CYTOreader

CYTOREADER is a cloud based deep learning application supporting cervical pre-cancer screening based on dual stain (p16/Ki67) liquid cytology (CINtec® plus). CYTOREADER comprises a fully automated workflow to digitize and classify glass slides for patient referral to colposcopy. It provides a web interface for rapid AI-assisted diagnostics of cervical pre-cancer screening.

The heart of the application is CYTOREADER AI EVALUATOR, the CYTOREADER dual stain detection algorithm, which is a deep neural network for the detection of dual stain positive cells. As CYTOREADER runs in the cloud, it has technically unlimited scalability in throughput and unlimited geographical outreach. It increases efficiency of slide interpretation, and provides diagnostic procedures with objectivity and high accuracy globally, especially also in settings that lack personnel, expertise or infrastructure. In full automation, CYTOREADER has shown superior accuracy compared to manual DS reading with less colposcopy referrals.

CYTOREADER emerged from a scientific project between the Steinbeis Center for Medical Systems Biology (STCMED) in cooperation with the Division of Cancer Epidemiology & Genetics of the US National Cancer Institute (NCI) and Kaiser Permanente Northern California (KPNC). CYTOREADER is currently used as research-only (RUO) in epidemiological studies.

References

  1. Wentzensen N, Arbyn M, Berkhof J, et al: Eurogin 2016 Roadmap: how HPV knowledge is changing screening practice. Int J Cancer 140:2192-2200, 2017

  2. Schiffman M, Wentzensen N, Wacholder S, et al: Human papillomavirus testing in the prevention of cervical cancer. J Natl Cancer Inst 103:368-383, 2011

  3. Gage JC, Schiffman M, Katki HA, et al: Reassurance against future risk of precancer and cancer conferred by a negative human papillomavirus test. J Natl Cancer Inst 106, 2014

  4. Katki HA, Kinney WK, Fetterman B, et al: Cervical cancer risk for women undergoing concurrent testing for human papillomavirus and cervical cytology: a population-based study in routine clinical practice. Lancet Oncol 12:663-672, 2011

  5. Cuschieri K, Ronco G, Lorincz A, et al: Eurogin roadmap 2017: Triage strategies for the management of HPV-positive women in cervical screening programs. Int J Cancer, 2018

  6. Wentzensen N, Schiffman M, Palmer T, et al: Triage of HPV positive women in cervical cancer screening. J Clin Virol 76 Suppl 1:S49-s55, 2016

  7. Wentzensen N, Clarke MA, Bremer R, et al: Clinical evaluation of HPV screening with p16/Ki-67 dual stain triage in a large organized cervical cancer screening program. JAMA Internal Medicine In Press, 2019

  8. Clarke MA, Cheung LC, Castle PE, et al: Five-Year Risk of Cervical Precancer Following p16/Ki-67 Dual-Stain Triage of HPV-Positive Women. JAMA Oncol, 2018

  9. Wentzensen N, Fetterman B, Castle PE, et al: p16/Ki-67 Dual Stain Cytology for Detection of Cervical Precancer in HPV-Positive Women. J Natl Cancer Inst 107:djv257, 2015

  10. Wentzensen N, Schwartz L, Zuna RE, et al: Performance of p16/Ki-67 immunostaining to detect cervical cancer precursors in a colposcopy referral population. Clin Cancer Res 18:4154-4162, 2012

  11. Lahrmann B, Valous NA, Eisenmann U, et al: Semantic focusing allows fully automated single-layer slide scanning of cervical cytology slides. PLoS One 8:e61441, 2013

  12. Grabe N, Lahrmann B, Pommerencke T, et al: A virtual microscopy system to scan, evaluate and archive biomarker enhanced cervical cytology slides. Cell Oncol 32:109-119, 2010

  13. Wentzensen N, Fetterman B, Tokugawa D, et al: Interobserver reproducibility and accuracy of p16/Ki-67 dual-stain cytology in cervical cancer screening. Cancer Cytopathol 122:914-920, 2014

  14. Solomon D, Davey D, Kurman R, et al: The 2001 Bethesda System: terminology for reporting results of cervical cytology. Jama 287:2114-2119, 2002

  15. Leisenring W, Alonzo T, Pepe MS: Comparisons of predictive values of binary medical diagnostic tests for paired designs. Biometrics 56:345-351, 2000

  16. Conrad RD, Liu AH, Wentzensen N, et al: Cytologic patterns of cervical adenocarcinomas with emphasis on factors associated with underdiagnosis. Cancer Cytopathol 126:950-958, 2018

Scientific lead

Prof. Dr. Niels Grabe
Nicolas Wentzensen, M.D., Ph.D.
Dr. Bernd Lahrmann

Contact

e-mail: contact@stcmed.com