Clinical trial · Interventional
Breast Ultrasound Image Reviewed With Assistance of Deep Learning Algorithms
Breast Ultrasound Image Reviewed With Assistance of Deep Learning
NCT03706534CI-TRIAL-00041331unknownN/AClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study evaluates a second review of ultrasound images of breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Cancer | Malignant Breast Neoplasm | CURATED_EXACT | 0.92 |
| Breast Lesions | — | UNRESOLVED | — |
| Breast Mass | — | UNRESOLVED | — |
Interventions
Interventions (4)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Biopsy | Procedure | — | UNRESOLVED |
| Ultrasound Image manual review | Device | — | UNRESOLVED |
| Ultrasound Image review with CADe | Device | — | UNRESOLVED |
| Ultrasound Image review with CADx | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- type
- ACTIVE_COMPARATOR
- label
- Manual review
- description
- The images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored. Radiologists also make assessment decision without any intervention from artificial intelligence. 10 radiologists review manually.
- interventionNames
- Device: Ultrasound Image review with CADe
- Device: Ultrasound Image review with CADx
- Device: Ultrasound Image manual review
- Procedure: Biopsy
- type
- EXPERIMENTAL
- label
- Review by S-Detect for Breast
- description
- The same images will be separately processed by the artificial intelligence system (S-Detect for Breast) by Samsung. The two results, one by the radiologists and the other by artificial intelligence system, will be compared to statistically quantify equivalence (CADe).
- interventionNames
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 19 Years
Show eligibility criteria text
1. Inclusion Criteria: * Adult females or males recommended for ultrasound-guided breast lesion biopsy or ultrasound follow-up with at least one suspicious lesion * Age \> 18 years * Able to provide informed consent 2. Exclusion Criteria: * Unable to read and understand English * Unable or unwilling to provide informed consent * A patient with current or previous diagnosis of breast cancer in the same quadrant * Unable or unwilling to undergo study procedures 3. Subject Characteristics 1. Number of Subjects: 300 subjects from 300 separate breast lesions can be acquired. If a subject has more than 1 suspicious lesion, each may be chosen by the radiologist attending as suitable for "second review". 2. Gender and Age of Subjects: Adult females or males aged 18 years or older who meet all of the inclusion criteria and none of the exclusion criteria will be considered for enrollment. Minors are excluded as breast cancer is very rare in this age group. 3. Racial and Ethnic Origin: There are no enrollment exclusions based on economic status, race, or ethnicity. Based on local and United States census data, the expected ethnic distribution will be approximately 26 Hispanic (approx. 16%) and 134 non-Hispanic people. Furthermore, the expected racial distribution is expected to be approximately 126 White (approx. 79% of the whole study), 21 Black or African America (13%), 8 Asian (5%), and 5 of other categories (3%). 4. Vulnerable Subjects: It is unlikely that any UR students or employees will be enrolled unless their primary physician refers them to UR Medicine Breast Imaging at Red Creek for breast ultrasound and a suspicious lesion is found. We do not expect any of these referrals to be from staffs who work directly with the PIs.
References
Publications (0)
Data not yet available
No reference posted for this study.