title: Simultaneous automatic scoring and co-registration of hormone receptors in tumor areas in whole slide images of breast cancer tissue slides.
abstract: Automation of downstream analysis may offer many potential benefits to routine histopathology. One area of interest for automation is in the scoring of multiple immunohistochemical markers to predict the patient's response to targeted therapies. Automated serial slide analysis of this kind requires robust registration to identify common tissue regions across sections. We present an automated method for co-localized scoring of Estrogen Receptor and Progesterone Receptor (ER/PR) in breast cancer core biopsies using whole slide images. Regions of tumor in a series of fifty consecutive breast core biopsies were identified by annotation on H&E whole slide images. Sequentially cut immunohistochemical stained sections were scored manually, before being digitally scanned and then exported into JPEG 2000 format. A two-stage registration process was performed to identify the annotated regions of interest in the immunohistochemistry sections, which were then scored using the Allred system. Overall correlation between manual and automated scoring for ER and PR was 0.944 and 0.883, respectively, with 90% of ER and 80% of PR scores within in one point or less of agreement. This proof of principle study indicates slide registration can be used as a basis for automation of the downstream analysis for clinically relevant biomarkers in the majority of cases. The approach is likely to be improved by implantation of safeguarding analysis steps post registration. © 2016 International Society for Advancement of Cytometry.
authors.affiliation: Department of Computer Science, University of Warwick, Coventry, United Kingdom.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Trahearn
authors.affiliation: Department of Pathology, University of Warwick, Coventry, United Kingdom.|Centre of Excellence for Digital Pathology, University Hospitals Coventry and Warwickshire, Coventry, United Kingdom.
authors.forename: Yee Wah
authors.initials: YW
authors.lastname: Tsang
authors.affiliation: Centre of Excellence for Digital Pathology, University Hospitals Coventry and Warwickshire, Coventry, United Kingdom.
authors.forename: Ian A
authors.initials: IA
authors.lastname: Cree
authors.affiliation: Department of Pathology, University of Warwick, Coventry, United Kingdom.|Centre of Excellence for Digital Pathology, University Hospitals Coventry and Warwickshire, Coventry, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Snead
authors.affiliation: Mathematics Institute, University of Warwick, Coventry, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Epstein
authors.affiliation: Department of Computer Science, University of Warwick, Coventry, United Kingdom.|Centre of Excellence for Digital Pathology, University Hospitals Coventry and Warwickshire, Coventry, United Kingdom.
authors.forename: Nasir
authors.initials: N
authors.lastname: Rajpoot
mesh_terms: D057205:Automation, Laboratory; D014408:Biomarkers, Tumor / Q000235:genetics*; D062005:Biopsy, Large-Core Needle; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D004801:Eosine Yellowish-(YS); D005260:Female; D015870:Gene Expression; D006416:Hematoxylin; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry / Q000379:methods; D011960:Receptors, Estrogen / Q000235:genetics*; D011980:Receptors, Progesterone / Q000235:genetics*; D012107:Research Design / Q000706:statistics & numerical data*
chemical_list: D014408:Biomarkers, Tumor; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; D004801:Eosine Yellowish-(YS); D006416:Hematoxylin
keywords: automation; breast; estrogen receptors; immunohistochemistry; molecular pathology; progesterone receptors