A virtual microscopy system to scan, evaluate and archive biomarker enhanced cervical cytology slides

• Verfasst von: Grabe, Niels [VerfasserIn]
• Verfasst von: Lahrmann, Bernd [VerfasserIn]
• Verfasst von: Pommerencke, Thora [VerfasserIn]
• Verfasst von: Knebel Doeberitz, Magnus von [VerfasserIn]
• Verfasst von: Reuschenbach, Miriam [VerfasserIn]
• Verfasst von: Wentzensen, Nicolas [VerfasserIn]
• Titel: A virtual microscopy system to scan, evaluate and archive biomarker enhanced cervical cytology slides
• Verf.angabe: Niels Grabe, Bernd Lahrmann, Thora Pommerencke, Magnus von Knebel Doeberitz, Miriam Reuschenbach and Nicolas Wentzensen
• E-Jahr: 2010
• Jahr: 2010 Feb 4
• Umfang: 11 S.
• Fussnoten: Gesehen am 28.04.2023
• Titel Quelle: Enthalten in: Cellular oncology
• Ort Quelle: Amsterdam [u.a.] : IOS Press, 2004
• Jahr Quelle: 2010
• Band/Heft Quelle: 32(2010), 1-2, Seite 109-119
• ISSN Quelle: 1875-8606
• DOI: doi:10.3233/CLO-2009-0508
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1843786796

Abstract

Background: Although cytological screening for cervical precancers has led to a reduction of cervical cancer incidence worldwide it is a subjective and variable method with low single-test sensitivity. New biomarkers like p16 that specifically highlight abnormal cervical cells can improve cytology performance. Virtual microscopy offers an ideal platform for assisted evaluation and archiving of biomarker-stained slides., - Methods: We first performed a quantitative analysis of p16-stained slides digitized with the Hamamatsu NDP slide scanner. From the results an automated algorithm was created to reliably detect cells, nuclei and p16-stained cells. The algorithm's performance was evaluated on two complete slides and tiles from 52 independent slides (11,628, 4094 and 25,619 cells/clusters, respectively)., - Results: We achieved excellent performance to discriminate unstained cells from nuclei and biomarker-stained cells. The automated algorithm showed a high overall and positive agreement (99.0-99.7% and 70.9-83.4%, respectively) with the gold standard and had a very high sensitivity (89.1-100.0%) and specificity (98.9-100.0%) to detect biomarker-stained cells., - Conclusions: We implemented a virtual microscopy system allowing highly efficient automated prescreening and archiving of biomarker-stained slides. Based on the initial results, we will evaluate the performance of our system in large epidemiologic studies against disease endpoints.