1
|
Wang L, Li W, Yang W, Sun X, Ding Y, Zhao Q, Liu W, Xie X, Xu J, Wei R, Zhu S, Ge Y, Wu PY, Song B. MRI Manifestations of Breast Cancer Stroma and their Role in Predicting Molecular Subtype: A Case-control Study. Curr Med Imaging 2024; 20:CMIR-EPUB-138768. [PMID: 38415486 DOI: 10.2174/0115734056287368240213135143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/21/2024] [Accepted: 01/29/2024] [Indexed: 02/29/2024]
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.
Collapse
Affiliation(s)
- Lanyun Wang
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Wenjing Li
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Wenjun Yang
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Xilin Sun
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Yi Ding
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Qian Zhao
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Weiyan Liu
- Department of General Surgery, Minhang Hospital, Fudan University, Shanghai, China
| | - Xiaoli Xie
- Department of Pathology, Minhang Hospital, Fudan University, Shanghai, China
| | - Jingjing Xu
- Department of Medical Examination Center, Minhang Hospital, Fudan University, Shanghai, China
| | - Ran Wei
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Shizhen Zhu
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | | | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing, China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| |
Collapse
|