Performance of Radiologist in Interpretation of Non-mass Lesions Detected by Automated Breast Ultrasound: With and Without Commercially Available AI
Ultrasound in Medicine & Biology, 2026
Abstract
Introduction This study evaluates the impact of commercially available artificial intelligence (AI) on radiologist performance in interpreting non-mass lesions detected by automated breast ultrasound.
Methods Researchers assessed radiologist interpretation of non-mass lesions with and without the assistance of QVCAD, a commercially available AI system from QView Medical.
Results The study demonstrates that AI assistance significantly improves radiologist accuracy and confidence in detecting and characterizing non-mass breast lesions, which are particularly challenging to identify in ultrasound imaging.
Conclusion Commercially available AI systems like QVCAD can enhance radiologist performance in breast ultrasound interpretation, potentially leading to earlier and more accurate detection of breast cancer.
