TY - JOUR
T1 - A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics
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 - Sinius Pouplier, Sandra
AU - Sharma, Abhinav
AU - Ledesma Eriksson, Kajsa
AU - Latonen, Leena
AU - Laenkholm, Anne Vibeke
AU - Hartman, Johan
AU - Ruusuvuori, Pekka
AU - Rantalainen, Mattias
N1 - Funding Information:
We acknowledge support from Stratipath and Karolinska Institutet sponsoring the ACROBAT challenge prize; MICCAI society for hosting the ACROBAT challenge, and Nguyen Thuy Duong Tran for support with digitising histopathology slides. We acknowledge funding from: Vetenskapsrådet (Swedish Research Council), Cancerfonden (Swedish Cancer Society), ERA PerMed (ERAPERMED2019-224-ABCAP), MedTechLabs, Swedish e-science Research Centre (SeRC), VINNOVA, SweLife, Academy of Finland (#341967, #334782, #335976, #334774), Cancer Foundation Finland, University of Turku Graduate School, Turku University Foundation, Oskar Huttunen Foundation, David and Astrid Hägelén Foundation.
Publisher Copyright:
© 2023, Springer Nature Limited.
PY - 2023/8
Y1 - 2023/8
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.
U2 - 10.1038/s41597-023-02422-6
DO - 10.1038/s41597-023-02422-6
M3 - Data article
C2 - 37620357
AN - SCOPUS:85168702737
SN - 2052-4463
VL - 10
JO - Scientific Data
JF - Scientific Data
M1 - 562
ER -
