Exhaled breath analysis for lung cancer detection using ion mobility spectrometry
- Background: Conventional methods for lung cancer detection including computed tomography (CT) and bronchoscopy are expensive and invasive. Thus, there is still a need for an optimal lung cancer detection technique. Methods: The exhaled breath of 50 patients with lung cancer histologically proven by bronchoscopic biopsy samples (32 adenocarcinomas, 10 squamous cell carcinomas, 8 small cell carcinomas), were analyzed using ion mobility spectrometry (IMS) and compared with 39 healthy volunteers. As a secondary assessment, we compared adenocarcinoma patients with and without epidermal growth factor receptor (EGFR) mutation. Results: A decision tree algorithm could separate patients with lung cancer including adenocarcinoma, squamous cell carcinoma and small cell carcinoma. One hundred-fifteen separated volatile organic compound (VOC) peaks were analyzed. Peak-2 noted as n-Dodecane using the IMS database was able to separate values with a sensitivity of 70.0% and a specificity of 89.7%. Incorporating a decision tree algorithm starting with n-Dodecane, a sensitivity of 76% and specificity of 100% was achieved. Comparing VOC peaks between adenocarcinoma and healthy subjects, n-Dodecane was able to separate values with a sensitivity of 81.3% and a specificity of 89.7%. Fourteen patients positive for EGFR mutation displayed a significantly higher n-Dodecane than for the 14 patients negative for EGFR (p<0.01), with a sensitivity of 85.7% and a specificity of 78.6%. Conclusion: In this prospective study, VOC peak patterns using a decision tree algorithm were useful in the detection of lung cancer. Moreover, n-Dodecane analysis from adenocarcinoma patients might be useful to discriminate the EGFR mutation.
Author of HS Reutlingen | Baumbach, Jörg Ingo |
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URN: | urn:nbn:de:bsz:rt2-opus4-85 |
DOI: | https://doi.org/10.1371/journal.pone.0114555 |
eISSN: | 1932-6203 |
Erschienen in: | PLOS ONE |
Publisher: | PLOS |
Place of publication: | Lawrence, Kanada |
Document Type: | Journal article |
Language: | English |
Publication year: | 2014 |
Tag: | computed tomography; ion mobility spectroscopy |
Volume: | 9 |
Issue: | 12 |
Page Number: | 13 |
First Page: | 1 |
Last Page: | 13 |
DDC classes: | 610 Medizin, Gesundheit |
Open access?: | Ja |
Licence (German): | Creative Commons - Namensnennung |