AI-enhanced 3D imaging to track drug-target engagement in breast cancer
Official title: AI enhanced lifetime-based mesoscopic in vivo imaging of tissue molecular heterogeneity
Funded at Rensselaer Polytechnic Institute · NIH-11350903 · Data updated 2026-11-12
This NIH grant funds a patient-centered imaging approach to watch how a cancer drug interacts with tumors over time using advanced AI-assisted 3D imaging.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rensselaer Polytechnic Institute NIH-funded |
| Lab location | 1 site (Troy, United States) |
| Project start | June 1, 2023 |
| Project end | May 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $736,568 |
| NIH project number | 5R01CA271371-04 |
| Project ID | NIH-11350903 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with HER2-positive breast cancer or who contribute tissue-derived models (e.g., patient-derived xenografts) may be relevant for related studies and future trials.
✕Less likely to help
This imaging method is not designed for routine care and may not benefit patients whose tumors do not fit the studied models.
What this research studies
Researchers at Rensselaer will develop and optimize a multimodal optical imaging platform that can measure how well a cancer drug engages its target in the same tissue across multiple time points. The work combines AI-driven 2D and 3D image formation with in vivo imaging in human breast tumors and patient-derived xenografts in animals, alongside tracking tumor blood vessels and metabolism to gauge drug response. By validating the approach in models treated with HER2-targeted therapy, the project aims to provide a noninvasive, longitudinal view of drug action that could speed translation to patients. Deep learning will be used to make image reconstruction fast, accurate, and user-friendly for researchers and clinicians.
Why it matters
Potential benefit: If successful, this imaging approach could enable researchers and clinicians to monitor how well a cancer drug is working in a patient’s tumor over time without invasive sampling.
How similar studies have gone: Previous work shows that multimodal imaging combined with AI can reveal drug distribution and response in tumors, but this project advances longitudinal, tissue-wide measurements in humans.
Where this research is happening
-
Rensselaer Polytechnic Institute
Troy, United States Active
Researchers
- Principal investigator: Intes, Xavier — Rensselaer Polytechnic Institute
- Study coordinator: Intes, Xavier
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.