A flexible electronic nose for odor discrimination using different methods of classification

Ovarian cancer is one of the leading causes of death from cancer in women. The lifetime risk is around 1.5%, which makes it the second most common gynecologic malignancy (the first one being breast cancer). To have a definitive diagnose, a surgical procedure is generally required and suspicious areas (samples) will be removed and sent for microscopic and other analysis. This paper describes the result of a pilot study in which an electronic nose is used to ldquosmellrdquo the aforementioned samples, analyze the multi-sensor signals and have a close to real-time answer on the detection of cancer. Besides being fast, the detection method is inexpensive and simple. Experimental analysis using real ovarian carcinoma samples shows that the use of proper algorithms for analysis of the multi-sensor data from the electronic nose yielded surprisingly good results with more than 77% classification rate. The electronic nose used in this pilot study was originally developed to be used as a ldquobomb dogrdquo and can distinguish between e.g. TNT, Dynamex, Prillit. However, it was constructed to be a flexible multi-sensor device and the individual (16) sensors can easily be replaced/exchanged. This is suggestive for further investigations to obtain even better results with new, specific sensors. In another pilot experiment, headspace of an ovarian carcinoma sample and a control sample were analyzed using gas chromatography-mass spectrometry. Significant differences in chemical composition and compound levels were recorded, which would explain the different response obtained with the electronic nose.