Electronic Nose Analysis of Exhaled Breath Volatiles to Identify Lung Cancer Cases: A Systematic Review

Emerging trends in metal oxide-based electronic noses for healthcare applications: a review

An electronic nose (E-nose) is a technology fundamentally inspired by the human nose, designed to detect, recognize, and differentiate specific odors or volatile components in complex and chaotic environments. Comprising an array of sensors with meticulously designed nanostructured architectures, E-noses translate the chemical information captured by these sensors into useful metrics using complex pattern recognition algorithms. E-noses can significantly enhance the quality of life by offering preventive point-of-care devices for medical diagnostics through breath analysis, and by monitoring and tracking hazardous and toxic gases in the environment. They are increasingly being used in defense and surveillance, medical diagnostics, agriculture, environmental monitoring, and product validation and authentication. The major challenge in developing a reliable E-nose involves miniaturization and low power consumption. Various sensing materials are employed to address these issues. This review presents the key advancements over the last decade in E-nose technology, specifically focusing on chemiresistive metal oxide sensing materials. It discusses their sensing mechanisms, integration into portable E-noses, and various data analysis techniques. Additionally, we review the primary metal oxide-based E-noses for disease detection through breath analysis. Finally, we address the major challenges and issues in developing and implementing a portable metal oxide-based E-nose.

Use of Sensor Array Analysis to Detect Ovarian Cancer through Breath, Urine, and Blood: A Case-Control Study

Ovarian cancer (OC) is the eighth most common cancer in women. Since screening programs do not exist, it is often diagnosed in advanced stages. Today, the detection of OC is based on clinical examination, transvaginal ultrasound (US), and serum biomarker (Carbohydrate Antigen 125 (CA 125) and Human Epididymis Protein 4 (HE4)) dosage, with a sensitivity of 88% and 95%, respectively, and a specificity of 84% for US and 76% for biomarkers. These methods are clearly not enough, and OC in its early stages is often missed. Many scientists have recently focused their attention on volatile organic compounds (VOCs). These are gaseous molecules, found in the breath, that could provide interesting information on several diseases, including solid tumors. To detect VOCs, an electronic nose was invented by a group of researchers. A similar device, the e-tongue, was later created to detect specific molecules in liquids. For the first time in the literature, we investigated the potential use of the electronic nose and the electronic tongue to detect ovarian cancer not just from breath but also from urine, blood, and plasma samples.

Volatile Organic Compounds Analysis as a Potential Novel Screening Tool for Breast Cancer: A Systematic Review

Introduction

An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells.

Methods

The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines.

Results

Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods.

Discussion

Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.

Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose

Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to identify Covid-19 patients. Given the scale of the pandemic, however, animal deployment is a challenging solution. In contrast, electronic noses (eNoses) are machines aimed at mimicking animal olfaction, and these can be deployed at scale. To test the hypothesis that SARS CoV-2 infection is associated with a body-odor detectable by an eNose, we placed a generic eNose in-line at a drive-through testing station. We applied a deep learning classifier to the eNose measurements, and achieved real-time detection of SARS CoV-2 infection at a level significantly better than chance, for both symptomatic and non-symptomatic participants. This proof of concept with a generic eNose implies that an optimized eNose may allow effective real-time diagnosis, which would provide for extensive relief in the Covid-19 pandemic.

Detection of Ovarian Cancer through Exhaled Breath by Electronic Nose: A Prospective Study

BACKGROUND

Diagnostic methods for the early identification of ovarian cancer (OC) represent an unmet clinical need, as no reliable diagnostic tools are available. Here, we tested the feasibility of electronic nose (e-nose), composed of ten metal oxide semiconductor (MOS) sensors, as a diagnostic tool for OC detection.

METHODS

Women with suspected ovarian masses and healthy subjects had volatile organic compounds analysis of the exhaled breath using e-nose.

RESULTS

E-nose analysis was performed on breath samples collected from 251 women divided into three groups: 86 OC cases, 51 benign masses, and 114 controls. Data collected were analyzed by Principal Component Analysis (PCA) and K-Nearest Neighbors' algorithm (K-NN). A first 1-K-NN (cases vs. controls) model has been developed to discriminate between OC cases and controls; the model performance tested in the prediction gave 98% of sensitivity and 95% of specificity, when the strict class prediction was applied; a second 1-K-NN (cases vs. controls + benign) model was built by grouping the non-cancer groups (controls + benign), thus considering two classes, cases and controls + benign; the model performance in the prediction was of 89% for sensitivity and 86% for specificity when the strict class prediction was applied.

CONCLUSIONS

Our preliminary results suggested the potential role of e-nose for the detection of OC. Further studies aiming to test the potential adoption of e-nose in the early diagnosis of OC are needed.

Electronic Nose as a Novel Method for Diagnosing Cancer: A Systematic Review

Cancer is fast becoming the most important cause of death worldwide, its mortality being mostly caused by late or wrong diagnosis. Novel strategies have been developed to identify early signs of cancer in a minimally obtrusive way, including the Electronic Nose (E-Nose) technology, user-friendly, cost- and time-saving alternative to classical approaches. This systematic review, conducted under the PRISMA guidelines, identified 60 articles directly dealing with the E-Nose application in cancer research published up to 31 January 2020. Among these works, the vast majority reported successful E-Nose use for diagnosing Lung Cancer, showing promising results especially when employing the Aeonose tool, discriminating subjects with Lung Cancer from controls in more than 80% of individuals, in most studies. In order to tailor the main limitations of the proposed approach, including the application of the protocol to advanced stage of cancer, sample heterogeneity and massive confounders, future studies should be conducted on early stage patients, and on larger cohorts, as to better characterize the specific breathprint associated with the various subtypes of cancer. This would ultimately lead to a better and faster diagnosis and to earlier treatment, possibly reducing the burden associated to such conditions.