RESUMEN
Background: Owing to the restricted predictive value of conventional prognostic factors and the inconsistent treatment strategies, several oral squamous cell carcinoma (OSCC) patients are still over-treated or under-treated. In recent years, computer-assisted nuclear fractal dimension (nFD) has emerged as an objective approach to predict the outcome of OSCC. Objective: This study is an attempt to find out the differences in nFD values of epithelial cells of normal tissue, fibroepithelial hyperplasia, verrucous carcinoma, and OSCC. Further effort to evaluate the predictive potential of nFD of tumor cells for cervical lymph node metastasis (cLNM) was also assessed. Methodology: Formalin-fixed paraffin-embedded blocks of OSCC tissues of patients treated with neck dissection were collected. Photomicrographs of H-&E-stained sections were subjected to the image analysis by ImageJ and Python programming to calculate nFD. The association of categorical variables with nFD was studied using cross-tabulation procedure and the Fisher exact test. Receiver operating curve analysis was performed to find out cutoff value of nFD. A logistic regression model was developed to test the individual and combined predictive potential of grading and nFD for cLNM. Results: A significant difference between the mean nFD of healthy cells and malignant epithelial cells was observed (P = 0.01). nFD was not found to be an independent predictor of cLNM, although nFD and grading together demonstrated significant predictive potential (P = 0.004). Conclusion: nFD combined with grading can predict lymph node metastasis in OSCC. To the best of our knowledge, this is the first study of its kind.
RESUMEN
BACKGROUND: Various clinical and histological factors have helped in predicting the survival of patients with oral squamous cell carcinoma (OSCC). However, there has been a need for more specialized diagnostic and prognostic factors to avoid subjective variation among opinion. Thus, fractal dimension (FD) can be used as an index of the morphological changes that the epithelial cells undergo during their transformation into neoplastic cell. In oral cancer study, nuclear FD (NFD) can be used as a quantitative index to discriminate between normal, dysplastic and neoplastic oral mucosa. AIM: To use nuclear fractal geometry to compare the morphometric complexity in the normal, epithelial dysplasia and OSCC cases and to verify the difference among the various histological grades of dysplasia and OSCC. It was fulfilled by estimating the FDs of the nuclear surface. MATERIALS AND METHODS: Histopathologically diagnosed cases of epithelial dysplasia and OSCC were taken from the archives. Photomicrographs were captured with the help of Lawrence and Mayo research microscope. The images were then subjected to image analysis using the Image J software with FracLac plugin java 1.6 to obtain FDs. FD of ten selected nuclei was calculated using the box-counting algorithm. STATISTICAL ANALYSIS: was done using descriptive analysis, ANOVA and Tukey's honest significant difference post hoc tests with STATAIC-13 software. RESULTS AND CONCLUSION: NFD can provide valuable information to discriminate between normal mucosa, dysplasia and carcinoma objectively without subjective discrimination.