A Study Of E-nose On Breath Detection And Its Clinical Application On Lung Cancer Diagnosis

Lung cancer is one of the most deadly diseases and the leading cause of cancer death in both men and women. The high mortality in patients with lung cancer results, in part, from the lack of effective tools to diagnose the disease at an early stage before it has spread to regional nodes or has metastasized beyond the lung. To our knowledge the electronic nose combined with a diagnosis model which based on the biomarkers can provide a non-invasive and more convenient method. In this dissertation we proposed a novel e-nose based on a kind of virtual array of surface acoustic wave (SAW) gas sensors and an imaging recognition method to diagnose lung cancer.The main research content of this work:1) The breath diagnosis method for lung cancerA. The specific volatile organic compounds (VOCs) exhaled by lung cancer cells in the microenvironment are the source biomarkers of lung cancer and also serve as direct evidence that the diagnosis of lung cancer by breath is possible. An innovative pathologic analysis method of lung cancer and the early diagnosis of lung cancer at the cellular level were introduced for this purpose.B. Head-Space solid-phase microextraction combined with gas chromatography (HSSPME-GC) is used as the detection system to determine the VOCs in the culture medium of several target cells, including different kinds of lung cancer cells, bronchial epithelial cells, tastebud cells, osteogenic cells, and lipocytes. As a result, each kind of cells has a unique chromatogram. There are 4 special VOCs that were found existing in all culture mediums of lung cancer cells, which are the metabolic products of lung cancer cells and can be viewed as markers of lung cancer. Compared with the retention time of standard component, one is Isoprene, one is Decane and another is Undecane. In the range of 1.6min~3.6min there are several VOCs, which the normal cells don't have, can be the markers to distinguish different cancer cells. Using the results we discussed the generation mechanism model of VOCs.C. 47 volunteers' breath samples were collected and detected by HSSPME-GC. The statistic result of sensitivity and specificity was used to determine the diagnosis model. Each combination of the diagnosis biomarkers were evaluated by analyzing the diagnosis accuracy using receiver operating characteristic (ROC) curve which was based on the same range of diagnosis cut-off point. After compared with the character VOCs in lung cancer cells' culture medium, the Decane and Undecance combination was chosen as the diagnosis model and it got 80% sensitivity and 70% specificity, the area under the ROC curve was almost 0.8.2) The electronic nose for breath detection of lung cancerA. A delay-line surface acoustic wave mass-temperature sensor was studied and designed. The central frequency is 120MHz and the sensing area is 0.5mm*0.5mm. Its sensitivity to mass change can reach 1KHz/ng and to temperature can reach 9KHz/℃. A mass sensitive gas detector was made by using a pair of this sensor. A PID temperature feed-back system was developed to control the working temperature of the detector. The accuracy reached to±0.02℃. Thus made the baseline noise smaller than 40Hz. B. An e-nose combined capillary column separation technology and sensor technique was developed. A breath diagnosis model of lung cancer was embedded into the e-nose's software. The circuit of the e-nose was calibrated by standard methods and the calibration components Decane and Undecane were also detected by the e-nose at the range of 10ng~2000ng and 4.5ng~400ng, respectively. The sensitivity is 12Hz/ng and 27Hz/ng, respectively. The limit of detection (LOD) is 10ng and 4.5ng, respectively.C. Studied the clinical application of the e-nose. Using the e-nose to detect lung cancer patients and the controls, compared the results with that of Tenxa-TA thermal desorption GC-FID system.a) The difference of pre-concentration of breath can lead to different detection results. There is only undecane appearing in both detections. 80 volunteers' breath samples (40 of healthy persons and 40 of lung cancer patients) were detected by Tenxa-TA thermal desorption GC-FID system. The retention time of 10.870 (Undecane), 17.867, 20.881, 21.809 and 24.331 can be regarded as the biomarker components.b) The e-nose detected 10 volunteers' breath samples (5 of healthy persons and 5 of lung cancer patients). The 5 components can be detected by e-nose only the retention time has a little different (-1.3 seconds). It's because the little difference of capillary column in the two systems.This research is significant for the understanding of cancerization process and will produce a relatively noninvasive tool effective in diagnosing lung cancer at an early and potentially curable stage. These breath biomarkers may eliminate the need for additional and often more invasive diagnostic tests that are costly, incur risk, and prolong the diagnostic evaluation of people with suspicion of lung cancer and can provide public health benefit by saving lives.