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Mirai-MRI: Validation of AI Models for Breast Cancer Risk

Mirai-MRI: Multi-site Prospective Validation of AI Models for Breast Cancer Risk

Status
Recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07121972
Enrollment
400
Registered
2025-08-14
Start date
2025-11-03
Completion date
2027-01-31
Last updated
2025-11-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Breast Cancer Risk, Cancer Risk

Keywords

Screening, BI-RADS

Brief summary

This is a multi-center, single arm trial to evaluate the cancer detection rate of supplemental screening magnetic resonance imaging (MRI) in participants who are high-risk by Mirai-MRI assessment. Mirai is an accurate cancer risk model based on full-resolution mammograms.

Detailed description

PRIMARY OBJECTIVE: 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.

Interventions

PROCEDUREMagnetic resonance imaging (MRI)

Undergo Magnetic resonance (MR) imaging

DEVICEArtificial Intelligence (AI)

AI applied to MRI images

Sponsors

Breast Cancer Research Foundation
CollaboratorOTHER
University of California, San Francisco
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SCREENING
Masking
NONE

Eligibility

Sex/Gender
FEMALE
Age
40 Years to 89 Years
Healthy volunteers
Yes

Inclusion criteria

1. All asymptomatic participants assigned female at birth, ages 40-89 years old with screening mammography assessed as Breast Imaging Reporting and Data System (BI-RADS) 1, BI-RADS 2, or initial BI-RADS 0 with subsequent diagnostic mammogram assessed as BI-RADS 1 or BI-RADS 2. 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

1. Screening mammogram that is assessed as BI-RADS 0 for technical recall. 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.

Design outcomes

Primary

MeasureTime frameDescription
Cancer detection rate (CDR)Up to 1 yearThe CDR is defined as the number of breast cancers identified per 1,000 magnetic resonance imaging (MRI) screening examinations performed 1 year following supplemental screening MRI.

Secondary

MeasureTime frameDescription
Comparison of CDR in low and high TC risk groupsUp to 1 yearThe 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 will be compared using a two-proportion exact test.
Positive predictive value of supplemental MRI screening and BI-RADS Score (PPV1)Up to 1 yearPPV1 is the percentage of all positive supplemental MRI screening in participants with high Mirai risk (Breast Imaging Reporting and Data System (BI-RADS) 3, 4, or 5) for which the participant was found to be positive for cancer within 1 year from the time of MRI.
Positive predictive value of supplemental MRI screening recommending histological or surgical follow-up (PPV2)Up to 1 yearPPV2 is the percentage of all supplemental MRI screenings in participants with high Mirai risk recommended for tissue diagnosis or surgical consultation (BI-RADS 4 and 5) that resulted in a histological diagnosis of cancer within 1 year.
Positive predictive value of biopsies resulting in histological diagnosis (PPV3)Up to 1 yearPPV3 is the percentage of all known biopsies performed as a result of positive supplemental MRI screening (BI-RADS 4 or 5) that resulted in a tissue diagnosis of cancer within 1 year.
False Positive Rate (FPR)Up to 1 yearA false positive is defined as an imaging result that incorrectly identifies a condition as present. The FPR = (False Positives / Total Tests) × 100 (or 1 - specificity) of results on supplemental screening MRIs in participants with high Mirai risk.
Mean tumor size detected in supplemental imagingUp to 1 yearMean tumor size in millimeters (mm) with in situ and invasive components separately on supplemental screening MRI in Mirai high risk participants.
Frequency of tumor stage detected in supplemental imagingUp to 1 yearThe frequency of tumor stage diagnosed using the supplemental screening MRI in Mirai high risk participants will be reported.
CDR of participants designated as low risk using the Tyrer-Cuzick (TC) criteriaUp to 1 yearCancer detection rate is defined as the number of breast cancers identified per 1,000 MRI screening examinations performed of supplemental screening breast MRI in participants with high Mirai risk and low (\<20%) lifetime TC risk.
Proportion of participants with lymph node involvement detected in supplemental imagingUp to 1 yearThe proportion of participants with demonstrated lymph node involvement of cancers detected on the supplemental screening MRI in Mirai high risk participants.
Correlation between race/ethnicity and CDRUp to 1 yearThe Spearman's correlation coefficient (rs) will be used to measure the strength and direction of association between race/ethnicity and CDR. The Spearman correlation coefficient, rs, results in values from +1 to -1 where a value of +1 indicates a perfect association, and rs of 0 indicates no association and an rs of -1 indicates a perfect negative association. The closer rs is to 0, the weaker the association
Correlation between menopausal status and CDRUp to 1 yearThe Spearman's correlation coefficient (rs) will be used to measure the strength and direction of association between menopausal status and CDR. The Spearman correlation coefficient, rs, results in values from +1 to -1 where a value of +1 indicates a perfect association, and rs of 0 indicates no association and an rs of -1 indicates a perfect negative association. The closer rs is to 0, the weaker the association
Correlation between hormonal status and CDRUp to 1 yearThe Spearman's correlation coefficient (rs) will be used to measure the strength and direction of association between hormonal status and CDR. The Spearman correlation coefficient, rs, results in values from +1 to -1 where a value of +1 indicates a perfect association, and rs of 0 indicates no association and an rs of -1 indicates a perfect negative association. The closer rs is to 0, the weaker the association.
Correlation between breast density and CDRUp to 1 yearThe Pearson correlation coefficient (r) will be used to measure the strength and direction of association between breast density and CDR. The Pearson correlation coefficient (r) can take values from +1 to -1 where a value of +1 indicates a perfect association, a value of 0 indicates no association, and a value of -1 indicates a perfect negative association. The closer r is to 0, the weaker the association.
Correlation between family history of cancer and CDRUp to 1 yearThe Spearman's correlation coefficient (rs) will be used to measure the strength and direction of association between history of cancer and CDR. The Spearman correlation coefficient, rs, results in values from +1 to -1 where a value of +1 indicates a perfect association, and rs of 0 indicates no association and an rs of -1 indicates a perfect negative association. The closer rs is to 0, the weaker the association.
Proportion of participants with Ki-67 expressed biomarkerUp to 1 yearKi-67 is divided according to percentage levels: \< 15% and \> 15%. The proportion of participants with pathologically confirmed Ki-67 by percentage level will be reported.

Countries

United States

Contacts

Primary ContactTiffany Tran
tiffany.tran3@ucsf.edu877-827-3222

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026