ArticleCancer cytopathology2025
Analysis of the sensitivity of high-grade squamous intraepithelial lesion Pap diagnosis and interobserver variability with the Hologic Genius Digital Diagnostics System.
Article in Cancer cytopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Enhancing efficiency and improving turnaround time: real-world impact of the Genius Digital Diagnostics System implementation.American journal of clinical pathology · 2026Article
- Artificial intelligence for colposcopic and cytological image analysis in early cervical cancer detection.iScience · 2026Review
- Technical considerations during validation of the Genius® Digital Diagnostic System.Journal of pathology informatics · 2026Article
- Assessment of the efficiency and accuracy of an artificial intelligence assistive system in the diagnosis of Pap cervical atypical glandular cell cytology.Cancer cytopathology · 2025Article
- Assessment of the efficacy and accuracy of cervical cytology screening with the Hologic Genius Digital Diagnostics System.Cancer cytopathology · 2025Article
- Double-Multiplex Immunostainings for Immune Profiling of Invasive Breast Carcinoma: Emerging Novel Immune-Based Biomarkers.International journal of molecular sciences · 2025Review
- Advancements in Digital Cytopathology Since COVID-19: Insights from a Narrative Review of Review Articles.Healthcare (Basel, Switzerland) · 2025Review
- Analysis of the sensitivity of high-grade squamous intraepithelial lesion Pap diagnosis and interobserver variability with the Hologic Genius Digital Diagnostics System.Cancer cytopathology · 2025Article
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9 authors.
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Abstract
backgroundArtificial 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).
methodsA 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.
resultsMost 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.
conclusionsNew-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.
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