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Updated: Dec 21, 2025
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Multiple b-value diffusion-weighted imaging in differentiating benign from malignant breast lesions: comparison of
1Imaging Diagnosis and Treatment Center, Xi'an International Medical Center Hospital, Xi'an, 710100, PR China; Department of Radiology, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, PR China.
Aim:
To prospectively evaluate multiple b-value diffusion-weighted imaging (DWI) in differentiating malignant from benign breast lesions.
Materials And Methods:
The study cohort included 103 patients who underwent 3 T magnetic resonance imaging (MRI). The conventional sequences included T1-weighted dynamic contrast-enhanced, T1-weighted and T2-weighted fat-suppressed sequences, single b-value (b=0, 1000 s/mm2) DWI, and multiple b-values (12 values, from 0 to 3,000 s/mm2) DWI. Pathological diagnosis of breast lesions was based on the latest World Health Organization (WHO) guide on the pathology and immunohistochemistry of the breast. SPSS Statistics V19.0 was used for the statistics analysis.
Results:
The following parameters were calculated: apparent diffusion coefficient (ADC), tissue diffusivity (D), perfusion fraction (f), pseudo-diffusion coefficient (D∗), distributed diffusion coefficient (DDC), and alpha (α) by the same radiologist twice (interval time of 3 months). There was good inter/intra-observer agreement for each of the parameters. The D, D∗, f, DDC, and α values were significantly different among malignant tumours, benign lesions, and normal breast tissue (p<0.05).
Conclusion:
D, f, DDC, α, and ADC values have good sensitivity and specificity, respectively. In addition, the combined use of D and f or DDC and α has good diagnostic performance. Thus, the applications of the new multi-b DWI variables or combined variables are promising.
