Correlation between imaging features and molecular subtypes of breast cancer in young women (≤30 years old).

OBJECTIVES To analyze the features of digital mammography (DM) plus digital breast tomosynthesis (DBT), ultrasonography (US) and magnetic resonance imaging (MRI) of breast cancer in young women (≤30 years old) and the correlation with molecular subtypes. MATERIALS AND METHODS We performed a retrospective study of imaging features of consecutive young women aged ≤30 years who were treated and surgically confirmed with breast cancer between January 2013 and December 2019 in our institution. All patients were Chinese women. DM + DBT and US were available for 170 lesions, MRI for 41 lesions. The imaging features were analysed by univariate and multivariate logistic regression analyses to find the predictive factors of the molecular subtypes. RESULTS The predictive factors of the luminal B(HER2-) subtype (n = 51) were the mass with microcalcifications, irregular shape, spiculated margins, and shadowing posterior features (all P < 0.01). The predictive factors of the luminal B(HER2+) subtype (n = 26) were the spiculated margins (DBT + DM), angular margins (US), shadowing posterior features, and high vascularity (all P < 0.05). The predictive factors of the luminal A subtype (n = 37) were the mass without microcalcifications, spiculated margins, shadowing posterior features, and low vascularity (all P < 0.05). The predictive factors of the triple-negative subtype (n = 31) were the mass without microcalcifications, oval/round shape, circumscribed margins, enhancement of posterior features, and rim enhancement (MRI) (all P < 0.005). The predictive factors of the human-epidermal-growth-factor-receptor-2-enriched subtype (n = 26) were the only microcalcifications, microlobulated margins, and combined posterior feature (all P < 0.05). CONCLUSION Compared with the general population of breast cancer, this young female population presents a different molecular phenotype distribution. Some imaging features of breast cancer in young women ≤30 years old can be used to predict certain tumor molecular subtypes.