Analysis of the sensitivity of high-grade squamous intraepithelial lesion Pap diagnosis and interobserver variability with the Hologic Genius Digital Diagnostics System

Lakshmi Harinath; Esther Elishaev; Yuhong Ye; Jonee Matsko; Amy Colaizzi; Stephanie Wharton; Rohit Bhargava; Liron Pantanowitz; Chengquan Zhao

doi:10.1002/cncy.22918

Analysis of the sensitivity of high-grade squamous intraepithelial lesion Pap diagnosis and interobserver variability with the Hologic Genius Digital Diagnostics System

Cancer Cytopathol. 2024 Nov 5. doi: 10.1002/cncy.22918. Online ahead of print.

Authors

Lakshmi Harinath¹, Esther Elishaev¹, Yuhong Ye², Jonee Matsko¹, Amy Colaizzi¹, Stephanie Wharton¹, Rohit Bhargava¹, Liron Pantanowitz¹, Chengquan Zhao¹

Affiliations

¹ Department of Pathology, UPMC Magee-Womens Hospital, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
² Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.

PMID: 39498535
DOI: 10.1002/cncy.22918

Abstract

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.

Keywords: Hologic Genius system; Pap (Papanicolaou) tests; artificial intelligence; digital pathology; high‐grade squamous intraepithelial lesion.