Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK.
Analyst. 2011 Jan 21;136(2):359-64. doi: 10.1039/c0an00382d. Epub 2010 Oct 22.
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.
先前的研究表明，膀胱癌特有的挥发性化合物可能存在于尿液的顶部空间中，这使得通过顶空分析来诊断膀胱癌成为可能。在本文中，我们评估了一种商业上可用的气体传感器阵列与专门设计的模式识别算法在这方面的应用。使用健康志愿者和膀胱癌患者提供的独立测试数据，我们获得了最佳诊断性能，总体准确率为 70%（敏感性为 70%，特异性为 70%）。当将患有其他非癌性泌尿系统疾病的患者的数据添加到健康对照组的数据中时，分类准确率降至 65%，敏感性为 60%，特异性为 67%。虽然这还不足以作为诊断测试，但它明显优于随机猜测，这使我们得出结论，尿液的顶部空间中存在有用的信息，但如果要充分利用这些信息，则需要更具信息量的分析技术，例如质谱分析。
