A Prospective Trial Comparing the Traditional Tyrer Cusick Model With an AI Model (Mirai) to Identify Women With Risk of Breast Cancer

Sponsor
University of Massachusetts, Worcester (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT05968157
Collaborator
(none)
500
1
1
17.1
29.3

Study Details

Study Description

Brief Summary

Accurate risk assessment is essential for the success of population screening programs and early detection efforts in breast cancer. Recently, we've developed a deep learning model based on full resolution mammograms - Mirai.

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 Our secondary aim is to study the impact of new guidelines by race and ethnicity, to ensure equitable improvements in cancer screening.

Condition or Disease Intervention/Treatment Phase
  • Procedure: Breast MRI
N/A

Study Design

Study Type:
Interventional
Anticipated Enrollment :
500 participants
Allocation:
N/A
Intervention Model:
Single Group Assignment
Masking:
None (Open Label)
Primary Purpose:
Screening
Official Title:
A Prospective Trial Comparing the Traditional Tyrer Cusick Model With an AI Model (Mirai) to Identify Women With Risk of Breast Cancer
Anticipated Study Start Date :
Aug 1, 2023
Anticipated Primary Completion Date :
Sep 1, 2024
Anticipated Study Completion Date :
Jan 1, 2025

Arms and Interventions

Arm Intervention/Treatment
Other: Breast MRI Screening for High Risk Patients

Breast MRI will be recommended for patients who are deemed high risk by either the traditional model (Tyrer Cusick) or the Mirai model.

Procedure: Breast MRI
Patients who are identified as high risk for breast cancer by Mirai guidelines are invited to receive supplemental MRI. In addition, the patients eligible for MRI screening according to other guidelines will also be screened to collect additional comparison data. Cancer outcomes will then be compared between patients only identified as high risk by Mirai and patients identified as high risk by existing guidelines.

Outcome Measures

Primary Outcome Measures

  1. CDR Mirai Assessment versus CDR Traditional High Risk Screening [1.5 years (duration of patient recruitment and outcome data collection)]

    Cancer detection rate from breast MRI following Mirai assessment of high risk on a screening mammorgram performed less than 1 year ago and compared with established CDR in traditional high risk screening.

Secondary Outcome Measures

  1. Cancer development within study population versus general population of average risk women [1.5 years (duration of patient recruitment and outcome data collection)]

    On subsequent follow-up with standard of care, assessment of what percentage of the study population develops breast cancer as compared to the general population of women at average risk of breast cancer.

Eligibility Criteria

Criteria

Ages Eligible for Study:
40 Years and Older
Sexes Eligible for Study:
Female
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Women who were identified as high risk on the retrospective study (dating from 2017-2022) 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

Contacts and Locations

Locations

Site City State Country Postal Code
1 UMass Medical School Worcester Massachusetts United States 01655

Sponsors and Collaborators

  • University of Massachusetts, Worcester

Investigators

  • Principal Investigator: Mohammed Shazeeb, PhD, UMass Chan Medical School

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Mohammad Salman Shazeeb, Director - Image Processing & Analysis Core; Director of Preclinical MRI & Co-Director of Scientific Affairs (Advanced MRI Center); UMass Chan Medical School, University of Massachusetts, Worcester
ClinicalTrials.gov Identifier:
NCT05968157
Other Study ID Numbers:
  • STUDY000000485
First Posted:
Aug 1, 2023
Last Update Posted:
Aug 1, 2023
Last Verified:
Jul 1, 2023
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by Mohammad Salman Shazeeb, Director - Image Processing & Analysis Core; Director of Preclinical MRI & Co-Director of Scientific Affairs (Advanced MRI Center); UMass Chan Medical School, University of Massachusetts, Worcester
Additional relevant MeSH terms:

Study Results

No Results Posted as of Aug 1, 2023