Mirai-MRI: Validation of AI Models for Breast Cancer Risk
NCT ID: NCT07121972
Last Updated: 2025-11-06
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
400 participants
INTERVENTIONAL
2025-11-03
2027-01-31
Brief Summary
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Detailed Description
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I. To estimate the cancer detection rate (CDR) of supplemental screening breast MRI in participants who are high-risk by the Mirai model
SECONDARY OBJECTIVES:
I. To estimate the CDR of supplemental screening breast MRI in participants with high Mirai risk and low (\<20%) lifetime Tyrer-Cuzick (TC) risk.
II. To compare the CDR of supplemental screening breast MRI in participants with high Mirai risk and high (≥ 20%) lifetime TC risk versus CDR in participants with high Mirai risk and low (\<20%) lifetime TC risk.
III. To estimate the positive predictive value (PPV)1, PPV2, and PPV3 of supplemental MRI screening in participants with high Mirai risk.
IV. To estimate the false positive rate (1 - specificity) of supplemental screening MRI in participants with high Mirai risk.
V. To evaluate the tumor size, stage, grade, histological and molecular subtypes, Ki-67 percentage, and lymph node involvement of cancers detected on supplemental screening MRI in Mirai high risk participants.
VI. To evaluate the association between race/ethnicity, menopausal status, hormonal status, breast density, family history of cancer, and CDR in Mirai high-risk participants.
Conditions
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Keywords
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Study Design
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NA
SINGLE_GROUP
SCREENING
NONE
Study Groups
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Supplemental MRI
Participants identified as Mirai high-risk on a negative/benign screening mammogram will receive a supplemental MRI within 12 months of receiving a screening mammogram. Breast cancer risk following the Tyrer-Cuzick risk model will be assessed for comparison.
Magnetic resonance imaging (MRI)
Undergo Magnetic resonance (MR) imaging
Artificial Intelligence (AI)
AI applied to MRI images
Interventions
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Magnetic resonance imaging (MRI)
Undergo Magnetic resonance (MR) imaging
Artificial Intelligence (AI)
AI applied to MRI images
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
2. Screening mammogram assessed as high-risk by Mirai (top 3 percentile of 2-year risk).
3. Availability of a routine screening mammogram report, along with a subsequent diagnostic mammogram report if applicable, and access to the corresponding Digital Imaging and Communications in Medicine (DICOM) images.
4. Ability to understand and the willingness to sign a written informed consent document.
Exclusion Criteria
2. Contraindications for MRI:
1. Metallic foreign body in the eye.
2. MRI unsafe implants and/or medical devices.
3. Adverse reaction to a (gadolinium-based) contrast agent in the past.
4. Pregnant women.
5. Claustrophobia.
6. Exceeds site specific size and/or weight limit for MRI.
3. If the participant meets site-specific criteria for screening estimated glomerular filtration rate (eGFR) prior to MRI, participants with severely impaired renal function (GFR \< 30 mL/min) will be excluded. According to University of California, San Francisco's policy for MRI with contrast (gadolinium-containing), serum creatinine with calculation of eGFR should be obtained within 6 weeks of the MRI study for participants with any of the following risk factors:
1. History of "kidney disease" as an adult, including renal tumor or transplant.
2. Diabetes treated with insulin or other prescribed medications.
3. Hypertension (high blood pressure) requiring medication.
4. Multiple myeloma.
5. Solid organ transplant.
6. History of severe hepatic disease/liver transplant/pending liver transplant.
40 Years
89 Years
FEMALE
Yes
Sponsors
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Breast Cancer Research Foundation
OTHER
University of California, San Francisco
OTHER
Responsible Party
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Principal Investigators
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Maggie Chung, MD
Role: PRINCIPAL_INVESTIGATOR
University of California, San Francisco
Locations
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University of California, San Diego
San Diego, California, United States
University of California, San Francisco
San Francisco, California, United States
University of Chicago Comprehensive Cancer Center
Chicago, Illinois, United States
University of Massachusetts Memorial Medical Center
Worcester, Massachusetts, United States
Countries
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Central Contacts
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Facility Contacts
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Tiffany Tran
Role: primary
Role: backup
Other Identifiers
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NCI-2025-06040
Identifier Type: REGISTRY
Identifier Source: secondary_id
25756
Identifier Type: -
Identifier Source: org_study_id