Electronic Nose For Breast Cancer Diagnosis And Application

Breast cancer is one of the most common human malignancies, and also is one of the major women malignancies. The incidence of breast cancer increased year by year, and the early diagnosis and treatment of breast cancer would significantly improve the five-year survival rate. Traditional diagnosis methods of breast cancer generally adopt X-ray scanning and live organization examination, the diagnosis procedure is relatively complex and long, which is adverse for early breast cancer diagnosis and treatment. In this project, we carried out the research for the diagnosis of the breast cancer based on electronic nose. The method is simple and easy to implement, and the research is helpful for the early diagnosis and treatment of breast cancer.From the point of view of breast cancer pathology, this paper first verifies the feasibility of medical electronic nose system. Then we introduce the state of the art of medical electronic nose systems, and medical electronic nose signal preprocessing methods and pattern recognition methods. After that, we explore the the application advantange of electronic nose based lossless diagnosis methods for the respiratory gas diagnosisAccording to the previous research of the respiratory diagnosis of breast cancer, combined with the pathology principle of breast cancer, we choose nonane, iso-Propyl alcohol, 1-phenyl-Ethanone, heptanal and isopropyl myristate as the volatile symbol of electronic nose based breast cancer respiratory diagnosis. We focused on the volatile symbol of breast cancer respiratory diagnosis to conduct researches and surveys. At last, we selected six metal oxide gas sensors, an electrochemical sensor, and temperature, humidity and pressure sensors to build a breast cancer diagnosis electronic nose system.Because of the low density of the volatile symbol of breast cancer respiratory diagnosis (ppt level), it is required that the sensors of electronic nose of breast cancer diagnosis can provide low LoD(Limit of Detection). However, under current technique condition, normal gas sensors can not achieve this requirement. And the above gas sensor arrays are unable to diagnose the respiratory of patient' respiratory gas. This paper describes the study of the gas concentration, and constructs a solid adsorption, thermal desorption gas concentration system, which is based on the international stardand and the consideration of the implementation of precise temperature control and throughput control. Finally, we conducted the test of the volatile symbol of breast cancer respiratory diagnosis based on the constructed breast cancer electronic nose system. In addition, we utilized the BP artificial neural network and RBF network to perform qualitative reorganization.Experiments had good effect, which verified the sensitive capacity of the system for the volatile symbol of breast cancer respiratory diagnosis.