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Logo of bmcclpaBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Clinical Pathology
 
BMC Clin Pathol. 2011; 11: 3.
Published online 2011 January 25. doi:  10.1186/1472-6890-11-3
PMCID: PMC3040126
Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer
Juho Konsti,corresponding author1 Mikael Lundin,1 Heikki Joensuu,2,3 Tiina Lehtimäki,1 Harri Sihto,3 Kaija Holli,4 Taina Turpeenniemi-Hujanen,5 Vesa Kataja,6,7 Liisa Sailas,6 Jorma Isola,8 and Johan Lundin1,9
1FIMM - Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
2Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland
3Molecular and Cancer Biology Research Program, Biomedicum Helsinki, University of Helsinki, Helsinki, Finland
4University of Tampere and Department of Oncology, Tampere University Hospital, Tampere, Finland
5Department of Oncology and Radiotherapy, Oulu University Central Hospital, Oulu, Finland
6Department of Oncology, Kuopio University Hospital, Kuopio, Finland
7Department of Oncology, Vaasa Central Hospital, Vaasa, Finland
8Institute of Medical Technology, University of Tampere, Tampere, Finland
9Division of Global Health, Karolinska Institutet, Stockholm, Sweden
corresponding authorCorresponding author.
Juho Konsti: juho.konsti/at/helsinki.fi; Mikael Lundin: mikael.lundin/at/helsinki.fi; Heikki Joensuu: heikki.joensuu/at/hus.fi; Tiina Lehtimäki: tiina.lehtimaki/at/helsinki.fi; Harri Sihto: harri.sihto/at/helsinki.fi; Kaija Holli: kaija.holli/at/uta.fi; Taina Turpeenniemi-Hujanen: turpeenniemi.hujanen/at/ppshp.fi; Vesa Kataja: Vesa.Kataja/at/kuh.fi; Liisa Sailas: Liisa.Sailas/at/kuh.fi; Jorma Isola: jorma.isola/at/uta.fi; Johan Lundin: johan.lundin/at/helsinki.fi
Received July 23, 2010; Accepted January 25, 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.
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