Dynamic anatomical ultrasound assessment for breast lesions: a prospective study of diagnostic performance.

PURPOSE: To determine whether a dynamic ultrasound approach, termed anatomical scanning and interpretation, improves diagnostic performance in differentiating benign from malignant breast lesions compared with conventional static-image BI-RADS assessment.

METHODS

This prospective study evaluated 102 breast lesions (33 masses, 41 non-masses, and 28 distortions) classified as BI-RADS 3, 4a, or 4b. Fourteen ultrasound technologists underwent dedicated training in dynamic anatomical scanning and interpretation. Each lesion was evaluated using real-time video clips and independently categorized as requiring follow-up or biopsy. A subsequent physician-technologist consensus was performed. With histopathology as the reference standard, performance was assessed using ROC analysis, with AUC comparisons performed using the DeLong test.

RESULTS

Among 102 lesions (58 benign, 44 malignant), individual technologist interpretation with dynamic imaging significantly improved diagnostic performance (AUC = 0.748, p = 0.0191) over static BI-RADS assessment (AUC = 0.619). Physician-technologist consensus showed further significant improvement (AUC = 0.865, p < 0.0001). In subgroup analysis, dynamic interpretation outperformed static assessment for masses (AUC = 0.849, p = 0.0036), but not for non-mass lesions (AUC = 0.794) or distortions (AUC = 0.618). In contrast, physician-technologist consensus interpretation demonstrated superior performance compared with static assessment across all lesion types: masses (AUC = 0.879, p < 0.0001), non-mass lesions (AUC = 0.910, p = 0.0005), and distortions (AUC = 0.838, p = 0.0432).

CONCLUSION

Dynamic anatomical scanning and interpretation significantly improve diagnostic performance over conventional static BI-RADS assessment. For non-mass lesions and architectural distortions, anatomical interpretation based on consensus between the physician and the technologist is considered essential to achieve optimal diagnostic accuracy.