期刊
CHEMOSENSORS
卷 9, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/chemosensors9080209
关键词
exhaled breath; MOS sensors; VOCs
资金
- European Institute of Oncology (Milan, Italy)
Breath analysis can be used for early detection of lung cancer and improving survival rates. This study utilized an electronic nose for automatic exhaled breath analysis, achieving recall and precision rates of 78% to 80% through a classification model combining gas sensor features and clinical features.
Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis.
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