NCT06934239

Brief Summary

The goal of this clinical trial is to compare patient-centered outcomes when screening digital breast tomosynthesis (DBT) exams are interpreted with versus without a leading FDA-cleared artificial intelligence (AI) decision-support tool in real-world U.S. settings and to assess patients' and radiologists' perspectives on AI in medicine. The main question it aims to answer is: Does an FDA-cleared AI decision-support tool for digital tomosynthesis (DBT) improve screening outcomes in real world US clinical settings? This trial will include all interpreting radiologists and all adult patients undergoing screening mammography at any of the participating breast imaging facilities across 6 regional health systems (University of California, Los Angeles (UCLA), University of California, San Diego (UCSD), University of Washington-Seattle, University of Wisconsin-Madison, Boston Medical Center, and University of Miami) during the trial period. All screening mammograms at these facilities will be randomized to either intervention (radiologist assisted by an AI decision support tool) versus usual care (radiologist alone) to see if interpreting these mammograms with the AI tool's assistance improves patient screening outcomes. We are targeting 400,000 screening exams across the participating health systems in this trial.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
400,000

participants targeted

Target at P75+ for phase_4

Timeline
46mo left

Started Oct 2025

Longer than P75 for phase_4

Geographic Reach
1 country

6 active sites

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress13%
Oct 2025Mar 2030

First Submitted

Initial submission to the registry

April 11, 2025

Completed
7 days until next milestone

First Posted

Study publicly available on registry

April 18, 2025

Completed
6 months until next milestone

Study Start

First participant enrolled

October 15, 2025

Completed
2.4 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

March 1, 2028

Expected
2 years until next milestone

Study Completion

Last participant's last visit for all outcomes

March 1, 2030

Last Updated

November 26, 2025

Status Verified

October 1, 2025

Enrollment Period

2.4 years

First QC Date

April 11, 2025

Last Update Submit

November 24, 2025

Conditions

Keywords

Breast cancer screeningArtificial intelligence (AI)

Outcome Measures

Primary Outcomes (2)

  • Cancer detection rate

    Number of screening exams recommended for breast biopsy (final Breast Imaging- Reporting and Data System \[BI-RADS\] assessment of 4 or 5) resulting in detected cancer, per 1,000 screening exams

    Cancer diagnosed within 90 days of positive study entry screening mammogram

  • Recall rate

    Number of screening exams recalled for diagnostic work-up (initial BI-RADS assessment of 0, 3, 4, or 5), per 1,000 screening exams

    Through study completion, an average of 1 year

Secondary Outcomes (6)

  • Interval cancer rate (i.e., false-negative rate)

    Cancer diagnosed within 365 days of a negative study entry screening mammogram

  • False positive recall rate

    No cancer diagnosed within 365 days of a positive study entry screening mammogram

  • False positive short-interval follow-up recommendation rate

    No cancer diagnosed within 365 days of a positive study entry screening mammogram

  • False positive biopsy recommendation rate

    No cancer diagnosed within 365 days of a positive study entry screening mammogram

  • Trust and confidence in AI

    Years 1,2 and Years 4,5

  • +1 more secondary outcomes

Study Arms (2)

Intervention (radiologist assisted by AI)

ACTIVE COMPARATOR

3D screening exams randomized to this arm will be interpreted by the radiologist assisted by the AI decision-support tool (i.e., intervention).

Device: Artificial intelligence (AI) decision-support tool

Standard care (radiologist alone)

NO INTERVENTION

3D screening exams randomized to this arm will be interpreted in accordance with standard care (i.e., interpreted by the radiologist alone, without an AI decision-support tool's assistance).

Interventions

The intervention is an AI decision-support tool to help radiologists interpret 3D screening mammograms. For exams randomized to this intervention arm, the first image displayed to the radiologist upon opening an exam on the viewing station will be a one-page, standardized AI report showing the overall exam risk (elevated, intermediate, or low), image region markings, lesion scores from 1-100 (100 being the highest suspicion), bounding boxes, and relevant slice locations for 3D exams. Radiologists can toggle markings on/off and retain full control over the final interpretation of the exam as positive or negative (i.e., they can choose to ignore the AI information). Randomization occurs 1:1 at the exam level via automated code at image acquisition. Returning patients in year two will be re-randomized. Radiologists cannot filter their exam lists by AI availability or risk, and randomization will be independently managed at each participating health system.

Intervention (radiologist assisted by AI)

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Be at least 18 years of age or older
  • Receive a screening mammogram at one of the participating breast imaging facilities OR be a radiologist who interprets screening mammograms at one of the participating breast imaging facilities.

You may not qualify if:

  • \. Patients who have opted out of all research at the health system

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (6)

University of California Los Angeles Health System

Los Angeles, California, 90024, United States

RECRUITING

University of California, San Diego

San Diego, California, 92093, United States

RECRUITING

University of Miami Health System

Miami, Florida, 33136, United States

RECRUITING

Boston Medical Center

Boston, Massachusetts, 02118, United States

RECRUITING

University of Washington Health System

Seattle, Washington, 98195, United States

RECRUITING

University of Wisconsin-Madison

Madison, Wisconsin, 53706, United States

RECRUITING

Study Officials

  • Joann G Elmore, MD, MPH

    University of California, Los Angeles

    PRINCIPAL INVESTIGATOR
  • Diana Miglioretti, PhD

    University of California, Davis

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Michelle L'Hommedieu, PhD

CONTACT

Study Design

Study Type
interventional
Phase
phase 4
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
PARTICIPANT
Purpose
SCREENING
Intervention Model
PARALLEL
Model Details: This is a study of an FDA-cleared artificial intelligence (AI) decision-support tool.
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

April 11, 2025

First Posted

April 18, 2025

Study Start

October 15, 2025

Primary Completion (Estimated)

March 1, 2028

Study Completion (Estimated)

March 1, 2030

Last Updated

November 26, 2025

Record last verified: 2025-10

Data Sharing

IPD Sharing
Will share

A de-identified dataset from this study will be deposited in the Patient-Centered Outcomes Data Repository (PCODR) housed at the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, in compliance with PCORI's Policy on Data Management and Data Sharing.

Locations