Publication: Screening and discrimination of Hepatocellular carcinoma patients by testing exhaled breath with smart devices using composite polymer/carbon nanotube gas sensors
Issued Date
2017-02-21
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2-s2.0-85015830615
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Mahidol University
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SCOPUS
Bibliographic Citation
BMEiCON 2016 - 9th Biomedical Engineering International Conference. (2017)
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Tanthip Eamsa-Ard, Thara Seesaard, Taya Kitiyakara, Teerakiat Kerdcharoen Screening and discrimination of Hepatocellular carcinoma patients by testing exhaled breath with smart devices using composite polymer/carbon nanotube gas sensors. BMEiCON 2016 - 9th Biomedical Engineering International Conference. (2017). doi:10.1109/BMEiCON.2016.7859609 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/42609
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Screening and discrimination of Hepatocellular carcinoma patients by testing exhaled breath with smart devices using composite polymer/carbon nanotube gas sensors
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Abstract
© 2016 IEEE. There is currently great interest in the medical application of electronic nose and chemical sensors, especially in the area of early diagnosis and screening of diseases. In this study, a pocket electronic nose based on eight nanocomposite gas sensors made of polymer and functionalized single-walled carbon nanotubes (f-SWCNTs) was shown to be capable to discriminate between the two sample groups of hepatocellular carcinoma (HCC) patients and healthy control subjects. Polymer/f-SWCNTs sensor-integrated electronic nose system has been designed and fabricated to be suitable for exhaled breath detection. This chemical gas sensor array has a good sensitivity to a broad range of volatile organic compounds (VOCs), sufficiently to cover the chemical species contained in the human exhaled breath such as acetone, ammonia, methyl-ethyl-ketone, and toluene (excluding water that has negligible impact on sensitivity of the sensors). The obtained results demonstrate that the e-nose has a potential to discriminate the patterns of exhaled breath odor from five healthy controls from five HCC patients, as analyzed by the principal component analysis (PCA) with 95% of the confidence level. In the near future, this approach may become very useful in clinical application to serve as a non-invasive device for screening patients with early-stage liver cancer.