Using AI to analyze kidney images before and after surgery

Artificial Intelligence-Based Methods to Characterize Kidney Macrostructure from Pre- and Post-Nephrectomy Computed Tomography Images

NIH-funded research Mayo Clinic Rochester · NIH-10977541

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 typeR01 grant
Study typeNIH-funded research
Funding institutionMayo Clinic Rochester NIH-funded
Lab location1 site (Rochester, United States)
Project IDNIH-10977541 on NIH RePORTER

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.

Who could benefit from this research

Good fit: Ideal candidates for this research are patients who are scheduled to undergo radical or partial nephrectomy for kidney cancer.

Not a fit: Patients who have not undergone kidney surgery or those with pre-existing severe kidney disease may not benefit from this research.

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 performed: 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

Rochester, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.