New Detection Method Of Lung Cancer Gas Marker Based On Colormetric Sensor Array

Recent years, lung cancer is the most common tumor in worldwide, and theincidence of mortality rates is the first one in all of the tumors. It’s a great threat tohuman life and health. But lung cancer is often insidious onset. It was always too late todiagnose, and lost the best time for treatment. The earlier the diagnosis is confirmed thehigher the cure success rate will be. To overcome this problem, there has beendeveloped a variety of modes for diagnosis, such as imaging tests, bronchial endoscopy,as well as the identification of a variety of lung cancer markers. But All of them couldnot meet the diagnostic needs in timeliness, economy, flexibility. They all rely on somelarge instrument in order to complete the analysis, it is difficult to use as a universalscreening techniques. The development of sensitive material sensing detection forvolatile organic compounds, give us a new way for diagnosing lung disease. In order toachieve the prediction of disease diagnosis we could capture the particular gas markerexhaled by patients with lung cancer using the sensing element. Rely on this technology,we designed and constructed a lung cancer gas marker identification system. Researcheswere carried out as follows:①Build up a device which could detect and recognize lung cancer gas markerquickly and conveniently. It contains the design of gas path, the signal acquisition modeof data and the choice of analyze approaches.②Screen, prepare three kinds16species lung cancer gas markers samples. Alkylhydrocarbon includes n-butane, n-pentane, n-heptane, decane and undecane. Benzeneand its derivatives includes benzene, anisole, styrene, cumene, p-xylene, and1,2,4-trimethylbenzene. Alkenes and aldehydes includes hexanal,1-hexene, heptanal,1-heptene and isoprene. All the markers were prepared in four concentration levels, theconcentration level from10^-6（ppm）-10^-9（ppb）, providing the lung cancer gas markerssamples for test.③Use the identification system to detect16kinds lung cancer gas markers. Getall the fingerprint data of four concentration levels of various markers. From the visionrecognition effect, the substance with different concentration sample could beenclassified very well. Analyse the interaction mechanisms of the molecular markers andthe array chip. Using cluster analysis method to identify the substances in differentconcentrations sample, the results showed that the sample in different concentrations could be distinguished significantly, and the samples in similar concentrations couldcluster in later stage. According to16kinds of lung cancer （ppb） gas markers samplefingerprint, distinguish the dates well respectively from the method of principalcomponent analysis and cluster analysis. Reflected the superiority of our detectionsystem for the lung cancer gas markers in low concentration.