Abstract
Breast cancer is one of the common malignant tumors in women. It seriously endangers women’s life and health. The human epidermal growth factor receptor 2 (HER2) protein is responsible for the division and growth of healthy breast cells. The overexpression of the HER2 protein is generally evaluated by immunohistochemistry (IHC). The IHC evaluation criteria mainly includes three indexes: staining intensity, circumferential membrane staining pattern, and proportion of positive cells. Manually scoring HER2 IHC images is an error-prone, variable, and time-consuming work. To solve these problems, this study proposes an automated predictive method for scoring whole-slide images (WSI) of HER2 slides based on a deep learning network. A total of 95 HER2 pathological slides from September 2021 to December 2021 were included. The average patch level precision and f1 score were 95.77% and 83.09%, respectively. The overall accuracy of automated scoring for slide-level classification was 97.9%. The proposed method showed excellent specificity for all IHC 0 and 3+ slides and most 1+ and 2+ slides. The evaluation effect of the integrated method is better than the effect of using the staining result only.
Funder
Informatization Plan of the Chinese Academy of Sciences
National Key Research and Development Program of China
Strategic Priority Research Program of the Chinese Academy of Sciences
Reference41 articles.
1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries;Sung;CA Cancer J. Clin.,2021
2. The Cancer Genome Atlas Network (2012). Comprehensive Molecular Portraits of Human Breast Tumours. Nature, 490, 61–70.
3. Female Breast Cancer Status According to ER, PR and HER2 Expression: A Population Based Analysis;Caldarella;Pathol. Oncol. Res. POR,2011
4. Recommendations for Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline Update;Wolff;Arch. Pathol. Lab. Med.,2013
5. Hao, J., and Li, J. (2021). Guidelines of Chinese Society of Clinical Oncology (CSCO) Brest Cancer 2021, People’s Medical Publishing House. [1st ed.].