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

Author:

Weitz PhilippeORCID,Valkonen MasiORCID,Solorzano Leslie,Carr Circe,Kartasalo KimmoORCID,Boissin Constance,Koivukoski SonjaORCID,Kuusela Aino,Rasic DusanORCID,Feng Yanbo,Sinius Pouplier SandraORCID,Sharma Abhinav,Ledesma Eriksson Kajsa,Latonen LeenaORCID,Laenkholm Anne-Vibeke,Hartman JohanORCID,Ruusuvuori Pekka,Rantalainen Mattias

Abstract

AbstractThe 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.

Funder

Vetenskapsrådet

Cancerfonden

VINNOVA

ERA PerMed, MedTechLabs, Swedish e-science Research Centre, SweLife

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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