We investigate the possibility of using ALA-derived PpIX fluorescence spectroscopy for the detection of epithelial hyperkeratosis (EH) or epithelial dysplasia (ED) lesions in oral submucous fibrosis (OSF) patients that could not be found by autofluorescence spectroscopy. Twenty percent of ALA solution gel was applied onto oral neoplasia and surrounding normal tissue [normal oral mucosa (NOM)] for 90 min. Fluorescence emission spectra were measured under 410 nm excitation. Generally, the most intense fluorescence emission peaks occurred at 460 and 630 nm. The ratios of the area under red peak (630±10 nm) to the area under blue peak (460±10 nm), denoted as R/B, were calculated. We found that OSF mucosa has the lowest R/B value, followed by NOM, EH on OSF, and ED on OSF. An ANOVA test showed significant differences between OSF, NOM, EH on OSF, and ED on OSF (p<0.05). However, measurements of autofluorescence (i.e., before ALA application) show no significant differences between OSF, NOM, EH on OSF, and ED on OSF (ANOVA test, p>0.05). These results indicate that ALA-induced PpIX fluorescence spectroscopy could be used to identify the premalignant lesions on oral fibrotic mucosa, which could not be found by autofluorescence.
An in vivo study of human oral cancer diagnosis by using autofluorescence spectroscopy is presented. A Xenon-lamp with a motor-controlled monochromator was adopted as the excitation light source. We chose the excitation wavelength of 330 nm, and the spectral measurement range was from 340 nm to 601 nm. A Y-type fiber bundle was used to guide the excitation light, and collect the autofluorescence of samples. The emitted light was detected by a motor-controlled monochromator and a PMT. After measurement, the measured sites were sectioned and sent for histological examination. In total 15 normal sites, 30 OSF (oral submucosa fibrosis) sites, 26 EH (epithelial hyperkratosis) sites, 13 ED (epithelial dysplasia) sites, and 13 SCC (squamous cell carcinoma) sites were measured. The discriminant algorithm was established by partial-least squares (PLS) method with cross-validation technique. By extracting the first two t-scores of each sample and make scattering plot, we found that the samples of different cancerous stages were in grouped distinct locations, except that samples of ED and EH were mixed together. It means that this algorithm can be used to classify normal, premalignant, and malignant tissues. We conclude that autofluorescence spectroscopy may be useful for in vivo detection of early stage oral cancer.
A study on in vivo measurement of autofluorescence spectra for hamster buccal pouch and development of oral carcinogenesis identification algorithm is presented. The measurement was preceded with a fiber-optics based fluorescence spectroscopy system. In total 75 samples, including 14 hyperkratosis, 23 normal, 28 dysplasia, and 10 SCC, were separated into 4 categories. All the spectra were normalized to have the same area below the spectrum curve. The results show that the autofluorescence spectra start to change as soon as the tissues have morphological alternation (eg hyperkratosis). The differences of ratios between the areas under 380+/- 15 nm and 460+/- 15 nm (denoted as A380+/- 15/ A460+/- 15) among categories are statistically significant. To develop a diagnostic algorithm for early neoplasia detection and evaluate its performance, a PLS discriminant analysis with cross-validation technique was proceeded. Sample points on the PLS score plot were grouped as four categories. By selecting suitable threshold, the accuracy rates for classifying 4 categories of samples are 86% (hyperkratosis), 87% (normal), 90% (dysplasia), and 100% (SCC), respectively. The results reveal that the autofluorescence spectroscopy technique is potential for in vivo detection of early neoplasia of oral tissues.
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