abstract Background Following creation of an IPAA in patients with ulcerative colitis (UC), more than 60% of subjects develop inflammatory complications. The current objective assessment for inflammation of the pouch is limited to surrogate stool and blood biomarkers or endoscopy. The development of non-invasive and accurate biomarkers for the assessment of IPAA inflammation is an area of unmet need. Measurement of exhaled breath volatile organic metabolome compounds (VOCs) has shown promise as a biomarker for the diagnosis and monitoring of inflammatory disorders. We here aimed to characterize the pattern of VOCs in the exhaled breath of patients with an IPAA and assess whether VOC analysis is able to discriminate patients with endoscopically active IPAA inflammation from patients without IPAA inflammation. Methods This is a cross-sectional study of patients with an IPAA created for the management of UC. Exhaled breath samples were collected at time of endoscopic evaluation of the pouch and 97 VOC metabolites assessed via selective ion flow tube mass spectrometry (SIFT-MS). The IPAA cohort was dichotomized using the endoscopic pouch disease activity index (PDAI) into endoscopic PDAI of &amp;gt;= 4 (severe inflammation), or endoscopic PDAI score &amp;lt;= 1 (mild or no inflammation). Principle component analysis (PCA) was conducted to reveal the VOCs with the strongest discriminatory capability and principle component regression (PCR) was performed to assess the association of exhaled breath VOC analysis in differentiating the groups. Results Exhaled breath metabolome analysis was performed on 10 subjects with PDAI &amp;gt;=4 and 7 subjects with PDAI &amp;lt;=1. Demographics are provided in Table 1. PCA indicated robust discrimination of the two groups based on breath VOCs (Figure 1). 10 out of 97 VOCs were up-regulated in the PDAI &amp;gt;=4 group compared to control, including ammonia and hydrogen sulfide. Isopropenyltoluene, tetrachloroethylene, and 3-pentanone provided the highest contribution to differentiate between the cohorts (Figure 2). Receiver operative curve (ROC) analysis of the PCR model indicated an area under the curve (AUC) of 0.81 (0.61-99), suggesting a strong association of breath VOCs with inflammation of the pouch (Figure 1). Conclusion VOC exhaled breath metabolome analysis shows a strong ability to discriminate patients with severe endoscopic pouch inflammation from patients with minimal to no endoscopic inflammation. The differences in reported VOCs point toward metabolic differences in bacterial fermentation, lipid and carbohydrate metabolism, and an increase in reactive oxygen species in patients with endoscopic pouch inflammation. Validation studies addressing the role of VOC analysis for non-invasive disease assessment patients with IPAA are ongoing.

Exhaled Breath Volatile Organic Compound Analysis for the Detection of Lung Cancer- A Systematic Review

A rapid and effective diagnostic method is essential for lung cancer since it shows symptoms only at its advanced stage. Research is being carried out in the area of exhaled breath analysis for the diagnosis of various pulmonary diseases including lung cancer. In this method exhaled breath volatile organic compounds (VOC) are analyzed with various techniques such as gas chromatography-mass spectrometry, ion mobility spectrometry, and electronic noses. The VOC analysis is suitable for lung cancer detection since it is non-invasive, fast, and also a low-cost method. In addition, this technique can detect primary stage nodules. This paper presents a systematic review of the various method employed by researchers in the breath analysis field. The articles were selected through various search engines like EMBASE, Google Scholar, Pubmed, and Google. In the initial screening process, 214 research papers were selected using various inclusion and exclusion criteria and finally, 55 articles were selected for the review. The results of the reviewed studies show that detection of lung cancer can be effectively done using the VOC analysis of exhaled breath. The results also show that this method can be used for detecting the different stages and histology of lung cancer. The exhaled breath VOC analysis technique will be popular in the future, bypassing the existing imaging techniques. This systematic review conveys the recent research opportunities, obstacles, difficulties, motivations, and suggestions associated with the breath analysis method for lung cancer detection.

Design and construction of a portable e-nose system for human exhaled breath VOC analysis

This paper describes the design and fabrication of a system that can analyze the human exhaled breath volatile organic compounds (VOCs). The expelled breath contains several VOCs in addition to nitrogen, oxygen, carbon dioxide, and water vapor. Some of these VOCs are biomarkers for certain lung diseases like lung cancer, cystic fibrosis, chronic obstructive pulmonary disease (COPD), etc, and they can even identify smokers and non-smokers by variations of VOCs. The development of the electronic nose (e-nose) with five metal oxide semiconductor (MOS) gas sensors, control circuit, and processing circuit is explained in this paper. The system is tested and verified in the detection of breath VOCs. The clinical feasibility of the system is checked in a small pilot study involving 4 lung cancer patients, 4 chronic obstructive pulmonary disease patients, 4 asthma patients, and 4 healthy controls including smokers and non-smokers. The results of the study are also included, along with the conclusions drawn from the work. The e-nose system developed with TGS gas sensors is economical and uses a non-invasive method of breath sampling, and surely it will be a diagnostic tool for the detection of lung cancer, COPD, and other major respiratory diseases in near future.

The peppermint breath test: a benchmarking protocol for breath sampling and analysis using GC–MS

Exhaled breath contains hundreds of volatile organic compounds (VOCs) which offer the potential for diagnosing and monitoring a wide range of diseases. As the breath research field has grown, sampling and analytical practices have become highly varied between groups. Standardisation would allow meta-analyses of data from multiple studies and greater confidence in published results. Washout of VOCs from ingestion into the blood and subsequently breath could provide data for an initial assessment of inter-group performance. The Peppermint Initiative has been formed to address this task of standardisation. In the current study we aimed to generate initial benchmark values for thermal desorption–gas chromatography–mass spectrometry (TD–GC–MS) analysis of breath samples containing peppermint-derived VOCs using data from three independent European research groups. Initially, headspace analysis of peppermint oil capsules was performed to determine compounds of interest. Ten healthy participants were recruited by each three groups across Europe. The standard Peppermint protocol was followed. In brief, each participant provided a baseline breath sample prior to taking a peppermint capsule, with further samples collected at 60, 90, 165, 285 and 360 min following ingestion. Sampling and analytical protocols were different for each group, in line with their usual practice. Samples were analysed by TD–GC–MS and benchmarking values determined for the time taken for detected peppermint VOCs to return to baseline values. Sixteen compounds were identified in the capsule headspace, and all were confirmed in breath following ingestion of the peppermint capsules. Additionally, 2,3-dehydro-1,8-cineole was uniquely found in the breath samples, with a washout profile that suggested it was a product of metabolism of peppermint compounds. Five compounds (α-pinene, β-pinene, eucalyptol, menthol and menthone) were quantified by all three groups. Differences were observed between the groups, particularly for the recovery of menthone and menthol. The average time taken for VOCs to return to baseline was selected as the benchmark and were 377, 423, 533, 418 and 336 min for α-pinene, β-pinene, eucalyptol, menthone and menthol respectively. We have presented an initial set of easy-to-measure benchmarking values for assessing the performance of TD–GC–MS systems for the analysis of VOCs in breath. These values will be updated when more groups provide additional data.

Effects of modular ion-funnel technology onto analysis of breath VOCs by means of real-time mass spectrometry

Proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) is a powerful tool for real-time monitoring of trace concentrations of volatile organic compounds (VOCs). The sensitivity of PTR-ToF-MS also depends on the ability to effectively focus and transmit ions from the relatively high-pressure drift tube (DT) to the low-pressure mass analyzer. In the present study, a modular ion-funnel (IF) is placed adjacent to the DT of a PTR-ToF-MS instrument to improve the ion-focusing. IF consists of a series of electrodes with gradually decreasing orifice diameters. Radio frequency (RF) voltage and direct current (DC) electric field are then applied to the electrodes to get the ions focused. We investigated the effect of the RF voltage and DC field on the sensitivity of a pattern of VOCs including hydrocarbons, alcohols, aldehydes, ketones, and aromatic compounds. In a proof-of-concept study, the instrument operating both as normal DT (DC-mode) and at optimal IF conditions (RF-mode) was applied for the breath analysis of 21 healthy human subjects. For the range of investigated VOCs, an improvement of one order of magnitude in sensitivity was observed in RF-mode compared with DC-mode. Limits of detection could be improved by a factor of 2–4 in RF-mode compared with DC-mode. Operating the instrument in RF-mode allowed the detection of more compounds in the exhaled air compared with DC-mode. Incorporation of the IF considerably improved the performance of PTR-ToF-MS allowing the real-time monitoring of a larger number of potential breath biomarkers.Graphical abstract

Exhaled breath analysis using on-line preconcentration mass spectrometry for gastric cancer diagnosis.

Breath volatile biomarkers are capable of distinguishing patients with various cancers. However, high throughput analytical technology is a prerequisite to a large-cohort study intended to discover reliable breath biomarkers for cancer diagnosis. Single-photon ionization (SPI) is a universal ionization technology, and SPI-mass spectrometry (SPI-MS) shows a remarkable advantage in the comprehensive detection of volatile organic compounds (VOCs), in particular, nonpolar compounds. In this study, we have introduced SPI-MS coupled with on-line thermal desorption (TD-SPI-MS) to demonstrate nontarget analysis of breath VOCs for gastric cancer patients. The breath fingerprints of the gastric cancer patients were significantly distinct from that of the control group. Acetone, isoprene, 1,3-dioxolan-2-one, phenol, meta-xylene, 1,2,3-trimethylbenzene, and phenyl acetate showed higher relative peak intensities in the breath profiles of gastric cancer patients. A diagnostic prediction model was further developed by using a training set (121 samples) and validated with a test set (53 samples). The predication accuracy of the developed model was 96.2%, and the area under the curve (AUC) of the receiver operator characteristic curve (ROC) was 0.997, indicating a satisfactory prediction ability of the developed model. Thus, by taking gastric cancer as an example, we have shown that TD-SPI-MS will be a promising tool for high throughput analysis of breath samples to discover characteristic VOCs in patients with various cancers.

Breath volatile compounds and conjugated polyunsaturated fatty acids as metabolic biomarkers reflecting the interaction between chitin-glucan and the gut microbiota.

AbstractIntroductionDietary fibers (DF) are considered as beneficial nutrients for health. Current data suggest that their interaction with the gut microbiota largely contributes to their physiological effects. The FiberTAG project(1) innovates in searching for new biomarkers reflecting the health effect of dietary fibers, including chitin-glucan (CG, extracted from the fungal exoskeleton Aspergillus niger). CG improves metabolic disorders associated with obesity in mice, but its effect on gut microbiota composition and function has never been evaluated in vivo in humans.Materials and MethodsCG (KitoZyme, Belgium) was given to healthy volunteers (n = 15), during three weeks (4.5g/day). Volatile Organic Compound (VOC) metabolites released in breath were analyzed using SYFT methodology. Fatty acid (FA) profiling was assessed in stool samples, by gas-liquid chromatography(2). The gut microbiome was analyzed by Illumina sequencing (V5-V6 region of 16S rRNA).ResultsThree weeks of CG supplementation was well tolerated and lead to changes in the kinetics of breath VOC, especially the short-chain fatty acid, alcohols and alkanes. Fecal vaccenic acid, produced upon the bacterial metabolism of fatty acids, was significantly increased by CG. Several bacterial genera were correlated with breath VOC (i.e. 2 methylbutyric acid and RuminococcaceaeUCG005). Moreover, Roseburia, often presented as a butyrate producer, was positively correlated with the production of a rumenic acid isomer “cis-9,cis-11-18:2”.DiscussionWe show that breath VOC analysis, a non-invasive methodology, reveals characteristics of microbiota-CG interactions. We also show that CG selectively changes the profile of FA metabolites, in favor of vaccenic acid, another bioactive metabolite produced by Roseburia, prone to act on host physiology. This study will help to establish a set of new biomarkers linking insoluble DF and gut microbiota, with focus on their interest in human health.

Recent advances in breath analysis to track human health by new enrichment technologies.

Detection of biomarkers in exhaled breath has been gaining increasing attention as a tool for diagnosis of specific diseases. However, rapid and accurate quantification of biomarkers associated with specific diseases requires the use of analytical methods capable of fast sampling and preconcentration from breath matrix. In this regard, solid phase microextraction and needle trap technology are becoming increasingly popular in the field of breath analysis due to the unique benefits imparted by such methods, such as the integration of sampling, extraction, and preconcentration in a single step. This review discusses recent advances in breath analysis using these sample preparation techniques, providing a summary of recent developments of analytical methods based on breath volatile organic compounds analysis, including the successful identification of various biomarkers related to human diseases.

A Mini Review of Trends towards Automated and Non-Invasive Techniques for Early Detection of Lung Cancer: From Radiomics through Proteogenomics to Breathomics

Carcinoma of the Lung is one of the most common cancers in the world and the leading cause of tumor-related deaths. Less than 15% of patients survive 5 years post diagnosis due to its relatively poor prognosis. This has been ascribed to lack of effective diagnostic methods for early detection. Different medical imaging techniques such as chest radiography, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are used in routine clinical practice for tumor detection. These techniques are medically unsatisfactory and inconvenient for patients due to poor diagnostic accuracy. Endobronchial biopsies are the gold standard for diagnosis but have the inherent risk of full or partial invasive procedures. Thus, diagnostic technology that uses data mining algorithms with medical image analysis, generally known as radiomics emerged. Radiomics extracts complex information from conventional radiographic images and quantitatively correlates image features with diagnostic and therapeutic outcomes. In spite of the benefits, radiomics is prone to high false positives and there is no established standard for acquisition of parameters. Further efforts towards outcome improvement led to the proteomic and genomic (proteogenomic) approach to lung cancer detection. Although proteogenomic has a diagnostic edge over traditional techniques, variations in bio-specimen and heterogeneity of lung cancer still possess a major challenge. Recent findings have established that changes normally occur in the gene or protein due to tumor growth in the lungs and this often leads to peroxidation of cell membrane that releases Volatile Organic Compounds (VOCs) through the breath of Lung Cancer patients. The comprehensive analysis of breath VOCs, which is tagged Breathomics in the literature, unveils opportunities for noninvasive biomarker discovery towards early detection. Breathomics has therefore become the current pace-setter in medical diagnostics research because of its non-invasiveness and cost effectiveness. This paper presents a mini survey of trends in early lung cancer detection from radiomics, through proteogenomic to breathomics.

Breath analysis by two-dimensional gas chromatography with dual flame ionisation and mass spectrometric detection – Method optimisation and integration within a large-scale clinical study

Precision medicine has spurred new innovations in molecular pathology leading to recent advances in the analysis of exhaled breath as a non-invasive diagnostic tool. Volatile organic compounds (VOCs) detected in exhaled breath have the potential to reveal a wealth of chemical and metabolomic information. This study describes the development of a method for the analysis of breath, based on automated thermal desorption (TD) combined with flow modulated comprehensive two-dimensional gas chromatography (GC×GC) with dual flame ionisation and quadrupole mass spectrometric detection (FID and qMS). The constrained optimisation and analytical protocol was designed to meet the practical demands of a large-scale multi-site clinical study, while maintaining analytical rigour to produce high fidelity data. The results demonstrate a comprehensive method optimisation for the collection and analysis of breath VOCs by GC×GC, integral to the standardisation and integration of breath analysis within large clinical studies.

Accuracy and Methodologic Challenges of Volatile Organic Compound–Based Exhaled Breath Tests for Cancer Diagnosis

The detection and quantification of volatile organic compounds (VOCs) within exhaled breath have evolved gradually for the diagnosis of cancer. The overall diagnostic accuracy of proposed tests remains unknown. To determine the diagnostic accuracy of VOC breath tests for the detection of cancer and to review sources of methodologic variability. An electronic search (title and abstract) was performed using the Embase and MEDLINE databases (January 1, 2000, to May 28, 2017) through the OVID platform. The search terms cancer, neoplasm, malignancy, volatile organic compound, VOC, breath, and exhaled were used in combination with the Boolean operators AND and OR. A separate MEDLINE search that used the search terms breath AND methodology was also performed for studies that reported factors that influenced the concentration of VOCs within exhaled breath in humans. The search was limited to human studies published in the English language. Trials that analyzed named endogenous VOCs within exhaled breath to diagnose or assess cancer were included in this review. Systematic review and pooled analysis were conducted in accordance with the recommendations of the Cochrane Library and Meta-analysis of Observational Studies in Epidemiology guidelines. Bivariate meta-analyses were performed to generate pooled point estimates of the hierarchal summary receiver operating characteristic curve of breath VOC analysis. Included studies were assessed according to the Standards for Reporting of Diagnostic Accuracy Studies checklist and Quality Assessment of Diagnostic Accuracy Studies 2 tool. The principal outcome measure was pooled diagnostic accuracy of published VOC breath tests for cancer. The review identified 63 relevant publications and 3554 patients. All reports constituted phase 1 biomarker studies. Pooled analysis of findings found a mean (SE) area under the receiver operating characteristic analysis curve of 0.94 (0.01), sensitivity of 79% (95% CI, 77%-81%), and specificity of 89% (95% CI, 88%-90%). Factors that may influence variability in test results included breath collection method, patient physiologic condition, test environment, and method of analysis. The findings of our review suggest that standardization of breath collection methods and masked validation of breath test accuracy for cancer diagnosis is needed among the intended population in multicenter clinical trials. We propose a framework to guide the conduct of future breath tests in cancer studies.

High-Throughput Breath Volatile Organic Compound Analysis Using Thermal Desorption Proton Transfer Reaction Time-of-Flight Mass Spectrometry.

Breath analysis is highly acceptable to patients and health care professionals, but its implementation in clinical practice remains challenging. Clinical trials and routine practice require a robust system for collection, storage, and processing of large numbers of samples. This work describes a platform based upon the hyphenation of thermal desorption (TD) with proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS), coupled by means of an original modification of the TD interface. The performance of TD-PTR-ToF-MS was tested against seven oxygenated volatile organic compounds (VOCs), belonging to three chemical classes (i.e., fatty acids, aldehydes, and phenols), previously identified as possible biomarkers of colorectal and esophago-gastric adenocarcinoma. Limits of detection and quantification were on the order of 0.2-0.9 and 0.3-1.5 parts per billion by volume (ppbV), respectively. Analytical recoveries from TD tubes were 80% or higher, linear response was in the low- to mid-ppbV range ( R2 = 0.98-0.99), and coefficients of variation were within 20% of mean values. The usability of the platform was evaluated in the analysis of a set of breath samples of clinical origin, allowing for a throughput of nearly 100 TD tubes for 24 h of continuous operation. All of these characteristics enhance the implementation of TD-PTR-ToF-MS for large-scale clinical studies.

Development of breath test for pneumoconiosis: a case-control study

BackgroundLipid peroxidation plays an important role in the pathogenesis of pneumoconiosis. Volatile organic compounds (VOCs) generated from lipid peroxidation might be used to detect pneumoconiosis. The objective of this study was to develop a breath test for pneumoconiosis.MethodsA case-control study was designed. Breath and ambient air were analysed by gas chromatography/mass spectrometry. After blank correction to prevent contamination from ambient air, we used canonical discriminant analysis (CDA) to assess the discrimination accuracy and principal component analysis (PCA) to generate a prediction score. The prediction accuracy was calculated and validated using the International Classification of Radiographs of the Pneumoconiosis criteria combined with an abnormal pulmonary function test as a reference standard. We generated a receiver operator characteristic (ROC) curve and calculated the area under the ROC curve (AUC) to estimate the screening accuracy of the breath test.ResultsWe enrolled 200 stone workers. After excluding 5 subjects with asthma and 16 subjects who took steroids or nonsteroidal anti-inflammatory drugs, a total of 179 subjects were used in the final analyses, which included 25 cases and 154 controls. By CDA, 88.8% of subjects were correctly discriminated by their exposure status and the presence of pneumoconiosis. After excluding the VOCs of automobile exhaust and cigarette smoking, pentane and C5-C7 methylated alkanes constituted the major VOCs in the breath of persons with pneumoconiosis. Using the prediction score generated from PCA, the ROC-AUC was 0.88 (95% CI = 0.80—0.95), and the mean ROC-AUC of 5-fold cross-validation was 0.90. The breath test had good accuracy for pneumoconiosis diagnosis.ConclusionThe analysis of breath VOCs has potential in the screening of pneumoconiosis for its non-invasiveness and high accuracy. We suggest that a multi-centre study is warranted and that all procedures must be standardized before clinical application.

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Gastrointestinal NursingVol. 15, No. 2 NewsNewsSue LearnerSue LearnerSearch for more papers by this authorSue LearnerPublished Online:21 Mar 2017https://doi.org/10.12968/gasn.2017.15.2.8AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Pombo-Rodrigues S, Hashem K, He F, MacGregor G (2017) Salt and sugars content of breakfast cereals in the UK from 1992 to 2015. Public Health Nutr (epub ahead of print). http://dx.doi.org/10.1017/S1368980016003463 Google ScholarConsensus Action on Salt and Health (2017) Breakfast cereals contain shocking levels of sugar (up to 35%) in spite of manufacturers' claims over the last 20 years. http://tinyurl.com/hjb2tcl (accessed 6 March 2017) Google ScholarECCO (2017) Breath test could help detect stomach and oesophageal cancers. http://tinyurl.com/zyeaz8z (accessed 6 March 2017) Google ScholarMarkar S, Wiggins T, Antonowicz S et al. (2017) Breath volatile organic compound analysis for the diagnosis of esophago-gastric cancer: multi-centre blinded validation clinical trial. Proceedings of the European Cancer Congress, Amsterdam, the Netherlands, 27–30 January 2017 Google ScholarKnapton S (2017) Parents should enforce ‘no seconds’ policy at mealtimes to prevent child obesity, says expert. The Daily Telegraph. http://tinyurl.com/h524lmg (accessed 16 February 2017) Google ScholarMarie Curie (2017) Palliative Care Knowledge Zone. mariecurie.org.uk/knowledgezone (accessed 16 February 2017) Google ScholarNHS England (2017) Provider-based Cancer Waiting Times for Q3 2016/17. http://tinyurl.com/zf35v78 (accessed 16 February 2017) Google ScholarSharp L, McDevitt J, Carsin AE et al. (2017) Smoking at diagnosis significantly decreases 5-year cancer-specific survival in a population-based cohort of 18 166 colon cancer patients. Aliment Pharmacol Ther (published online). http://dx.doi.org/10.1111/apt.13944 Google ScholarNeoptolemos J, Palmer D, Ghaneh P et al. (2017) Comparison of adjuvant gemcitabine and capecitabine with gemcitabine monotherapy in patients with resected pancreatic cancer (ESPAC-4). Lancet (published online). http://dx.doi.org/10.1016/s0140-6736(16)32409-6 Google Scholar FiguresReferencesRelatedDetails 2 March 2017Volume 15Issue 2ISSN (print): 1479-5248ISSN (online): 2052-2835 Metrics History Published online 21 March 2017 Published in print 2 March 2017 Information© MA Healthcare LimitedPDF download

Breath volatile organic compound analysis for the diagnosis of oesophago-gastric cancer; multi-centre blinded validation clinical trial

Breath volatile organic compound analysis for the diagnosis of oesophago-gastric cancer; multi-centre blinded validation clinical trial

BreathDx \u2013 molecular analysis of exhaled breath as a diagnostic test for ventilator\u2013associated pneumonia: protocol for a European multicentre observational study

BackgroundThe 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/designThe 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).DiscussionTo 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 registrationUKCRN 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).