| Title: | Recognizing lung cancer and stages using a self-developed electronic nose system |
| Author(s): | Chen K; Liu L; Nie B; Lu B; Fu L; He Z; Li W; Pi X; Liu H; |
| Address: | "Key Laboratory of Biotechnology Science and Technology, Ministry of Education, College of Bioengineering,Chongqing University, Chongqing, PR China; The First Affiliated Hospital of Xinxiang Medical College, Henan, PR China. Electronic address: chenkewys@163.com. Key Laboratory of Biotechnology Science and Technology, Ministry of Education, College of Bioengineering,Chongqing University, Chongqing, PR China. Electronic address: liu_lei@cqu.edu.cn. Key Laboratory of Biotechnology Science and Technology, Ministry of Education, College of Bioengineering,Chongqing University, Chongqing, PR China. Electronic address: 20165686@cqu.edu.cn. Chongqing University-University of Cincinnati Joint Co-op Institute, Chongqing University, Chongqing, PR China. Electronic address: lubu@mail.uc.edu. Chongqing University-University of Cincinnati Joint Co-op Institute, Chongqing University, Chongqing, PR China. Electronic address: fuln@mail.uc.edu. Chongqing Red Cross Hospital, Chongqing, PR China. Electronic address: 1762419487@qq.com. School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, PR China. Electronic address: wang.l@cqut.edu.cn. Key Laboratory of Biotechnology Science and Technology, Ministry of Education, College of Bioengineering,Chongqing University, Chongqing, PR China. Electronic address: pixitian@cqu.edu.cn. Key Laboratory of Biotechnology Science and Technology, Ministry of Education, College of Bioengineering,Chongqing University, Chongqing, PR China. Electronic address: liuhongying@cqu.edu.cn" |
| DOI: | 10.1016/j.compbiomed.2021.104294 |
| ISSN/ISBN: | 1879-0534 (Electronic) 0010-4825 (Linking) |
| Abstract: | "Exhaled breath contains thousands of gaseous volatile organic compounds (VOCs) that could be used as non-invasive biomarkers of lung cancer. Breath-based lung cancer screening has attracted wide attention on account of its convenience, low cost and easy popularization. In this paper, the research of lung cancer detection and staging is conducted by the self-developed electronic nose (e-nose) system. In order to investigate the performance of the device in distinguishing lung cancer patients from healthy controls, two feature extraction methods and two different classification models were adopted. Among all the models, kernel principal component analysis (KPCA) combined with extreme gradient boosting (XGBoost) achieved the best results among 235 breath samples. The accuracy, sensitivity and specificity of e-nose system were 93.59%, 95.60% and 91.09%, respectively. Meanwhile, the device could innovatively classify stages of 90 lung cancer patients (i.e., 44 stage III and 46 stage IV). Experimental results indicated that the recognition accuracy of lung cancer stages was more than 80%. Further experiments of this research also showed that the combination of sensor array and pattern recognition algorithms could identify and distinguish the expiratory characteristics of lung cancer, smoking and other respiratory diseases" |
| Keywords: | Breath Tests Early Detection of Cancer *Electronic Nose Exhalation Humans *Lung Neoplasms/diagnosis Electronic nose Extreme gradient boosting Kernel principal component analysis Lung cancer Volatile organic compounds; |
| Notes: | "MedlineChen, Ke Liu, Lei Nie, Bo Lu, Binchun Fu, Lidan He, Zichun Li, Wang Pi, Xitian Liu, Hongying eng Research Support, Non-U.S. Gov't 2021/03/02 Comput Biol Med. 2021 Apr; 131:104294. doi: 10.1016/j.compbiomed.2021.104294. Epub 2021 Feb 23" |
