Deep Learning Image Analysis of Benign Breast Disease to Identify Subsequent Risk of Breast Cancer.
Journal:
JNCI cancer spectrum
PMID:
33644680
Abstract
BACKGROUND: New biomarkers of risk may improve breast cancer (BC) risk prediction. We developed a computational pathology method to segment benign breast disease (BBD) whole slide images into epithelium, fibrous stroma, and fat. We applied our method to the BBD BC nested case-control study within the Nurses' Health Studies to assess whether computer-derived tissue composition or a morphometric signature was associated with subsequent risk of BC.