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Journal of the American Society of Cytopathology · 2025

Diagnostic performance of the hologic genius digital diagnostics system for low-grade squamous intraepithelial lesion (LSIL) ThinPrep papanicolaou tests.

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Harinath Lakshmi, Elishaev Esther, Ye Yuhong, Matsko Jonee, Colaizzi Amy, Wharton Stephanie, Bhargava Rohit, Hanna Matthew, Harrington Sarah, Pantanowitz Liron, Zhao Chengquan

Аннотация

INTRODUCTION: Advancements in digital imaging technology for Papanicolaou test slides, combined with artificial intelligence are driving the development and adoption of innovative computer-assisted screening methods for cervical cancer within the cytology community. Our study aimed to assess the performance of the Hologic Genius Digital Diagnostic System (HGDDS) in the interpretation of low-grade squamous intraepithelial lesions (LSIL) in ThinPrep Papanicolaou slides.

MATERIALS AND METHODS: As part of a validation study performed with 890 ThinPrep Papanicolaou slides using the HGDDS, a subset of 146 LSIL cases were included in this study. Performance characteristics for the detection of cervical intraepithelial neoplasia (CIN) and interobserver variability among 3 cytopathologists were assessed.

RESULTS: On evaluation of the consensus results of the 3 cytopathologists, of the 146 LSIL Papanicolaou cases, 60.3% were interpreted as LSIL with the HGDDS. The remainder were interpreted as ASCUS (26%), ASC-H (10.3%), HSIL (2.7%), and NILM (0.7%). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for detecting CIN1+ lesions in the ASCUS + category with the HGDDS were 100%, 25%, 97.9%, and 100%, respectively. The sensitivity, specificity, PPV, and NPV for the detection of CIN1+ lesions in the LSIL + category with the HGDDS were 74.7%, 75%, 99.1%, and 7.7%, respectively. Kendall's W coefficient was 0.792, indicating strong agreement among participating pathologists.

CONCLUSIONS: Our study demonstrated that ThinPrep Papanicolaou tests with LSIL could be interpreted with strong agreement among pathologists and with good performance indicators when utilizing the HGDDS.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты