[Artificial intelligent-based whole slide digital pathology for endotype classification of chronic rhinosinusitis...

Objectives: To investigate the pathological inflammatory features based on artificial intelligence for whole slide image (AI-WSI), and to evaluate its consistency and clinical relevance with the conventional mean of ten random high-power fields (10-HPF). Ultimately, a WSI-based pathological endotype classification for chronic rhinosinusitis with nasal polyps (CRSwNP) was established. Methods: A total of 407 CRSwNP patients admitted to the Department of Otorhinolaryngology-Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-sen University from January 2020 to December 2023 were retrospectively enrolled. The cohort included 288 males and 119 females, aged from 18 to 84 years. Quantitative analysis of inflammatory cells in the pathological sections of these patients was performed using the traditional 10 HPF method and the AI-WSI method, respectively. Subsequently, a typing system was established based on AI-WSI results using unsupervised clustering, discriminant analysis, and classification tree modeling, and the tissue components and clinical characteristics of each subtype were compared. Data analysis was conducted using SPSS 26.0 and R 4.4.2 software. Results: Significant differences were observed in the proportion of inflammatory cells between the AI-WSI and 10 HPF methods, with a Cohen's Kappa coefficient of 0.48. The existing 10 HPF-based typing criterion was not suitable for the inflammatory feature results of AI-WSI. Cluster analysis of AI-WSI data identified four distinct subtypes: eosinophil (Eos)-predominant, plasma cell (Pla)-predominant, lymphocyte (Lym)-predominant, and neutrophil (Neu)-predominant. The Eos-predominant subtype accounted for 28.26%, characterized by the highest recurrence rate (39.13%) and olfactory dysfunction. The Lym-predominant and Pla-predominant subtypes presented milder symptoms, with recurrence rates of 13.63% and 16.13%, respectively. Although the Neu-predominant subtype was associated with significant head and facial pain, it had a lower recurrence rate (11.11%). Conclusions: There are differences in the pathological inflammatory features between the traditional 10 HPF method and the AI-WSI method, and the features derived from AI-WSI are currently difficult to directly apply to existing typing criterion. This study successfully establishes a four-subtype classification system for CRSwNP based on AI-WSI, which demonstrates good stability and discriminative ability.