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BACKGROUND: Artificial intelligence (AI)-based systems are transforming cytopathology practice. The aim of this study was to evaluate the sensitivity of high-grade squamous intraepithelial lesion (HSIL) Papanicolaou (Pap) diagnosis assisted by the Hologic Genius Digital Diagnostics System (GDDS). METHODS: A validation study was performed with 890 ThinPrep Pap tests with the GDDS independently. From this set, a subset of 183 cases originally interpreted as HSIL confirmed histologically were included in this study. The sensitivity for detecting HSIL by three cytopathologists was calculated. RESULTS: Most HSIL cases were classified as atypical glandular cell/atypical squamous cell-high grade not excluded (AGC/ASC-H) and above by all cytopathologists. Of these cases, 11.5% were classified as low-grade squamous intraepithelial lesion (LSIL) by pathologist A (P-A), 6% by pathologist B (P-B), and 5.5% by pathologist C (P-C); 3.8%, 2.7%, and 1.6% of these cases were classified as atypical squamous cell of unknown significance (ASC-US) by P-A, P-B, and P-C, respectively. The sensitivity for detection of cervical intraepithelial neoplasia 2 and above (CIN2+) lesions was 100% if ASC-US and above (ASC-US+) abnormalities were counted among all three pathologists. The sensitivity for detection of CIN2+ lesions was 84.7%, 91.3%, and 92.9% by P-A, P-B, and P-C, respectively, for ASC-H and above abnormalities. The Kendall W coefficient was 0.722, which indicated strong agreement between all pathologists. CONCLUSIONS: New-generation AI-assisted Pap test screening systems such as the GDDS have the potential to transform cytology practice. In this study, the GDDS aided in interpreting HSIL in ThinPrep Pap tests, with good sensitivity and agreement between the pathologists who interacted with this system.
Harinath et al. (Tue,) studied this question.