Objectives: To test whether 3 T multiparametric magnetic resonance imaging (mMRI) provides information related to molecular subtypes of breast cancer.
Methods: Women with mammographic or US findings of breast lesions (BI-RADS 4-5) underwent 3 T mMRI (DCE, DWI and MR spectroscopy). The histological type of breast cancer was assessed. Estrogen-receptor (ER), progesterone-receptor (PgR), Ki-67 status and HER-2 expression, assessed by immunohistochemistry (IHC), defined four molecular subtypes: Luminal-A, Luminal-B, HER2-enriched and triple-negative. Non-parametric tests (Kruskal-Wallis, k-sample equality of medians, and Mann-Whitney), logistic regression or ANOVA, and a multivariate analysis were performed to investigate correlations between the four molecular subtypes and mMRI (lesion volume, margins or distribution, enhancement pattern, ADC, type of kinetic curve, and total choline (tCho) signal-to-noise-ratio (SNR)). A ROC analysis was finally performed to test the diagnostic power of a multivariate logistic regression model.
Results: 433 patients (453 lesions) were considered. Volume was smaller in Luminal-B and larger in triple-negative tumours compared to the other subtypes combined. Margins were significantly correlated to Luminal-A and Luminal-B. The type of curve was significantly correlated to Luminal-A. ADC values were higher in Luminal-A. tCho SNR was higher in triple-negative tumours. The ROC analysis showed that the area under the curve (AUC) significantly improved when multiple MRI features were used compared to individual parameters.
Conclusions: A significant correlation was found between some MRI features and molecular subtypes of breast tumours. A multiparametric approach improved the diagnostic power of MRI. However, further research is needed in order to predict the molecular subtype on the sole basis of mMRI.
Keywords: Breast; Breast cancer; Magnetic resonance imaging; Prognostic factors; Triple negative breast neoplasms.
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