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J Thorac Oncol. 2012 Oct;7(10):1528-33.

Non-invasive breath analysis of pulmonary nodules.

Author information

1
Thoracic Cancer Research and Detection Center, Sheba Medical Center, Tel Aviv University, Tel Aviv, Israel.

Abstract

INTRODUCTION:

The search for non-invasive diagnostic methods of lung cancer (LC) has led to new avenues of research, including the exploration of the exhaled breath. Previous studies have shown that LC can, in principle, be detected through exhaled-breath analysis. This study evaluated the potential of exhaled-breath analysis for the distinction of benign and malignant pulmonary nodules (PNs).

METHODS:

Breath samples were taken from 72 patients with PNs in a prospective trial. Profiles of volatile organic compounds were determined by (1) gas chromatography/mass spectrometry (GC-MS) combined with solid-phase microextraction and (2) a chemical nanoarray.

RESULTS:

Fifty-three PNs were malignant and 19 were benign with similar smoking histories and comorbidities. Nodule size (mean ± SD) was 2.7 ± 1.7 versus 1.6 ± 1.3 cm (p = 0.004), respectively. Within the malignant group, 47 were non-small-cell lung cancer and six were small-cell lung cancer. Thirty patients had early-stage disease and 23 had advanced disease. Gas chromatography/mass spectrometry analysis identified a significantly higher concentration of 1-octene in the breath of LC, and the nanoarray distinguished significantly between benign versus malignant PNs (p < 0.0001; accuracy 88 ± 3%), between adeno- and squamous-cell carcinomas [LINE SEPARATOR](p < 0.0001; 88 ± 3%) and between early stage and advanced disease (p < 0.0001; 88 ± 2%).

CONCLUSIONS:

In this pilot study, breath analysis discriminated benign from malignant PNs in a high-risk cohort based on LC-related volatile organic compound profiles. Furthermore, it discriminated adeno- and squamous-cell carcinoma and between early versus advanced disease. Further studies are required to validate this noninvasive approach, using a larger cohort of patients with PNs detected by computed tomography.

PMID:
22929969
PMCID:
PMC3444531
DOI:
10.1097/JTO.0b013e3182637d5f
[Indexed for MEDLINE]
Free PMC Article

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