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Breath analysis in disease diagnosis: methodological considerations and applications

Lourenco, Celia and Turner, Claire (2014). Breath analysis in disease diagnosis: methodological considerations and applications. Metabolites, 4(2) pp. 465–498.

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URL: http://www.mdpi.com/2218-1989/4/2/465
DOI (Digital Object Identifier) Link: https://doi.org/10.3390/metabo4020465
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Abstract

Breath analysis is a promising field with great potential for non-invasive diagnosis of a number of disease states. Analysis of the concentrations of volatile organic compounds (VOCs) in breath with an acceptable accuracy are assessed by means of using analytical techniques with high sensitivity, accuracy, precision, low response time, and low detection limit, which are desirable characteristics for the detection of VOCs in human breath. “Breath fingerprinting”, indicative of a specific clinical status, relies on the use of multivariate statistics methods with powerful in-built algorithms. The need for standardisation of sample collection and analysis is the main issue concerning breath analysis, blocking the introduction of breath tests into clinical practice. This review describes recent scientific developments in basic research and clinical applications, namely issues concerning sampling and biochemistry, highlighting the diagnostic potential of breath analysis for disease diagnosis. Several considerations that need to be taken into account in breath analysis are documented here, including the growing need for metabolomics to deal with breath profiles.

Item Type: Journal Item
Copyright Holders: 2014 The Authors
Project Funding Details:
Funded Project NameProject IDFunding Body
Proton Transfer reaction mass spectrometry (PIMMS)Not SetEU
Extra Information: This article belongs to the Special Issue Breath Analysis in Metabolomics
Keywords: volatile organic compounds (VOCs); trace gas analysis; volatile biomarkers; metabolomics
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Life, Health and Chemical Sciences
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Innovation, Knowledge & Development research centre (IKD)
Item ID: 40513
Depositing User: Claire Turner
Date Deposited: 09 Jul 2014 13:55
Last Modified: 10 Dec 2018 10:50
URI: http://oro.open.ac.uk/id/eprint/40513
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