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. 2018 May;169(1):33-42.
doi: 10.1007/s10549-018-4669-2. Epub 2018 Jan 18.

Digital image analysis of Ki67 proliferation index in breast cancer using virtual dual staining on whole tissue sections: clinical validation and inter-platform agreement

Timco Koopman  1 , Henk J Buikema  1 , Harry Hollema  1 , Geertruida H de Bock  2 , Bert van der Vegt  3
Affiliations

Digital image analysis of Ki67 proliferation index in breast cancer using virtual dual staining on whole tissue sections: clinical validation and inter-platform agreement

Timco Koopman et al. Breast Cancer Res Treat. 2018 May.

Abstract

Purpose: The Ki67 proliferation index is a prognostic and predictive marker in breast cancer. Manual scoring is prone to inter- and intra-observer variability. The aims of this study were to clinically validate digital image analysis (DIA) of Ki67 using virtual dual staining (VDS) on whole tissue sections and to assess inter-platform agreement between two independent DIA platforms.

Methods: Serial whole tissue sections of 154 consecutive invasive breast carcinomas were stained for Ki67 and cytokeratin 8/18 with immunohistochemistry in a clinical setting. Ki67 proliferation index was determined using two independent DIA platforms, implementing VDS to identify tumor tissue. Manual Ki67 score was determined using a standardized manual counting protocol. Inter-observer agreement between manual and DIA scores and inter-platform agreement between both DIA platforms were determined and calculated using Spearman's correlation coefficients. Correlations and agreement were assessed with scatterplots and Bland-Altman plots.

Results: Spearman's correlation coefficients were 0.94 (p < 0.001) for inter-observer agreement between manual counting and platform A, 0.93 (p < 0.001) between manual counting and platform B, and 0.96 (p < 0.001) for inter-platform agreement. Scatterplots and Bland-Altman plots revealed no skewness within specific data ranges. In the few cases with ≥ 10% difference between manual counting and DIA, results by both platforms were similar.

Conclusions: DIA using VDS is an accurate method to determine the Ki67 proliferation index in breast cancer, as an alternative to manual scoring of whole sections in clinical practice. Inter-platform agreement between two different DIA platforms was excellent, suggesting vendor-independent clinical implementability.

Keywords: Breast cancer; Digital image analysis (DIA); Immunohistochemistry (IHC); Inter-platform agreement; Ki67 proliferation index; Virtual dual staining.

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Conflict of interest statement

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical standards

All patient material was handled according to the ‘Code of conduct for health research’ of the Dutch Federation of Biomedical Scientific Societies [25]. Therefore, all experiments were performed in accordance to Dutch law and no additional permission from our Ethics Committee was required.

Figures

Fig. 1
Fig. 1
Digital image analysis of Ki67 with virtual dual staining. Corresponding cytokeratin (a) and Ki67 (b) stains are virtually aligned and Ki67 nuclear classification is determined among the cells in the area classified as tumor, shown in platform A (c, d) and platform B (e, f). Images at 200× magnification
Fig. 2
Fig. 2
Scatterplots with correlation coefficients (left) and Bland–Altman plots of agreement (right) between whole tumor Ki67 proliferation index by manual counting versus platform A (upper row), manual counting versus platform B (middle row), and platform A versus platform B (lower row)
Fig. 3
Fig. 3
Cases with ≥ 10% difference in Ki67 proliferation index between digital image analysis and manual counting due to tumor morphology or staining artifacts. One case had clear cell morphology, causing erroneous tumor classification (a–c). Two cases had nuclear overlap and cell clustering (d), causing misclassification of Ki67 both by platform A (e) and platform B (f). In one case, artifactual cytoplasmic Ki67 staining (g) was correctly handled by platform A (h) but was classified as positive nuclear staining by platform B (i). One case with hematoxylin overstaining (j) led to false-positive classification of nuclei by platform A (k) but not by platform B (l). Images at 200× magnification
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