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 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.
Grabe
Niels
N
Institute of Medical Biometry and Informatics, Section Medical Informatics, University Hospital Heidelberg, Heidelberg, Germany. niels.grabe@med.uniheidelberg.de
Lahrmann
Bernd
B
Pommerencke
Thora
T
von Knebel Doeberitz
Magnus
M
Reuschenbach
Miriam
M
Wentzensen
Nicolas
N
D014408:Biomarkers, Tumor / Q000032:analysis*; D003584:Cytological Techniques / Q000379:methods*; D055088:Early Detection of Cancer / Q000379:methods; D005260:Female; D006801:Humans; D010784:Photomicrography / Q000379:methods*; D002583:Uterine Cervical Neoplasms / Q000737:chemistry* / Q000175:diagnosis / Q000473:pathology
D014408:Biomarkers, Tumor