Miguel Mascarenhas Saraiva, Lucas Spindler, Nadia Fathallah, Hélene Beaussier, Célia Mamma, Mathilde Quesnée, Tiago Ribeiro, João Afonso, Mariana Carvalho, Rita Moura, Patrícia Andrade, Hélder Cardoso, Julien Adam, João Ferreira, Guilherme Macedo, Vincent de Parades
INTRODUCTION: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell cancer (ASCC) precursors. Preliminary studies on the application of artificial intelligence (AI) models to this modality have revealed promising results. However, the impact of staining techniques and anal manipulation on the effectiveness of these algorithms has not been evaluated. We aimed to develop a deep learning system for automatic differentiation of high (HSIL) versus low-grade (LSIL) squamous intraepithelial lesions in HRA images in different subsets of patients (non-stained, acetic acid, lugol, and after manipulation)...
January 25, 2024: Clinical and Translational Gastroenterology