Improving breast cancer risk assessment using standard biopsy images
Official title: Efficient and cost-effective breast cancer risk stratification using whole slide histopathology images
Funded at Wake Forest University Health Sciences · NIH-10823271 · Data updated 2026-11-12
This study is looking to improve how we predict the risk of breast cancer coming back by using regular biopsy images, which could help doctors create more personalized treatment plans and avoid unnecessary chemotherapy for patients with certain types of breast cancer.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Wake Forest University Health Sciences NIH-funded |
| Lab location | 1 site (Winston-Salem, United States) |
| Project start | April 6, 2023 |
| Project end | March 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $203,434 |
| NIH project number | 5R21CA273665-02 |
| Project ID | NIH-10823271 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with estrogen receptor positive, HER2 negative breast cancer who are at risk of recurrence.
✕Less likely to help
Patients with other types of breast cancer or those who do not have estrogen receptor positive, HER2 negative tumors may not benefit from this research.
What this research studies
This research aims to enhance the accuracy of breast cancer risk assessment by utilizing routine biopsy images stained with hematoxylin and eosin (H&E). The goal is to develop an automated method that can predict the Oncotype DX recurrence score without the need for expensive and time-consuming gene assays. By analyzing the histopathological features in these images, the research seeks to stratify patients based on their risk of cancer recurrence, particularly for those with estrogen receptor positive and HER2 negative breast cancer. This approach could lead to more personalized treatment plans and reduce unnecessary chemotherapy for patients.
Why it matters
Potential benefit: If successful, this research could provide a more accessible and cost-effective method for assessing breast cancer recurrence risk, leading to better treatment decisions for patients.
How similar studies have gone: Other research has shown promise in using automated methods for predicting cancer recurrence risk from histopathological images, but this specific approach is innovative and aims to improve upon existing methods.
Where this research is happening
-
Wake Forest University Health Sciences
Winston-Salem, United States Active
Researchers
- Principal investigator: Gurcan, Metin Nafi — Wake Forest University Health Sciences
- Study coordinator: Gurcan, Metin Nafi
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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.