Joint analysis of differential mobility spectrometer and mass spectrometer features for tuberculosis biomarkers

Cunha, Meredith G.; Hoenigman, Shirley; Kanchagar, Chitra; Rearden, Preshious; Sassetti, Christopher S.; Trevejo, José; Keshava, Nirmal

doi:10.1109/iembs.2008.4649164

Cited by 2 publications

(1 citation statement)

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“…Another issue that would strength the utility of EB research in disease diagnose is the improvement of data fusion possibilities, developing tools to allow the merging of data obtained from different EB analysis approaches. Regarding this, Cunha et al identified putative biomarkers for tuberculosis exploiting a data collection system that uses a differential mobility spectrometer (DMS) in parallel with a MS. With this approach, they could use synergistically the statistical tools previously developed for DMS in MS chemical identification [ 274 ]. Nevertheless, more research is required to allow merger of data obtained using the state of art approaches (GC-MS and PTR-MS, for instance) with the more recent POC e-noses technologies.…”

Section: Data Analysis and Discriminatory Models Used In Breath Bimentioning

confidence: 99%

Breath Analysis as a Potential and Non-Invasive Frontier in Disease Diagnosis: An Overview

et al. 2015

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Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.

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Section: Data Analysis and Discriminatory Models Used In Breath Bimentioning

confidence: 99%