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Updated: Mar 7, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
MR imaging features associated with distant metastasis-free survival of patients with invasive breast cancer: a
Sung Eun Song1,2, Sung Ui Shin1, Hyeong-Gon Moon3
1Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
Purpose:
Preoperative breast magnetic resonance (MR) imaging features of primary breast cancers may have the potential to act as prognostic biomarkers by providing morphologic and kinetic features representing inter- or intra-tumor heterogeneity. Recent radiogenomic studies reveal that several radiologist-annotated image features are associated with genes or signal pathways involved in tumor progression, treatment resistance, and distant metastasis (DM). We investigate whether preoperative breast MR imaging features are associated with worse DM-free survival in patients with invasive breast cancer.
Methods:
Of the 3536 patients with primary breast cancers who underwent preoperative MR imaging between 2003 and 2009, 147 patients with DM were identified and one-to-one matched with control patients (n = 147) without DM according to clinical-pathologic variables. Three radiologists independently reviewed the MR images of 294 patients, and the association of DM-free survival with MR imaging and clinical-pathologic features was assessed using Cox proportional hazard models.
Results:
Of MR imaging features, rim enhancement (hazard ratio [HR], 1.83 [95% confidence interval, CI 1.29, 2.51]; p = 0.001) and peritumoral edema (HR, 1.48 [95% CI 1.03, 2.11]; p = 0.032) were the significant features associated with worse DM-free survival. The significant MR imaging features, however, were different between breast cancer subtypes and stages.
Conclusion:
Preoperative breast MR imaging features of rim enhancement and peritumoral edema may be used as prognostic biomarkers that help predict DM risk in patients with breast cancer, thereby potentially enabling improved personalized treatment and monitoring strategies for individual patients.
