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Updated: Jan 30, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Diffusion tensor imaging parameters in differentiation recurrent breast cancer from post-operative changes in
Ahmed Abdel Khalek Abdel Razek1, Mona Zaky1, Dalia Bayoumi1
1Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt.
Aim Of The Work:
To investigate mean diffusivity (MD) and fractional anisotropy (FA) measured by diffusion tensor imaging (DTI) as complementary tools to differentiate recurrent breast cancer from post-operative changes in patients with breast-conserving surgery (BCS).
Patients And Methods:
Prospective study was conducted upon 30 patients with BCS that underwent DTI and dynamic contrast MR imaging. DTI was performed using an axial two-dimensional spin-echo echo-planar imaging sequence. The MD and FA of the lesions were calculated by 2 observers. A single pixel seed isotropic region of interest was placed in the solid part of the tumor on the axial color FA map guided by an enhanced part of the tumor. The final diagnosis was done by biopsy for all patients.
Results:
The pathological examination proved to be recurrent breast cancer (n = 13) and post-operative changes (n = 17). Recurrent breast cancer had significantly lower MD (P = 0.001, 0.001) and higher FA (P = 0.003, 0.02) than in post-operative changes for both observers respectively. At ROC curve analysis of MD, the AUC was 0.86 and 0.85 by both observers. The threshed MD was (0.86, 0.85 × 10-3 mm2/s) used for differentiation between entities revealed sensitivity (76.9%, 92.3%), specificity (82.4%, 64.7%) and accuracy (80%, 76.7%) of both observers respectively. At ROC curve analysis of FA, the AUC was 0.82 and 0.75 by both observers. The threshold FA (0.82, 0.75) was used for differentiation between entities revealed sensitivity (92.3%, 76.9%), specificity (70.6%, 70.6%) and accuracy of (80.0%, 73.3%) of both observers respectively. There was a strong positive correlation of MD (r = 0.86) and FA (r = 0.73) of both observers. Combined analysis of FA and MD used for differentiation between entities had AUC (0.90, 0.88) revealed sensitivity (92.3%, 92.3%), specificity (82.4%, 70.6%) and accuracy of (86.7%, 80.0%) for both observers respectively.
Conclusions:
Combined analysis of MD and FA of DTI may play an important role as a non-invasive method for differentiation recurrent breast cancer from post-operative changes in patients with BCS.
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