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

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 p...

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Hauptverfasser: Grabe, Niels (VerfasserIn) , Lahrmann, Bernd (VerfasserIn) , Pommerencke, Thora (VerfasserIn) , Knebel Doeberitz, Magnus von (VerfasserIn) , Reuschenbach, Miriam (VerfasserIn) , Wentzensen, Nicolas (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2010 Feb 4
In: Cellular oncology
Year: 2010, Jahrgang: 32, Heft: 1-2, Pages: 109-119
ISSN:1875-8606
DOI:10.3233/CLO-2009-0508
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3233/CLO-2009-0508
Verlag, lizenzpflichtig, Volltext: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4237613/
Volltext
Verfasserangaben:Niels Grabe, Bernd Lahrmann, Thora Pommerencke, Magnus von Knebel Doeberitz, Miriam Reuschenbach and Nicolas Wentzensen

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520 |a 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. 
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