Non-Invasive Method for Tuberculosis Exhaled Breath Classification Using Electronic Nose

2021 ◽  
pp. 1-1
Author(s):  
Hendrick Hendrick ◽  
Rahmat Hidayat ◽  
Gwo-Jiun Horng ◽  
Zhi-Hao Wang
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.


Nutrients ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1636 ◽  
Author(s):  
Aahana Shrestha ◽  
Utpal K. Prodhan ◽  
Sarah M. Mitchell ◽  
Pankaja Sharma ◽  
Matthew P.G. Barnett ◽  
...  

Hydrogen (H2) measurement in exhaled breath is a reliable and non-invasive method to diagnose carbohydrate malabsorption. Currently, breath H2 measurement is typically limited to clinic-based equipment. A portable breath analyser (AIRE, FoodMarble Digestive Health Limited, Dublin, Ireland) is a personalised device marketed for the detection and self-management of food intolerances, including lactose malabsorption (LM). Currently, the validity of this device for breath H2 analysis is unknown. Individuals self-reporting dairy intolerance (six males and six females) undertook a lactose challenge and a further seven individuals (all females) underwent a milk challenge. Breath samples were collected prior to and at frequent intervals post-challenge for up to 5 h with analysis using both the AIRE and a calibrated breath hydrogen analyser (BreathTracker, QuinTron Instrument Company Inc., Milwaukee, WI, USA). A significant positive correlation (p < 0.001, r > 0.8) was demonstrated between AIRE and BreathTracker H2 values, after both lactose and milk challenges, although 26% of the AIRE readings demonstrated the maximum score of 10.0 AU. Based on our data, the cut-off value for LM diagnosis (25 ppm H2) using AIRE is 3.0 AU and it is effective for the identification of a response to lactose-containing foods in individuals experiencing LM, although its upper limit is only 81 ppm.


Biosensors ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 171 ◽  
Author(s):  
Simone Scarlata ◽  
Panaiotis Finamore ◽  
Martina Meszaros ◽  
Silvano Dragonieri ◽  
Andras Bikov

Chronic obstructive pulmonary disease (COPD) is a common progressive disorder of the respiratory system which is currently the third leading cause of death worldwide. Exhaled breath analysis is a non-invasive method to study lung diseases, and electronic noses have been extensively used in breath research. Studies with electronic noses have proved that the pattern of exhaled volatile organic compounds is different in COPD. More recent investigations have reported that electronic noses could potentially distinguish different endotypes (i.e., neutrophilic vs. eosinophilic) and are able to detect microorganisms in the airways responsible for exacerbations. This article will review the published literature on electronic noses and COPD and help in identifying methodological, physiological, and disease-related factors which could affect the results.


2016 ◽  
Vol 3 (2) ◽  
pp. 357-364 ◽  
Author(s):  
Sabrina Gschwind ◽  
Halshka Graczyk ◽  
Detlef Günther ◽  
Michael Riediker

Analysis of exhaled breath condensate (EBC) represents a non-invasive method for detecting inhaled nanoparticles (NPs) associated with various occupational and environmental exposures.


2020 ◽  
Vol 21 (24) ◽  
pp. 9416
Author(s):  
Johann-Christoph Licht ◽  
Hartmut Grasemann

Respiratory tract infections are common, and when affecting the lower airways and lungs, can result in significant morbidity and mortality. There is an unfilled need for simple, non-invasive tools that can be used to screen for such infections at the clinical point of care. The electronic nose (eNose) is a novel technology that detects volatile organic compounds (VOCs). Early studies have shown that certain diseases and infections can result in characteristic changes in VOC profiles in the exhaled breath. This review summarizes current knowledge on breath analysis by the electronic nose and its potential for the detection of respiratory diseases with and without infection.


2020 ◽  
Vol 311 ◽  
pp. 127932 ◽  
Author(s):  
Tarik Saidi ◽  
Mohammed Moufid ◽  
Kelvin de Jesus Beleño-Saenz ◽  
Tesfalem Geremariam Welearegay ◽  
Nezha El Bari ◽  
...  

2019 ◽  
Vol 8 (2) ◽  
pp. 460-469
Author(s):  
Aliza Aini Md Ralib ◽  
Nik Nursyahida Bt Nik Mohd Zamri ◽  
Ahmad Hafiz Faqruddin Hazadi ◽  
Rosminazuin Ab Rahim ◽  
Nor Farahidah Za’bah ◽  
...  

The increasing global trends in healthcare priorities towards improving the effectiveness of diagnostic procedure by utilizing a non-invasive method which is breath analysis. This will benefit in increasing treatment efficiency and also reducing healthcare costs. Breath is a simple technique where the sample are easily obtained and can be provided immediately. The most popular method that had been used in hospital are urine and blood. Contradict with breath, urine and blood take too much time to analyse the disease and a painful process. The detection technique of breath analysis is done by using electroacoustic wave sensor from piezoelectric substrate. This acoustic wave sensor has been used to detect the changes in the frequency where it will be used to detect the disease. Breath analysis is a technique where it uses an electronic nose (E-nose) as a device. E-nose consist of Quartz Crystal Microbalance (QCM) sensor in order to differentiate odor in human breath. QCM is a sensitive weighing device which have a high efficiency. AT-cut quartz was chosen as the piezoelectric material and aluminum as the electrode. The objective of this paper is to design and simulate a QCM sensor for breath analysis application. Other than that, it also to determine the important key parameters that influence the performance of breath analysis which is sensitivity and resonant frequency. QCM sensor is being simulate by using COMSOL Multiphysics software. This is to evaluate the behavior of QCM sensor in terms of Eigen frequency analysis. The simulated QCM sensor with quartz radius of 166 um resonates at 8.871 MHz. The sensitivity of the sensor is 0.167 MHz/ng after exposed to acetone gas which act as the breath marker for detection of diseases in exhaled breath. Hence, the proposed design can be used as a non-invasive approach for early detection of disease through breath analysis.


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