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Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors

机译:通过一系列非选择性气体传感器通过呼吸分析识别肺癌

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Previous finding shown that the composition of the breath of patients with lung cancer contains information that could be used to detect the disease. These volatiles are mainly alkanes and aromatic compounds. Sensor arrays technology (electronic nose) proved to be useful to screen samples characterised by different headspace composition. Here we investigated the possibility of using an electronic nose to check whether volatile compounds present in expired air may diagnose lung cancer. Breath samples were collected and immediately analysed by an electronic nose. A total of 60 individuals were involved in the experiment. 35 of them were affected by lung cancer. 18 individuals were measured as reference and nine were measured after the surgical therapy. Two individuals were measured twice. before and after the surgical therapy, fora total of 62 measurements. An electronic nose, composed by eight quartz microbalance (QMB) gas sensors, coated with different metalloporphyrins, was used. These sensors show a good sensitivity towards those compounds previously indicated as possible lung cancer markers in breath. The application of a 'partial least squares-discriminant analysis' (PLS-DA) found out a 100% of classification of lung cancer affected patients, 94% of reference was correctly classified. The class of post-surgery patients were correctly individuated in 44% of the cases, while the other samples were classified as healthy references. The alteration of breath composition induced by the presence of lung cancer was enough to allow a complete identification of the sample of diseased individuals. Extended studies are necessary to evaluate the resolution of the method, namely the stage at which the disease may be identified in order to use this instrument for early diagnosis. (C) 2003 Elsevier Science B.V. All rights reserved. [References: 21]
机译:先前的发现表明,肺癌患者的呼吸成分包含可用于检测疾病的信息。这些挥发物主要是烷烃和芳族化合物。事实证明,传感器阵列技术(电子鼻)可用于筛选以不同顶空成分为特征的样品。在这里,我们研究了使用电子鼻检查呼出的空气中存在的挥发性化合物是否可以诊断肺癌的可能性。收集呼吸样品并立即通过电子鼻进行分析。共有60个人参与了该实验。其中有35人受到肺癌的影响。手术治疗后测量18个人作为参考,测量9个人。对两个人进行两次测量。手术治疗前后,总共进行62次测量。使用由八个石英微天平(QMB)气体传感器组成的电子鼻,涂有不同的金属卟啉。这些传感器对先前指示为呼吸中可能的肺癌标志物的那些化合物显示出良好的敏感性。 “偏最小二乘判别分析”(PLS-DA)的应用发现,肺癌影响患者的分类为100%,参照分类的正确率为94%。在44%的病例中正确区分了手术后患者的类别,而其他样本被归类为健康参考。肺癌的存在引起的呼吸成分改变足以完全鉴定出患病个体的样本。为了使用该仪器进行早期诊断,必须进行广泛的研究以评估方法的分辨率,即可以确定疾病的阶段。 (C)2003 Elsevier Science B.V.保留所有权利。 [参考:21]

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