Format

Send to

Choose Destination
Lung Cancer. 2012 Mar;75(3):326-31. doi: 10.1016/j.lungcan.2011.08.009. Epub 2011 Sep 15.

An electronic nose distinguishes exhaled breath of patients with Malignant Pleural Mesothelioma from controls.

Author information

1
Department of Respiratory Diseases, University of Bari, Bari, Italy. sdragonieri@hotmail.com

Abstract

BACKGROUND:

Malignant Pleural Mesothelioma (MPM) is a tumour of the surface cells of the pleura that is highly aggressive and mainly caused by asbestos exposure. Electronic noses capture the spectrum of exhaled volatile organic compounds (VOCs) providing a composite biomarker profile (breathprint).

OBJECTIVE:

We tested the hypothesis that an electronic nose can discriminate exhaled air of patients with MPM from subjects with a similar long-term professional exposure to asbestos without MPM and from healthy controls.

METHODS:

13 patients with a histology confirmed diagnosis of MPM (age 60.9±12.2 year), 13 subjects with certified, long-term professional asbestos exposure (age 67.2±9.8), and 13 healthy subjects without asbestos exposure (age 52.2±16.2) participated in a cross-sectional study. Exhaled breath was collected by a previously described method and sampled by an electronic nose (Cyranose 320). Breathprints were analyzed by canonical discriminant analysis on principal component reduction. Cross-validated accuracy (CVA) was calculated.

RESULTS:

Breathprints from patients with MPM were separated from subjects with asbestos exposure (CVA: 80.8%, sensitivity 92.3%, specificity 85.7%). MPM was also distinguished from healthy controls (CVA: 84.6%). Repeated measurements confirmed these results.

CONCLUSIONS:

Molecular pattern recognition of exhaled breath can correctly distinguish patients with MPM from subjects with similar occupational asbestos exposure without MPM and from healthy controls. This suggests that breathprints obtained by electronic nose have diagnostic potential for MPM.

PMID:
21924516
DOI:
10.1016/j.lungcan.2011.08.009
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center