Breath Analysis of Lung Cancer Patients Using an Electronic Nose Detection System

• Published in: IEEE sensors journal Vol. 10; no. 9; pp. 1514 - 1518
• Main Authors: Tran, Vanessa H, Hiang Ping Chan, Thurston, Michelle, Jackson, Paul, Lewis, Craig, Yates, Deborah, Bell, Graham, Thomas, Paul S
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2010; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cancer detection; Diseases; Electronic nose; Electronic noses; Gas detectors; Hospitals; Lung cancer; Lungs; Medical diagnostic imaging; Oncology; Sensor arrays; Volatile organic compounds
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2009.2038356

Background. The measurement of gaseous compounds in exhaled breath, such as volatile organic compounds (VOCs), may provide a noninvasive technique for assessing lung pathology, some of which are associated with lung cancer (LC). VOC analysis is laborious while electronic noses are emerging as rapid detectors of an array of gaseous markers recognizing a characteristic "smellprint." Objectives. To conduct a pilot breath analysis using an electronic nose to test the hypothesis that there would be significant differences in the smellprint patterns between newly diagnosed LC patients and control subjects. Methods. Eighty-nine subjects were recruited, consisting of nonsmokers (33), ex-smokers (11), smokers (18), patients with respiratory disorders (11), and LC patients (16). Subjects exhaled into gas-impermeable bags for offline eNose measurements with a six-channel electronic detection module ENS Mk 3 (E-Nose Pty, Sydney). The time-response curve from each channel was evaluated for four parameters: rate to peak height, peak height, rate to recovery, and area under the curve. Results. The results showed significant differences between lung cancer and control groups when measuring peak height in channel 1 (p = 0.025); rate to recovery in channel 3 (p = 0.045); and rate to peak height in channel 3 (p = 0.001). Conclusion. The results show promise in that there were significant differences in the smellprint of subjects with lung cancer compared with control subjects. Further standardization of the technique will assist in improving the sensitivity and specificity of the method, with potential to use the analysis in a number of diseases where characteristic signatures occur in the breath.