AI-assisted review of donated kidney biopsy images
Optimizing Preimplantation Kidney Transplant Biopsy Interpretation with Artificial Intelligence Assistance - Resubmission - 1
Using an AI tool to help pathologists read donor kidney biopsies so more usable deceased-donor kidneys can be transplanted for people on the waitlist.
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 ID | NIH-11181564 on NIH RePORTER |
What this research studies
This project builds an AI system that reads digital images of preimplantation kidney biopsies to match expert pathologist interpretations. The team will train a novel self-supervised deep learning model to find histologic patterns linked to good transplant outcomes and compare its readings to on-call pathologist reports. The goal is to give transplant teams fast, reliable biopsy information any time of day so potentially good kidneys are not needlessly discarded. If successful, the AI would be deployed to support decision-making across transplant centers and reduce variability in biopsy interpretation.
Who could benefit from this research
Good fit: People on the deceased-donor kidney transplant waitlist or those receiving an organ offer that relies on a preimplantation biopsy would be the primary group affected by this work.
Not a fit: Patients receiving living-donor transplants or those not eligible for transplant would be unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this could increase the number of usable deceased-donor kidneys offered for transplant and help shorten waitlist times and reduce deaths while waiting.
How similar studies have performed: Previous AI approaches in pathology have shown promise at reproducing expert interpretations, but applying a new self-supervised histomorphology method specifically to preimplantation kidney discard is relatively novel.
Where this research is happening
New York, United States
- 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.
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.