Citation:
Christina M. Weber, Michael Cauchi, Mitesh Patel, Conrad Bessant, Claire Turner, Lezlie E. Britton
and Carolyn M. Willis, Evaluation of a gas sensor array and pattern recognition for the identification
of bladder cancer from urine headspace, Analyst, Volume 136, Issue 2, 2011, Pages 359-364.
Abstract:
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.
