MIRAI-MRI: Comparing Screening MRI for Patients at High Risk for Breast Cancer Identified by Mirai and Tyrer-Cuzick

Study Results

Results pending

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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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

200 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-02-04

Study Completion Date

2027-09-30

Brief Summary

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Accurate risk assessment is essential for the success of population screening programs and early detection efforts in breast cancer. Mirai is a new deep learning model based on full resolution mammograms.

Mirai is a mammography-based deep learning model designed to predict risk at multiple timepoints, leverage potentially missing risk factor information, and produce predictions that are consistent across mammography machines. Mirai was trained on a large dataset from Massachusetts General Hospital (MGH) in the United States and found to be significantly more accurate than the Tyrer-Cuzick model, a current clinical standard.

The primary aim of this study is to prospectively quantify the clinical benefit (i.e. MRI/CEM cancer detection rate) of Mirai-based guidelines and to compare them to the current standard of care.

1. Conduct a prospective study where patients who are identified as high risk by Mirai guidelines are invited to receive supplemental MRI within 12 months.
2. Compare cancer outcomes between patients only identified as high risk by Mirai and patients identified as high risk by existing guidelines The secondary aim is to study the impact of new guidelines by race and ethnicity, to ensure equitable improvements in cancer screening.

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Detailed Description

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Conditions

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Breast Cancer

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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High Risk Participants--MIRAI

Patients who are deemed high risk on standard breast screening mammogram by the MIRAI model

Group Type EXPERIMENTAL

Breast MRI

Intervention Type DIAGNOSTIC_TEST

Supplemental MRI (in addition to standard of care MRI).

MIRAI

Intervention Type DEVICE

Artificial intelligence software

High Risk Participants--non-MIRAI

Patients who are deemed high risk by Tyrer-Cuzick model but not MIRAI

Group Type ACTIVE_COMPARATOR

Breast MRI

Intervention Type DIAGNOSTIC_TEST

Supplemental MRI (in addition to standard of care MRI).

Interventions

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Breast MRI

Supplemental MRI (in addition to standard of care MRI).

Intervention Type DIAGNOSTIC_TEST

MIRAI

Artificial intelligence software

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Women who were identified as high risk on the retrospective study (dating from 2017-2025) using MIRAI will be recruited and consented for the prospective study
* Women over 40 years of age identified as high risk according to traditional guidelines will also be potentially eligible for this study
* Following consent and enrollment in the study, a participant will subsequently receive the following:

1. These patients will be invited to receive a supplemental MRI examination currently considered the most sensitive test for breast cancer detection.
2. Any positive diagnosis on MRI will be followed by biopsy to confirm 'truth" of diagnosis.
* To be selected, a given record must include the following:

1. A report of a routine screening mammogram or diagnostic mammogram, and availability of the DICOM images from that report with the PACS system.
2. Reports of all follow up screening and diagnostic studies documented on PACS.
3. Some may have interventional procedures (as long as all of these are done at one of Umass sites) and documentation of these biopsy results in the hospitals EHR.

Exclusion Criteria

* Under age 40. Women under 40 years are not routinely xrayed with a mammogram.
* Xray breast cancer screening imaging study that has artifacts, corruption, or other image quality degradation.
* Pregnant patients because they do not routinely receive screening mammogram
* Adult male patients with breast cancer

Minimum Eligible Age

40 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Responsible Party

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Mohammad Salman Shazeeb

Director - Image Processing & Analysis Core; Director of Preclinical MRI & Co-Director of Scientific Affairs (Advanced MRI Center); UMass Chan Medical School

Responsibility Role PRINCIPAL_INVESTIGATOR