Improving breast cancer risk assessment using standard biopsy images
Efficient and cost-effective breast cancer risk stratification using whole slide histopathology images
['FUNDING_R21'] · WAKE FOREST UNIVERSITY HEALTH SCIENCES · NIH-10823271
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
| Phase | ['FUNDING_R21'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | WAKE FOREST UNIVERSITY HEALTH SCIENCES (nih funded) |
| Locations | 1 site (WINSTON-SALEM, UNITED STATES) |
| Trial ID | NIH-10823271 on ClinicalTrials.gov |
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.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients diagnosed with estrogen receptor positive, HER2 negative breast cancer who are at risk of recurrence.
Not a fit: 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.
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 performed: 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
WINSTON-SALEM, UNITED STATES
- 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
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: Breast Cancer, Cancers, neoplasm/cancer