Using machine learning to improve breast MRI screening for women at risk of breast cancer
Machine learning for risk-adjusted breast MRI screening
['FUNDING_R01'] · CITY COLLEGE OF NEW YORK · NIH-10984492
This study is looking to improve breast MRI screenings for women at high risk of breast cancer, like those with a family history or certain genetic traits, by using smart technology to help figure out who really needs these tests, so we can avoid unnecessary procedures while still keeping an eye on those who need it most.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | CITY COLLEGE OF NEW YORK (nih funded) |
| Locations | 1 site (NEW YORK, UNITED STATES) |
| Trial ID | NIH-10984492 on ClinicalTrials.gov |
What this research studies
This research focuses on enhancing breast MRI screening for women with a high risk of breast cancer, such as those with a strong family history or genetic mutations. By utilizing advanced machine learning techniques, the project aims to analyze a large dataset of breast MRI exams to identify which women may not need to undergo unnecessary screenings. The goal is to accurately estimate individual cancer risk based on current MRI and mammogram images, potentially reducing the number of unnecessary exams while still ensuring that high-risk patients receive appropriate care. The research leverages a comprehensive database from Memorial Sloan Kettering Cancer Center, which includes extensive clinical outcomes and imaging data.
Who could benefit from this research
Good fit: Ideal candidates for this research are women with a strong family history of breast cancer or known genetic mutations that increase their risk.
Not a fit: Patients who do not have a family history of breast cancer or genetic predispositions may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and efficient breast cancer screening, reducing unnecessary procedures for low-risk women while ensuring that high-risk individuals receive timely care.
How similar studies have performed: Other research has shown promise in using machine learning for medical imaging, indicating that this approach could be effective in improving breast cancer screening.
Where this research is happening
NEW YORK, UNITED STATES
- CITY COLLEGE OF NEW YORK — NEW YORK, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: PARRA, LUCAS C — CITY COLLEGE OF NEW YORK
- Study coordinator: PARRA, LUCAS C
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions: anti-cancer therapy, Breast Cancer, Breast Cancer Detection, breast cancer diagnosis