EligibleTrials

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

Recruiting · NCT05968157 · Interventional (participants receive a specific treatment) · Lead sponsor: University of Massachusetts, Worcester

View the official record on ClinicalTrials.gov →
Breast Cancer

Interventions studied

Breast MRIMIRAI

What this trial is about

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.

Who can take part

Age range
40 Years and older
Sex
Female
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not applicable (e.g. observational or device study)
Study type
Interventional (participants receive a specific treatment)

Inclusion criteria

Exclusion criteria

Where it is running

1 location listed across 1 US state.

Read the full protocol, contacts and eligibility on ClinicalTrials.gov →

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