Multimodal Large Language Models for Breast Ultrasound Report Auditing: Workflow-Error Detection, False-Positive Burden, and Limits of Key-Image Interpretation.

A workflow-error-enriched 300-report subset was constructed, comprising 240 reports with 329 inserted errors and 60 error-free reports.

Error-level recall increased from 63.2% to 75.4% and from 72.0% to 83.6%, respectively.

The physician reader achieved 91.7% report-level sensitivity and 83.0% error-level recall without false positives.

In the full cohort, key-image input underperformed physician-interpreted findings input for malignancy classification (AUC, 0.879 vs 0.971) and BI-RADS risk classification (AUC, 0.887 vs 0.984).