Virkningen af kunstig intelligens på screening af brystkræft
Evaluering af virkningen af kunstig intelligens på brystkræftscreeningskvalitet og effektivitet: Et prospektivt randomiseret kontrolleret forsøg
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.
Studieoversigt
Status
Betingelser
Intervention / Behandling
Detaljeret beskrivelse
During the RCT the AI support tool will be randomized to be turned on or off (1:1) at the mammography exam level. Patients who return for screening exams in year 2 of recruitment will be randomized again (e.g., they will not retain their prior randomization). Radiologists will not be able to sort exams based on AI availability or AI scores. Randomizing by exam level will ensure that we capture a substantial number of interpretations with vs. without AI for each radiologist, allowing for quantification of the radiologist-level AI learning curve. We are not randomizing at the facility level as some radiologists interpret exams acquired at different facilities on the same day. By randomizing AI at the exam level, we will have the best ability to estimate and adjust for temporal trends in screening outcomes across individual radiologists. Randomization across large regional health systems will be managed independently at each participating site.
Our RCT randomizes screening mammography exams to be interpreted either with or without an AI decision-support tool. As a result, radiologists cannot be blinded to study arm during screening mammography interpretation. However, interpreting radiologists and facility staff (e.g., those scheduling the exams) will not know in advance which patients will be randomized to the AI tool. Randomization occurs within minutes after the breast imaging acquisition (i.e., when the mammography technologist captures the images) by an automated system that was developed by a third-party AI platform and successfully piloted at UCLA. Thus, the AI data (or lack thereof) is embedded within the mammogram before the radiologist opens the exam, preventing any option to "add AI" to an exam randomized to be interpreted without AI. Radiologists will be aware of AI availability only at the time of interpretation, as AI information will appear upon opening the exam (e.g., the AI information pops up with the exam images).
Undersøgelsestype
Tilmelding (Anslået)
Fase
- Fase 4
Kontakter og lokationer
Studiekontakt
- Navn: Michelle L'Hommedieu, PhD
- Telefonnummer: (310) 592-9454
- E-mail: mlhommedieu@mednet.ucla.edu
Studiesteder
-
-
California
-
Los Angeles, California, Forenede Stater, 90024
- Rekruttering
- University of California Los Angeles Health System
-
Ledende efterforsker:
- Hannah S. Milch, MD
-
Kontakt:
- Michelle L'Hommedieu, PhD
- Telefonnummer: (310) 592-9454
- E-mail: mlhommedieu@mednet.ucla.edu
-
Ledende efterforsker:
- Joann G Elmore, MD, MPH
-
San Diego, California, Forenede Stater, 92093
- Rekruttering
- University of California, San Diego
-
Ledende efterforsker:
- Haydee Ojeda-Fournier, MD
-
Kontakt:
- Haydee Ojeda-Fournier, MD
- Telefonnummer: (858) 442-1902
- E-mail: hojeda@health.ucsd.edu
-
-
Florida
-
Miami, Florida, Forenede Stater, 33136
- Rekruttering
- University of Miami Health System
-
Kontakt:
- Jose Net, MD
- Telefonnummer: (305) 215-0461
- E-mail: jnet@med.miami.edu
-
Ledende efterforsker:
- Jose Net, MD
-
-
Massachusetts
-
Boston, Massachusetts, Forenede Stater, 02118
- Rekruttering
- Boston Medical Center
-
Kontakt:
- Clare Poynton, MD, PhD
- Telefonnummer: (617) 638-6626
- E-mail: clare.poynton@bmc.org
-
Ledende efterforsker:
- Clare Poynton, MD, PhD
-
-
Washington
-
Seattle, Washington, Forenede Stater, 98195
- Rekruttering
- University of Washington Health System
-
Kontakt:
- Janie Lee, MD, MSc
- Telefonnummer: (206) 606-6241
- E-mail: jmlee58@fredhutch.org
-
Ledende efterforsker:
- Janie Lee, MD, MSc
-
-
Wisconsin
-
Madison, Wisconsin, Forenede Stater, 53706
- Rekruttering
- University of Wisconsin-Madison
-
Kontakt:
- Christoph Lee, MD, MSc
- Telefonnummer: (608) 263-9377
- E-mail: cilee3@uwhealth.org
-
Ledende efterforsker:
- Christoph Lee, MD, MSc
-
-
Deltagelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
Tager imod sunde frivillige
Køn, der er berettiget til at studere
Beskrivelse
This trial will include all radiologists interpreting screening mammography and all adult patients undergoing screening mammography at any of the participating breast imaging facilities across 6 regional health systems (UCLA, UC San Diego, University of Washington-Seattle, University of Wisconsin-Madison, Boston Medical Center, and University of Miami) during the trial period. Individuals must meet the following eligiblity criteria.
Inclusion Criteria:
- 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.
Exclusion Criteria:
1. Patients who have opted out of all research at the health system
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
- Primært formål: Screening
- Tildeling: Randomiseret
- Interventionel model: Parallel tildeling
- Maskning: Enkelt
Våben og indgreb
Deltagergruppe / Arm |
Intervention / Behandling |
|---|---|
|
Aktiv komparator: Intervention (radiologist assisted by AI)
3D screening exams randomized to this arm will be interpreted by the radiologist assisted by the AI decision-support tool (i.e., intervention). |
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. |
|
Ingen indgriben: Standard care (radiologist alone)
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). |
Hvad måler undersøgelsen?
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Cancer detection rate
Tidsramme: Cancer diagnosed within 90 days of positive study entry screening mammogram
|
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
Tidsramme: Through study completion, an average of 1 year
|
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
|
Sekundære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Interval cancer rate (i.e., false-negative rate)
Tidsramme: Cancer diagnosed within 365 days of a negative study entry screening mammogram
|
Number of screening exams with a negative assessment (final BI-RADS assessment of 1 or 2) and breast cancer diagnosed within 1 year, per 1,000 screening exams |
Cancer diagnosed within 365 days of a negative study entry screening mammogram
|
|
False positive recall rate
Tidsramme: No cancer diagnosed within 365 days of a positive study entry screening mammogram
|
Proportion of screening exams recalled for additional imaging (final BI-RADS assessment of 1, 2, or 3), with no breast cancer diagnosed within 1 year |
No cancer diagnosed within 365 days of a positive study entry screening mammogram
|
|
False positive short-interval follow-up recommendation rate
Tidsramme: No cancer diagnosed within 365 days of a positive study entry screening mammogram
|
Proportion of screening exams recalled for short-interval follow-up (final BI-RADS assessment of 3) with no breast cancer diagnosed within 1 year |
No cancer diagnosed within 365 days of a positive study entry screening mammogram
|
|
False positive biopsy recommendation rate
Tidsramme: No cancer diagnosed within 365 days of a positive study entry screening mammogram
|
Proportion of screening exams recalled for breast biopsy (final BI-RADS assessment of 4 or 5) with no breast cancer diagnosed within 1 year |
No cancer diagnosed within 365 days of a positive study entry screening mammogram
|
|
Trust and confidence in AI
Tidsramme: Years 1,2 and Years 4,5
|
Trust and confidence in AI gathered from focus group and survey data |
Years 1,2 and Years 4,5
|
|
Efficiency metrics (only for the UCLA site)
Tidsramme: Through study completion, an average of 1 year
|
Interpretation time required for radiologists to interpret each mammogram with versus without AI. Delivery time, using time stamp data from exam acquisition to delivery of results to patients (aka turnaround time). |
Through study completion, an average of 1 year
|
Samarbejdspartnere og efterforskere
Samarbejdspartnere
Efterforskere
- Ledende efterforsker: Diana Miglioretti, PhD, University of California, Davis
- Ledende efterforsker: Joann G Elmore, MD, MPH, University of California, Los Angeles
Datoer for undersøgelser
Studer store datoer
Studiestart (Faktiske)
Primær færdiggørelse (Anslået)
Studieafslutning (Anslået)
Datoer for studieregistrering
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først opslået (Faktiske)
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Andre undersøgelses-id-numre
- 24-1192
Plan for individuelle deltagerdata (IPD)
Planlægger du at dele individuelle deltagerdata (IPD)?
IPD-planbeskrivelse
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.
Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter
Studerer et amerikansk FDA-reguleret lægemiddelprodukt
Studerer et amerikansk FDA-reguleret enhedsprodukt
produkt fremstillet i og eksporteret fra U.S.A.
Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .