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.