Prediction of breast cancer molecular subtypes using radiomics signatures of synthetic mammography from digital breast tomosynthesis

• Published in: Scientific reports Vol. 10; no. 1; pp. 21566 - 11
• Main Authors: Son, Jinwoo, Lee, Si Eun, Kim, Eun-Kyung, Kim, Sungwon
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.12.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 631/67/1347; 631/67/2321; Adult; Aged; Biomarkers, Tumor - genetics; Breast cancer; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - genetics; Breast Neoplasms - pathology; ErbB-2 protein; Female; Humanities and Social Sciences; Humans; Invasiveness; Mammography; Mammography - methods; Middle Aged; multidisciplinary; Multivariate analysis; Patients; Radiomics; Receptor, ErbB-2 - genetics; Retrospective Studies; Science; Science (multidisciplinary)

We aimed to predict molecular subtypes of breast cancer using radiomics signatures extracted from synthetic mammography reconstructed from digital breast tomosynthesis (DBT). A total of 365 patients with invasive breast cancer with three different molecular subtypes (luminal A + B, luminal; HER2-pos...