Anal high-grade squamous intraepithelial lesions: identification, classification, and management

Abstract Squamous intraepithelial lesions are premalignant conditions for anal cancer, the incidence of which is slowly increasing worldwide. These premalignant lesions are commonly found in high-risk individuals such as those who are immunosuppressed, and men who have sex with men. The development of squamous intraepithelial lesions is driven by chronic human papillomavirus infection that induces cellular proliferation and dysplastic modification in mucosal and cutaneous epithelia. Among a wide family of human papillomavirus strains, high-risk genotypes such as human papillomavirus 16 and 18 are responsible for most high-grade precancerous lesions and their subsequent progression to invasive cancer. Historically, premalignant lesions have been described by a variety of different classification systems that has changed as our understanding of their pathophysiology has evolved. Precancerous lesions are currently classified based on the degree of dysplasia in the anal epithelium. Anal intraepithelial neoplasia I or low-grade squamous intraepithelial neoplasia (LSIL) describes a low-grade dysplastic lesion capable of spontaneous regression, while anal intraepithelial neoplasia III or high-grade squamous intraepithelial neoplasia (HSIL) describes those lesions with capacity for infiltration and malignant change. The need for active screening in high-risk groups is now established, as proactive treatment of HSIL significantly reduces the development of anal cancer. High-resolution anoscopy is a diagnostic modality that allows for the identification and treatment of anal dysplasia, halting its progression to squamous cell carcinoma. Using vital dyes and dedicated instruments offering high magnification and resolution, it is possible to visualize and treat very small and/or flat premalignant lesions that would be invisible on standard diagnostic anoscopy. The evolution of artificial intelligence is set to further enhance its diagnostic ability, and shorten the learning curve for its implementation.