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Open Access Research article

Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer

Juho Konsti1*, Mikael Lundin1, Heikki Joensuu23, Tiina Lehtimäki1, Harri Sihto3, Kaija Holli4, Taina Turpeenniemi-Hujanen5, Vesa Kataja67, Liisa Sailas6, Jorma Isola8 and Johan Lundin19

Author Affiliations

1 FIMM - Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland

2 Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland

3 Molecular and Cancer Biology Research Program, Biomedicum Helsinki, University of Helsinki, Helsinki, Finland

4 University of Tampere and Department of Oncology, Tampere University Hospital, Tampere, Finland

5 Department of Oncology and Radiotherapy, Oulu University Central Hospital, Oulu, Finland

6 Department of Oncology, Kuopio University Hospital, Kuopio, Finland

7 Department of Oncology, Vaasa Central Hospital, Vaasa, Finland

8 Institute of Medical Technology, University of Tampere, Tampere, Finland

9 Division of Global Health, Karolinska Institutet, Stockholm, Sweden

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BMC Clinical Pathology 2011, 11:3  doi:10.1186/1472-6890-11-3

Published: 25 January 2011

Abstract

Background

The aim of the study was to develop a virtual microscopy enabled method for assessment of Ki-67 expression and to study the prognostic value of the automated analysis in a comprehensive series of patients with breast cancer.

Methods

Using a previously reported virtual microscopy platform and an open source image processing tool, ImageJ, a method for assessment of immunohistochemically (IHC) stained area and intensity was created. A tissue microarray (TMA) series of breast cancer specimens from 1931 patients was immunostained for Ki-67, digitized with a whole slide scanner and uploaded to an image web server. The extent of Ki-67 staining in the tumour specimens was assessed both visually and with the image analysis algorithm. The prognostic value of the computer vision assessment of Ki-67 was evaluated by comparison of distant disease-free survival in patients with low, moderate or high expression of the protein.

Results

1648 evaluable image files from 1334 patients were analysed in less than two hours. Visual and automated Ki-67 extent of staining assessments showed a percentage agreement of 87% and weighted kappa value of 0.57. The hazard ratio for distant recurrence for patients with a computer determined moderate Ki-67 extent of staining was 1.77 (95% CI 1.31-2.37) and for high extent 2.34 (95% CI 1.76-3.10), compared to patients with a low extent. In multivariate survival analyses, automated assessment of Ki-67 extent of staining was retained as a significant prognostic factor.

Conclusions

Running high-throughput automated IHC algorithms on a virtual microscopy platform is feasible. Comparison of visual and automated assessments of Ki-67 expression shows moderate agreement. In multivariate survival analysis, the automated assessment of Ki-67 extent of staining is a significant and independent predictor of outcome in breast cancer.