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Updated: Jan 17, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Multiparametric MRI and clinical factors for predicting early recurrence of breast cancer after modified radical
Quan-Hua Chen1, Chongze Yang2, Lan-Hui Qin2
1Department of Radiology, Guigang People's Hospital, Guigang, 537100, Guangxi Zhuang Autonomous Region, People's Republic of China; Department of Radiology, the First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
Objective:
To determine whether preoperative multiparametric MRI features and clinicopathological factors can predict early recurrence in breast cancer patients following modified radical mastectomy (MRM).
Materials And Methods:
This retrospective study included 132 patients who underwent MRM at two hospitals from January 2012 to December 2022. Patients were classified into early recurrence (disease-free survival ≤3 years, n = 86) or late recurrence (>3 years, n = 46). We collected preoperative MRI features (tumor size, morphology, enhancement patterns, apparent diffusion coefficient (ADC) values, early enhancement rate, time-signal intensity curves) and clinical/pathological factors (age, menstruation status, neoadjuvant chemotherapy, T/N/TNM stage, tumor grade, axillary nodal involvement, vascular/nerve/nipple/skin invasion, ER, PR, HER-2, Ki-67, molecular subtype, and adjuvant therapies). Univariate and multivariate analyses (binary logistic and Cox regression) identified independent predictors of early recurrence and their impact on disease-free survival. Predictive accuracy was assessed by ROC curves.
Results:
Significant factors associated with early recurrence (P < 0.05) included tumor size, ADC value, early enhancement rate, axillary lymph node metastasis, T and TNM stage, vascular invasion, ER, PR, HER-2, molecular subtype, and endocrine therapy. Multivariate analysis identified early enhancement rate, lower ADC value, and larger tumor diameter as independent predictors (AUC = 0.899). These MRI factors, together with lack of endocrine therapy, also independently influenced disease-free survival.
Conclusion:
Preoperative multiparametric MRI features, especially early enhancement rate and tumor size, combined with endocrine therapy status, can predict early recurrence, enhancing prognosis for patients undergoing MRM.
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