BU-CAD
TaiHao Medical Inc.BU-CAD is a software application designed to assist physicians by analyzing breast ultrasound images to identify and evaluate soft tissue lesions suspicious for breast cancer. It highlights regions of interest and provides malignancy scores and BI-RADS classifications to support clinical decision-making. It also supports viewing of mammography images and includes tools for image adjustment and documentation, helping improve diagnostic accuracy and efficiency.
Intended Use
BU-CAD is a software application indicated to assist trained interpreting physicians in analyzing the breast ultrasound images of patients with soft tissue breast lesions suspicious for breast cancer who are being referred for further diagnostic ultrasound examination. It outputs regions of interest and lesion contours, assisting physicians to identify suspicious soft tissue lesions from up to two orthogonal views of a single lesion, and region-based analysis of lesion malignancy with BI-RADS categories and descriptors.
Technology
BU-CAD consists of a Viewer, a Lesion Identification Module, and a Lesion Analysis Module. The Viewer loads breast ultrasound and mammography images, supporting adjustments and measurements. The Lesion Identification Module automatically detects regions of interest and lesion contours on ultrasound images. The Lesion Analysis Module generates lesion malignancy scores, BI-RADS categories, and descriptors based on user-specified or automated ROIs, aiding diagnosis.
Performance
Clinical performance evaluation was conducted via a multi-reader multi-case (MRMC) study with 628 cases and 16 readers. Results demonstrated that users aided by BU-CAD had a statistically significant improvement in diagnostic performance (mean AUC increase of 0.0374). Sensitivity, specificity, PPV, and NPV also improved with BU-CAD assistance. The software reduced interpretation time by approximately 40% and improved reader determination of BI-RADS descriptors. Standalone testing on 1139 cases showed high lesion identification accuracy (93.24%) and stable diagnostic AUCs.
Predicate Devices
No predicate devices specified
Device Timeline
- 1
Submission
3/5/2021
9 months - 2
FDA Approval
12/21/2021
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