Using computer analysis of kidney transplant biopsies to predict transplant success
Official title: Computational Image Analysis of Renal Transplant Biopsies to Predict Graft Outcome
Funded at University of Florida · NIH-10920408 · Data updated 2026-11-12
This study is looking at how using advanced computer imaging can help doctors better understand kidney tissue in transplant patients, with the hope of improving transplant success and reducing the need for extra surgeries.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Florida NIH-funded |
| Lab location | 1 site (Gainesville, United States) |
| Project start | September 6, 2023 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $532,457 |
| NIH project number | 5R01DK129541-02 |
| Project ID | NIH-10920408 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who are first-time kidney transplant recipients.
✕Less likely to help
Patients who are not undergoing kidney transplantation or those with previous transplant failures may not benefit from this research.
What this research studies
This research focuses on improving kidney transplant outcomes by utilizing advanced computer image analysis techniques on biopsy samples. By integrating high-resolution digital imaging with artificial intelligence, the project aims to identify chronic changes in kidney tissue that traditional methods may overlook. This innovative approach seeks to enhance the prediction of graft dysfunction and optimize treatment strategies for transplant recipients. Ultimately, the goal is to improve the management of kidney transplants and reduce the need for additional surgeries.
Why it matters
Potential benefit: If successful, this research could lead to better prediction of kidney transplant success, improving patient outcomes and quality of life.
How similar studies have gone: Other research has shown promise in using digital image analysis for predicting transplant outcomes, indicating that this approach may be effective.
Where this research is happening
-
University of Florida
Gainesville, United States Active
Researchers
- Principal investigator: Sarder, Pinaki — University of Florida
- Study coordinator: Sarder, Pinaki
Related research
Other NIH-funded projects on the same topics.
-
Targeting early oral GVHD to improve mouth health after stem cell transplant
A study at UW–Madison will explore why some transplant patients develop painful oral GVHD and test ideas to prevent and lessen mouth-related problems.
-
Innate and Adaptive Immunoregulation in Liver Transplant Ischemia/Reperfusion Injury
A liver transplant-focused project investigates how the body’s early and later immune responses affect transplant failure or success after reperfusion.
-
Exercise-based frailty program for people awaiting lung transplants
A tailored exercise and lifestyle program is being tested to reduce frailty and improve outcomes for people waiting for a lung transplant.
-
Diabetes and Donor Tissue in Corneal Transplants
This grant studies whether corneas from donors with diabetes affect the success of Descemet membrane endothelial keratoplasty (DMEK) and what factors predict better or worse outcomes.
-
Microbial clues to diagnose and predict infections in kidney transplant patients
A patient-focused project will look for microbial biomarkers in stool, blood, and urine to help doctors predict and diagnose infections in people who have had a kidney transplant.
-
Medicare Advantage and Transplant Access for Rural and Vulnerable Communities
Aimed at understanding how Medicare Advantage affects early steps to kidney transplant for adults in rural or socioeconomically challenged groups.
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.