NDLI: The use of digital images improves reproducibility of the ki-67 labeling index as a proliferation marker in breast cancer.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Vörös, András Csörgo, Erika Kovári, Bence Lázár, Péter Kelemen, Gyöngyi Cserni, Gábor
Description	Author Affiliation: Vörös A ( Department of Pathology, University of Szeged, Állomás u 2, 6725, Szeged, Hungary, andrasvoros@libero.it.)
Abstract	The proportion of Ki-67 immunostained cells (Ki-67 labeling index, LI) is one of the most commonly used histology methods for estimating proliferation of breast carcinomas. Although the Ki-67 LI is used in treatment decision making, its reproducibility shows variation in different studies, and is generally less then optimal. The aim of the present study was to investigate how the use of a standardized, partially digitalized counting method could affect reproducibility of determining the Ki-67 LI. Thirty breast cancer core-biopsy samples were stained with B-56, SP-6 and MIB-1 monoclonal Ki-67 antibodies. Each sample was represented by a single digital photograph taken with a x20 objective. Four investigators determined the Ki-67 LI on these digital images by estimation, then by counting with the help of a grid overlaid on the same images. Altogether 720 evaluations were made by 4 independent pathologists. Good to excellent correlation was found between estimations and calculations of each observer. Kappa values >0.6 suggest substantial inter-observer agreement when classifying the cases into a 15 % and 30 % cut-off determined three-tiered or a 4-quarter-based four-tiered categorization, which is better than the fair reproducibility gained on the real slides in a previous study. The results also suggest that the type of the antibody may also impact on the consistency of both estimating and calculating the Ki-67 LIs. The results indicate that counting on digital images may significantly improve reproducibility of determining the KI-67 LI. Interestingly, estimation on the same images is not worse, but is obviously faster and more convenient.
File Format	HTM / HTML
ISSN	12194956
Issue Number	2
Volume Number	20
e-ISSN	15322807
Journal	Pathology & Oncology Research
Language	English
Publisher	Springer
Publisher Date	2014-04-01
Publisher Place	Netherlands
Access Restriction	Subscribed
Subject Keyword	Discipline Oncology Tumor Markers, Biological Metabolism Breast Neoplasms Pathology Cell Proliferation Physiology Ki-67 Antigen Adult Aged Antibodies, Antinuclear Antibodies, Monoclonal Female Humans Immunohistochemistry Methods Middle Aged Oligopeptides Reproducibility Of Results Journal Article
Content Type	Text
Resource Type	Article
Subject	Cancer Research Pathology and Forensic Medicine Oncology

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