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Updated: Aug 15, 2025
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted
Rie Ota1, Masako Kataoka2, Mami Iima3
1Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan; Department of Radiology, Tenri Hospital, Nara, Japan.
Purpose:
To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS).
Methods:
Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses.
Results:
The area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83-0.95) for reader 1, and 0.89 (95% CI: 0.82-0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively.
Conclusion:
Our results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.
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