Title:MRI Manifestations of Breast Cancer Stroma and their Role in Predicting
Molecular Subtype: A Case-control Study
Volume: 20
Author(s): Lanyun Wang, Wenjing Li, Wenjun Yang, Xilin Sun, Yi Ding, Qian Zhao, Weiyan Liu, Xiaoli Xie, Jingjing Xu, Ran Wei, Shizhen Zhu, Yaqiong Ge, Pu-Yeh Wu and Bin Song*
Affiliation:
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
Keywords:
Breast cancer, Tumor stroma, Stroma distribution, Magnetic resonance image, Molecular subtype, Mental health.
Abstract:
Objective:
This study explored whether breast MRI manifestations could be used to predict the stroma distribution of breast cancer (BC) and the role of tumor
stroma-based MRI manifestations in molecular subtype prediction.
Methods:
57 patients with pathologically confirmed invasive BC (non-special type) who had lumpy BC on MRI within one week before surgery were
retrospectively collected in the study. Stroma distributions were classified according to their characteristics in the pathological sections. The
stromal distribution patterns among molecular subtypes were compared with the MRI manifestations of BC with different stroma distribution types
(SDTs).
Results:
SDTs were significantly different and depended on the BC hormone receptor (HR) (P<0.001). There were also significant differences among five
SDTs on T2WI, ADC map, internal delayed enhanced features (IDEF), marginal delayed enhanced features (MDEF), and time signal intensity
(TSI) curves. Spiculated margin and the absence of type-I TSI were independent predictors for BC with star grid type stroma. The appearance
frequency of hypo-intensity on T2WI in HR- BCs was significantly lower (P=0.043) than in HR+ BCs. Star grid stroma and spiculated margin
were key factors in predicting HR+ BCs, and the AUC was 0.927 (95% CI: 0.867-0.987).
Conclusion:
Breast MRI can be used to predict BC's stromal distribution and molecular subtypes.
