Abstract
Most oral injuries are diagnosed by histopathological analysis of a biopsy, which is an invasive procedure and does not give immediate results. On the other hand, Raman spectroscopy is a real time and minimally invasive analytical tool with potential for the diagnosis of diseases. The potential for diagnostics can be improved by data post-processing. Hence, this study aims to evaluate the performance of preprocessing steps and multivariate analysis methods for the classification of normal tissues and pathological oral lesion spectra. A total of 80 spectra acquired from normal and abnormal tissues using optical fiber Raman-based spectroscopy (OFRS) were subjected to PCA preprocessing in the z-scored data set, and the KNN (K-nearest neighbors), J48 (unpruned C4.5 decision tree), RBF (radial basis function), RF (random forest), and MLP (multilayer perceptron) classifiers at WEKA software (Waikato environment for knowledge analysis), after area normalization or maximum intensity normalization. Our results suggest the best classification was achieved by using maximum intensity normalization followed by MLP. Based on these results, software for automated analysis can be generated and validated using larger data sets. This would aid quick comprehension of spectroscopic data and easy diagnosis by medical practitioners in clinical settings.
Highlights
Optical biopsy refers to techniques where the light-tissue interaction is analyzed and information regarding the pathological state of the tissue is obtained, either in vivo or ex vivo
Et al [1] have described many molecular interactions and features in cells and tissues that cannot be assessed by conventional histopathology, but can be probed by optical techniques
Unlike the conventional histopathology, which is based on morphological changes; optical spectroscopy use biochemical information and can be used to obtain early and differential diagnosis of multiple lesions [2,3,4,5,6,7,8,9]
Summary
Optical biopsy refers to techniques where the light-tissue interaction is analyzed and information regarding the pathological state of the tissue is obtained, either in vivo or ex vivo. Many researches are exploring the use of Raman spectroscopy as an in vivo tool [10,11,12,13], to help pathologists get an early and reliable diagnosis for therapeutic decision making. This technique can be used as a tool for monitoring the type and stages of pathological processes. This procedure will assist pathologists in the diagnosis, optimizing the surgical procedure by the involved health professional [14,15,16,17]
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