Work

Computational pathology in the identification of HER2-low breast cancer: Opportunities and challenges

Year: 2023

Type: review

Abstract: For the past 2 decades, pathologists have been accustomed to reporting the HER2 status of breast cancer as either positive or negative, based on HER2 IHC. Today, however, there is a clinical imperative to employ a 3-tier approach to interpreting HER2 IHC that can also identify tumours categorised as HER2-low. Meeting this need for a finer degree of discrimination may be challenging, and in this article, we consider the potential for the integration of computational approaches to support pathologists in achieving accurate and reproducible HER2 IHC scoring as well as outlining some of the practicalities involved.

Source: Journal of Pathology Informatics

DOI: 10.1016/j.jpi.2023.100343

Authors: Marie Brevet, Zaibo Li, Anil Parwani

Institution: The Ohio State University

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,400