Development and validation of an artificial intelligence-based pipeline for predicting oral epithelial dysplasia malignant transformation

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Shephard, Adam J. ; Mahmood, Hanya ; Raza, Shan E. Ahmed ; Araujo, Anna Luiza Damaceno ; Santos-Silva, Alan Roger ; Lopes, Marcio Ajudarte ; Vargas, Pablo Agustin ; McCombe, Kris D. ; Craig, Stephanie G. ; James, Jacqueline ; Brooks, Jill ; Nankivell, Paul ; Mehanna, Hisham ; Khurram, Syed Ali ; Rajpoot, Nasir M.

• Document type: Journal article
• Source: COMMUNICATIONS MEDICINE; v. 5, n. 1, p. 11-pg., 2025-05-20.

Abstract

BackgroundOral epithelial dysplasia (OED) is a potentially malignant histopathological diagnosis given to lesions of the oral cavity that are at risk of progression to malignancy. Manual grading of OED is subject to substantial variability and does not reliably predict prognosis, potentially resulting in sub-optimal treatment decisions.MethodWe developed a Transformer-based artificial intelligence (AI) pipeline for the prediction of malignant transformation from whole-slide images (WSIs) of Haematoxylin and Eosin (H&E) stained OED tissue slides, named ODYN (Oral Dysplasia Network). ODYN can simultaneously classify OED and assign a predictive score (ODYN-score) to quantify the risk of malignant transformation. The model was trained on a large cohort using three different scanners (Sheffield, 358 OED WSIs, 105 control WSIs) and externally validated on cases from three independent centres (Birmingham and Belfast, UK, and Piracicaba, Brazil; 108 OED WSIs).ResultsModel testing yielded an F1-score of 0.96 for classification of dysplastic vs non-dysplastic slides, and an AUROC of 0.73 for malignancy prediction, gaining comparable results to clinical grading systems.ConclusionsWith further large-scale prospective validation, ODYN promises to offer an objective and reliable solution for assessing OED cases, ultimately improving early detection and treatment of oral cancer. (AU)

• FAPESP's process: 21/14585-7 - Artificial intelligence applied to the clinical and histopathological diagnosis of Head and Neck Cancer
• Grantee: Anna Luiza Damaceno Araujo
• Support Opportunities: Scholarships in Brazil - Post-Doctoral