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A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics.
Weitz, Philippe; Valkonen, Masi; Solorzano, Leslie; Carr, Circe; Kartasalo, Kimmo; Boissin, Constance; Koivukoski, Sonja; Kuusela, Aino; Rasic, Dusan; Feng, Yanbo; Sinius Pouplier, Sandra; Sharma, Abhinav; Ledesma Eriksson, Kajsa; Latonen, Leena; Laenkholm, Anne-Vibeke; Hartman, Johan; Ruusuvuori, Pekka; Rantalainen, Mattias.
Afiliação
  • Weitz P; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. philippe.weitz@ki.se.
  • Valkonen M; Institute of Biomedicine, University of Turku, Turku, Finland.
  • Solorzano L; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Carr C; Institute of Biomedicine, University of Turku, Turku, Finland.
  • Kartasalo K; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Boissin C; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Koivukoski S; Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland.
  • Kuusela A; Institute of Biomedicine, University of Turku, Turku, Finland.
  • Rasic D; Department of Surgical Pathology, Zealand University Hospital, Roskilde, Denmark.
  • Feng Y; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Sinius Pouplier S; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Sharma A; Department of Surgical Pathology, Zealand University Hospital, Roskilde, Denmark.
  • Ledesma Eriksson K; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Latonen L; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Laenkholm AV; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Hartman J; Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland.
  • Ruusuvuori P; Foundation for the Finnish Cancer Institute, Helsinki, Finland.
  • Rantalainen M; Department of Surgical Pathology, Zealand University Hospital, Roskilde, Denmark.
Sci Data ; 10(1): 562, 2023 08 24.
Article em En | MEDLINE | ID: mdl-37620357
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama Tipo de estudo: Diagnostic_studies / Guideline Limite: Female / Humans Idioma: En Revista: Sci Data Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suécia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama Tipo de estudo: Diagnostic_studies / Guideline Limite: Female / Humans Idioma: En Revista: Sci Data Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suécia