Evaluation of TaiHao Breast Ultrasound Diagnosis Software
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- TaiHao Medical Inc.
- Enrollment
- 16
- Locations
- 1
- Primary Endpoint
- Comparing the Area Under the LROC Curve
Study Overview
Brief Summary
The BR-USCAD DS Module is a computer-assisted detection and diagnosis software based on a deep learning algorithm. This retrospective, fully-crossed, multi-reader, multi-case (MRMC) study aims to compare the performances of readers without and with the aid of the Breast Ultrasound Image Reviewed with Assistance of Computer-Assisted Detection and Diagnosis System (BR-USCAD DS) in interpreting breast ultrasound images of lesions.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Crossover
- Primary Purpose
- Diagnostic
- Masking
- None
Eligibility Criteria
- Ages
- 21 Years to — (Adult, Older Adult)
- Sex
- Female
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •B-mode breast ultrasound image
- •Female, age 21 or older
- •Breast lesion images acquired before a biopsy or surgery - these images were retrospectively collected with histology report.
- •Non-biopsied benign lesions with negative follow-up for a minimum of 24 months
- •At least two orthogonal views of a lesion
Exclusion Criteria
- •Breast lesion images acquired after biopsy or surgery.
- •Any breast surgeries or interventional procedures in the 12 months prior to ultrasound imaging
- •Case demonstrating administrative or technical errors
- •Multiple lesions in one 2-D ultrasound image
- •Breast ultrasound images with Doppler, elastography, or other overlays present
- •Case with less than 2-year follow-up and without biopsy confirmation
Arms & Interventions
First session: manual review first and then review with CADx
Reader Group X interpret the "Dataset A" cases in different random order without any assistance of AI first, and then interpret the "Dataset B" cases in different random order with TaiHao AI system.
Intervention: Reader Group X - Session 1 (Diagnostic Test)
First session: review with CADx first and then manual review
Reader Group Y interpret the "Dataset A" cases in different random order with TaiHao AI system first, and then interpret the "Dataset B" cases in different random order without any assistance of AI.
Intervention: Reader Group Y - Session 1 (Diagnostic Test)
Second session: manual review first and then review with CADx
At least 4 weeks after first session for memory washing out. Reader Group X interpret the "Dataset A" cases in different random order with TaiHao AI system first, and then interpret the "Dataset B" cases in different random order without any assistance of AI.
Intervention: Reader Group X - Session 2 (Diagnostic Test)
Second session: review with CADx first and then manual review
At least 4 weeks after first session for memory washing out. Rader Group Y interpret the "Dataset A" cases in different random order without any assistance of AI first, and then interpret the "Dataset B" cases in different random order with TaiHao AI system.
Intervention: Reader Group Y - Session 2 (Diagnostic Test)
Outcomes
Primary Outcomes
Comparing the Area Under the LROC Curve
Time Frame: 10 weeks
The area under the LROC curve (AUC_LROC) on the diagnosis of benign and malignant lesions was computed and compared for Aim 1 (baseline) and Arm 2 (with BU-CAD assistance) studies.
Secondary Outcomes
- The Sensitivity, Specificity, PPV, and NPV Were Computed and Compared for Aim 1 (Baseline) and Arm 2 (With BU-CAD Assistance) Studies.(10 weeks)
- The Reading Time Was Computed and Compared for Aim 1 (Baseline) and Arm 2 (With BU-CAD Assistance) Studies.(10 weeks)