
Oral Epithelial Dysplasia: A Narrative Review on Histological Grading, Computer-aided Diagnostics and Treatment Approaches
ZE01-ZE07
Correspondence
Taibur Rahman,
Ph.D. Scholar, Department of Mathematical and Computational Sciences Division, Institute of Advanced Study in Science and Technology, Guwahati-781036, Assam, India.
E-mail: taiburat8@gmail.com
Head and Neck (H&N) cancer represents a significant global health burden, ranking sixth among all cancer types worldwide, with a particularly high prevalence in developing countries. Oral cancer, a subset of H&N cancer, encompasses malignant growths within the oral cavity region. Oral Epithelial Dysplasia (OED) serves as a precursor lesion to oral cancer and is identifiable through histological examination by pathologists. While histological grading correlates with progression cancer risk, accurately predicting lesion advancement remains challenging due to limited research and study. Despite established grading criteria based on architectural and cytological changes in the oral cavity histological images, variability exists among pathologists in assessing OED presence and grade. The present article explores OED as a precancerous lesion, delving into various histological grading systems based on architectural and cytological changes. Additionally, it examines the role of Computer-aided Diagnostics (CAD) leveraging Artificial Intelligence (AI) in OED detection. Lastly, the paper discusses treatment modalities for oral cavity cancers.