Using Fluorescence Spectroscopy to Distinguish Precancerous Mucosa

Malignant tumor has remained the number one leading cause of death in recent years. The main types of cancers include colorectal cancer, oral cancer, and cervical cancer that originates from the mucosa and are difficult to diagnose. Recently, many research teams have been working on the application of biomedical spectroscopy for the diagnosis of precancerous mucosa. The objective of this study is the development of a standard fluorescent spectroscopy calibration process for a movable image spectrograph system, including the calibration of shape and relative intensity as well as calibration by liquid phantoms. In this study, there are the comparison of two different calibration methods and the results of phantom experiments. The phantom experiments, which include liquid phantoms and two-layer phantoms, are to validate the performance of the system and the accuracy of the Monte Carlo algorithm. The compositions of phantoms are polystyrene microspheres, hemoglobin and fluorophores. In addition, we measured fluorescence spectra of normal buccal mucosa to quantify the fluorescence efficiencies of the autofluorescence molecules. In the results, the root-mean-square percentage errors (RMSPE) of absolute fluorescence between calibrated spectra and Monte Carlo simulation of the liquid phantom ranges from 9% to 14%. This proves that this method can calibrate measured spectra and quantify the efficiencies of fluorescence using the Monte Carlo algorithm. The RMSPE of calibrated spectra of calibration of shape and relative intensity and calibration by liquid phantoms ranges from 10% to 22%. The RMSPE of absolute fluorescence between calibrated spectra and Monte Carlo simulation of the two-layer phantoms ranges from 11% to 48%. According to the optical parameters of normal, benign inflammation, and dysplasia tissue, six two-layer phantoms were designed. In the results, there is a difference of peak-shift direction between two-layer phantoms of benign inflammation and dysplasia tissue in 400 to 420 nm. This difference may be a key point for distinguishing between benign inflammation and dysplasia tissue. When we measured the buccal mucosal fluorescence spectra of normal volunteers, we measured diffuse reflectance spectra simultaneously. We extracted scattering parameters and absorption parameters of tissue by iterative curve fitting tool with inverse Monte Carlo model. We inputted the extracted optical parameters to the Monte Carlo forward model to quantify the fluorescence efficiencies of NADH and collagen. We proved the probability of quantifying the fluorescence efficiency by Monte Carlo algorithm.