School of Engineering, University of Warwick, Coventry CV4 7AL, UK.
Sensors (Basel). 2012 Sep 26;12(10):13002-18. doi: 10.3390/s121013002.
It is well known that the electronic nose can be used to identify differences between human health and disease for a range of disorders. We present a pilot study to investigate if the electronic nose and a newer technology, FAIMS (Field Asymmetric Ion Mobility Spectrometry), can be used to identify and help inform the treatment pathway for patients receiving pelvic radiotherapy, which frequently causes gastrointestinal side-effects, severe in some. From a larger group, 23 radiotherapy patients were selected where half had the highest levels of toxicity and the others the lowest. Stool samples were obtained before and four weeks after radiotherapy and the volatiles and gases emitted analysed by both methods; these chemicals are products of fermentation caused by gut microflora. Principal component analysis of the electronic nose data and wavelet transform followed by Fisher discriminant analysis of FAIMS data indicated that it was possible to separate patients after treatment by their toxicity levels. More interestingly, differences were also identified in their pre-treatment samples. We believe these patterns arise from differences in gut microflora where some combinations of bacteria result to give this olfactory signature. In the future our approach may result in a technique that will help identify patients at "high risk" even before radiation treatment is started.
众所周知，电子鼻可用于识别一系列疾病的人体健康和疾病之间的差异。我们进行了一项初步研究，以调查电子鼻和一种新技术 FAIMS（场非对称离子迁移谱）是否可用于识别并为接受骨盆放射治疗的患者提供治疗途径的信息，这种治疗通常会引起胃肠道副作用，严重的甚至会导致放射性肠炎。我们从一个更大的患者群体中选择了 23 名接受放射治疗的患者，其中一半的毒性水平最高，另一半的毒性水平最低。在放射治疗前和治疗后四周采集粪便样本，并使用两种方法分析挥发物和气体的排放；这些化学物质是肠道微生物群落发酵的产物。电子鼻数据的主成分分析和小波变换，以及 FAIMS 数据的 Fisher 判别分析表明，有可能根据毒性水平对治疗后的患者进行区分。更有趣的是，在他们的治疗前样本中也发现了差异。我们认为这些模式是由肠道微生物群落的差异引起的，某些细菌组合会产生这种嗅觉特征。将来，我们的方法可能会产生一种技术，甚至在开始放射治疗之前就可以帮助识别“高风险”患者。
