Unsupervised radiomics-driven endotyping of chronic rhinosinusitis with nasal polyps: a multimodal characterization of CT imaging, clinical phenotypes, and proteomic profiling

BACKGROUND: The current phenotyping of chronic rhinosinusitis with nasal polyps (CRSwNP) into eosinophilic (eCRSwNP) and non-eosinophilic (non-eCRSwNP) subtypes is increasingly insufficient to address complex clinical challenges, especially as some non-eCRSwNP patients have poor prognoses. Identifying intrinsic endotypes non-invasively is crucial for precision therapy. To identify CRSwNP endotypes via unsupervised clustering of paranasal sinus computed tomography (CT) radiomics features and analyze their clinical and biological significance. METHODS: Retrospective study of CRSwNP patients undergoing functional endoscopic sinus surgery (FESS) (Jan 2016-Apr 2021) with preoperative CT. Clustering analysis was performed on patients using 1409 radiomic features. Proteomics analyzed nasal polyps from 41 patients. Clinical characteristics and prognoses were compared. RESULTS: In total, 661 patients were included (median age, 50 years; interquartile range, 40–60 years; 213 [32%] women). Three radiomic clusters were identified. Endotype 3 had the worst prognosis, followed by endotype 1; endotype 2 had the best prognosis (log-rank test, P = 0.026 / 0.0026). Endotype 3 exhibited the lowest lymphocyte count (Kruskal-Wallis test, P = 0.049), highest CT scores (P < 0.0001) and nasal endoscopic scores (P < 0.0001). Endotype 3 showed enrichment in inflammatory pathways (complement activation, immune signaling, humoral response). Endotype 2 correlated with lipoprotein processes. Endotype 1 (intermediate prognosis) showed co-enrichment of lipoprotein and inflammatory pathways. CONCLUSION: Unsupervised CT radiomics clustering identified three prognostically distinct CRSwNP endotypes with differing clinical and biological features. This provides a novel non-invasive method for endotyping and prognostic assessment.