Application of Autofluorescence Imaging On Clinical Oral Cancer Screening

Abstract

In recent years many research teams of autofluorescence had revealed that the autofluorescence intensity of tumor region is different from normal region and some research results can be used in oral screening as well This method is non-invasive and it only needs to get the autofluorescence image/signal of tissue without touching it thus so patient will not feel any pain Therefore helping doctors effectively discover cancerous cells by using fluorescence spectroscopy to obtain spectral characteristics or using imaging technology to observe the changing intensity of fluorescence imaging is target of many research teams Autofluorescence is generated by tissue matrix or fluorophores in living cells During the period of a tumor developing the structure of tissue and metabolism will be changed In this study we are concerned with two fluorescent metabolites Nicotinamide adenine dinucleotide (NADH) and Flavin adenine dinucleotide (FAD) and its Redox ratio NADH / (NADH +FAD) as our biomarker to indicate the metabolism of tissues We developed a device to observe the autofluorescence; the device was installed with the LEDs as light source to excite NADH/FAD autofluorescence and one CCD camera covered by band-pass filters to separate the autofluorescence from excitation light To prove the device can be applied in cancer detection we have done an animal trial We injected cancer cell line into the right buccal mucosa of the hamsters and used the device to observe the tumor growing for a period of time The result of this trial reveals that redox ratio and its heterogeneity is significant in distinguishing the tumor/normal cell For this reason we make the device of animal trial smaller to using in human clinical trial which has two wavelengths of LEDs as an exaction light source and one CCD camera with two filters to get the suitable autofluorescence ? In this study we use our device to get clinical data from the Dentistry of National Cheng Kung University Hospital which include the biopsy confirmed oral cancer squamous cell carcinoma (SCC) and leukoplakia as the experimental group some healthy people are chosen as the control group We analyze the intensity and the heterogeneity of autofluorescence image and its redox ratio and use quadratic discriminant analysis (QDA) classifier to classify data The result shows that it has a good sensitivity and specificity in cancer detection

Date of Award	2014 Aug 20
Original language	English
Supervisor	Pau-Choo Chung (Supervisor)