Differentiation of chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control group by breath analysis using ion mobility spectrometry

Non-invasive methods with potential for diagnosis of lung diseases gain increasing interest. Within the present study the exhaled breath of 132 persons (97 Chronic obstructive pulmonary disease (COPD) patients [35 COPD without lung cancer, 62 COPD with lung cancer] and 35 healthy volunteers) was investigated using an Ion Mobility Spectrometer (IMS) coupled to a Multi-Capillary Column (MCC) without any pre-separation or pre-enrichment. One hundred four different peaks were considered within the IMS-Chromatograms of the 10 mL breath samples of both groups. A principal component analysis (PCA) of these 104 peaks identified a single analyte, that allowed a separation of the healthy persons and the COPD patients (with and without lung cancer). The sensitivity obtained was 60%, the specificity 91%, the positive predictive value 95%. The peak was characterized as cyclohexanone (CAS 108-94-1). Subsequent studies must validate the identity of the peak used for separation of the two groups with a greater population and external standards. Breath gas analysis using ion mobility spectrometry offers a chance of separating healthy persons and COPD patients using a single analyte at a defined concentration.     

Statistical and bioinformatical methods to differentiate chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control by breath analysis using ion mobility spectrometry

Human breath analysis is a powerful and especially a non-invasive technique for the monitoring and hopefully also for the diagnosis of respiratory diseases, including chronic obstructive pulmonary disease (COPD). The exhaled breath of 95 patients suffering COPD and of 35 healthy controls was investigated using an Ion Mobility Spectrometer (IMS) coupled to a Multi-Capillary Column (MCC) without any pre-separation or pre-enrichment. Starting with the results from a Mann–Whitney-Wilcoxon rank sum test to find analytes with the highest potential with respect to differentiation, box and whisker plots, metabolic maps and probability charts were introduced and compared. In addition, the sensitivity, specificity, positive and negative predictive values and the accuracy of the relation were also summarized. The findings were compared to the results of a principal component analysis. Finally, decision trees were introduced to visualize the interdependencies between the analytes and the classifications. The application of these biostatistical methods with simultaneous inclusion of several VOCs for disease classification by ion mobility spectrometry of human breath will provide much more information than using single peaks and single concentration dependencies for disease classification and discrimination of various groups. Towards the future application of potential biomarkers for clinical diagnostic procedures, complex analytical methods, such as ion mobility spectrometry, need statistical and bioinformatical tools which are simple in application, visualize the results and support decisions on the basis of the data obtained from measurements of analytes in exhaled human breath.     

Detection of infectious agents in the airways by ion mobility spectrometry of exhaled breath

Diseases of the lung, e. g. chronic obstructive pulmonary disease (COPD), interstitial lung diseases, bronchiectasis or cystic fibrosis, often lead to recurrent severe respiratory infections that cause exacerbations of the underlying disease. These acute or chronic inflammatory processes can result in a progressive destruction of the lung and in an ongoing decline in lung function. Therefore longer inpatient stays for intravenous antibiotic treatment are necessary and the quality of life in these patients is severely limited. A rapid detection of infectious agents in human lungs is often crucial, because the choice of the appropriate therapeutic regime depends at first on the identification of the infecting species. Standard methods for detection and identification are either time consuming, of low sensitivity or expensive. It is known that bacteria, and also mitosporic fungi, produce volatile organic compounds (VOCs) that can be detected in exhaled breath by ion mobility spectrometry (IMS), were a distinct detection of a specific VOC is related to a “peak”. We investigated, whether the detection and characterisation of VOCs by Multi-capillary column coupled to IMS in exhaled breath of patients whose airways are either infected or colonized by Pseudomonas aeruginosa compared to healthy non-smoker controls is capable of identifying those infectious agents. To realize a non invasive identification of pathogens, the exhaled breath of 53 persons (24 patients suffering chronic or infectious on Pseudomonas and 29 healthy controls) was investigated using an ion mobility spectrometer type BioScout. In total 224 different signals were found. Actually, 21 different signals are able to differentiate the two groups, Control and Pseudomonas, with rank sum values less than 0.2. For all 224 signals Box-and-Wisker plots were realized. The peaks with the lowest rank sum values F (0,107) and PS0 (0,112) show rather good separation of both groups. Our preliminary results demonstrate that distinct patterns of a small number of IMS-peaks are sufficient for the identification of these infectious agents. Therefore MCC-IMS seems to be a promising method for the non-invasive identification of patients which are colonized or infected with bacteria such as Pseudomonas aeruginosa.     

Detection of volatile organic compounds from wood-based panels by gas chromatography-field asymmetric ion mobility spectrometry (GC-FAIMS)

The focus of this work was to detect formaldehyde (HCHO) as a very volatile compound (VVOC) among other volatile organic compounds in the low concentration ranges that are relevant for the production control in wood processing industries. We show that a quick and easy derivatization of HCHO can be used for a reliable and straightforward identification with GC-FAIMS. Headspace samples of specimens made from wood-based panels were collected and pre-concentrated on a conventional solid phase microextraction fiber (SPME) and thermally desorbed in a split/splitless GC-injector. A standard gas-mixer generator based on the dynamical permeation principle was used to produce known concentrations of HCHO. The results are compared with gas chromatography??mass spectrometry (GC-MS).     

Electrical sensing of volatile organic compounds in exhaled breath for disease diagnosis

In recent years, electrical sensors toward breath volatolomics have attracted increasing interest owing to their wide feasibility in noninvasive disease diagnostics. In this article, the working principles of active nanomaterials (e.g. metal oxides, polymers, and nanocarbon) toward volatile organic compounds are presented, with a special focus on the influence of surface chemistry and structural feature of these nanomaterials on the sensing performance. The latest and representative achievements on the direct analysis of three typical exhaled volatile organic compounds, including acetone, ammonia, and hydrogen sulfide, that are recognized as important disease biomarkers, are highlighted, indicating the capability of the electrical sensors in enabling noninvasive diagnosis and real-time monitoring. The opportunities and challenges in this field are provided in the end, with an emphasis on the background interference and data recognition which are key factors in developing prospective electrical sensors toward volatolomics analysis.     

Detection of microbial volatile organic compounds (MVOCs) by ion-mobility spectrometry

Traces of microbial volatile organic compounds (MVOCs) in air can indicate the presence of growth of moulds in the indoor environment. Ion-mobility spectrometry is a very promising method for detection of these MVOCs, because of its high sensitivity. For development of an in-situ method for detection of MVOCs, a portable ion-mobility spectrometer (IMS) was used and test gases of 14 MVOCs and their respective mixtures were investigated. IMS spectra were recorded as a function of concentration of MVOCs in air. Drift time and mobility of reactant ions formed in positive polarity mode were determined and correlated with the mass-to-charge ratio (m/z) of the MVOCs investigated. The estimated detection limit has a specific value for each MVOC and is in the range 3 to 96 μg m⁻³ (1 to 52 ppb_V). Indoor trials show that IMS can indicate hidden mould growth.     

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.     

An exploratory comparative study of volatile compounds in exhaled breath and emitted by skin using selected ion flow tube mass spectrometry

Selected ion flow tube mass spectrometry (SIFT-MS) has been used to carry out a pilot parallel study on five volunteers to determine changes occurring in several trace compounds present in exhaled breath and emitted from skin into a collection bag surrounding part of the arm, before and after ingesting 75 g of glucose in the fasting state. SIFT-MS enabled real-time quantification of ammonia, methanol, ethanol, propanol, formaldehyde, acetaldehyde, isoprene and acetone. Following glucose ingestion, blood glucose and trace compound levels were measured every 30 min for 2 h. All the above compounds, except formaldehyde, were detected at the expected levels in exhaled breath of all volunteers; all the above compounds, except isoprene, were detected in the collection bag. Ammonia, methanol and ethanol were present at lower levels in the bag than in the breath. The aldehydes were present at higher levels in the bag than in breath. The blood glucose increased to a peak about 1 h post-ingestion, but this change was not obviously correlated with temporal changes in any of the compounds in breath or emitted by skin, except for acetone. The decrease in breath acetone was closely mirrored by skin-emitted acetone in three volunteers. Breath and skin acetone also clearly change with blood glucose and further work may ultimately enable inferences to be drawn of the blood glucose concentration from skin or breath measurements in type 1 diabetes.     

Modular and reconfigurable gas chromatography/differential mobility spectrometry (GC/DMS) package for detection of volatile organic compounds (VOCs)

Due to the versatility of present day microcontroller boards and open source development environments, new analytical chemistry devices can now be built outside of large industry and instead within smaller individual groups. While there are a wide range of commercial devices available for detecting and identifying volatile organic compounds (VOCs), most of these devices use their own proprietary software and complex custom electronics, making modifications or reconfiguration of the systems challenging. The development of microprocessors for general use, such as the Arduino prototyping platform, now enables custom chemical analysis instrumentation. We have created an example system using commercially available parts, centered around on differential mobility spectrometer (DMS) device. The Modular Reconfigurable Gas Chromatography - Differential Mobility Spectrometry package (MR-GC-DMS) has swappable components allowing it to be quickly reconfigured for specific application purposes as well as broad, generic use. The MR-GC-DMS has a custom user-friendly graphical user interface (GUI) and precisely tuned proportional-integral-derivative controller (PID) feedback control system managing individual temperature-sensitive components. Accurate temperature control programmed into the microcontroller greatly increases repeatability and system performance. Together, this open-source platform enables researchers to quickly combine DMS devices in customized configurations for new chemical sensing applications.     

Fingerprint identification of volatile organic compounds in gasoline contaminated groundwater using gas chromatography differential ion mobility spectrometry

Groundwater can be contaminated when e.g. gasoline tanks leak. Due to sampling and lab analysis, groundwater monitoring is time consuming and expensive. The technologies developed for rapid on-site analysis of gasoline contaminated groundwater face the technical limitation to distinguish the gasoline from complex matrices. In the present study the fingerprint identification of volatile organic components (VOCs) in gasoline contaminated groundwater using gas chromatography (GC) differential ion mobility spectrometry (DMS) is investigated. Groundwater was spiked with five sorts of gasoline (one reformulated gasoline, gasoline without additives and three different brand gasoline collected on petrol stations) and analyzed by GC-DMS. Seven VOCs (benzene, toluene, ethyl benzene, m-xylene, p-xylene, o-xylene, 1,2,4-trimethylbenzene) were identified by GC mass spectrometry (GC-MS) as well as by GC-DMS and selected as markers. The semi-quantitative determination of the selected compounds was achieved. The limits of detection of the GC-DMS are 46.42?ng for benzene, 1.13?ng for toluene, 1.80?ng for ethylbenzene, 0.22?ng for m-xylene, 1.13?ng for p-xylene, 0.61?ng for o-xylene and 0.37?ng for 1,2,4-trimethylbenzene, respectively. These results reveal the feasibility of GC-DMS for on-site monitoring of contaminated groundwater.     

Correlation analysis on data sets to detect infectious agents in the airways by ion mobility spectrometry of exhaled breath

A correlation analysis of peaks found in IMS-Chromatograms was carried out to show the potential of the method in clinical applications. As an example, the data of exhaled breath of patients suffering infections of Pseudomonas were compared to healthy non-smokers. Using a rank sum calculation and providing a correlation table of all peaks found, delivers the basis for visualisation of highest ranked analytes. In addition, a consideration of positive and negative correlated peaks could support sub-grouping, if present. A set of signals could be found for discriminating the two groups of patients using MCC-IMS. Investigations of exhaled breath using ion mobility spectrometry seems to provide a promising means for the non-invasive identification of patients which are colonized or infected with bacteria such as Pseudomonas aeruginosa.     

Detection of explosives by ion mobility spectrometry

Ion mobility spectrometry is an effective method for detecting mine-explosive devices and explosive charges and for revealing objects and peoples who came into contact with explosives. This is because of the excellent analytical and performance characteristics of the corresponding instruments. In the present work, we described the objects to be detected, formulated the basic terms and definitions, considered the physicochemical basics of the separation of ions by their mobility in a gas under an electric field, and presented experimental data on the main analytical characteristics of spectrometers: their ability to identify analytes, resolution power, time to provide readings, sensitivity, and detection limit.     

Differential scanning calorimetry (DSC) of blood serum in chronic obstructive pulmonary disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a major global health challenge with a gloom perspective of being one of the big three cause of death by 2020. No reliable/reproducible biomarker has been identified so far to match the clinically-based staging system (GOLD). Blood samples of 30 subjects divided into 6 groups (no-COPD/-smoker, no-COPD/non-smoker, COPD I, COPD II, COPD III, COPD IV) with 5 patients in each were tested by differential scanning calorimetry. There is a clear 15.4 % difference between the heat flow maxima measured when no-COPD subjects were compared in accordance to their smoking/non-smoking status. Odds ratio of different heat flow in actively smoking COPD patients in stage IV and stage I was 1.61. A reverse tendency is detected in the relevant non-smoking COPD groups. The differences are inconsistent in intermediate stages (COPD II and III). DSC seems to be an applicable and objective method for monitoring nicotine abuse. There is a chance to detect specific typology of thermokinetic patterns in the two extremes of COPD (I vs. IV). Further studies with increased sample size are needed to allow calculations on specificity/sensitivity/positive and negative predictive value of enthalpies and heat flow maximums. The first clinically relevant blood-based COPD marker on the intravascular side of the alveo-capillary screen is demonstrated by our pilot study.     

Sampling and analysis of volatile organic compounds in bovine breath by solid-phase microextraction and gas chromatography-mass spectrometry

A relatively noninvasive method consisting of a face mask sampling device, solid-phase microextraction (SPME) fibers, and a gas chromatography-mass spectrometry (GC-MS) for the identification of volatile organic compounds (VOCs) in bovine breath was developed. Breath of three morbid steers with respiratory tract infections and three healthy steers were sampled seven times in 19 days for 15 min at each sampling. The breath VOCs adsorbed on the divinylbenzene (DVB)-Carboxen-polydimethyl siloxane (PDMS) 50/30 microm SPME fibers were transported to a laboratory GC-MS system for separation and identification with an in-house spectral library of standard chemicals. A total of 21 VOCs were detected, many of them for the first time in cattle breath. Statistical analyses using Chi-square test on the frequency of detection of each VOC in each group was performed. The presence of acetaldehyde (P < or = 0.05) and decanal (P < or = 0.10) were associated more with clinically morbid steers while methyl acetate, heptane, octanal, 2,3-butadione, hexanoic acid, and phenol were associated with healthy steers at P < or = 0.10. The results suggest that noninvasive heath screening using breath analyses could become a useful diagnostic tool for animals and humans.     

Reactivity of ambient volatile organic compounds （VOCs） in summer of 2004 in Beijing

Ambient volatile organic compounds （VOCs） were sampled at six sites in Beijing in the summer of 2004 and analyzed by GCMS. The chemical reactivities of 73 quantified VOCs species were evaluated by OH loss rates （LOH） and ozone formation potentials （OFPs）. Top 15 reactive species, mainly alkenes and aromatics, were identified by these two methods, and accounted for more than 70% of total reactivity of VOCs. In urban areas, isoprene was the most reactive species in term of OH loss rate, contributing 11.4% to the LOH of VOCs. While toluene, accounting for 9.4% of OFPs, appeared to have a long-time role in the photochemical processes. Tongzhou site is obviously influenced by local chemical industry, but the other five sites showed typical urban features influenced mainly by vehicular emissions.     

Non-labeling multiplex surface enhanced Raman scattering (SERS) detection of volatile organic compounds (VOCs)

In this paper, we report multiplex SERS based VOCs detection with a leaning nano-pillar substrate. The VOCs analyte molecules adsorbed at the tips of the nano-pillars produced SERS signal due to the field enhancement occurring at the localized surface plasmon hot spots between adjacent leaning nano-pillars. In this experiment, detections of acetone and ethanol vapor at different concentrations were demonstrated. The detection limits were found to be 0.0017 ng and 0.0037 ng for ethanol and acetone vapor molecules respectively. Our approach is a non-labeling method such that it does not require the incorporation of any chemical sensing layer for the enrichment of gas molecules on sensor surface. The leaning nano-pillar substrate also showed highly reproducible SERS signal in cyclic VOCs detection, which can reduce the detection cost in practical applications. Further, multiplex SERS detection on different combination of acetone and ethanol vapor was also successfully demonstrated. The vibrational fingerprints of molecular structures provide specific Raman peaks for different VOCs contents. To the best of our knowledge, this is the first multiplex VOCs detection using SERS. We believe that this work may lead to a portable device for multiplex, specific and highly sensitive detection of complex VOCs samples that can find potential applications in exhaled breath analysis, hazardous gas analysis, homeland security and environmental monitoring.     

Simple analysis of volatile organic compounds (VOCs) in the atmosphere using passive samplers.

A simple analysis of volatile organic compounds (VOCs), such as benzene, toluene, m,p-xylene, and o-xylene, at low levels in the atmosphere was conducted using passive samplers. The methods were applied to analyzing the behavior and origin of VOCs in Kyoto City. The passive samplers were exposed for 7 - 14 days at sampling sites in Kyoto City and for 30 days in the mountains (Mt. Hiei and Mt. Daimonji). Shibata gas-tube samplers packed with activated carbon were used for the determination of VOCs. The absorbed VOCs were extracted into carbon disulfide (CS2) and measured by FID-GC. The determination limits and relative standard deviations for VOCs were 0.3 microg/m3 and 3%, respectively. The samplers were set up at 5 sites in March, 2001 and at 13 stations on Mt. Hiei in November, 2002. The average concentrations of ambient benzene, which were higher than the environmental criterion (3.0 microg/m3), except for those on Mt. Daimonji from March, 2001, to February, 2002, decreased to below 3.0 microg/m3 from March, 2002, to February, 2003. The decrease in ambient benzene may have been due to a decrease in the benzene content in gasoline by the end of 1999, and also by implementation of the Pollutant Release and Transfer Register (PRTR) Act in 2001.     

Passive sampling for volatile organic compounds (VOCs) in air at environmentally relevant concentration levels

A sensitive and reliable method is described for the determination of aromatic and chlorinated hydrocarbons (benzene, toluene, o-, m-, p-xylene, trichloromethane, trichloroethane, trichloroethene and tetrachloroethene) in indoor and outdoor air at environmental concentration levels. The procedure can be easily extended to other VOCs. Using passive samplers the VOCs have been adsorbed onto charcoal during a four-week sampling period and subsequently desorbed with carbon disulfide. After injection with a cold split-splitless multi-injector the VOCs have been separated by capillary gas chromatography. Quantification has been achieved using an electron capture detector (ECD) and a flame ionization detector (FID) switched in series. A limit of about 1 g/m³ for aromatic hydrocarbons and of about 0.01 g/m³ for chlorinated hydrocarbons has been obtained. The procedure has been successfully applied in the framework of a field study to measure indoor and outdoor air concentrations in Essen and Borken, two differently polluted areas of Northrhine-Westphalia.