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: | , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2010 Feb 4
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| 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/ |
| Verfasserangaben: | Niels Grabe, Bernd Lahrmann, Thora Pommerencke, Magnus von Knebel Doeberitz, Miriam Reuschenbach and Nicolas Wentzensen |
MARC
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| 245 | 1 | 2 | |a A virtual microscopy system to scan, evaluate and archive biomarker enhanced cervical cytology slides |c 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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