AI-assisted kidney transplant biopsy interpretation to reduce discards
Official title: Optimizing Preimplantation Kidney Transplant Biopsy Interpretation with Artificial Intelligence Assistance - Resubmission - 1
Funded at New York University School of Medicine · NIH-11380794 · Data updated 2026-11-12
A kidney transplant study uses artificial intelligence to help interpret biopsy images so more usable kidneys aren’t discarded.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York University School of Medicine NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 5, 2024 |
| Project end | June 30, 2029 |
| Funding year | 2026 |
| Award (this year) | $728,255 |
| NIH project number | 5R01DK138067-03 |
| Project ID | NIH-11380794 on NIH RePORTER |
Who could benefit from this research
✓Could help
Candidates on the kidney transplant waitlist or recipients who may receive kidneys from deceased donors.
✕Less likely to help
Patients unlikely to benefit include those not undergoing kidney transplantation or donors whose biopsies are not used.
What this research studies
This project aims to make preimplantation kidney biopsy readings more accurate and available around the clock by using a new AI framework and deep learning. It focuses on real-time help for pathologists when deciding whether a donor kidney should be used, especially during off-hours. If successful, the approach could lower unnecessary discards and improve transplant outcomes for patients on the waitlist.
Why it matters
Potential benefit: If successful, patients could receive more kidney transplants with better outcomes and shorter waiting times.
How similar studies have gone: Previous work shows AI can aid pathology interpretation, with potential for improved consistency and speed in biopsy readings.
Where this research is happening
-
New York University School of Medicine
New York, United States Active
Researchers
- Principal investigator: Segev, Dorry L. — New York University School of Medicine
- Study coordinator: Segev, Dorry L.
Related research
Other NIH-funded projects on the same topics.
-
Microbial clues to diagnose and predict infections in kidney transplant patients
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-
Immunological mechanisms behind treatment-resistant kidney transplant rejection
This grant explores why certain kidney transplant rejections don’t respond to standard treatments and what immune cells in the graft are driving that resistance.
-
Complement-Bound Exosomes and Kidney Transplant Immunity
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-
Blood vessel signals predicting heart problems after kidney transplant
This project studies blood markers and tissue patterns after kidney transplants to identify which patients are at highest risk of cardiovascular problems.
-
Understanding how BK virus links infection to kidney transplant rejection
This project looks at how BK polyomavirus reactivation affects kidney transplant patients and aims to use pre-transplant T cell information to tailor immunosuppression and monitoring.
-
Characterization of a LILRB3 SNP cluster and its link to kidney transplant outcomes
A study in kidney transplant recipients looks at genetic factors that may be tied to higher risk of graft failure.
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.