Current automated cervical cytology screening systems depend heavily on manipulation of glass slides. We developed CytoProcessor, which takes advantage of virtual slide technology and artificial intelligence to detect, to classify and sort Pap smear cells in order to increase sensitivity while saving time in diagnosis making. A gallery of abnormal cell thumbnails is presented to the user in a web application. He can then interact with it to visualize the given cells in the whole slide image. We set out to compare CytoProcessor and the ThinPrep Imaging System. A representative population of 1352 cases was selected from the routine workflow for diagnosis by both methods. All discordances were resolved by a consensus committee. CytoProcessor significantly improves diagnostic sensitivity without compromising specificity. If the CytoProcessor diagnosis had been used,
1.5% of patients would have been missed. In contrast, 4% of patients were missed with the ThinPrep Imaging System (2.6-fold decrease). CytoProcessor is better at cases where abnormal cells are isolated, specifically on LSIL lesions with koïlocytes. With CytoProcessor, 2.2 hours of human resources are saved every 100 slides thanks to the completely digitized workflow and its computer assisted screening tool. Besides, the first pathologist using the solution in a private laboratory in routine testified to go 6 times faster. CytoProcessor is the first of the new generation of remote and automated screening systems, demonstrating improved sensitivity and gains in time. Moreover, the fully digital nature of this solution allows to make diagnosis remotely
Current automated cervical cytology screening systems require purchase of a dedicated preparation machine and use of a specific staining protocol. CytoProcessor (DATEXIM, Caen, France) is a new automated system, designed to integrate seamlessly into the laboratory’s existing workflow. We previously demonstrated the superior performance of CytoProcessor for diagnosis of ThinPrep slides compared to the ThinPrep Imaging System (HOLOGIC, Marlborough, MA). Next, we analyzed whether CytoProcessor technology can be adapted for use on Novaprep slides.
Using artificial intelligence, we developed a new algorithm in CytoProcessor for the analysis of slides prepared using the NOVAPREP Processor System NPS50 (Novacyt, Vélizy‐Villacoublay, France). A representative population of 309 cases was selected from the routine workflow in a public hospital. We compared the diagnoses made using CytoProcessor or conventional screening with a microscope. All discordances were resolved by a consensus committee.
The performance of CytoProcessor in terms of diagnostic accuracy on Novaprep slides was very similar to that observed previously on ThinPrep slides. Compared to conventional screening, CytoProcessor slightly improves diagnostic sensitivity while maintaining a statistically equivalent specificity. Diagnosis was reached 1.6 times faster with CytoProcessor compared to using a microscope.
CytoProcessor is a robust automated cervical cytology screening system that can be used successfully with samples having very different characteristics. As previously shown, CytoProcessor confers significant gains in processing time and diagnostic precision. CytoProcessor is accessible through a secured internet connection, making remote diagnosis of Papanicolaou tests possible.
Current automated cervical cytology screening systems still heavily depend on manipulation of glass slides. We developed a new system called CytoProcessorTM (DATEXIM, Caen, France), which increases sensitivity and takes advantage of virtual slide technology to simplify the workflow and save worker time. We used an approach based on artificial intelligence to identify abnormal cells among the tens of thousands in a cervical preparation. Objectives: We set out to compare the diagnostic sensitivity and specificity of CytoProcessorTM and the ThinPrep Imaging System (HOLOGIC, Marlborough, MA, USA).
A representative population of 1,352 cases was selected from the routine workflow in a private laboratory. Diagnoses were established using the ThinPrep Imaging System and CytoProcessorTM. All discordances were resolved by a consensus committee.
Compared to the ThinPrep Imaging System, CytoProcessorTM significantly improves diagnostic sensitivity without compromising specificity. The sensitivity of detection of “atypical squamous cells of undetermined significance (ASC-US) and more severe” and “low-grade squamous intraepithelial lesion and more severe” was significantly higher using CytoProcessorTM. Considering that cases with a truth diagnosis of ASC-US or more severe required clinical follow-up, 1.5% of the cases (21/1,360) would have been missed if the CytoProcessorTM diagnosis had been used for clinical decision-making. In contrast, 4% of the cases (54/1,360) were missed when the ThinPrep Imaging System diagnosis was used for clinical decision-making. There were 2.6 times fewer false negatives using CytoProcessorTM. The CytoProcessorTM workflow was 1.5 times faster in terms of worker time.
CytoProcessorTM is the first of a new generation of automated screening systems, demonstrating improved sensitivity and yielding significant gains in processing time. In addition, the fully digital nature of slide presentation in CytoProcessorTM allows the remote diagnosis of Papanicolaou tests for the first time.
PLANUCA is a collaboration between the DATEXIM company, the Cherbourg Public Hospital Center (CHPC), and the GREYC (University of Caen), funded by the EEC and Lower Normandy. We aim to develop a telepathology web application incorporating computer-aided diagnosis tools for health professionals in the field of cervical cancer screening. Our application, CytoProcessorTM, is designed for use by cytotechnologists, who furnish the sorted slides to the pathologists for diagnosis. Our results demonstrate a significant 1me advantage using CytoProcessorTM, and an increased sensitivity (99%) compared to conventional methods. This tool will empower resource-poor countries to conduct large scale screening programs, as well as improving the diagnostic accuracy of cervical cancer screening worldwide.