Improved concordance of challenging human epidermal growth factor receptor 2 dual in‐situ hybridisation cases with the use of a digital image analysis algorithm in breast cancer

Author:

Gough Madeline12ORCID,Liu Cheng13,Srinivasan Bhuvana1,Wilkinson Lisa1,Dunk Louisa1,Yang Yuanhao2ORCID,Schreiber Veronika2,Tuffaha Haitham4ORCID,Kryza Thomas2ORCID,Hooper John D2ORCID,Lakhani Sunil R56ORCID,Snell Cameron E127ORCID

Affiliation:

1. Mater Pathology, Duncombe Building, Raymond Terrace South Brisbane Australia

2. Mater Research Institute, Translational Research Institute Woolloongabba Australia

3. Faculty of Medicine The University of Queensland Herston Australia

4. Centre for the Business and Economics of Health The University of Queensland St Lucia Australia

5. Centre for Clinical Research The University of Queensland Herston Australia

6. Pathology Queensland The Royal Brisbane Women's Hospital Herston Australia

7. Anatomical Pathology Peter MacCallum Cancer Centre Melbourne Australia

Abstract

AimsAccurate assessment of human epidermal growth factor receptor 2 (HER2) expression by HER2 immunohistochemistry and in‐situ hybridisation (ISH) is critical for the management of patients with breast cancer. The revised 2018 ASCO/CAP guidelines define 5 groups based on HER2 expression and copy number. Manual pathologist quantification by light microscopy of equivocal and less common HER2 ISH groups (groups 2–4) can be challenging, and there are no data on interobserver variability in reporting of these cases. We sought to determine whether a digital algorithm could improve interobserver variability in the assessment of difficult HER2 ISH cases.Methods and resultsHER2 ISH was evaluated in a cohort enriched for less common HER2 patterns using standard light microscopy versus analysis of whole slide images using the Roche uPath HER2 dual ISH image analysis algorithm. Standard microscopy demonstrated significant interobserver variability with a Fleiss's kappa value of 0.471 (fair–moderate agreement) improving to 0.666 (moderate–good) with the use of the algorithm. For HER2 group designation (groups 1–5), there was poor–moderate reliability between pathologists by microscopy [intraclass correlation coefficient (ICC) = 0.526], improving to moderate–good agreement (ICC = 0.763) with the use of the algorithm. In subgroup analysis, the algorithm improved concordance particularly in groups 2, 4 and 5. Time to enumerate cases was also significantly reduced.ConclusionThis work demonstrates the potential of a digital image analysis algorithm to improve the concordance of pathologist HER2 amplification status reporting in less common HER2 groups. This has the potential to improve therapy selection and outcomes for patients with HER2‐low and borderline HER2‐amplified breast cancers.

Funder

Mater Foundation

Roche Diagnostics

Publisher

Wiley

Subject

General Medicine,Histology,Pathology and Forensic Medicine

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