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Updated: Jun 3, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Prognostic value DCE-MRI parameters in predicting factor disease free survival and overall survival for breast cancer
Nermin Tuncbilek1, Fusun Tokatli, Semsi Altaner
1Department of Radiology, Trakya University School of Medicine, Uzunoglu 2, Apt. No: 60 Daire: 4/13, 22030 Edirne, Turkey. drtuncbilek@hotmail.com
Purpose:
The aim of the study is to assess the predictive power of DCE-MRI semi-quantitative parameters during treatment of breast cancer, for disease-free (DFS) and overall survival (OS).
Materials And Methods:
Forty-nine women (age range, 28-84 years; mean, 50.6 years) with breast cancer underwent dynamic contrast enhancement MRI at 1.0T imaging, using 2D FLASH sequences. Time intensity curves (TICs) were obtained from the regions showing maximal enhancement in subtraction images. Semi-quantitative parameters (TICs; maximal relative enhancement within the first minute, E (max/1); maximal relative enhancement of the entire study, E(max); steepest slope of the contrast enhancement curve; and time to peak enhancement) derived from the DCE-MRI data. These parameters were then compared with presence of recurrence or metastasis, DFS and OS by using Cox regression (proportional hazards model) analysis, linear discriminant analysis.
Results:
The results from of the 49 patients enrolled into the survival analysis demonstrated that traditional prognostic parameters (tumor size and nodal metastasis) and semi-quantitative parameters (E(max/1), and steepest slope) demonstrated significant differences in survival intervals (p<0.05). Further Cox regression (proportional hazards model) survival analysis revealed that semi-quantitative parameters contributed the greatest prediction of both DFS, OS in the resulting models (for E(max/1): p=0.013, hazard ratio 1.022; for stepest slope: p=0.004, hazard ratio 1.584).
Conclusion:
This study shows that DCE-MRI has utility predicting survival analysis with breast cancer patients.
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