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A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics
Philippe Weitz1, Masi Valkonen2, Leslie Solorzano3
1Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. philippe.weitz@ki.se.
Insights
This study introduces the largest public dataset of whole slide images (WSIs) for breast cancer, featuring matched hematoxylin and eosin (H&E) and immunohistochemistry (IHC) stains from the same tumors. This resource supports advancements in computational pathology for biomarker analysis.
Area of Science:
- Pathology
- Computational Biology
- Oncology
Background:
- Hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining of FFPE breast cancer tissue sections are crucial for pathological assessment.
- IHC is widely used for biomarker status (ER, PGR, HER2, KI67) in diagnostics.
- Computational pathology shows promise for biomarker assessment using whole slide images (WSIs).
Purpose of the Study:
- To address the scarcity of public data for computational pathology in breast cancer research.
- To create the largest publicly available dataset of matched H&E and IHC WSIs from primary breast cancer specimens.
Main Methods:
- Collected FFPE tissue sections from surgical resections of female primary breast cancer patients.
- Stained sections with H&E and various IHC markers.
- Acquired whole slide images (WSIs) for all stained sections.
- Matched WSIs from H&E and IHC stains from the same tumor tissue.
Main Results:
- Published the largest public dataset to date containing matched H&E and IHC WSIs.
- The dataset comprises 4,212 WSIs from 1,153 primary breast cancer patients.
- This dataset represents a significant resource for developing and validating computational pathology algorithms.
Conclusions:
- The newly released dataset significantly enhances the availability of high-quality, matched imaging data for breast cancer research.
- Facilitates the development of advanced computational tools for more accurate and efficient biomarker analysis.
- Aims to accelerate progress in precision medicine for breast cancer through improved image analysis techniques.
Abstract:
The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is essential for the pathologic assessment of surgically resected breast cancer specimens. IHC staining has been broadly adopted into diagnostic guidelines and routine workflows to assess the status of several established biomarkers, including ER, PGR, HER2 and KI67. Biomarker assessment can also be facilitated by computational pathology image analysis methods, which have made numerous substantial advances recently, often based on publicly available whole slide image (WSI) data sets. However, the field is still considerably limited by the sparsity of public data sets. In particular, there are no large, high quality publicly available data sets with WSIs of matching IHC and H&E-stained tissue sections from the same tumour. Here, we publish the currently largest publicly available data set of WSIs of tissue sections from surgical resection specimens from female primary breast cancer patients with matched WSIs of corresponding H&E and IHC-stained tissue, consisting of 4,212 WSIs from 1,153 patients.
