A WSI-Independent Inference Framework for Cervical and Urinary Cytology Using Hierarchical Labels.

BACKGROUND: Cytology artificial intelligence (AI) systems often depend on whole-slide images (WSIs) or high-magnification cell images and are commonly optimized for a single specimen type. We developed CYTOLONE-v2, a contrastive language-image pretraining (CLIP)-based hierarchical classification framework for cervical and urinary cytology that is designed for individual-field inference without WSI input. METHODS: CYTOLONE-v1.1, previously trained for cervical cytology, was further trained by low-rank adaptation using WSI-derived urinary cytology fields equivalent to ×10 magnification. The 90-case source cohort was divided at the case level into training (72 cases; 360 fields) and validation (18 cases; 90 fields) subsets. Five diagnosis-representative fields were manually selected from each case. Field-level performance was evaluated in an independent urinary test cohort of 40 cases (20 Reactive change and 20 Urothelial carcinoma; 200 fields), and retention was assessed using an independent cervical cytology test set. RESULTS: In urinary cytology, CYTOLONE-v2 achieved field-level accuracies of 64.0% for Anomaly and Malignancy and 72.5% for Diagnosis. At the Diagnosis level, sensitivity for urothelial carcinoma was 99.0% (95% confidence interval [CI], 96.7%-100%), whereas specificity against Reactive change was 46.0% (95% CI, 30.0%-62.0%). Cervical cytology accuracy was retained at the Anomaly level (94.8% vs. 94.7% with CYTOLONE-v1.1), decreased modestly at the Malignancy level (91.2% vs. 93.5%), and decreased more at the Bethesda and Diagnosis levels. CONCLUSIONS: CYTOLONE-v2 demonstrates the technical feasibility of extending a hierarchical cytology classification framework from cervical to urinary cytology. The findings are limited to selected WSI-derived fields and a Reactive change-versus-Urothelial carcinoma test cohort; external, case-level, direct-microscopy and prospective workflow validation is required before clinical utility can be established.