Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists

Abstract

Context.— Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing. Objective.— To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) for breast cancer where QIA is used. Design.— The College of American Pathologists (CAP) convened a panel of pathologists, histotechnologists, and computer scientists with expertise in image analysis, immunohistochemistry, quality management, and breast pathology to develop recommendations for QIA of HER2 IHC in breast cancer. A systematic review of the literature was conducted to address 5 key questions. Final recommendations were derived from strength of evidence, open comment feedback, expert panel consensus, and advisory panel review. Results.— Eleven recommendations were drafted: 7 based on CAP laboratory accreditation requirements and 4 based on expert consensus opinions. A 3-week open comment period received 180 comments from more than 150 participants. Conclusions.— To improve accurate, precise, and reproducible interpretation of HER2 IHC results for breast cancer, QIA and procedures must be validated before implementation, followed by regular maintenance and ongoing evaluation of quality control and quality assurance. HER2 QIA performance, interpretation, and reporting should be supervised by pathologists with expertise in QIA.

Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association

“…HER2 analysis performance, interpretation, and reporting should be supervised by pathologists with expertise in image analysis. [137]…”

HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides

“…Taken together, the clinical pathology and DP vendor communities seem to be beginning to appreciate the importance of quantifiable QC processes for engendering DP workflows. 26 Before DP systems can be used within a clinical setting, slide scanners themselves must receive regulatory approval. Scanner manufacturers have been attempting to quantitatively assess the reproducibility of scanner-generated images, especially to ensure consistency of image quality over time.…”

“…27,28 With penetration of these scanners into clinical workflows, these types of validation studies may become enshrined as part of the routine quality assurance and maintenance of the scanners. 26 As such, from both regulatory and maintenance standpoints, a single automated QC pipeline like HistoQC can provide quantitative metrics for benchmarking the quality and consistency of scanner-generated DP images.…”

Commentary: Guideline for Performing Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Quantitative Image Analysis well

“…Biomarker testing in breast cancer is an important activity for pathology laboratories and the patients they serve. A recent guideline[1] from the College of American Pathologists (CAP) provides timely guidance on implementing and performing quantitative image analysis (QIA) for human epidermal growth factor receptor 2 (HER2) for breast cancer. This document provides a nice complement to the recently updated joint CAP/American Society of Clinical Oncology (ASCO) guideline related to HER2 testing in breast cancer[2] for those laboratories using or contemplating QIA for HER2.…”