scholarly journals The Use of Breath Analysis for Diagnosing COVID-19: Opportunities, Challenges, and Considerations for Future Pandemic Responses

Author(s):  
Mustafa Abumeeiz ◽  
Lauren Elliott ◽  
Phillip Olla

Abstract Due to the COVID-19 pandemic, there is currently a need for accurate, rapid, and easy-to-administer diagnostic tools to help communities manage local outbreaks and assess the spread of disease. The use of Artificial Intelligence within the domain of breath analysis techniques has shown to have potential in diagnosing a variety of diseases such as cancer and lung disease by analyzing volatile organic compounds (VOCs) in exhaled breath. This combined with their rapid, easy-to-use, and non-invasive nature makes them a good candidate for use in diagnosing COVID-19 in large scale public health operations. However, there remains issues with their implementation when it comes to the infrastructure currently available to support their use on a broad scale. This includes issues of standardization, and whether or not a characteristic VOC pattern can be identified for COVID-19. Despite these difficulties, breathalysers offer potential to assist in pandemic responses and their use should be investigated.

Biosensors ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 55 ◽  
Author(s):  
Tiele ◽  
Wicaksono ◽  
Kansara ◽  
Arasaradnam ◽  
Covington

Early diagnosis of inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), remains a clinical challenge with current tests being invasive and costly. The analysis of volatile organic compounds (VOCs) in exhaled breath and biomarkers in stool (faecal calprotectin (FCP)) show increasing potential as non-invasive diagnostic tools. The aim of this pilot study is to evaluate the efficacy of breath analysis and determine if FCP can be used as an additional non-invasive parameter to supplement breath results, for the diagnosis of IBD. Thirty-nine subjects were recruited (14 CD, 16 UC, 9 controls). Breath samples were analysed using an in-house built electronic nose (Wolf eNose) and commercial gas chromatograph–ion mobility spectrometer (G.A.S. BreathSpec GC-IMS). Both technologies could consistently separate IBD and controls [AUC ± 95%, sensitivity, specificity], eNose: [0.81, 0.67, 0.89]; GC-IMS: [0.93, 0.87, 0.89]. Furthermore, we could separate CD from UC, eNose: [0.88, 0.71, 0.88]; GC-IMS: [0.71, 0.86, 0.62]. Including FCP did not improve distinction between CD vs UC; eNose: [0.74, 1.00, 0.56], but rather, improved separation of CD vs controls and UC vs controls; eNose: [0.77, 0.55, 1.00] and [0.72, 0.89, 0.67] without FCP, [0.81, 0.73, 0.78] and [0.90, 1.00, 0.78] with FCP, respectively. These results confirm the utility of breath analysis to distinguish between IBD-related diagnostic groups. FCP does not add significant diagnostic value to breath analysis within this study.


2021 ◽  
Author(s):  
Rianne de Vries ◽  
René M. Vigeveno ◽  
Simone Mulder ◽  
Niloufar Farzan ◽  
Demi R. Vintges ◽  
...  

AbstractBackgroundRapid and accurate detection of SARS-CoV-2 infected individuals is crucial for taking timely measures and minimizing the risk of further SARS-CoV-2 spread. We aimed to assess the accuracy of exhaled breath analysis by electronic nose (eNose) for the discrimination between individuals with and without a SARS-CoV-2 infection.MethodsThis was a prospective real-world study of individuals presenting to public test facility for SARS-CoV-2 detection by molecular amplification tests (TMA or RT-PCR). After sampling of a combined throat/nasopharyngeal swab, breath profiles were obtained using a cloud-connected eNose. Data-analysis involved advanced signal processing and statistics based on independent t-tests followed by linear discriminant and ROC analysis. Data from the training set were tested in a validation, a replication and an asymptomatic set.FindingsFor the analysis 4510 individuals were available. In the training set (35 individuals with; 869 without SARS-CoV-2), the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.947 (CI:0.928-0.967). These results were confirmed in the validation set (0.957; CI:0.942-0.971, n=904) and externally validated in the replication set (0.937; CI:0.926-0.947, n=1948) and the asymptomatic set (0.909; CI:0.879-0.938, n=754). Selecting a cut-off value of 0.30 in the training set resulted in a sensitivity/specificity of 100/78, >99/84, 98/82% in the validation, replication and asymptomatic set, respectively.InterpretationeNose represents a quick and non-invasive method to reliably rule out SARS-CoV-2 infection in public health test facilities and can be used as a screening test to define who needs an additional confirmation test.FundingMinistry of Health, Welfare and SportResearch in contextEvidence before this studyElectronic nose technology is an emerging diagnostic tool for diagnosis and phenotyping of a wide variety of diseases, including inflammatory respiratory diseases, lung cancer, and infections.As of Feb 13, 2021, our search of PubMed using keywords “COVID-19” OR “SARS-CoV-2” AND “eNose” OR “electronic nose” OR “exhaled breath analysis” yielded 4 articles (1-4) that have assessed test characteristics of electronic nose to diagnose COVID-19. In these small studies the obtained signals using sensor-based technologies, two-dimensional gas chromatography and time-of-flight mass spectrometry, or proton transfer reaction time-of-flight mass spectrometry, provided adequate discrimination between patients with and without COVID-19.Added value of this studyWe prospectively studied the accuracy of exhaled breath analysis by electronic nose (eNose) to diagnose or rule out a SARS-CoV-2 infection in individuals with and without symptoms presenting to a public test facility. In the training set with 904 individuals, the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.948. In three independent validation cohorts of 3606 individuals in total, eNose was able to reliably rule out SARS-CoV-2 infection in 70-75% of individuals, with a sensitivity ranging between 98-100%, and a specificity between 78-84%. No association was found between cycle thresholds values, as semi-quantitative measure of viral load, and eNose variables.Implications of all the available evidenceThe available findings, including those from our study, support the use of eNose technology to distinguish between individuals with and without a SARS-CoV-2 infection with high accuracy. Exhaled breath analysis by eNose represents a quick and non-invasive method to reliably rule out a SARS-CoV-2 infection in public health test facilities. The results can be made available within seconds and can therefore be used as screening instrument. The eNose can reliably rule out a SARS-CoV-2 infection, eliminating the need for additional time-consuming, stressful, and expensive diagnostic tests in the majority of individuals.


2021 ◽  
Vol 11 ◽  
Author(s):  
Yoon Ju Jung ◽  
Ho Seok Seo ◽  
Ji Hyun Kim ◽  
Kyo Young Song ◽  
Cho Hyun Park ◽  
...  

BackgroundScreening endoscopy is considered to be the most accurate tool for early detection of gastric cancer, but it is both invasive and costly. It is therefore essential to develop cost-effective and non-invasive diagnostic tools for gastric cancer. The aim of this study is to investigate the presence of certain volatile organic compounds (VOCs) associated with gastric cancer and to survey the usefulness of VOCs as screening tools of gastric cancer.MethodsThe present study was conducted prospectively to identify the relationship between gastric cancer and specific VOCs quantified by mass spectrometry. Exhaled breath samples from a total of 43 participants were analysed. This study was approved by the Institutional Review Board of the College of Medicine, Catholic University of Korea (KC16TISI0598), and registered to clinical research information service (KCT0004356).ResultsNine VOCs differed significantly between the control and cancer patient groups. When participants were divided into control, early gastric cancer (EGC), and advanced gastric cancer (AGC) groups, seven VOCs remained significantly different. Of these, four (propanal, aceticamide, isoprene and 1,3 propanediol) showed gradual increases as cancer advanced, from normal control to EGC to AGC. In receiver operating characteristic curves for these four VOCs, the area under the curve for gastric cancer prediction was highest (0.842) when more than two VOCs were present.ConclusionsThe present study offers potential directions for non-invasive gastric cancer screening, and may inspire advanced diagnostic technologies in the era of smart home healthcare. However, despite the high accuracy, cancer-specific VOCs from several studies on different populations, and analytic methods show inconsistency, it is necessary to establish standards for each analytical method, and to validate on each population.


Metabolites ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 317
Author(s):  
Michalis Koureas ◽  
Paraskevi Kirgou ◽  
Grigoris Amoutzias ◽  
Christos Hadjichristodoulou ◽  
Konstantinos Gourgoulianis ◽  
...  

The aim of the present study was to investigate the ability of breath analysis to distinguish lung cancer (LC) patients from patients with other respiratory diseases and healthy people. The population sample consisted of 51 patients with confirmed LC, 38 patients with pathological computed tomography (CT) findings not diagnosed with LC, and 53 healthy controls. The concentrations of 19 volatile organic compounds (VOCs) were quantified in the exhaled breath of study participants by solid phase microextraction (SPME) of the VOCs and subsequent gas chromatography-mass spectrometry (GC-MS) analysis. Kruskal–Wallis and Mann–Whitney tests were used to identify significant differences between subgroups. Machine learning methods were used to determine the discriminant power of the method. Several compounds were found to differ significantly between LC patients and healthy controls. Strong associations were identified for 2-propanol, 1-propanol, toluene, ethylbenzene, and styrene (p-values < 0.001–0.006). These associations remained significant when ambient air concentrations were subtracted from breath concentrations. VOC levels were found to be affected by ambient air concentrations and a few by smoking status. The random forest machine learning algorithm achieved a correct classification of patients of 88.5% (area under the curve—AUC 0.94). However, none of the methods used achieved adequate discrimination between LC patients and patients with abnormal computed tomography (CT) findings. Biomarker sets, consisting mainly of the exogenous monoaromatic compounds and 1- and 2- propanol, adequately discriminated LC patients from healthy controls. The breath concentrations of these compounds may reflect the alterations in patient’s physiological and biochemical status and perhaps can be used as probes for the investigation of these statuses or normalization of patient-related factors in breath analysis.


2019 ◽  
Vol 8 (11) ◽  
pp. 1783 ◽  
Author(s):  
Valentina Agnese Ferraro ◽  
Stefania Zanconato ◽  
Eugenio Baraldi ◽  
Silvia Carraro

Background: In the context of the so-called unified airway theory, chronic rhinosinusitis (CRS) and asthma may coexist. The inflammation underlying these conditions can be studied through the aid of biomarkers. Main body: We described the main biological mediators that have been studied in pediatric CRS and asthma, and, according to the available literature, we reported their potential role in the diagnosis and management of these conditions. As for CRS, we discussed the studies that investigated nasal nitric oxide (nNO), pendrin, and periostin. As for asthma, we discussed the role of fractional exhaled nitric oxide (feNO), the role of periostin, and that of biological mediators measured in exhaled breath condensate (EBC) and exhaled air (volatile organic compounds, VOCs). Conclusion: Among non-invasive biomarkers, nNO seems the most informative in CRS and feNO in asthma. Other biological mediators seem promising, but further studies are needed before they can be applied in clinical practice.


Biosensors ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 476
Author(s):  
Kaushiki Dixit ◽  
Somayeh Fardindoost ◽  
Adithya Ravishankara ◽  
Nishat Tasnim ◽  
Mina Hoorfar

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.


2017 ◽  
Vol 9 (15) ◽  
pp. 2342-2350 ◽  
Author(s):  
Samin Hamidi ◽  
Maryam Khoubnasabjafari ◽  
Khalil Ansarin ◽  
Vahid Jouyban-Gharamaleki ◽  
Abolghasem Jouyban

Breath analysis is a potential and non-invasive tool for monitoring drugs levels and the status of respiratory or systemic disorders and attracted more attentions in recent years.


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