Closing the Automation Gap: Robust AI for Dual-Stain Cervical Cancer Screening Triage

Dual-stain cytology, using p16 and Ki67, is superior to conventional PAP cytology for triage of HPV-positive test results in cervical cancer screening. Its AI-based evaluation can remove subjectivity, improve performance and facilitate implementation. Using 5,722 dual-stain slides from population-based screening cohorts, we developed and validated Cytoreader-V2. In the SurePath Kaiser Implementation Study, Cytoreader-V2 achieved 87.2\%/57.8\% (sensitivity/specificity) compared to 89.9/52.6 (manual DS) and 85.8/41.9 (Pap cytology). In the ThinPrep Biopsy Study, it reached 95.7/44.4 versus 89.4/35.0 (manual DS), and in anal DS cytology slides, 87.0/41.3 compared to 87.0/27.7 (manual). Robustness testing demonstrated significant stability across image transformations. Cytoreader-V2 improves specificity and reproducibility compared to manual dual-stain reading while maintaining high sensitivity. Its adaptability across populations with consistent performance makes it scalable for diverse clinical settings. Cytoreader-V2 can be a transformative tool in global cervical cancer screening as a critical AI applications in digital pathology.