Profiles of Volatile Biomarkers Detect Tuberculosis from Skin

Abstract Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource‐limited settings. According to the World Health Organization (WHO), a rapid, sputum‐free, and cost‐effective triage test for real‐time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB‐specific volatile organic compounds (VOCs) that are …

Breath testing: the future for digestive cancer detection.

Ex vivo emission of volatile organic compounds from gastric cancer and non-cancerous tissue

The presence of certain volatile organic compounds (VOCs) in the breath of patients with gastric cancer has been reported by a number of research groups; however, the source of these compounds remains controversial. Comparison of VOCs emitted from gastric cancer tissue to those emitted from non-cancerous tissue would help in understanding which of the VOCs are associated with gastric cancer and provide a deeper knowledge on their generation. Gas chromatography with mass spectrometric detection (GC-MS) coupled with head-space needle trap extraction (HS-NTE) as the pre-concentration technique, was used to identify and quantify VOCs released by gastric cancer and non-cancerous tissue samples c…

Screening for gastric cancer using exhaled breath samples.

Abstract Background The aim was to derive a breath-based classifier for gastric cancer using a nanomaterial-based sensor array, and to validate it in a large screening population. Methods A new training algorithm for the diagnosis of gastric cancer was derived from previous breath samples from patients with gastric cancer and healthy controls in a clinical setting, and validated in a blinded manner in a screening population. Results The training algorithm was derived using breath samples from 99 patients with gastric cancer and 342 healthy controls, and validated in a population of 726 people. The calculated training set algorithm had 82 per cent sensitivity, 78 per cent specificity and 79 …

Ultrasensitive Silicon Nanowire for Real-World Gas Sensing: Noninvasive Diagnosis of Cancer from Breath Volatolome

We report on an ultrasensitive, molecularly modified silicon nanowire field effect transistor that brings together the lock-and-key and cross-reactive sensing worlds for the diagnosis of (gastric) cancer from exhaled volatolome. The sensor is able to selectively detect volatile organic compounds (VOCs) that are linked with gastric cancer conditions in exhaled breath and to discriminate them from environmental VOCs that exist in exhaled breath samples but do not relate to the gastric cancer per se. Using breath samples collected from actual patients with gastric cancer and from volunteers who do not have cancer, blind analysis validated the ability of the reported sensor to discriminate betw…

Constructing Interpretable Classifiers to Diagnose Gastric Cancer Based on Breath Tests

Quick, inexpensive and accurate diagnosis of gastric cancer is a necessity, but at this moment the available methods do not hold up. One of the most promising possibilities is breath test analysis, which is quick, relatively inexpensive and comfortable to the person tested. However, this method has not yet been well explored. Therefore in this article the authors propose using transparent classification models to explain diagnostic patterns and knowledge, which is acquired in the process. The models are induced using decision tree classification algorithms and RIPPER algorithm for decision rule induction. The accuracy of these models is compared to neural network accuracy.

Repeatability Study on a Classifier for Gastric Cancer Detection from Breath Sensor Data

The SNIFFPHONE device is a portable multichannel gas sensor, aiming to detect gastric cancer (GC) from breath samples. It employs gold nanoparticle (GNP) sensors reacting to volatile organic compounds (VOCs) in the exhaled breath, a non-invasive technique to support early diagnosis. This study evaluates the repeatability of the SNIFFPHONE classification result for measurements conducted on healthy subjects over a short period of time of less than 10 minutes. Due to the portable nature of the device, repeatability is studied with respect to varying measurement location. We find the classification results repeatable with a statistically significant 81 % Pearson correlation coefficient, even t…

How do international gastric cancer prevention guidelines influence clinical practice globally?

Clinical guidelines recommend particular approaches, including 'screen-and-treat' strategy for Helicobacter pylori, to prevent gastric cancer. However, little of this is implemented in clinical practice. The aim of the study was to identify barriers to implementation of international guidelines. A web-based questionnaire distributed globally to specialists in the field. Altogether 886 responses from 75 countries were received. Of the responders, 570 (64%) were men of mean age 47 years. There were 606 gastroenterologists and 65 epidemiologists among the responders. Altogether, 79.8% of the responders disagreed that the burden of gastric cancer is a diminishing problem. 'Screen-and-treat' str…

Overview on SNIFFPHONE:A portable device for disease diagnosis

We present SNIFFPHONE, a handy and easy-To-use device that allows the non-invasive detection of gastric diseases. It analyzes the user's exhaled breath using specifically developed gas sensors. The device is coupled to a smartphone, which governs the breath analysis process, sends the data measurements to an external data analysis server, and finally gives feedback to the user. In this work, we describe the SNIFFPHONE device and the general platform under development.

Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection

Background: Gastric cancer is one of the deadliest malignant diseases, and the non-invasive screening and diagnostics options for it are limited. In this article, we present a multi-modular device for breath analysis coupled with a machine learning approach for the detection of cancer-specific breath from the shapes of sensor response curves (taxonomies of clusters). Methods: We analyzed the breaths of 54 gastric cancer patients and 85 control group participants. The analysis was carried out using a breath analyzer with gold nanoparticle and metal oxide sensors. The response of the sensors was analyzed on the basis of the curve shapes and other features commonly used for comparison. These f…

Non-contact breath sampling for sensor-based breath analysis

Breath analysis holds great promise for real-time and non-invasive medical diagnosis. Thus, there is a considerable need for simple-in-use and portable analyzers for rapid detection of breath indicators for different diseases in their early stages. Sensor technology meets all of these demands. However, miniaturized breath analyzers require adequate breath sampling methods. In this context, we propose non-contact sampling; namely the collection of breath samples by exhalation from a distance into a miniaturized collector without bringing the mouth into direct contact with the analyzing device. To evaluate this approach different breathing maneuvers have been tested in a real-time regime on a…

Geographical variation in the exhaled volatile organic compounds.

Breath-gas analysis has demonstrated that concentration profiles of volatile organic compounds (VOCs) could be used for detecting a variety of diseases, among them gastric cancer (GC) and peptic ulcer disease (PUD). Here, we explore how geographical variation affects the disease-specific changes in the chemical composition of breath samples, as compared to control states (less severe gastric conditions). Alveolar exhaled breath samples from 260 patients were collected at two remotely different geographic locations (China and Latvia), following similar breath-collection protocols. Each cohort included 130 patients that were matched in terms of diagnosis (37 GC/32 PUD/61 controls), average ag…

Detection of cancer through exhaled breath: a systematic review

// Agne Krilaviciute 1 , Jonathan Alexander Heiss 1 , Marcis Leja 2 , Juozas Kupcinskas 3 , Hossam Haick 4 and Hermann Brenner 1,5,6 1 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany 2 Faculty of Medicine, University of Latvia, Digestive Diseases Center GASTRO, and Riga East University Hospital, Riga, Latvia 3 Department of Gastroenterology, Lithuanian University of Health Sciences, Kaunas, Lithuania 4 Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion – Israel Institute of Technology, Haifa, Israel 5 Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany…

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules.

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined.…

Breath testing as potential colorectal cancer screening tool

Although colorectal cancer (CRC) screening is included in organized programs of many countries worldwide, there is still a place for better screening tools. In this study, 418 breath samples were collected from 65 patients with CRC, 22 with advanced or nonadvanced adenomas, and 122 control cases. All patients, including the controls, had undergone colonoscopy. The samples were analysed with two different techniques. The first technique relied on gas chromatography coupled with mass spectrometry (GC-MS) for identification and quantification of volatile organic compounds (VOCs). The T-test was used to identify significant VOCs (p values < 0.017). The second technique relied on sensor analysis…

Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath

Two of the biggest challenges in medicine today are the need to detect diseases in a noninvasive manner and to differentiate between patients using a single diagnostic tool. The current study targets these two challenges by developing a molecularly modified silicon nanowire field effect transistor (SiNW FET) and showing its use in the detection and classification of many disease breathprints (lung cancer, gastric cancer, asthma, and chronic obstructive pulmonary disease). The fabricated SiNW FETs are characterized and optimized based on a training set that correlate their sensitivity and selectivity toward volatile organic compounds (VOCs) linked with the various disease breathprints. The b…

Analysis of the effects of microbiome-related confounding factors on the reproducibility of the volatolomic test.

Volatile organic compound (VOC) testing in breath has potential in gastric cancer (GC) detection. Our objective was to assess the reproducibility of VOCs in GC, and the effects of conditions modifying gut microbiome on the test results. Ten patients with GC were sampled for VOC over three consecutive days; 17 patients were sampled before and after H. pylori eradication therapy combined with a yeast probiotic; 61 patients were sampled before and after bowel cleansing (interventions affecting the microbiome). The samples were analyzed by: (1) gas chromatography linked to mass spectrometry (GC-MS), applying the non-parametric Wilcoxon test (level of significance p    0.05); (2) by cross-reacti…

Sensing gastric cancer via point‐of‐care sensor breath analyzer

Background Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. Methods A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant an…

A nanomaterial-based breath test for distinguishing gastric cancer from benign gastric conditions

Background: Upper digestive endoscopy with biopsy and histopathological evaluation of the biopsy material is the standard method for diagnosing gastric cancer (GC). However, this procedure may not be widely available for screening in the developing world, whereas in developed countries endoscopy is frequently used without major clinical gain. There is a high demand for a simple and non-invasive test for selecting the individuals at increased risk that should undergo the endoscopic examination. Here, we studied the feasibility of a nanomaterial-based breath test for identifying GC among patients with gastric complaints. Methods: Alveolar exhaled breath samples from 130 patients with gastric …

Associations of diet and lifestyle factors with common volatile organic compounds in exhaled breath of average-risk individuals.

Background Detection of diseases via exhaled breath remains an attractive idea despite persisting gaps in understanding the origin of volatile organic compounds (VOCs) and their relationship with the disease of interest. Data on factors potentially influencing the results of breath analysis remain rather sparse and often controversial. In this study, we aimed to investigate the associations of common VOCs in exhaled breath of average-risk individuals with socio-demographic and lifestyle factors, medical conditions as well as diet. Methods Alveolar breath samples of 1447 men and women were collected in the morning after fasting and were analyzed using gas-chromatography linked with mass-spec…

Detection of precancerous gastric lesions and gastric cancer through exhaled breath.

Timely detection of gastric cancer (GC) and the related precancerous lesions could provide a tool for decreasing both cancer mortality and incidence.968 breath samples were collected from 484 patients (including 99 with GC) for two different analyses. The first sample was analysed by gas chromatography linked to mass spectrometry (GCMS) while applying t test with multiple corrections (p value0.017); the second by cross-reactive nanoarrays combined with pattern recognition. For the latter, 70% of the samples were randomly selected and used in the training set while the remaining 30% constituted the validation set. The operative link on gastric intestinal metaplasia (OLGIM) assessment staging…