Fractal dimensions in oral squamous cell carcinoma: A novel diagnostic paradigm

Abstract

Fractal dimension analysis is a novel computational method that quantifies the intricacy and irregularity of structures, and has demonstrated potential in numerous medical applications, such as the analysis of cancerous tissues. Our study investigated the utility of fractal dimension analysis in differentiating normal mucosa from oral squamous cell carcinoma (OSCC). We used a retrospective methodology to analyse the histopathological data of 50 OSCC cases and 25 healthy oral mucosa samples, which were sourced from the obtained data. A statistically significant difference (p < 0.05) was observed in the mean fractal dimension between OSCC and normal mucosa samples, indicating the existence of distinct structural complexities associated with malignant transformation. Fractal dimension analysis offers valuable insights into intricate spatial arrangements and irregularities within tissue structures, which may not be readily apparent through conventional histopathological assessment alone. The higher fractal dimension values observed in OSCC tissues suggest the presence of fractal-like patterns indicative of self-similarity and complexity, which may be associated with tumour aggressiveness and progression. In conclusion, our study suggests the use of fractal analysis as a diagnostic tool for oral carcinoma. Furthermore, the combination of fractal image analysis and artificial intelligence may facilitate automated diagnosis of oral squamous cell carcinoma.