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01.12.2017 | Research | Ausgabe 1/2017 Open Access

Diagnostic Pathology 1/2017

Data integration from pathology slides for quantitative imaging of multiple cell types within the tumor immune cell infiltrate

Diagnostic Pathology > Ausgabe 1/2017
Zhaoxuan Ma, Stephen L. Shiao, Emi J. Yoshida, Steven Swartwood, Fangjin Huang, Michael E. Doche, Alice P. Chung, Beatrice S. Knudsen, Arkadiusz Gertych
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s13000-017-0658-8) contains supplementary material, which is available to authorized users.



Immune cell infiltrates (ICI) of tumors are scored by pathologists around tumor glands. To obtain a better understanding of the immune infiltrate, individual immune cell types, their activation states and location relative to tumor cells need to be determined. This process requires precise identification of the tumor area and enumeration of immune cell subtypes separately in the stroma and inside tumor nests. Such measurements can be accomplished by a multiplex format using immunohistochemistry (IHC).


We developed a pipeline that combines immunohistochemistry (IHC) and digital image analysis. One slide was stained with pan-cytokeratin and CD45 and the other slide with CD8, CD4 and CD68. The tumor mask generated through pan-cytokeratin staining was transferred from one slide to the other using affine image co-registration. Bland-Altman plots and Pearson correlation were used to investigate differences between densities and counts of immune cell underneath the transferred versus manually annotated tumor masks. One-way ANOVA was used to compare the mask transfer error for tissues with solid and glandular tumor architecture.


The overlap between manual and transferred tumor masks ranged from 20%–90% across all cases. The error of transferring the mask was 2- to 4-fold greater in tumor regions with glandular compared to solid growth pattern (p < 10−6). Analyzing data from a single slide, the Pearson correlation coefficients of cell type densities outside and inside tumor regions were highest for CD4 + T-cells (r = 0.8), CD8 + T-cells (r = 0.68) or CD68+ macrophages (r = 0.79). The correlation coefficient for CD45+ T- and B-cells was only 0.45. The transfer of the mask generated an error in the measurement of intra- and extra- tumoral CD68+, CD8+ or CD4+ counts (p < 10−10).


In summary, we developed a general method to integrate data from IHC stained slides into a single dataset. Because of the transfer error between slides, we recommend applying the antibody for demarcation of the tumor on the same slide as the ICI antibodies.
Additional file 1:Fig. S1 Visualization of staining components used to generate a 3-D cell density map of cancer areas. (a) A whole-slide multicolor RGB bright-field image of breast cancer tissue stained for CD45 (brown), Pan-CK (red) and a hematoxylin nuclear counter-stain (blue). (b-d) The whole-slide multicolor RGB image was color-deconvoluted to separate the staining components: (b) CD45+ image, (c) Pan-CK+ image, and (d) hematoxylin image. (e) A 3-D cell density map of Pan-CK-positive cells (which demarcates areas of epithelial cells) was derived from the Pan-CK component image. Areas of benign glands and in-situ ductal carcinoma were visually excluded by a pathologist. A threshold applied to the map lead to the identification of cancer areas which were processed to segment out a cancer mask. (f) The locations of the cancer mask were transferred to a tissue image with no Pan-CK staining to enable the enumeration of immune cells in IHC stained slides. Fig. S2 Transfer of cancer mask from slide-1 to slide-2. The cancer mask is generated in slide-1 based on Pan-CK staining. Hematoxylin-stained nuclei in slide-1 are identified and co-registered with corresponding, hematoxylin-stained nuclei in slide-2. A transformation matrix is established based on co-registered nuclei to transform the cancer mask in slide-1 for alignment with slide-2 in the whole ROI. After co-registration the cancer mask is transferred from slide-1 to slide-2. (PPTX 1673 kb)
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