期刊
SENSORS
卷 17, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/s17020287
关键词
lung cancer; volatile organic compounds (VOCs); exhaled air; screening; gas chromatography-mass spectrometry analysis; support vector machine (SVM)
资金
- Knowledge Hub Aichi (the priority research project) of Aichi Prefecture and Special Research Aid of the President of Aichi Prefectural University, Japan [P3-G3-S1]
Monitoring exhaled breath is a very attractive, noninvasive screening technique for early diagnosis of diseases, especially lung cancer. However, the technique provides insufficient accuracy because the exhaled air has many crucial volatile organic compounds (VOCs) at very low concentrations (ppb level). We analyzed the breath exhaled by lung cancer patients and healthy subjects (controls) using gas chromatography/mass spectrometry (GC/MS), and performed a subsequent statistical analysis to diagnose lung cancer based on the combination of multiple lung cancer-related VOCs. We detected 68 VOCs as marker species using GC/MS analysis. We reduced the number of VOCs and used support vector machine (SVM) algorithm to classify the samples. We observed that a combination of five VOCs (CHN, methanol, CH3CN, isoprene, 1-propanol) is sufficient for 89.0% screening accuracy, and hence, it can be used for the design and development of a desktop GC-sensor analysis system for lung cancer.
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