Comparing MRI screening for high-risk breast cancer patients using Mirai and Tyrer-Cuzick models

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

This study is testing if a new AI tool called Mirai can find breast cancer in high-risk women better than the usual method, so they can get screened with MRI within a year.

Quick facts

• Phase: Not applicable
• Study type: Interventional
• Enrollment: 200 (estimated)
• Ages: 40 Years and up
• Sex: Female
• Sponsor: University of Massachusetts, Worcester (Academic / other)
• Locations: 1 site (Worcester, Massachusetts)
• Trial ID: NCT05968157 on ClinicalTrials.gov

What this trial studies

This study aims to evaluate the effectiveness of the Mirai deep learning model in identifying high-risk breast cancer patients compared to the traditional Tyrer-Cuzick model. Women identified as high risk will be invited to undergo supplemental MRI screening within 12 months. The study will assess the cancer detection rates from MRI and compare these results to the current standard of care. By leveraging advanced AI technology, the study seeks to improve early detection and risk assessment in breast cancer screening.

Who should consider this trial

Good fit: Ideal candidates are women over 40 years old identified as high risk for breast cancer by the Mirai model or traditional guidelines.

Not a fit: Patients who are not classified as high risk for breast cancer will likely not benefit from this study.

Why it matters

Potential benefit: If successful, this study could enhance early detection of breast cancer in high-risk patients, potentially leading to better outcomes.

How similar studies have performed: Previous studies have shown promise in using AI models for breast cancer risk assessment, suggesting a potential for success in this novel approach.

Eligibility criteria

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

Where this trial is running

Worcester, Massachusetts

• UMass Medical School — Worcester, Massachusetts, United States (Recruiting)

Study contacts

• Principal investigator: Mohammed Salman Shazeeb, PhD — UMass Chan Medical School
• Study coordinator: Sara Schiller, MPH

Conditions Breast Cancer; Screening; Artificial Intelligence