Implementing 100% quality control in a cervical cytology workflow using whole slide images and artificial intelligence provided by the Techcyte SureView™ System

Maria del Mar Rivera Rolon & Juan Carlos Santa‐Rosario et al.

Abstract

Background

Recent advancements in digital pathology have extended into cytopathology. Laboratories screening cervical cytology specimens now choose between limited imaging options and traditional manual microscopy. The Techcyte SureView™ Cervical Cytology System, designed for digital cytopathology, was validated at CorePlus, a pathology laboratory in Puerto Rico, and adopted as a 100% quality control (QC) tool.

Methods

The validation study included 1442 whole slide images (WSIs) from 1273 ThinPrep® and 169 SurePath™ cervical cytology slides, digitized with the 3DHISTECH Panoramic 1000 DX scanner using dry and water immersion scanning profiles. These WSIs were processed by the Techcyte SureView™ system, with a board‐certified cytopathologist reviewing artificial intelligence (AI)‐identified objects of interest and comparing them to traditional light microscopy results.

Results

Techcyte SureView™ with the water immersion scanning profile outperformed both the dry scanning profile and light microscopy in detecting squamous and glandular abnormalities. It achieved 97% accuracy, 82% sensitivity, 99% specificity, 98% negative predictive value, and 86% positive predictive value. Additionally, the review time was rapid. The system has been operational for several months, enhancing accuracy and workflow efficiency.

Conclusions

This study demonstrates that digital cytopathology, particularly through the Techcyte SureView™ system, can improve laboratory workflow and performance. Successful validation led CorePlus to integrate the AI algorithm into their workflow as a 100% QC review tool, resulting in improved accuracy, benefiting both laboratory professionals and patients.

Authors
Maria del Mar Rivera Rolon, Erik Gustafson, Riley Cole, Jaylene Matos, Kellie Hicken, Jacob Hicks, Brian Cahoon, Mariano de Socarraz, Juan Carlos Santa‐Rosario