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. 2025 Jul 1;98(1171):1080-1089.
doi: 10.1093/bjr/tqaf084.

Combining a breast apparent diffusion coefficient category system with Breast Imaging Reporting and Data System assessment improves specificity of breast lesions diagnosis

Bing Zhang  1 , Zhuanzhuan Guo  1 , Xin Chen  1 , Yuelang Zhang  1 , Quanxin Yang  1 , Lingjie Tan  2 , Wenbin Liang  1 , Zhe Lei  1 , Le Liu  1 , Baobin Guo  1 , Xiaoqian Zhou  1 , Kai Qu  3
Affiliations

Combining a breast apparent diffusion coefficient category system with Breast Imaging Reporting and Data System assessment improves specificity of breast lesions diagnosis

Bing Zhang et al. Br J Radiol. .

Abstract

Purpose: To investigate the diagnostic performance of the predefined breast apparent diffusion coefficient (ADC-B) category system in differentiating malignant from benign breast lesions and to compare with the Breast Imaging Reporting and Data System (BI-RADS).

Methods: This was a single-institution retrospective study of patients who underwent breast MRI between April 2019 and May 2023. Dynamic contrast-enhanced (DCE) MRI and diffusion weighted imaging (DWI) were performed using a 3-T MRI system. Data on lesion morphology (mass, non-mass), size, and ADC were collected. Histology was the standard of reference. The analysis assessed the inter-reader agreement in measuring ADC and ADC-B category using the intraclass correlation coefficient (ICC), as well as the diagnostic performance based on the receiver operating characteristic (ROC) curve.

Results: A total of 376 lesions in 358 women (mean age, 46.29 years; SD, 11.03) with pathologic results (236 malignant and 140 benign) were included. The inter-reader agreement was excellent in measuring ADC (ICC = 0.991) and assessing ADC-B category (ICC = 0.967). Overall diagnostic performance for ADC-B category (area under the curve [AUC], 0.858; 95% CI: 0.816-0.894) was higher than for BI-RADS (AUC, 0.805; 95% CI: 0.759-0.846; P = 0.029). The AUC of ADC-B category combined with BI-RADS reached 0.870 (95% CI: 0.829-0.904) for ADC-measurable lesions and 0.861 (95% CI: 0.822-0.894) for all lesions. The diagnostic combination significantly improves the specificity of BI-RADS (from 17.1% to 49.5% for ADC measurable lesions and from 20% to 45.6% for all lesions; P < 0.001) while maintaining sensitivity.

Conclusion: The combination of predefined ADC-B category and BI-RADS has the potential to enable classification of breast lesion types with high accuracy.

Advance in knowledge: While DWI has been incorporated into clinical MRI protocols at numerous medical centres, it has not been included in the official BI-RADS criteria. Adding ADC-B category system to BI-RADS classification significantly improves the specificity of breast lesion classification without decreasing sensitivity compared to the BI-RADS alone.

Keywords: breast lesions; diagnosis; diffusion MRI.

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