Breath analysis: translation into clinical practice

Neural network classification of mobility spectra for volatile organic compounds using tandem differential mobility spectrometry with field induced fragmentation

A spectral library of field induced fragmentation (FIF) spectra for 45 oxygen-containing volatile organic compounds from 5 chemical classes was obtained using tandem differential mobility spectrometry (DMS). Protonated monomers were mobility isolated in a first DMS stage, fragmented with electric fields >10,000 V/cm in a middle (or reactive) stage, and mobility characterized in a second DMS stage. Other spectral libraries were obtained for protonated monomers and for complete mobility spectra from a single DMS stage. Neural networks from Python/Tensorflow software, prepared in-house, and from commercial NeuralWorks Professional II/PLUS were trained to assign spectra into a chemical class. The success at classification was determined for familiar and unfamiliar spectra from these three libraries. Classification test scores were best with FIF spectra with >0.99 for familiar compounds and 0.52 for unfamiliar compounds and were consistent with neural network learning of structural information from fragment ions when compared to other spectral libraries. Radar charts are introduced as measures of classification and as a tool to explore mis-classification. This work shows that ion fragmentation with multi-stage tandem DMS portends molecular identification with the portability and robustness of ambient pressure ion mobility analyzers.

SERS Approach to Probe the Adsorption Process of Trace Volatile Benzaldehyde on Layered Double Hydroxide Material

The study of the physicochemical process of volatile organic compound (VOC) adsorption on porous materials is significant for design and screening of adsorbent materials and treatment of VOCs. Traditional measurement methods for studying the adsorption process require lots of adsorbates and adsorbents and are time-consuming. We proposed a facile strategy to study the adsorption process of trace gaseous aldehydes on layered double hydroxide (LDH) using surface-enhanced Raman spectroscopy (SERS). We prepared a composite of Ag nanocubes@hollow Co-Ni LDH (AgNCs@Co-Ni LDH) with a strong adsorption capability and high SERS sensitivity. The adsorption properties of LDH for benzaldehyde in terms of general kinetics and isotherms were investigated. The kinetic adsorption process could be fitted better by the pseudo-first-order kinetics with a higher correlation coefficient than by the pseudo-second-order model, and the adsorption rate of 0.0308 min^-1 was obtained from the fitting curve. The isotherm adsorption fits the Langmuir isotherm model, and its adsorption constant is 6.25 × 10⁶ L/mol. Taking advantage of the excellent adsorptive performance and SERS activity, the AgNCs@Co-Ni LDH composite can be used as an effective SERS probe to detect gaseous aldehydes, and it shows a linear dynamic range (5-100 ppb) with a limit of detection reaching 1.83 ppb for benzaldehyde, better than that achieved by previous studies. Therefore, this work has not only established a new measurement method for probing the adsorption process with extremely low consumption of both adsorbates and adsorbents, but also may lay the groundwork for the construction of rapid and ultra-sensitive SERS sensors for probing VOCs in the future.

Quantitative response to nitrite from field-induced decomposition of the chloride adduct of RDX by reactive stage tandem ion mobility spectrometry

An additional dimension of selectivity for the determination of RDX by ion mobility spectrometry (IMS) was introduced through field-induced decomposition of RDX·Cl^- to NO₂^- on a spectral baseline free of interfering peaks. In this variant of reactive stage tandem IMS, the explosive ion is decomposed selectively in the presence of an interferent and from significantly convolved peaks which were mobility isolated within a narrow range of drift times using dual ion shutters. Field-induced decomposition at 170 °C and field strength of 112 Td (∼16 kV cm^-1) provided 15% decomposition yield and RDX, amid interferent, was detected decisively even when peaks differed in reduced mobility coefficients (K_o) by only 0.02 cm² V^-1 s^-1. A nitrite peak with S/N of 8.5 was observed with vapour concentrations of 54 ppb for RDX and 329 ppb for Interferent A in the ionization volume corresponding to 2 ng of RDX and 100 ng of Interferent A deposited on sample traps in the thermal desorption inlet. Findings on quantitative response suggest the presence of excessive amounts of interferent caused ionization suppression of RDX. Still, RDX was determined quantitatively using sequential processing of ions by mobility isolation, selective field induced decomposition, and mobility analysis in a second drift region.

Exhaled breath analysis in disease detection

Investigating the use of exhaled breath analysis to diagnose and monitor different diseases has attracted much interest in recent years. This review introduces conventionally used methods and some emerging technologies aimed at breath analysis and their relevance to lung disease, airway inflammation, gastrointestinal disorders, metabolic disorders and kidney diseases. One section correlates breath components and specific diseases, whereas the other discusses some unique ideas, strategies, and devices to analyze exhaled breath for the diagnosis of some common diseases. This review aims to briefly introduce the potential application of exhaled breath analysis for the diagnosis and screening of various diseases, thereby providing a new avenue for the detection of non-invasive diseases.

Field Induced Fragmentation (Fif) Spectra of Oxygen Containing Volatile Organic Compounds with Reactive Stage Tandem Ion Mobility Spectrometry and Functional Group Classification by Neural Network Analysis

Mobility isolated spectra were obtained for protonated monomers of 42 volatile oxygen containing organic compounds at ambient pressure using a tandem ion mobility spectrometer with a reactive stage between drift regions. Fragment ions of protonated monomers of alcohols, acetates, aldehydes, ketones, and ethers were produced in the reactive stage using a 3.3 MHz symmetrical sinusoidal waveform with an amplitude of 1.4 kV and mobility analyzed in a 19 mm long drift region. The resultant field induced fragmentation (FIF) spectra included residual intensities for protonated monomers and fragment ions with characteristic drift times and peak intensities, associated with ion mass and chemical class. High efficiency of fragmentation was observed with single bond cleavage of alcohols and in six-member ring rearrangements of acetates. Fragmentation was not observed, or seen weakly, with aldehydes, ethers, and ketones due to their strained four-member ring transition states. Neural networks were trained to categorize spectra by chemical class and tested with FIF spectra of both familiar and unfamiliar compounds. Rates of categorization were class dependent with best performance for alcohols and acetates, moderate performance for ketones, and worst performance for ethers and aldehydes. Trends in the rates of categorization within a chemical family can be understood as steric influences on the energy of activation for ion fragmentation. Electric fields greater than 129 Td or new designs of reactive stages with improved efficiency of fragmentation will be needed to extend the practice of reactive stage tandem IMS to an expanded selection of volatile organic compounds.

Field induced fragmentation spectra from reactive stage-tandem differential mobility spectrometry

A planar tandem differential mobility spectrometer was integrated with a middle reactive stage to fragment ions which were mobility selected in a first analyzer stage using characteristic compensation and separation fields.

Evolution of clinical and environmental health applications of exhaled breath research: Review of methods and instrumentation for gas-phase, condensate, and aerosols

Human breath, along with urine and blood, has long been one of the three major biological media for assessing human health and environmental exposure. In fact, the detection of odor on human breath, as described by Hippocrates in 400 BC, is considered the first analytical health assessment tool. Although less common in comparison to contemporary bio-fluids analyses, breath has become an attractive diagnostic medium as sampling is non-invasive, unlimited in timing and volume, and does not require clinical personnel. Exhaled breath, exhaled breath condensate (EBC), and exhaled breath aerosol (EBA) are different types of breath matrices used to assess human health and disease state. Over the past 20 years, breath research has made many advances in assessing health state, overcoming many of its initial challenges related to sampling and analysis. The wide variety of sampling techniques and collection devices that have been developed for these media are discussed herein. The different types of sensors and mass spectrometry instruments currently available for breath analysis are evaluated as well as emerging breath research topics, such as cytokines, security and airport surveillance, cellular respiration, and canine olfaction.

Breath based volatile organic compounds in the detection of breast, lung, and colorectal cancers: A systematic review

BACKGROUND

Detecting volatile organic compounds (VOCs) could provide a rapid, noninvasive, and inexpensive screening tool for detecting cancer.

OBJECTIVE

In this systematic review, we identified specific exhaled breath VOCs correlated with lung, colorectal, and breast cancer.

METHODS

We identified relevant studies published in 2015 and 2016 by searching Pubmed and Web of Science. The protocol for this systematic review was registered in PROSPERO and the PRISMA guidelines were used in reporting. VOCs and performance data were extracted.

RESULTS

Three hundred and thirty three records were identified and 43 papers were included in the review, of which 20 were review articles themselves. We identified 17 studies that listed the VOCs with at least a subset of statistics on detection cutoff levels, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and gradient.

CONCLUSIONS

Breath analysis for cancer screening and early detection shows promise, because samples can be collected easily, safely, and frequently. While gas chromatography-mass spectrometry is considered the gold standard for identifying specific VOCs, breath analysis has moved into analyzing patterns of VOCs using a variety of different multiple sensor techniques, such as eNoses and nanomaterials. Further development of VOCs for early cancer detection requires clinical trials with standardized breath sampling methods.

Calibration and performance of synchronous SIM/scan mode for simultaneous targeted and discovery (non-targeted) analysis of exhaled breath samples from firefighters

Traditionally, gas chromatography-mass spectrometry (GC/MS) analysis has used a targeted approach called selected ion monitoring (SIM) to quantify specific compounds that may have adverse health effects. Due to method limitations and the constraints of preparing duplicate samples, the information that could be obtained from separately collecting the full scan chromatogram of the sample has often been sacrificed. However, the hybrid technique called synchronous SIM/scan mode alternates between the two acquisition modes, maintaining the accuracy and sensitivity of SIM for targeted analysis while also providing the full scan chromatogram for discovery of non-target compounds. This technology was assessed using calibration data and real-world breath samples from a joint EPA/NIOSH collaboration that investigated the safety of firefighters' protective gear during controlled structure burns. Collecting field samples is costly and must be performed strategically to ensure that time points and replicates are accurate and representative of the intended population. This is difficult to accomplish with firefighters who are working under volatile conditions. The synchronous SIM/scan method decreases the number of field samples that need to be collected by half and reduces error in trying to recreate time points since a breath sample from a single sorbent tube can be used to collect both the SIM and scan data simultaneously. As a practical demonstration of the method, we investigate thirty-six firefighter breath samples, document organic compounds of interest, and identify additional non-target compounds.

Online Measurement of Exhaled NO Concentration and Its Production Sites by Fast Non-equilibrium Dilution Ion Mobility Spectrometry

Exhaled nitric oxide (NO) is one of the most promising breath markers for respiratory diseases. Its profile for exhalation and the respiratory NO production sites can provide useful information for medical disease diagnosis and therapeutic procedures. However, the high-level moisture in exhaled gas always leads to the poor selectivity and sensitivity for ion spectrometric techniques. Herein, a method based on fast non-equilibrium dilution ion mobility spectrometry (NED-IMS) was firstly proposed to directly monitor the exhaled NO profile on line. The moisture interference was eliminated by turbulently diluting the original moisture to 21% of the original with the drift gas and dilution gas. Weak enhancement was observed for humid NO response and its limit of detection at 100% relative humidity was down to 0.58 ppb. The NO concentrations at multiple exhalation flow rates were measured, while its respiratory production sites were determined by using two-compartment model (2CM) and Högman and Meriläinen algorithm (HMA). Last but not the least, the NO production sites were analyzed hourly to tentatively investigate the daily physiological process of NO. The results demonstrated the capacity of NED-IMS in the real-time analysis of exhaled NO and its production sites for clinical diagnosis and assessment.

Ion Mobility in Clinical Analysis: Current Progress and Future Perspectives

BACKGROUND

Ion mobility spectrometry (IMS) is a rapid separation tool that can be coupled with several sampling/ionization methods, other separation techniques (e.g., chromatography), and various detectors (e.g., mass spectrometry). This technique has become increasingly used in the last 2 decades for applications ranging from illicit drug and chemical warfare agent detection to structural characterization of biological macromolecules such as proteins. Because of its rapid speed of analysis, IMS has recently been investigated for its potential use in clinical laboratories.

CONTENT

This review article first provides a brief introduction to ion mobility operating principles and instrumentation. Several current applications will then be detailed, including investigation of rapid ambient sampling from exhaled breath and other volatile compounds and mass spectrometric imaging for localization of target compounds. Additionally, current ion mobility research in relevant fields (i.e., metabolomics) will be discussed as it pertains to potential future application in clinical settings.

SUMMARY

This review article provides the authors' perspective on the future of ion mobility implementation in the clinical setting, with a focus on ambient sampling methods that allow IMS to be used as a “bedside” standalone technique for rapid disease screening and methods for improving the analysis of complex biological samples such as blood plasma and urine.

Detection of volatile organic compounds (VOCs) from exhaled breath as noninvasive methods for cancer diagnosis

The detection of cancer at an early stage is often significant in the successful treatment of the disease. Tumor cells have been reported to generate unique cancer volatile organic compound (VOC) profiles which can reflect the disease conditions. The detection and analysis of VOC biomarkers from exhaled breath has been recognized as a new frontier in cancer diagnostics and health inspections owing to its potential in developing rapid, noninvasive, and inexpensive cancer screening tools. To detect specific VOCs of low concentrations from exhaled breath, and to enhance the accuracy of early diagnosis, many breath collection and analysis approaches have been developed. This paper will summarize and critically review the exhaled-breath VOC-related sampling, collection, detection, and analytical methods, especially the recent development in VOC sensors. VOC sensors are commonly inexpensive, portable, programmable, easy to use, and can obtain data in real time with high sensitivities. Therefore, many sensor-based VOC detection techniques have huge potential in clinical point-of-care use.