Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes

Zhiqi Yang; Xiaofeng Chen; Tianhui Zhang; Fengyan Cheng; Yuting Liao; Xiangguan Chen; Zhuozhi Dai; Weixiong Fan

doi:10.3389/fonc.2021.628824

Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes

Front Oncol. 2021 Sep 16:11:628824. doi: 10.3389/fonc.2021.628824. eCollection 2021.

Authors

Zhiqi Yang^{1

2}, Xiaofeng Chen^{1

2}, Tianhui Zhang¹, Fengyan Cheng¹, Yuting Liao³, Xiangguan Chen^{1

2}, Zhuozhi Dai⁴, Weixiong Fan¹

Affiliations

¹ Department of Radiology, Meizhou People's Hospital, Meizhou, China.
² Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.
³ Pharmaceutical Diagnostics, GE Healthcare, Guangzhou, China.
⁴ Department of Radiology, Shantou Central Hospital, Shantou, China.

Abstract

Objectives: To assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques.

Methods: A total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor, progesterone receptor, human epidermal growth factorreceptor-2 (HER-2) status, and the Ki-67 proliferation index were collected for analysis. Quantitative parameters (K^trans, V_e, K_ep), semiquantitative parameters (W_-in, W_-out, TTP), and apparent diffusion coefficient (ADC) values were compared in relation to breast cancer receptor status and molecular subtypes. Statistical analysis were performed to compare the parameters in the receptor status and molecular subtype groups.Multivariate analysis was performed to explore confounder-adjusted associations, and receiver operating characteristic curve analysis was used to assess the classification performance and calculate thresholds.

Results: Younger age (<49.5 years, odds ratio (OR) =0.95, P=0.004), lower K_ep (<0.704,OR=0.14, P=0.044),and higher TTP (>0.629 min, OR=24.65, P=0.011) were independently associated with progesterone receptor positivity. A higher TTP (>0.585 min, OR=28.19, P=0.01) was independently associated with estrogen receptor positivity. Higher K_ep (>0.892, OR=11.6, P=0.047), lower TTP (<0.582 min, OR<0.001, P=0.004), and lower ADC (<0.719 ×10^-3 mm²/s, OR<0.001, P=0.048) had stronger independent associations with triple-negative breast cancer (TNBC) compared to luminal A, and those parameters could differentiate TNBC from luminal A with the highest AUC of 0.811.

Conclusions: K_ep and TTP were independently associated with hormone receptor status. In addition, the K_ep, TTP, and ADC values had stronger independent associations with TNBC than with luminal A and could be used as imaging biomarkers for differentiate TNBC from Luminal A.

Keywords: breast neoplasms; diffusion weighted imaging; dynamic contrast enhanced magnetic resonance imaging (DCE-MRI); magnetic resonance imaging; molecular subtypes; pharmacokinetics; receptor status.