Prediction of genetic profile of breast carcinoma on MRI using a combination of DCE-MRI, DWI, and MR spectroscopy: A prospective observational study

Abstract

Background: Classification of breast cancer based on gene expression has emerged as the standard approach in its management, owing to the distinct prognoses and treatment responses observed among different subtypes. The aim of this study was to prospectively assess the imaging features of the molecular subtypes of breast cancer using multiparametric magnetic resonance imaging (mMRI) with the combined assessment of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion-weighted imaging (DWI), and MR spectroscopy (MRS).

Methods: This was a prospective observational single-center cohort study, which included women with BI-RADS 4–5 lesions on mammography/ultrasound (US) who subsequently underwent 1.5 T MRI (encompassing DCE-MRI, DWI, and MRS). The histological subtypes of breast cancer were assessed. Estrogen receptor (ER), progesterone receptor (PR), Ki-67 status, and human epidermal growth receptor-2 (HER2) expression, assessed by immunohistochemistry (IHC), defined four molecular subtypes: luminal A, luminal B, HER2-enriched (Her2en), and triple-negative breast carcinoma (TNBC). Statistical associations between the four molecular subtypes and MRI features were investigated.

Results: Fifty patients were included in the study. Circumscribed margins were significantly correlated with triple-negative tumors compared to others (78% versus 6%, p < 0.001). Spiculated margins were observed in nontriple negative tumors. Rim enhancement was significantly correlated to triple-negative tumors compared to all other subtypes (71.4% versus 25%, p = 0.035). Mean apparent diffusion coefficient (ADC) values were significantly lower for luminal subtypes compared to non-luminal subtypes (p < 0.001). The total choline (tCho) signal-to-noise ratio (SNR) was higher in triple-negative tumors. A combined algorithm using DCE-MRI, DWI, and MRS can predict TNBC and Her2en with specificity of 86.6% and 100%, respectively, and sensitivity of 100% and 85.37%, respectively.

Conclusion: The combination of mMRI with DCE-MRI, DWI, and MRS can accurately differentiate the molecular subtypes of breast carcinoma.

Keywords

breast cancer / multiparametric magnetic resonance imaging / diffusion-weighted imaging / MR spectroscopy / algorithm

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2024 The Author(s). Malignancy Spectrum published by John Wiley & Sons Australia, Ltd on behalf of Higher Education Press.