Using AI to analyze kidney images before and after surgery
Official title: Artificial Intelligence-Based Methods to Characterize Kidney Macrostructure from Pre- and Post-Nephrectomy Computed Tomography Images
Funded at Mayo Clinic Rochester · NIH-10977541 · Data updated 2026-11-12
This study is looking at how artificial intelligence can help doctors understand kidney changes in cancer patients before and after surgery, to see if these changes might lead to chronic kidney disease later on, which could help improve care for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Mayo Clinic Rochester NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project start | August 21, 2024 |
| Project end | June 30, 2028 |
| Funding year | 2024 |
| Award (this year) | $351,377 |
| NIH project number | 1R01DK137827-01A1 |
| Project ID | NIH-10977541 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients who are scheduled to undergo radical or partial nephrectomy for kidney cancer.
✕Less likely to help
Patients who have not undergone kidney surgery or those with pre-existing severe kidney disease may not benefit from this research.
What this research studies
This research investigates how artificial intelligence can analyze CT scans of kidneys before and after surgery for cancer. It aims to identify changes in kidney structure that may indicate the risk of developing chronic kidney disease (CKD) after surgery. By using advanced imaging techniques, the study will evaluate the size and condition of the remaining kidney tissue and its potential to compensate for the loss of the affected kidney. The findings could help in predicting patient outcomes and tailoring follow-up care.
Why it matters
Potential benefit: If successful, this research could lead to better monitoring and management of kidney health in patients who have undergone nephrectomy.
How similar studies have gone: Other studies have shown promise in using AI for medical imaging analysis, suggesting that this approach could be effective in predicting kidney health outcomes.
Where this research is happening
-
Mayo Clinic Rochester
Rochester, United States Active
Researchers
- Principal investigator: Denic, Aleksandar — Mayo Clinic Rochester
- Study coordinator: Denic, Aleksandar
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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.