1. Evaluation of gas chromatography mass spectrometry and pattern recognition for the identification of bladder cancer from urine headspace
- Author
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Lezlie E. Britton, Conrad Bessant, Carolyn M. Willis, P. B. Spratt, Geraint Morgan, Michael Cauchi, Bruce J. Bolt, C. M. Weber, D. C. Turner, and Claire Turner
- Subjects
0301 basic medicine ,Bladder cancer ,Chemistry ,business.industry ,General Chemical Engineering ,010401 analytical chemistry ,General Engineering ,Cancer ,Pattern recognition ,Urine ,medicine.disease ,01 natural sciences ,0104 chemical sciences ,Analytical Chemistry ,03 medical and health sciences ,030104 developmental biology ,Healthy volunteers ,medicine ,Artificial intelligence ,Gas chromatography–mass spectrometry ,business - Abstract
Previous studies have indicated that volatile organic compounds specific to bladder cancer may exist in urine headspace, raising the possibility that they may be of diagnostic value for this particular cancer. To further examine this hypothesis, urine samples were collected from patients diagnosed with either bladder cancer or a non‐cancerous urological disease/infection, and from healthy volunteers, from which the volatile metabolomes were analysed using gas chromatography mass spectrometry. The acquired data were subjected to a specifically designed pattern recognition algorithm, involving cross‐model validation. The best diagnostic performance, achieved with independent test data provided by healthy volunteers and bladder cancer patients, was 89% overall accuracy (90% sensitivity and 88% specificity). Permutation tests showed that these were statistically significant, providing further evidence of the potential for volatile biomarkers to form the basis of a non‐invasive diagnostic technique.
- Published
- 2016
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