ArticleJournal of ultrasound2026
Can new ultrasound imaging techniques improve breast lesions characterization?: prospective comparison between ultrasound BI-RADS, histological result, semi-automatic software-"Live BreastAssist", strain elastography, shear wave elastography and microvascular flow.
Article in Journal of ultrasound, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMultiparametric ultrasound (mpUS) integrates BI-RADS (Breast Imaging Report And Data System) morphological assessment with biomechanical biomarkers, including strain elastography (SE) and shear-wave elastography (SWE), along with microvascular flow (M-Flow). Furthermore real-time computer-aided diagnosis (CAD/AI) systems, including Live Breast Assist and S-Detect are employed to standardize image interpretation, thereby reducing operator dependence. PURPOSE: To evaluate the diagnostic accuracy and reproducibility of mpUS supported by CAD/AI versus B-mode ultrasound alone, assessing their concordance with histopathology for the benign/malignant dichotomy and the incremental contribution of SE, SWE, and M-Flow. Additionally inter-operator agreement was quantified. MATERIALS AND
methodsIn this single-center prospective study 78 consecutive patients presenting with 78 breast lesions, underwent B-mode/BI-RADS evaluation, Color Doppler, M-Flow (percentage of vascularization), SE (strain ratio), and SWE (quantitative stiffness in kPa). Live Breast Assist was semi-automatically employed during data acquisition, while S-Detect provided focal lesion characterization when deemed necessary. Histopathological examination served as the gold standard.
resultsHistology identified 60 malignancies (76.9%) and 18 benign lesions (23.1%).The highest diagnostic performance was shown by M-Flow (AUC 0.926), reaching 95.1% of sensitivity and 82.4% of specificity. SE also showed strong discriminative ability (AUC 0.885). SWE exhibited lower accuracy (AUC 0.658). B-mode alone achieved an AUC of 0.864. Although with a higher false-negative rate compared with the expert operator, Live Breast Assist demonstrated high specificity (88.2%) and an excellent PPV (96.4%). Inter-operator agreement was substantial (κ = 0.63).
conclusionmpUS with CAD/AI support enhanced diagnostic accuracy and reproducibility for benign/malignant distinction, providing robust biomechanical and vascular biomarkers. This approach may reduce unnecessary biopsies in indeterminate BI-RADS lesions, though tumor grading remains the purview of pathology.
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