Fully Automated Artificial Intelligence Solution for Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Scoring in Breast Cancer: A Multireader Study
This study demonstrated utility of a fully automated AI solution to aid in scoring HER2 IHC accurately according to ASCO/CAP 2018/2023 guidelines. Pathologists supported by AI showed improvements in HER2 IHC scoring consistency and accuracy, especially for distinguishing HER2 0 from 1+ cases. This AI solution could be used by pathologists as a decision support tool for enhancing reproducibility and consistency of HER2 scoring and particularly for identifying HER2-low breast cancers.
Authors
- Marina Maklakovski
- Stuart J. Schnitt (ORCID: https://orcid.org/0000-0002-3608-7828)
- Judith Sandbank (ORCID: https://orcid.org/0000-0002-4228-3358)
- Savitri Krishnamurthy (ORCID: https://orcid.org/0000-0001-9030-4136)
- Anne Vincent‐Salomon (ORCID: https://orcid.org/0000-0001-5754-5771)
- Giuseppe Mallel (ORCID: https://orcid.org/0000-0002-8673-7526)
- Eugenia Colón (ORCID: https://orcid.org/0000-0003-2416-6518)
- Yuval Globerson
- Manuela Vecsler (ORCID: https://orcid.org/0000-0002-7951-4885)
- Jeanne Thomassin‐Piana (ORCID: https://orcid.org/0000-0002-5264-2705)
- Kanchan Kantekure
- Lilach Bien
- Chaim Linhart
- Maya Grinwald
- Rita Canas‐Marques (ORCID: https://orcid.org/0000-0002-7184-4230)
- W Finck
Institutions
- Champalimaud Foundation (PT)
- Brigham and Women's Hospital (US)
- Beth Israel Deaconess Medical Center (US)
- The University of Texas MD Anderson Cancer Center (US)
- Harvard University (US)
- Université Paris Sciences et Lettres (FR)
- Assuta Medical Center (IL)
- Saint Göran Hospital (SE)
- Dana-Farber Cancer Institute (US)
- Institut Curie (FR)
Publication Details
- Journal
- JCO Precision Oncology
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1200/po.24.00353
- Citations
- 18
- Primary Topic
- HER2/EGFR in Cancer Research
- Type
- article
- Field-Weighted Citation Impact
- 5.09
Funders
- University of Texas MD Anderson Cancer Center