0000000000595521
AUTHOR
Yoav Y. Broza
showing 6 related works from this author
Screening for gastric cancer using exhaled breath samples.
2019
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 …
Geographical variation in the exhaled volatile organic compounds.
2013
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…
Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules.
2016
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.…
A nanomaterial-based breath test for distinguishing gastric cancer from benign gastric conditions
2013
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.
2018
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…
Sensing gastric cancer via point‐of‐care sensor breath analyzer
2021
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…