Ion mobility spectrometry coupled with multi-capillary columns for metabolic profiling of human breath

Evaluation of Fourier deconvolution ion mobility spectrometer as high-performance gas chromatography detector for the analysis of plant extract flavors

The Fourier deconvolution ion mobility spectrometer (FDIMS) offers multiplexing and improves the resolving power and signal-to-noise ratio. To evaluate the FDIMS as a detector for gas chromatography for the analysis of complex samples, we connected a drift tube ion mobility spectrometer to a commercial gas chromatograph and compared the performance including resolving power, sensitivity, and linear range using 2,6-di‑tert-butylpyridine. Mixed standards were also injected into the tandem system to evaluate the performance under optimized conditions. A complex plant extract sample used as natural flavoring was investigated using the resulting system. The results show that the instrument implemented with the Fourier deconvolution multiplexing method demonstrated higher performance over the traditional signal averaging method including higher resolving power, better limit of detection, and wider linear range for a variety of compounds and natural plant extract flavorings.

A novel coupling technique based on thermal desorption gas chromatography with mass spectrometry and ion mobility spectrometry for breath analysis

Exhaled breath analysis is evolving into an increasingly important non-invasive diagnostic tool. Volatile organic compounds (VOCs) in breath contain information about health status and are promising biomarkers for several diseases, including respiratory infections caused by bacteria. To monitor the composition of VOCs in breath or the emission of VOCs from bacteria, sensitive analytical techniques are required. Next to mass spectrometry, ion mobility spectrometry (IMS) is considered a promising analytical tool for detecting gaseous analytes in the parts per billion by volume to parts per trillion by volume range. This work presents a new, dual coupling of thermal desorption gas chromatography to a quadrupole mass spectrometer (MS) and an IMS by operating a simple splitter. Nearly identical retention times can be reached in the range of up to 30 min with slight deviations of 0.06 min-0.24 min. This enables the identification of unknown compounds in the IMS chromatogram using unambiguous mass spectral identification, as there are still no commercially available databases for IMS. It is also possible to discriminate one of the detectors using the splitter to improve detection limits. Using a test liquid mixture of seven ketones, namely 2-butanone, 2-pentanone, 2-hexanone, 2-heptanone, 2-octanone, 2-nonanone, and 2-decanone with a concentration of 0.01 g l-1reproducibilities ranging from 3.0% to 7.6% for MS and 2.2%-5.3%, for IMS were obtained, respectively. In order to test the system optimized here for the field of breath analysis, characteristic VOCs such as ethanol, isoprene, acetone, 2-propanol, and 1-propanol were successfully identified in exhaled air using the dual detector system due to the match of the corresponding IMS, and MS spectra. The presented results may be considered to be a starting point for the greater use of IMS in combination with MS within the medical field.

Determining the clinical utility of a breath test for screening an asbestos-exposed population for pleural mesothelioma: baseline results

Pleural mesothelioma (PM) is an aggressive cancer of the serosal lining of the thoracic cavity, predominantly caused by asbestos exposure. Due to nonspecific symptoms, PM is characterized by an advanced-stage diagnosis, resulting in a dismal prognosis. However, early diagnosis improves patient outcome. Currently, no diagnostic biomarkers or screening tools are available. Therefore, exhaled breath was explored as this can easily be obtained and contains volatile organic compounds, which are considered biomarkers for multiple (patho)physiological processes. A breath test, which differentiates asbestos-exposed (AEx) individuals from PM patients with 87% accuracy, was developed. However, before being implemented as a screening tool, the clinical utility of the test must be determined. Occupational AEx individuals underwent annual breath tests using multicapillary column/ion mobility spectrometry. A baseline breath test was taken and their individual risk of PM was estimated. PM patients were included as controls. In total, 112 AEx individuals and six PM patients were included in the first of four screening rounds. All six PM patients were correctly classified as having mesothelioma (100% sensitivity) and out of 112 AEx individuals 78 were classified by the breath-based model as PM patients (30% specificity). Given the large false positive outcome, the breath test will be repeated annually for three more consecutive years to adhere to the 'test, re-test' principle and improve the false positivity rate. A low-dose computed tomography scan in those with two consecutive positive tests will correlate test positives with radiological findings and the possible growth of a pleural tumor. Finally, the evaluation of the clinical value of a breath-based prediction model may lead to the initiation of a screening program for early detection of PM in Aex individuals, which is currently lacking. This clinical study received approval from the Antwerp University Hospital Ethics Committee (B300201837007).

Alveolar gradients in breath analysis. A pilot study with comparison of room air and inhaled air by simultaneous measurements using ion mobility spectrometry

Analyzing exhaled breath samples, especially using a highly sensitive method such as MCC/IMS (multi-capillary column/ion mobility spectrometry), may also detect analytes that are derived from exogenous production. In this regard, there is a discussion about the optimal interpretation of exhaled breath, either by considering volatile organic compounds (VOCs) only in exhaled breath or by additionally considering the composition of room air and calculating the alveolar gradients. However, there are no data on whether the composition and concentration of VOCs in room air are identical to those in truly inhaled air directly before analyzing the exhaled breath. The current study aimed to determine whether the VOCs in room air, which are usually used for the calculation of alveolar gradients, are identical to the VOCs in truly inhaled air. For the measurement of inhaled air and room air, two IMS, each coupled with an MCC that provided a pre-separation of the VOCs, were used in parallel. One device was used for sampling room air and the other for sampling inhaled air. Each device was coupled with a newly invented system that cleaned room air and provided a clean carrier gas, whereas formerly synthetic air had to be used as a carrier gas. In this pilot study, a healthy volunteer underwent three subsequent runs of sampling of inhaled air and simultaneous sampling and analysis of room air. Three of the selected 11 peaks (P4-unknown, P5-1-Butanol, and P9-Furan, 2-methyl-) had significantly higher intensities during inspiration than in room air, and four peaks (P1-1-Propanamine, N-(phenylmethylene), P2-2-Nonanone, P3-Benzene, 1,2,4-trimethyl-, and P11-Acetyl valeryl) had higher intensities in room air. Furthermore, four peaks (P6-Benzaldehyde, P7-Pentane, 2-methyl-, P8-Acetone, and P10-2-Propanamine) showed inconsistent differences in peak intensities between inhaled air and room air. To the best of our knowledge, this is the first study to compare simultaneous sampling of room air and inhaled air using MCC/IMS. The simultaneous measurement of inhaled air and room air showed that using room air for the calculation of alveolar gradients in breath analysis resulted in different alveolar gradient values than those obtained by measuring truly inhaled air.

Humidity and measurement of volatile propofol using MCC-IMS (EDMON)

The bedside Exhaled Drug MONitor - EDMON measures exhaled propofol in ppbv every minute based on multi-capillary column - ion mobility spectrometry (MCC-IMS). The MCC pre-separates gas samples, thereby reducing the influence of the high humidity in human breath. However, preliminary analyses identified substantial measurement deviations between dry and humid calibration standards. We therefore performed an analytical validation of the EDMON to evaluate the influence of humidity on measurement performance. A calibration gas generator was used to generate gaseous propofol standards measured by an EDMON device to assess linearity, precision, carry-over, resolution, and the influence of different levels of humidity at 100% and 1.7% (without additional) relative humidity (reference temperature: 37°C). EDMON measurements were roughly half the actual concentration without additional humidity and roughly halved again at 100% relative humidity. Standard concentrations and EDMON values correlated linearly at 100% relative humidity (R²=0.97). The measured values were stable over 100min with a variance ≤ 10% in over 96% of the measurements. Carry-over effects were low with 5% at 100% relative humidity after 5min of equilibration. EDMON measurement resolution at 100% relative humidity was 0.4 and 0.6 ppbv for standard concentrations of 3 ppbv and 41 ppbv. The influence of humidity on measurement performance was best described by a second-order polynomial function (R²≥0.99) with influence reaching a maximum at about 70% relative humidity. We conclude that EDMON measurements are strongly influenced by humidity and should therefore be corrected for sample humidity to obtain accurate estimates of exhaled propofol concentrations.

Patterns of volatile organic compounds in excrements of preterm neonates

BACKGROUND

As neonates are susceptible for many diseases, establishing noninvasive diagnostic methods is desirable. We hypothesized that volatile organic compounds (VOCs) could be successfully measured in diaper samples.

METHODS

We performed a feasibility study to investigate whether ambient air-independent headspace measurements of the VOC profiles of diapers from premature infants can be conducted using ion mobility spectrometer coupled with multi-capillary columns (B & S Analytik GmbH).

RESULTS

We analysed 39 diapers filled with stool (n = 10) or urine (n = 20) respectively, using empty diapers as a control (n = 9). A total of 158 different VOCs were identified, and we classified the content of the diapers (urine or stool) according to their VOC profiles with a significance level of p < 0.05.

CONCLUSIONS

We have developed a novel method to study headspace VOC profiles of biosamples using ion mobility spectrometry coupled with multi-capillary columns. Using this method, we have characterized the VOC profiles of stool and urine of preterm neonates. Future studies are warranted to characterize specific VOC profiles in infections and other diseases of the preterm neonate, thus establishing quick and noninvasive diagnostics in the routine care of the highly vulnerable preterm and term neonates.

Blood Culture Headspace Gas Analysis Enables Early Detection of Escherichia coli Bacteremia in an Animal Model of Sepsis

(1) Background: Automated blood culture headspace analysis for the detection of volatile organic compounds of microbial origin (mVOC) could be a non-invasive method for bedside rapid pathogen identification. We investigated whether analyzing the gaseous headspace of blood culture (BC) bottles through gas chromatography-ion mobility spectrometry (GC-IMS) enables differentiation of infected and non-infected; (2) Methods: BC were gained out of a rabbit model, with sepsis induced by intravenous administration of E. coli (EC group; n = 6) and control group (n = 6) receiving sterile LB medium intravenously. After 10 h, a pair of blood cultures was obtained and incubated for 36 h. The headspace from aerobic and anaerobic BC was sampled every two hours using an autosampler and analyzed using a GC-IMS device. MALDI-TOF MS was performed to confirm or exclude microbial growth in BCs; (3) Results: Signal intensities (SI) of 113 mVOC peak regions were statistically analyzed. In 24 regions, the SI trends differed between the groups and were considered to be useful for differentiation. The principal component analysis showed differentiation between EC and control group after 6 h, with 62.2% of the data variance described by the principal components 1 and 2. Single peak regions, for example peak region P_15, show significant SI differences after 6 h in the anaerobic environment (p < 0.001) and after 8 h in the aerobic environment (p < 0.001); (4) Conclusions: The results are promising and warrant further evaluation in studies with an extended microbial panel and indications concerning its transferability to human samples.

Drift Time Corrections Based on a Practical Measurement of the Depletion Zone to Allow Accurate and Reproducible Determination of the Reduced Mobility of Ions in DT-IMS

The reduced mobility of an ion is a key parameter for identifying ions and comparing spectra in drift time ion mobility spectrometry. As the resolution of spectrometers improves, accurate determination of the reduced mobility is increasingly important. The drift time, used to calculate the reduced mobility, is affected by the ion gate, and this effect has previously been compensated with a linear correction. These corrections, however, do not allow for changes in the distances that the ions must drift to reach the detector caused by the electric field around the ion gate. As these corrections are a linear correction, nonlinearity in the influence of the ion gate may also lead to greater errors. By measuring the length of the depletion zone in front of the ion gate the extra distance traveled by the ions may be corrected for. This measurement also provides the boundary conditions for when a correction to the drift time may be accurately applied. This work shows that the length of the depletion zone can be experimentally measured and that it is consistent for a particular geometry of ion gate.

Detection of Volatile Toxic Industrial Chemicals with Classical Ion Mobility Spectrometry and High-Kinetic Energy Ion Mobility Spectrometry

Due to their high sensitivity and compact design, ion mobility spectrometers are widely used to detect toxic industrial chemicals (TICs) in air. However, when analyzing complex gas mixtures, classical ion mobility spectrometry (IMS) suffers from false-positive rates due to limited resolving power or false-negative rates caused by competitive ion-molecule reactions and the resulting suppression of certain analyte ions. To overcome these limitations, high-kinetic energy IMS (HiKE-IMS) was introduced some years ago. In contrast to classical IMS, HiKE-IMS is operated at decreased pressures of 20···60 mbar and high reduced electric field strengths E/N of up to 120 Td. Under these conditions, the influence of competitive ion-molecule reactions on the prevailing ion population should be less pronounced, thus reducing false negatives. Additionally, effects such as fragmentation and field-dependent ion mobility may help to reduce false positives. In this work, the capabilities and limitations of HiKE-IMS in the field of on-site detection of the volatile TICs NH₃, HCN, H₂S, HCl, NO₂, Cl₂, and SO₂ are evaluated for the first time. Based on the limits of detection and the extent of spectral and chemical cross-sensitivities in gas mixtures, the results obtained for HiKE-IMS are compared with those obtained for classical IMS. It is shown that HiKE-IMS is less sensitive in comparison to classical IMS. However, when used for TIC detection, the reduced sensitivity of HiKE-IMS is not a major drawback. With values around 1 ppm_v, the achievable limits of detection for almost all TICs are below the AEGL-2 (4h) levels. Furthermore, in comparison to classical IMS, it is still striking that HiKE-IMS shows significantly less spectral and chemical cross-sensitivities and thus exhibits considerably lower false-positive and false-negative rates. Overall, it thus turns out that HiKE-IMS is a promising alternative to classical IMS in the field of on-site detection of TICs.

Simultaneous measurement of inhaled air and exhaled breath by double multicapillary column ion-mobility spectrometry, a new method for breath analysis: results of a feasibility study

The high sensitivity of the methods applied in breath analysis entails a high risk of detecting analytes that do not derive from endogenous production. Consequentially, it appears useful to have knowledge about the composition of inhaled air and to include alveolar gradients into interpretation.

The current study aimed to standardise sampling procedures in breath analysis, especially with multicapillary column ion-mobility spectrometry (MCC-IMS), by applying a simultaneous registration of inhaled air and exhaled breath.

A “double MCC-IMS” device, which for the first time allows simultaneous analysis of inhaled air and exhaled breath, was developed and tested in 18 healthy individuals. For this, two BreathDiscovery instruments were coupled with each other.

Measurements of inhaled air and exhaled breath in 18 healthy individuals (mean age 46±10.9 years; nine men, nine women) identified 35 different volatile organic compounds (VOCs) for further analysis. Not all of these had positive alveolar gradients and could be regarded as endogenous VOCs: 16 VOCs had a positive alveolar gradient in mean; 19 VOCs a negative one. 12 VOCs were positive in >12 of the healthy subjects.

For the first time in our understanding, a method is described that enables simultaneous measurement of inhaled air and exhaled breath. This facilitates the calculation of alveolar gradients and selection of endogenous VOCs for exhaled breath analysis. Only a part of VOCs in exhaled breath are truly endogenous VOCs. The observation of different and varying polarities of the alveolar gradients needs further analysis.

Simultaneous analysis of inhaled air and exhaled breath by a newly invented double MCC-IMS device shows that exhaled breath contains confounding exogeneous analytes and only a smaller number of truly endogenous VOCs, which can be used for further analysishttps://bit.ly/3HGVzV5

Identification of volatile compounds from bacteria by spectrometric methods in medicine diagnostic and other areas: current state and perspectives

Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. KEY POINTS: • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future.

Quantification of Volatile Acetone Oligomers Using Ion-Mobility Spectrometry

BACKGROUND

Volatile acetone is a potential biomarker that is elevated in various disease states. Measuring acetone in exhaled breath is complicated by the fact that the molecule might be present as both monomers and dimers, but in inconsistent ratios. Ignoring the molecular form leads to incorrect measured concentrations. Our first goal was to evaluate the monomer-dimer ratio in ambient air, critically ill patients, and rats. Our second goal was to confirm the accuracy of the combined (monomer and dimer) analysis by comparison to a reference calibration system.

METHODS

Volatile acetone intensities from exhaled air of ten intubated, critically ill patients, and ten ventilated Sprague-Dawley rats were recorded using ion-mobility spectrometry. Acetone concentrations in ambient air in an intensive care unit and in a laboratory were determined over 24 hours. The calibration reference was pure acetone vaporized by a gas generator at concentrations from 5 to 45 ppb_v (parts per billion by volume).

RESULTS

Acetone concentrations in ambient laboratory air were only slightly greater (5.6 ppb_v; 95% CI 5.1-6.2) than in ambient air in an intensive care unit (5.1 ppb_v; 95% CI 4.4-5.5; p < 0.001). Exhaled acetone concentrations were only slightly greater in rats (10.3 ppb_v; 95% CI 9.7-10.9) than in critically ill patients (9.5 ppb_v; 95% CI 7.9-11.1; p < 0.001). Vaporization yielded acetone monomers (1.3-5.3 mV) and dimers (1.4-621 mV). Acetone concentrations (ppb_v) and corresponding acetone monomer and dimer intensities (mV) revealed a high coefficient of determination (R ² = 0.96). The calibration curve for acetone concentration (ppb_v) and total acetone (monomers added to twice the dimers; mV) was described by the exponential growth 3-parameter model, with an R ² = 0.98.

CONCLUSION

The ratio of acetone monomer and dimer is inconsistent and varies in ambient air from place-to-place and across individual humans and rats. Monomers and dimers must therefore be considered when quantifying acetone. Combining the two accurately assesses total volatile acetone.

Investigating Bacterial Volatilome for the Classification and Identification of Mycobacterial Species by HS-SPME-GC-MS and Machine Learning

Species of Mycobacteriaceae cause disease in animals and humans, including tuberculosis and leprosy. Individuals infected with organisms in the Mycobacterium tuberculosis complex (MTBC) or non-tuberculous mycobacteria (NTM) may present identical symptoms, however the treatment for each can be different. Although the NTM infection is considered less vital due to the chronicity of the disease and the infrequency of occurrence in healthy populations, diagnosis and differentiation among Mycobacterium species currently require culture isolation, which can take several weeks. The use of volatile organic compounds (VOCs) is a promising approach for species identification and in recent years has shown promise for use in the rapid analysis of both in vitro cultures as well as ex vivo diagnosis using breath or sputum. The aim of this contribution is to analyze VOCs in the culture headspace of seven different species of mycobacteria and to define the volatilome profiles that are discriminant for each species. For the pre-concentration of VOCs, solid-phase micro-extraction (SPME) was employed and samples were subsequently analyzed using gas chromatography–quadrupole mass spectrometry (GC-qMS). A machine learning approach was applied for the selection of the 13 discriminatory features, which might represent clinically translatable bacterial biomarkers.

Headspace analyses using multi-capillary column-ion mobility spectrometry allow rapid pathogen differentiation in hospital-acquired pneumonia relevant bacteria

Background

Hospital-acquired pneumonia (HAP) is a common problem in intensive care medicine and the patient outcome depends on the fast beginning of adequate antibiotic therapy. Until today pathogen identification is performed using conventional microbiological methods with turnaround times of at least 24 h for the first results. It was the aim of this study to investigate the potential of headspace analyses detecting bacterial species-specific patterns of volatile organic compounds (VOCs) for the rapid differentiation of HAP-relevant bacteria.

Methods

Eleven HAP-relevant bacteria (Acinetobacter baumanii, Acinetobacter pittii, Citrobacter freundii, Enterobacter cloacae, Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Pseudomonas aeruginosa, Proteus mirabilis, Staphylococcus aureus, Serratia marcescens) were each grown for 6 hours in Lysogeny Broth and the headspace over the grown cultures was investigated using multi-capillary column-ion mobility spectrometry (MCC-IMS) to detect differences in the VOC composition between the bacteria in the panel. Peak areas with changing signal intensities were statistically analysed, including significance testing using one-way ANOVA or Kruskal-Wallis test (p < 0.05).

Results

30 VOC signals (23 in the positive ion mode and 7 in the negative ion mode of the MCC-IMS) showed statistically significant differences in at least one of the investigated bacteria. The VOC patterns of the bacteria within the HAP panel differed substantially and allowed species differentiation.

Conclusions

MCC-IMS headspace analyses allow differentiation of bacteria within HAP-relevant panel after 6 h of incubation in a complex fluid growth medium. The method has the potential to be developed towards a feasible point-of-care diagnostic tool for pathogen differentiation on HAP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02102-8.

Changes in volatile organic compounds provoked by lipopolysaccharide- or alpha toxin-induced inflammation in ventilated rats

Inflammation may alter volatile organic compounds (VOCs) in exhaled breath. We therefore used ion mobility spectrometry (IMS) to evaluate exhaled breath components in two non-infectious inflammatory models. Fifty male Sprague Dawley rats were anesthetized and ventilated for 24 h. Five treatments were randomly assigned: (1) lipopolysaccharide low dose [5 mg/kg]; (2) lipopolysaccharide high dose [10 mg/kg]; (3) alpha toxin low dose [40 µg/kg]; (4) alpha toxin high dose [80 µg/kg]; and, (5) NaCl 0.9% as control group. Gas was sampled from the expiratory line of the ventilator every 20 min and analyzed with IMS combined with a multi-capillary column. VOCs were identified by comparison with an established database. Survival analysis was performed by log-rank test, other analyses by one-way or paired ANOVA-tests and post-hoc analysis according to Holm-Sidak. Rats given NaCl and low-dose alpha toxin survived 24 h. The median survival time in alpha toxin high-dose group was 23 (95%-confidence interval (CI): 21, 24) h. In contrast, the median survival time in rats given high-dose lipopolysaccharide was 12 (95% CI: 9, 14) and only 13 (95% CI: 10, 16) h in those given high-dose lipopolysaccharide. 73 different VOCs were detected, of which 35 were observed only in the rats, 38 could be found both in the blank measurements of ventilator air and in the exhaled air of the rats. Forty-nine of the VOCs were identifiable from a registry of compounds. Exhaled volatile compounds were comparable in each group before injection of lipopolysaccharide and alpha toxin. In the LPS groups, 1-pentanol increased and 2-propanol decreased. After alpha toxin treatment, 1-butanol and 1-pentanol increased whereas butanal and isopropylamine decreased. Induction of a non-infectious systemic inflammation (niSI) by lipopolysaccharide and alpha toxin changes VOCs in exhaled breath. Exhalome analysis may help identify niSI.

Volatile organic compounds in head and neck squamous cell carcinoma-An in vitro pilot study

Owing to the lack of specific symptoms, diagnosis of head and neck squamous cell carcinoma (HNSCC) may be delayed. We evaluated volatile organic compounds in tumor samples from patients suffering from HNSCC and tested the hypothesis that there is a characteristic altered composition in the headspace of HNSCC compared with control samples from the same patient with normal squamous epithelium. These results provide the basis for future noninvasive breath analysis in HNSCC. Headspace air of suspected tumor and contralateral control samples in 20 patients were analyzed using ion-mobility spectrometry. Squamous cell carcinoma was diagnosed in 16 patients. In total, we observed 93 different signals in headspace measurements. Squamous cell carcinomas revealed significantly higher levels of volatile cyclohexanol (0.54 ppb_v , 25th to 75th percentiles 0.35-0.86) compared with healthy squamous epithelium (0.24 ppb_v , 25th to 75th percentiles 0.12-0.3; p < 0.001). In conclusion, head and neck squamous cell carcinoma emitted significantly higher levels of volatile cyclohexanol in headspace compared with normal squamous epithelium. These findings form the basis for future breath analysis for diagnosis, therapy control and the follow-up of HNSSC to improve therapy and aftercare.

Exhaled Breath Analysis in Diagnosis of Malignant Pleural Mesothelioma: Systematic Review

Malignant pleural mesothelioma (MPM) is mainly related to previous asbestos exposure. There is still dearth of information on non-invasive biomarkers to detect MPM at early stages. Human studies on exhaled breath biomarkers of cancer and asbestos-related diseases show encouraging results. The aim of this systematic review was to provide an overview on the current knowledge about exhaled breath analysis in MPM diagnosis. A systematic review was conducted on MEDLINE (PubMed), EMBASE and Web of Science databases to identify relevant studies. Quality assessment was done by the Newcastle-Ottawa Scale. Six studies were identified, all of which showed fair quality and explored volatile organic compounds (VOC) based breath profile using Gas Chromatography Coupled to Mass Spectrometry (GC-MS), Ion Mobility Spectrometry Coupled to Multi-capillary Columns (IMS-MCC) or pattern-recognition technologies. Sample sizes varied between 39 and 330. Some compounds (i.e, cyclohexane, P3, P5, P50, P71, diethyl ether, limonene, nonanal, VOC IK 1287) that can be indicative of MPM development in asbestos exposed population were identified with high diagnostic accuracy rates. E-nose studies reported breathprints being able to distinguish MPM from asbestos exposed individuals with high sensitivity and a negative predictive value. Small sample sizes and methodological diversities among studies limit the translation of results into clinical practice. More prospective studies with standardized methodologies should be conducted on larger populations.

Sr-Doped Cubic In2O3/Rhombohedral In2O3 Homojunction Nanowires for Highly Sensitive and Selective Breath Ethanol Sensing: Experiment and DFT Simulation Studies

In recent years, it is urgent and challenging to fabricate highly sensitive and selective gas sensors for breath analyses. In this work, Sr-doped cubic In₂O₃/rhombohedral In₂O₃ homojunction nanowires (NWs) are synthesized by one-step electrospun technology. The Sr doping alters the cubic phase of pure In₂O₃ into the rhombohedral phase, which is verified by the high-resolution transmittance electron microscopy, X-ray diffraction, and Raman spectroscopy, and is attributable to the low cohesive energy as calculated by the density functional theory (DFT). As a proof-of-concept of fatty liver biomarker sensing, ethanol sensors are fabricated using the electrospun In₂O₃ NWs. The results show that 8 wt % Sr-doped In₂O₃ shows the highest ethanol sensing performance with a high response of 21-1 ppm, a high selectivity over other interfering gases such as methanol, acetone, formaldehyde, toluene, xylene, and benzene, a high stability measured in 6 weeks, and also a high resistance to high humidity of 80%. The outstanding ethanol sensing performance is attributable to the enhanced ethanol adsorption by Sr doping as calculated by DFT, the stable rhombohedral phase and the preferred (104) facet exposure, and the formed homojunctions favoring the electron transfer. All these results show the effective structural modification of In₂O₃ by Sr doping, and also the great potency of the homojunction Sr-doped In₂O₃ NWs for highly sensitive, selective, and stable breath ethanol sensing.

Volatile Organic Compounds in Patients With Acute Kidney Injury and Changes During Dialysis

OBJECTIVES

To characterize volatile organic compounds in breath exhaled by ventilated care patients with acute kidney injury and changes over time during dialysis.

DESIGN

Prospective observational feasibility study.

SETTING

Critically ill patients on an ICU in a University Hospital, Germany.

PATIENTS

Twenty sedated, intubated, and mechanically ventilated patients with acute kidney injury and indication for dialysis.

INTERVENTIONS

Patients exhalome was evaluated from at least 30 minutes before to 7 hours after beginning of continuous venovenous hemodialysis.

MEASUREMENTS AND MAIN RESULTS

Expired air samples were aspirated from the breathing circuit at 20-minute intervals and analyzed using multicapillary column ion-mobility spectrometry. Volatile organic compound intensities were compared with a ventilated control group with normal renal function. A total of 60 different signals were detected by multicapillary column ion-mobility spectrometry, of which 44 could be identified. Thirty-four volatiles decreased during hemodialysis, whereas 26 remained unaffected. Forty-five signals showed significant higher intensities in patients with acute kidney injury compared with control patients with normal renal function. Among these, 30 decreased significantly during hemodialysis. Volatile cyclohexanol (23 mV; 2575th, 19-38), 3-hydroxy-2-butanone (16 mV, 9-26), 3-methylbutanal (20 mV; 14-26), and dimer of isoprene (26 mV; 18-32) showed significant higher intensities in acute kidney impairment compared with control group (12 mV; 10-16 and 8 mV; 7-14 and not detectable and 4 mV; 0-6; p < 0.05) and a significant decline after 7 hours of continuous venovenous hemodialysis (16 mV; 13-21 and 7 mV; 6-13 and 9 mV; 8-13 and 14 mV; 10-19).

CONCLUSIONS

Exhaled concentrations of 45 volatile organic compounds were greater in critically ill patients with acute kidney injury than in patients with normal renal function. Concentrations of two-thirds progressively decreased during dialysis. Exhalome analysis may help quantify the severity of acute kidney injury and to gauge the efficacy of dialysis.

Breath Analysis: A Systematic Review of Volatile Organic Compounds (VOCs) in Diagnostic and Therapeutic Management of Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a rare neoplasm related to asbestos exposure and with high mortality rate. The management of patients with MPM is complex and controversial, particularly with regard to early diagnosis. In the last few years, breath analysis has been greatly implemented with this aim. In this review the strengths of breath analysis and preliminary results in searching breath biomarkers of MPM are highlighted and discussed, respectively. Through a systematic electronic literature search, collecting papers published from 2000 until December 2018, fifteen relevant scientific papers were selected. All papers considered were prospective, comparative, observational case-control studies although every single one pilot and based on a relatively small number of samples. The identification of diagnostic VOCs pattern, through breath sample characterization and the statistical data treatment, allows to obtain a strategic information for clinical diagnostics. To date the collected data provide just preliminary information and, despite the promising results and diagnostic accuracy, conclusions cannot be generalized due to the limited number of individuals included in each cohort study. Furthermore none of studies was externally validated, although validation process is a necessary step towards clinical implementation. Breathomics-based biomarker approach should be further explored to confirm and validate preliminary findings and to evaluate its potential role in monitoring the therapeutic response.

Hybrid Analytical Platform Based on Field-Asymmetric Ion Mobility Spectrometry, Infrared Sensing, and Luminescence-Based Oxygen Sensing for Exhaled Breath Analysis

The reliable online analysis of volatile compounds in exhaled breath remains a challenge, as a plethora of molecules occur in different concentration ranges (i.e., ppt to %) and need to be detected against an extremely complex background matrix. Although this complexity is commonly addressed by hyphenating a specific analytical technique with appropriate preconcentration and/or preseparation strategies prior to detection, we herein propose the combination of three different detector types based on truly orthogonal measurement principles as an alternative solution: Field-asymmetric ion mobility spectrometry (FAIMS), Fourier-transform infrared (FTIR) spectroscopy-based sensors utilizing substrate-integrated hollow waveguides (iHWG), and luminescence sensing (LS). By carefully aligning the experimental needs and measurement protocols of all three methods, they were successfully integrated into a single compact analytical platform suitable for online measurements. The analytical performance of this prototype system was tested via artificial breath samples containing nitrogen (N₂), oxygen (O₂), carbon dioxide (CO₂), and acetone as a model volatile organic compound (VOC) commonly present in breath. All three target analytes could be detected within their respectively breath-relevant concentration range, i.e., CO₂ and O₂ at 3-5 % and at ~19.6 %, respectively, while acetone could be detected with LOQs as low as 165-405 ppt. Orthogonality of the three methods operating in concert was clearly proven, which is essential to cover a possibly wide range of detectable analytes. Finally, the remaining challenges toward the implementation of the developed hybrid FAIMS-FTIR-LS system for exhaled breath analysis for metabolic studies in small animal intensive care units are discussed.

Statistical analysis of MCC-IMS data for two group comparisons-an exemplary study on two devices

The Multi-capillary-column-Ion-mobility-spectrometry (MCC-IMS) technology for measuring breath gas can be used for distinguishing between healthy and diseased subjects or between different types of diseases. The statistical methods for classifying the corresponding breath samples typically neglects potential confounding clinical and technical variables, reducing both accuracy and generalizability of the results. Especially measuring samples on different technical devices can heavily influence the results. We conducted a controlled breath gas study including 49 healthy volunteers to evaluate the effect of the variables sex, smoking habits and technical device. Every person was measured twice, once before and once after consuming a glass of orange juice. The two measurements were obtained on two different devices. The evaluation of the MCC-IMS data regarding metabolite detection was performed once using the software VisualNow, which requires manual interaction, and once using the fully automated algorithm SGLTR-DBSCAN. We present statistical solutions, peak alignment and scaling, to adjust for the different devices. For the other potential confounders sex and smoking, in our study no significant influence was identified.

Ultra-high-resolution ion mobility spectrometry-current instrumentation, limitations, and future developments

With recent advances in ionization sources and instrumentation, ion mobility spectrometers (IMS) have transformed from a detector for chemical warfare agents and explosives to a widely used tool in analytical and bioanalytical applications. This increasing measurement task complexity requires higher and higher analytical performance and especially ultra-high resolution. In this review, we will discuss the currently used ion mobility spectrometers able to reach such ultra-high resolution, defined here as a resolving power greater than 200. These instruments are drift tube IMS, traveling wave IMS, trapped IMS, and field asymmetric or differential IMS. The basic operating principles and the resulting effects of experimental parameters on resolving power are explained and compared between the different instruments. This allows understanding the current limitations of resolving power and how ion mobility spectrometers may progress in the future. Graphical abstract.

Coupling of a High-Resolution Ambient Pressure Drift Tube Ion Mobility Spectrometer to a Commercial Time-of-flight Mass Spectrometer

Ion mobility spectrometry provides information about molecular structures of ions. Hence, high resolving power allows separation of isomers which is of major interest in several applications. In this work, we couple our high-resolution ion mobility spectrometer (IMS) with a resolving power of R_p = 100 to a time-of-flight mass spectrometer (TOF-MS). Besides, the benefit of an increased resolving power such an IMS-MS also helps analyzing and understanding the ionization processes in IMS. Usually, the coupling between IMS and TOF-MS is realized by synchronizing data acquisition of the IMS and MS resulting in two-dimensional data containing ion mobility and mass spectra. However, due to peak widths of less than 100 μs in our high-resolution IMS, this technique is not practicable due to significant peak broadening during the ion transfer into the MS and an insufficient data acquisition rate of the MS. Thus, a novel but simple interface between the IMS and MS has been designed which minimizes ion losses, allows recording of ion mobility at full IMS resolving power, and enables a shuttered transmission of ions into the MS. The interface is realized by replacing the Faraday plate used in IMS by a Faraday grid that is shielded by two additional aperture grids. For demonstration, positive product ions of benzene, toluene, and m-xylene in air are investigated. The IMS is equipped with a radioactive ³H source. Besides the well-known product ions M⁺ and M·NO⁺, a dimer ion is also observed for benzene and toluene, consisting of two molecules and three further hydrogen atoms. Graphical Abstract ᅟ.

Developments to monitor the exhalome in organ failure in critically ill patients-a look into the future

Critically ill patients typically need some kind of functional organ support or replacement. Cardiopulmonary and renal replacement therapies are well established measures in intensive care units. However, there are also inherent risks associated with these treatments. The appropriate and timely commencement, maintenance and termination of organ replacement procedures currently use weak surrogates as decision support in clinical practice. A more reasonable application of extracorporeal organ support can be expected to potentially lower adverse events and save costs in healthcare systems, if a precise online monitoring was available. The analysis of the exhalome offers great opportunities to detect circulatory, pulmonary, and renal failure in critically ill patients. Volatile organic compounds and exhalation patterns are associated with a series of metabolic disorders and may be key to indicate the appropriate time point for initiation, maintenance and termination of organ support technologies. It may thus be expected that mortality, infection risk, replacement therapy days, and medical costs of intensive care treatment may possibly be reduced using exhalome analysis for control of organ replacement therapies in the distant future.

Review: Endogenously Produced Volatiles for In Vitro Toxicity Testing Using Cell Lines

Due to the ∼86,000 chemicals registered under the Toxic Substances Control Act and increasing ethical concerns regarding animal testing, it is not economically or technically feasible to screen every registered chemical for toxicity using animal-based toxicity assays. To address this challenge, regulatory agencies are investigating high-throughput screening in vitro methods to increase speed of toxicity testing, while reducing the overall cost. One approach for rapid toxicity testing currently being investigated is monitoring of volatile emissions produced by cell lines in culture. Such a metabolomics approach would measure gaseous emissions from a cell line and determine if such gaseous metabolites are altered upon exposure to a xenobiotic. Herein, we describe the history and rationale of monitoring endogenously produced volatiles for identification of pathologic conditions, as well as emerging applications in toxicity testing for such an approach.

Volatile organic compounds in ventilated critical care patients: a systematic evaluation of cofactors

Background

Expired gas (exhalome) analysis of ventilated critical ill patients can be used for drug monitoring and biomarker diagnostics. However, it remains unclear to what extent volatile organic compounds are present in gases from intensive care ventilators, gas cylinders, central hospital gas supplies, and ambient air. We therefore systematically evaluated background volatiles in inspired gas and their influence on the exhalome.

Methods

We used multi-capillary column ion-mobility spectrometry (MCC-IMS) breath analysis in five mechanically ventilated critical care patients, each over a period of 12 h. We also evaluated volatile organic compounds in inspired gas provided by intensive care ventilators, in compressed air and oxygen from the central gas supply and cylinders, and in the ambient air of an intensive care unit. Volatiles detectable in both inspired and exhaled gas with patient-to-inspired gas ratios < 5 were defined as contaminating compounds.

Results

A total of 76 unique MCC-IMS signals were detected, with 39 being identified volatile compounds: 73 signals were from the exhalome, 12 were identified in inspired gas from critical care ventilators, and 34 were from ambient air. Five volatile compounds were identified from the central gas supply, four from compressed air, and 17 from compressed oxygen. We observed seven contaminating volatiles with patient-to-inspired gas ratios < 5, thus representing exogenous signals of sufficient magnitude that might potentially be mistaken for exhaled biomarkers.

Conclusions

Volatile organic compounds can be present in gas from central hospital supplies, compressed gas tanks, and ventilators. Accurate assessment of the exhalome in critical care patients thus requires frequent profiling of inspired gases and appropriate normalisation of the expired signals.

Detection of gas traces using semiconductor sensors, ion mobility spectrometry, and mass spectrometry

This article deals with the state-of-the-art instrumentation and application in the field of solid state gas sensorics, ion mobility spectrometry and mass-spectrometry-related research for the detection and measurements of low gas and vapor concentrations. The advantages and disadvantages of gas-analytical devices and systems are discussed, as well as the possibilities of its complex and/or complementary applications. Ion mobility spectrometry-mass spectrometry and subsequent techniques based on solid-state gas sensors are proposed for planned medical study.

Doping-assisted low-pressure photoionization mass spectrometry for the real-time detection of lung cancer-related volatile organic compounds

Real-time detection of lung cancer-related volatile organic compounds (VOCs) is a promising, non-intrusive technique for lung cancer (LC) prescreening. In this study, a novel method was designed to enhance the detection selectivity and sensitivity of LC-related polar VOCs by dichloromethane (CH₂Cl₂) doping-assisted low-pressure photoionization mass spectrometry (LPPI-MS). Compared with conventional LPPI-MS, CH₂Cl₂ doping-assisted LPPI-MS boosted the peak intensities of n-propanol, n-pentanal, acetone, and butyl acetate in nitrogen specifically by 53, 18, 16, and 43 times, respectively. The signal intensities of their daughter ions were inhibited or reduced. At relative humidity (RH) of 20%, the sensitivities of n-propanol, n-pentanal, acetone, and butyl acetate detection ranged from 116 to 452 counts/ppbv with a detection time of 10s and R² >0.99 for the linear calibration curves. The method was also applicable under higher RH levels of 50% and 90%. Breath samples obtained from 10 volunteers and spiked samples were investigated. Eight-fold enhancements in the signal intensities of polar VOCs were observed in the normal and spiked samples. These preliminary results demonstrate the efficacy of the dichloromethane doping-assisted LPPI technique for the detection of LC-related polar VOCs. Further studies are indispensible to illustrating the detailed mechanism and applying the technique to breath diagnosis.

Detection of malignant pleural mesothelioma in exhaled breath by multicapillary column/ion mobility spectrometry (MCC/IMS)

Malignant pleural mesothelioma (MPM) is predominantly caused by previous asbestos exposure. Diagnosis often happens in advanced stages restricting any therapeutic perspectives. Early stage detection via breath analysis was explored using multicapillary column/ion mobility spectrometry (MCC/IMS) to detect volatile organic compounds (VOCs) in the exhaled breath of MPM patients in comparison to former occupational asbestos-exposed and non-exposed controls. Breath and background samples of 23 MPM patients, 22 asymptomatic former asbestos (AEx) workers and 21 healthy non-asbestos exposed persons were taken for analysis. After background correction, we performed a logistic least absolute shrinkage and selection operator (lasso) regression to select the most important VOCs, followed by receiver operating characteristic (ROC) analysis. MPM patients were discriminated from both controls with 87% sensitivity, 70% specificity and respective positive and negative predictive values of 61% and 91%. The overall accuracy was 76% and the area under the ROC-curve was 0.81. AEx individuals could be discriminated from MPM patients with 87% sensitivity, 86% specificity and respective positive and negative predictive values of 87% and 86%. The overall accuracy was 87% with an area under the ROC-curve of 0.86. Breath analysis by MCC/IMS allows MPM patients to be discriminated from controls and holds promise for further investigation as a screening tool for former asbestos-exposed persons at risk of developing MPM.

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.

The effect of reusing wipes for particle collection

Sample collection for Ion Mobility Spectrometry (IMS) analysis is typically completed by swiping a collection wipe over a suspect surface to collect trace residues. The work presented here addresses the need for a method to measure the collection efficiency performance of surface wipe materials as a function of the number of times a wipe is used to interrogate a surface. The primary purpose of this study is to investigate the effect of wipe reuse, i.e., the number of times a wipe is swiped across a surface, on the overall particle collection and IMS response. Two types of collection wipes (Teflon coated fiberglass and Nomex) were examined by swiping multiple times, ranging from 0 to 1000, over representative surfaces that are common to security screening environments. Particle collection efficiencies were determined by fluorescence microscopy and particle counting techniques, and were shown to improve dramatically with increased number of swiping cycles. Ion mobility spectrometry was used to evaluate the chemical response of known masses of explosives (deposited after reusing wipes) as a function of the wipe reuse number. Results show that chemical response can be negatively affected, and greatly depends upon the conditions of the surface in which the wipe is interrogating. For most parameters tested, the PCE increased after the wipe was reused several times. Swiping a dusty cardboard surface multiple times also caused an increase in particle collection efficiency but a decrease in IMS response. Scanning electron microscopy images revealed significant surface degradation of the wipes on dusty cardboard at the micrometer spatial scale level for Teflon coated wipes. Additionally, several samples were evaluated by including a seven second thermal desorption cycle at 235°C into each swipe sampling interval in order to represent the IMS heating cycle. Results were similar to studies conducted without this heating cycle, suggesting that the primary mechanism for wipe deterioration is mechanical rather than thermal.

Measuring Compounds in Exhaled Air to Detect Alzheimer's Disease and Parkinson's Disease

Background

Alzheimer’s disease (AD) is diagnosed based upon medical history, neuropsychiatric examination, cerebrospinal fluid analysis, extensive laboratory analyses and cerebral imaging. Diagnosis is time consuming and labour intensive. Parkinson’s disease (PD) is mainly diagnosed on clinical grounds.

Objective

The primary aim of this study was to differentiate patients suffering from AD, PD and healthy controls by investigating exhaled air with the electronic nose technique. After demonstrating a difference between the three groups the secondary aim was the identification of specific substances responsible for the difference(s) using ion mobility spectroscopy. Thirdly we analysed whether amyloid beta (Aβ) in exhaled breath was causative for the observed differences between patients suffering from AD and healthy controls.

Methods

We employed novel pulmonary diagnostic tools (electronic nose device/ion-mobility spectrometry) for the identification of patients with neurodegenerative diseases. Specifically, we analysed breath pattern differences in exhaled air of patients with AD, those with PD and healthy controls using the electronic nose device (eNose). Using ion mobility spectrometry (IMS), we identified the compounds responsible for the observed differences in breath patterns. We applied ELISA technique to measure Aβ in exhaled breath condensates.

Results

The eNose was able to differentiate between AD, PD and HC correctly. Using IMS, we identified markers that could be used to differentiate healthy controls from patients with AD and PD with an accuracy of 94%. In addition, patients suffering from PD were identified with sensitivity and specificity of 100%. Altogether, 3 AD patients out of 53 participants were misclassified. Although we found Aβ in exhaled breath condensate from both AD and healthy controls, no significant differences between groups were detected.

Conclusion

These data may open a new field in the diagnosis of neurodegenerative disease such as Alzheimer’s disease and Parkinson’s disease. Further research is required to evaluate the significance of these pulmonary findings with respect to the pathophysiology of neurodegenerative disorders.

Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles

Computational breath analysis is a growing research area aiming at identifying volatile organic compounds (VOCs) in human breath to assist medical diagnostics of the next generation. While inexpensive and non-invasive bioanalytical technologies for metabolite detection in exhaled air and bacterial/fungal vapor exist and the first studies on the power of supervised machine learning methods for profiling of the resulting data were conducted, we lack methods to extract hidden data features emerging from confounding factors. Here, we present Carotta, a new cluster analysis framework dedicated to uncovering such hidden substructures by sophisticated unsupervised statistical learning methods. We study the power of transitivity clustering and hierarchical clustering to identify groups of VOCs with similar expression behavior over most patient breath samples and/or groups of patients with a similar VOC intensity pattern. This enables the discovery of dependencies between metabolites. On the one hand, this allows us to eliminate the effect of potential confounding factors hindering disease classification, such as smoking. On the other hand, we may also identify VOCs associated with disease subtypes or concomitant diseases. Carotta is an open source software with an intuitive graphical user interface promoting data handling, analysis and visualization. The back-end is designed to be modular, allowing for easy extensions with plugins in the future, such as new clustering methods and statistics. It does not require much prior knowledge or technical skills to operate. We demonstrate its power and applicability by means of one artificial dataset. We also apply Carotta exemplarily to a real-world example dataset on chronic obstructive pulmonary disease (COPD). While the artificial data are utilized as a proof of concept, we will demonstrate how Carotta finds candidate markers in our real dataset associated with confounders rather than the primary disease (COPD) and bronchial carcinoma (BC). Carotta is publicly available at http://carotta.compbio.sdu.dk [1].

Determination of volatile compounds by GC-IMS to assign the quality of virgin olive oil

The characterisation of different olive oil categories (extra virgin, virgin and lampante) using Ion Mobility Spectrometry (IMS) was improved by replacing the multicapillary column (MCC) with a capillary column (CC). The data obtained with MCC-IMS and CC-IMS were evaluated, studying both the global and the specific information obtained after the analysis of the volatile fraction of olive oils. A better differentiation of the oil categories was obtained employing CC vs MCC, since the classification percentage obtained with the CC-IMS was 92% as opposed to 87% obtained with MCC-IMS; although in productivity analytical terms, MCC offer a faster analysis than GC. The specific information obtained was also used to build a database, with a view to facilitating the characterization of specific attributes of olive oils. A total of 26 volatile metabolites (aldehydes, ketones, alcohols and esters) were identified. Finally, as revealed by an ANOVA test, some volatiles differed markedly in content among the different categories of oil. The data obtained confirms the potential of IMS as a reliable analytical screening technique, which can be used to assign the correct category to an olive oil sample.

Review on ion mobility spectrometry. Part 2: hyphenated methods and effects of experimental parameters

Ion Mobility Spectrometry (IMS) is a widely used and 'well-known' technique of ion separation in the gaseous phase based on the differences of ion mobilities under an electric field. This technique has received increased interest over the last several decades as evidenced by the pace and advances of new IMS devices available. In this review we explore the hyphenated techniques that are used with IMS, specifically mass spectrometry as an identification approach and a multi-capillary column as a pre-separation approach. Also, we will pay special attention to the key figures of merit of the ion mobility spectrum and how data sets are treated, and the influences of the experimental parameters on both conventional drift time IMS (DTIMS) and miniaturized IMS also known as high Field Asymmetric IMS (FAIMS) in the planar configuration. The present review article is preceded by a companion review article which details the current instrumentation and contains the sections that configure both conventional DTIMS and FAIMS devices. These reviews will give the reader an insightful view of the main characteristics and aspects of the IMS technique.