A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics

Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Sinius Pouplier; Abhinav Sharma; Kajsa Ledesma Eriksson; Leena Latonen; Anne-Vibeke Laenkholm; Johan Hartman; Pekka Ruusuvuori; Mattias Rantalainen

doi:10.1038/s41597-023-02422-6

A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics

Philippe Weitz^*, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

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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.

Original language	English
Article number	562
Journal	Scientific Data
Volume	10
Number of pages	6
ISSN	2052-4463
DOIs	https://doi.org/10.1038/s41597-023-02422-6
Publication status	Published - 2023

Bibliographical note

Publisher Copyright:
© 2023, Springer Nature Limited.

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10.1038/s41597-023-02422-6Licence: CC BY

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Cite this

Weitz, P., Valkonen, M., Solorzano, L., Carr, C., Kartasalo, K., Boissin, C., Koivukoski, S., Kuusela, A., Rasic, D., Feng, Y., Pouplier, S. S., Sharma, A., Ledesma Eriksson, K., Latonen, L., Laenkholm, A.-V., Hartman, J., Ruusuvuori, P., & Rantalainen, M. (2023). A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics. Scientific Data, 10, Article 562. https://doi.org/10.1038/s41597-023-02422-6

Weitz, P, Valkonen, M, Solorzano, L, Carr, C, Kartasalo, K, Boissin, C, Koivukoski, S, Kuusela, A, Rasic, D, Feng, Y, Pouplier, SS, Sharma, A, Ledesma Eriksson, K, Latonen, L, Laenkholm, A-V, Hartman, J, Ruusuvuori, P & Rantalainen, M 2023, 'A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics', Scientific Data, vol. 10, 562. https://doi.org/10.1038/s41597-023-02422-6

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title = "A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics",

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.",

author = "Philippe Weitz and Masi Valkonen and Leslie Solorzano and Circe Carr and Kimmo Kartasalo and Constance Boissin and Sonja Koivukoski and Aino Kuusela and Dusan Rasic and Yanbo Feng and Pouplier, {Sandra Sinius} and Abhinav Sharma and {Ledesma Eriksson}, Kajsa and Leena Latonen and Anne-Vibeke Laenkholm and Johan Hartman and Pekka Ruusuvuori and Mattias Rantalainen",

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year = "2023",

doi = "10.1038/s41597-023-02422-6",

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journal = "Scientific Data",

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AU - Weitz, Philippe

AU - Valkonen, Masi

AU - Solorzano, Leslie

AU - Carr, Circe

AU - Kartasalo, Kimmo

AU - Boissin, Constance

AU - Koivukoski, Sonja

AU - Kuusela, Aino

AU - Rasic, Dusan

AU - Feng, Yanbo

AU - Pouplier, Sandra Sinius

AU - Sharma, Abhinav

AU - Ledesma Eriksson, Kajsa

AU - Latonen, Leena

AU - Laenkholm, Anne-Vibeke

AU - Hartman, Johan

AU - Ruusuvuori, Pekka

AU - Rantalainen, Mattias

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

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DO - 10.1038/s41597-023-02422-6

M3 - Journal article

C2 - 37620357

AN - SCOPUS:85168702737

SN - 2052-4463

VL - 10

JO - Scientific Data

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