CYTOREADER™

Automated Reading of Dual Stain Cytology,
AI-Based Image Analysis, Standardized Cancer Screening.

Cervical cancer screening is one of the most globally impactful cancer preventive measures and stands out due to its high degree of automation when primary HPV testing is used, which enables efficient and large-scale implementation but is lacking specificity. Therefore, effective triage and management of HPV-positive women is critical to avoid unnecessary colposcopy referrals and associated harms while maintaining high sensitivity for cervical precancer. Triage with p16/Ki-67 dual-stain (DS) testing has shown high sensitivity and specificity for detection of cervical precancers; however, its currently missing automation is hindering global implementation and adoption of the assay itself, in turn restricting the full potential of HPV-based cancer screeening. Dual-stain (DS) has already been included as an important component in the US Enduring Consensus Guidelines and the World Health Organization (WHO) cervical cancer screening guidelines as a recommended triage method for managing HPV-positive individuals. Compared with PAP cytology, dual-stain requires fewer subsequent colposcopies and detects more, and earlier, cervical intraepithelial neoplasia grade 3 or greater.

CYTOREADER™ Dual-Stain Diagnostics

CYTOREADER™ is the first and only AI-driven solution for assisting with dual-stain cytology (p16/Ki-67) and ist built around a new AI-based algorithm integrated into a fully automated laboratory and analysis process. It is designed to most efficiently assist readers in detecting dual-stain events in very high throughput cervical cancer screening. The system allows for a fast and efficient analysis of all cells on a ThinPrep® or Surepath® liquid cytology slides stained with the CINtec PLUS® dual-stain assay. It creates a gallery of the 30 most relevant diagnostic image tiles based on computed likelihood for an image to contain a dual-stain positive cell. Readers thus get the decisive information necessary for fast diagnosis at immediate sight. Fully automatic reading of dual-stain slides using CYTOREADER has been evaluated in externallly validated, blinded scientific studies by the US National Cancer Institute.

Components for using CYTOREADER comprise:

  • Whole-Slide Scanning: Scanning: Scanning liquid cytology slides from ThinPrep® or Surepath™ with Whole-Slide Scanners (Hamamatsu Nanozoomer or Roche DP-Series).
  • AI-Powered Cytoreader-V2: New Deep-Learning-Algorithm Cytoreader-V2 with exceptional robustness using a whole ensemble of different AI algorithms.
  • Slide Management: Slide-Management server to store whole slides and manage the automatic slide workflow. Cases are offloaded from the system for archiving to external storage units.
  • AI-Based Quality Control: Our suite of AI-based quality algorithms for fully automatic supervision of a successful ICC dual-stain staining pattern for each case under review, a high focus quality, and sufficient cellularity.
  • Web-Based Review Station:The browser-based review station allowing extremely fast case evaluation based on the AI results. Case review can be performed locally or remotely from any geographical location.
  • Scalable Deployment: The system is deployable locally or cloud-based and can be scaled nearly without limits on in-house or external IT GPU hardware.

*Cytoreader is not yet FDA or CE certified and is for research use only.
*The underlying AI technology is patent protected in the US (US 11,954,593 B2), European Union (IE20180171A) and China (CN112543934A).

Image

Cytoreader-V2 Validation

Cytoreader-V2 was validated on 3,803 patients from the Kaiser Permanente Northern California (KPNC) Dual Stain Implementation Study (SurePathTM) [1], the NCI Biopsy Study (ThinPrep®) [2,3], the Improving Risk Informed HPV Screening study IRIS (SurePathTM) [4,5], the study STRIDES Studying Risk to Improve DisparitiES in Cervical Cancer in Mississippi (ThinPrep®) [6,5], and ACSS, the Anal Cancer Screening Study (ThinPrep®) [2,8]. Cytoreader-V2 has been evaluated to work with the Whole Slide Imaging (WSI) Scanners from Hamamatsu Photonics (Nanozoomer-Series) or Roche (DP-Series).

Image

All Slide Types

Cytoreader-V2 has unique robustness as each image tile is evaluated by an ensemble of AI algorithms simultaneously and has been validated on the dual-stain assay CINtec+® from Roche and on liquid cytology slides prepared with ThinPrep® and SurePath™. It comprises a complex, barcode-automated workflow management. Also multiple AI algorithms automatically check in-parallel quality of all slides for focus quality, cellularity and staining failures. This way correct dual-stain immunochemistry is AI supervised. Cytotechs or pathologists can make a diagnosis extremely fast in any web browser by displaying the 30 most likely dual-stain-containing tiles for each case.

Features

CYTOREADER Diagnostics

CYTOREADER Diagnostics

Efficiently assess the 30 most relevant dual-stain events directly linked to the whole-slide image for quick diagnostics.

Shortcut Key Navigation

Shortcut Key Navigation

Streamline workflow with shortcut keys that enable rapid toggling through galleries, entering diagnoses, and transitioning between slides in under one minute.

Guided Viewing

Guided Viewing

Enhance slide analysis by annotating regions of interest, viewing computed likelihoods, and utilizing heatmaps for comprehensive insights.

Blinded Study Mode

Blinded Study Mode

Enable blinded analysis of computational results for training, quality control, and statistical monitoring of diagnostic performance.

Team Workflow for QC

Team Workflow for QC

Facilitate collaborative team workflows with AI-assisted pre-screening by cytotechs and final sign-off by pathologists, ensuring optimal quality control in dual-stain readings.

Slide Management

Slide Workflow Management

Efficiently manage slide workflows automatically or user-assisted, group slides into virtual boxes, assign tasks to cytotechs or pathologists, monitor analyses progress, and generate PDF reports.

Contact

Responsible for content:

Germany: H-Labs GmbH, Heckerstr. 9, 69124 Heidelberg, Germany

Internationally: Centauris med d.o.o., Rudarska 1, 52220 Labin, Croatia

Contact: Prof. Dr. Niels Grabe

Email: niels.grabe@stcmed.com


References
  • 1 Wentzensen, N., Clarke, M., Bremer, R., Bodelon, C., Cheung, L., Chen, X., Demarco, M., Egemen, D., Perkins, R., Kinney, W., Gage, J. & Castle, P. (2019). Clinical Evaluation of Human Papillomavirus Screening With p16/Ki-67 Dual Stain Triage in a Large Organized Cervical Cancer Screening Program. JAMA Internal Medicine, 179(7), 881-889. doi: 10.1001/jamainternmed.2019.0000
  • 2 Wentzensen, N., Schwartz, L., Zuna, R., & Al. (2012). Performance of p16/Ki-67 immunostaining to detect cervical cancer precursors in a colposcopy referral population. Clinical Cancer Research, 18(15), 4154-4162. doi: 10.1158/1078-0432.CCR-12-0244
  • 3 Wentzensen, N., Walker, J., Gold, M., & Al. (2015). Multiple biopsies and detection of cervical cancer precursors at colposcopy. Journal of Clinical Oncology, 33(1), 83-89. doi: 10.1200/JCO.2014.59.1121
  • 4 Gage, J., Raine-Bennett, T., Schiffman, M., & Al. (2022). The Improving Risk Informed HPV Screening (IRIS) Study: Design and Baseline Characteristics. Cancer Epidemiology, Biomarkers & Prevention, 31(2), 486-492. doi: 10.1158/1055-9965.EPI-21-1023
  • 5 Clarke, M., Wentzensen, N., Perkins, R., Garcia, F., Arrindell, D., Chelmow, D., Cheung, L., Darragh, T., Egemen, D., Guido, R., Huh, W., Locke, A., Lorey, T., Nayar, R., Risley, C., Saslow, D., Smith, R., Unger, E., & Massad, L. (2024). Recommendations for Use of p16/Ki67 Dual Stain for Management of Individuals Testing Positive for Human Papillomavirus. Journal of Lower Genital Tract Disease.
  • 6 Risley, C., Stewart, M., Geisinger, K., & Al. (2021). STRIDES - STudying Risk to Improve DisparitiES in Cervical Cancer in Mississippi - Design and baseline results of a Statewide Cohort Study.
  • 7 Wentzensen, N., Follansbee, S., Borgonovo, S., & Al. (2012). Human papillomavirus genotyping, human papillomavirus mRNA expression, and p16/Ki-67 cytology to detect anal cancer precursors in HIV-infected MSM. AIDS, 26(13), 2185-2192. doi: 10.1097/QAD.0b013e328355b8a3
  • 8 Cohen, C., Wentzensen, N., Lahrmann, B., Tokugawa, D., Poitras, N., Bartels, L., Krauthoff, A., Keil, A., Miranda, F., Castle, P., & Others (2022). Automated evaluation of p16/Ki-67 dual-stain cytology as a biomarker for detection of anal precancer in men who have sex with men and are living with human immunodeficiency virus. Clinical Infectious Diseases, 75(3), 1565-1572. doi: 10.1093/cid/ciac008
  • 9 Wentzensen N, Lahrmann B, Clarke MA,& et al (2020). : Accuracy and Efficiency of Deep-Learning–Based Automation of Dual Stain Cytology in Cervical Cancer Screening.J Natl Cancer Inst djaa066