TY  - JOUR
AU  - Gu, Jun
AU  - Tang, Zhenya
AU  - Chen, Hui
AU  - Sfamenos, Steven
AU  - Geiersbach, Katherine
PY  - 2020
DA  - 2020/05/13
TI  - HER2 FISH for Breast Cancer: Advances in Quantitative Image Analysis and Automation
JO  - OBM Genetics
SP  - 109
VL  - 04
IS  - 02
AB  - Quantitative image analysis of the status of human epidermal growth factor receptor 2 (HER2) by both immunohistochemistry staining and fluorescent in situ hybridization (FISH) is important for the treatment of breast cancer. Guidelines of the American Society for Clinical Oncology and College of American Pathologists, for HER2 FISH, have evolved over time to improve test accuracy, and efforts have been made to better address the problems with the interpretation that are encountered with borderline-positive cases. Standardization and automation of HER2 sample preparation, processing, and digital quantitation are being considered. We compared the manual quantitation of HER2 FISH with automated scoring and reviewed the history and current status of automated scoring of HER2 FISH. We explored areas for the possible automation of the process of HER2 FISH and discussed the latest improvements in quantitative image analysis. We conclude that an integrated review of hematoxylin and eosin staining, immunohistochemistry, and FISH by digital image analysis technology would help pathologists to readily identify tumor areas, differentiate invasive from in situ carcinoma, and to recognize HER2 signal patterns (even in clustered heterogeneity). An integrated system would also allow automatic alerts for discrepancies in results for FISH versus immunohistochemistry, and for tumor histology and grade.
SN  - 2577-5790
UR  - https://doi.org/10.21926/obm.genet.2002109
DO  - 10.21926/obm.genet.2002109
ID  - Gu2020
ER  -