Evaluation of a gas sensor array and pattern recognition for the identification of bladder cancer from urine headspace

Previous studies have indicated that volatile compounds specific to bladder cancer may exist in urine headspace, raising the possibility that headspace analysis could be used for diagnosis of this particular cancer. In this paper, we evaluate the use of a commercially available gas sensor array coupled with a specifically designed pattern recognition algorithm for this purpose. The best diagnostic performance that we were able to obtain with independent test data provided by healthy volunteers and bladder cancer patients was 70% overall accuracy (70% sensitivity and 70% specificity). When the data of patients suffering from other non-cancerous urological diseases were added to those of the healthy controls, the classification accuracy fell to 65% with 60% sensitivity and 67% specificity. While this is not sufficient for a diagnostic test, it is significantly better than random chance, leading us to conclude that there is useful information in the urine headspace but that a more informative analytical technique, such as mass spectrometry, is required if this is to be exploited fully.