OUP accepted manuscript

Headspace Injection Method for Intermittent Sampling and Profiling Analyses of Volatile Organic Compounds Using Dielectric Barrier Discharge Ionization (DBDI)

A direct headspace injection method is presented and optimized for the analysis of volatile organic compounds (VOCs) using dielectric barrier discharge ionization-mass spectrometry (DBDI-MS), incorporating an intermediate vial in which the sample headspace is injected. The setup is built of commonly available, cheap consumable parts and easily enables the incorporation of different gases for generating different ionization atmospheres. The method can be fully automated by using standard GC autosamplers, and its rapid analysis time is suitable for high-throughput applications. We show that this method is suitable for both profiling analysis of complex samples such as biofluids and quantitative measurements for real-time reaction monitoring. Our optimized method demonstrated improved reproducibility and sensitivity, with detection limits for compounds tested in the high nanomolar to the low micromolar range, depending on the compound. Key parameters for method optimization were identified such as sample vial volume, headspace-to-liquid ratio, incubation temperature, and equilibration time. These settings were systematically evaluated to maximize the signal intensity and improve repeatability between measurements. Two use cases are demonstrated: (i) quantitative measurement of ethanol production by a metal-organic framework from CO2 and (ii) profiling of biofluids following the consumption of asparagus.

Breath of Health: spectroscopy-based breath test for the detection of SARS-CoV-2

BACKGROUND

Nucleic acid amplification tests (NAAT) are considered the gold standard for COVID-19 diagnosis. These tests require professional manpower and equipment, long processing and swab sampling which is unpleasant to the patients. Several volatile organic compounds (VOCs) have been identified in the breath of COVID-19 patients. Detection of these VOCs using a breath test could help rapidly identify COVID-19 patients.

OBJECTIVE

Assess the accuracy of 'Breath of Health' (BOH) COVID-19 Fourier-transform infra-red (FTIR) Spectroscopy-based breath test.

METHODS

Breath samples from patients with or without symptoms suggestive for COVID-19 who had NAAT results were collected using Tedlar bags and were blindly analysed using BOH FTIR spectroscopy. BOH Measures several VOCs simultaneously and differentiating positive and negative results. BOH results were compared to NAAT results as gold standard.

RESULTS

Breath samples from 531 patients were analysed. The sensitivity of BOH breath test was found to be 79.5% and specificity was 87.2%. Positive predictive value (PPV) was 74.7% and negative predictive value (NPV) 90.0%. Calculated accuracy rate was 84.8% and area under the curve 0.834. Subgroup analysis revealed that the NPV of patients without respiratory symptoms was superior over the NPV of symptomatic patients (94.7% vs 80.7%, P-value < 0.0001) and PPV of patients with respiratory symptoms outranks the PPV of individuals without symptoms (85.3% vs 69.2%, P-value 0.0196).

CONCLUSION

We found BOH COVID-19 breath test to be a patient-friendly, rapid, non-invasive diagnostic test with high accuracy rate and NPV that could efficiently rule out COVID-19 especially among individuals with low pre-test probability.

Colorectal Cancer Diagnosis through Breath Test Using a Portable Breath Analyzer-Preliminary Data

Screening methods available for colorectal cancer (CRC) to date are burdened by poor reliability and low patient adherence and compliance. An altered pattern of volatile organic compounds (VOCs) in exhaled breath has been proposed as a non-invasive potential diagnostic tool for distinguishing CRC patients from healthy controls (HC). The aim of this study was to evaluate the reliability of an innovative portable device containing a micro-gas chromatograph in enabling rapid, on-site CRC diagnosis through analysis of patients' exhaled breath. In this prospective trial, breath samples were collected in a tertiary referral center of colorectal surgery, and analysis of the chromatograms was performed by the Biomedical Engineering Department. The breath of patients with CRC and HC was collected into Tedlar bags through a Nafion filter and mouthpiece with a one-way valve. The breath samples were analyzed by an automated portable gas chromatography device. Relevant volatile biomarkers and discriminant chromatographic peaks were identified through machine learning, linear discriminant analysis and principal component analysis. A total of 68 subjects, 36 patients affected by histologically proven CRC with no evidence of metastases and 32 HC with negative colonoscopies, were enrolled. After testing a training set (18 CRC and 18 HC) and a testing set (18 CRC and 14 HC), an overall specificity of 87.5%, sensitivity of 94.4% and accuracy of 91.2% in identifying CRC patients was found based on three VOCs. Breath biopsy may represent a promising non-invasive method of discriminating CRC patients from HC.