Using AI with kidney ultrasound to find scarring
Official title: Development and Validation of a Deep Learning system to estimate Interstitial Fibrosis from a kidney ultrasonography image
Funded at University of California, San Diego · NIH-11143702 · Data updated 2026-11-12
This project is creating an artificial intelligence tool that uses routine kidney ultrasound pictures to find and measure scarring in the kidneys for people with chronic kidney disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project start | September 22, 2023 |
| Project end | July 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $327,174 |
| NIH project number | 5R01DK138395-03 |
| Project ID | NIH-11143702 on NIH RePORTER |
Who could benefit from this research
✓Could help
This research is relevant to patients with chronic kidney disease who may have or be at risk for interstitial fibrosis.
✕Less likely to help
Patients without chronic kidney disease or those not needing assessment for kidney scarring would not directly benefit from this specific research.
What this research studies
Kidney scarring, called interstitial fibrosis, is a common problem in chronic kidney disease and can predict how well your kidneys will work in the future. Currently, the only way to know if you have this scarring is through a kidney biopsy, which is an invasive procedure. This project aims to develop a new, non-invasive way to detect and measure kidney scarring using artificial intelligence to interpret standard ultrasound images. If successful, this could help doctors understand your kidney health better without needing a biopsy.
Why it matters
Potential benefit: If successful, this could provide a non-invasive way to detect and monitor kidney scarring, helping doctors make more informed treatment decisions for patients with chronic kidney disease.
How similar studies have gone: Preliminary data has shown promising results for using deep learning with kidney ultrasound to assess fibrosis, indicating a novel and potentially successful approach.
Where this research is happening
-
University of California, San Diego
La Jolla, United States Active
Researchers
- Principal investigator: Athavale, Ambarish — University of California, San Diego
- Study coordinator: Athavale, Ambarish
Related research
Other NIH-funded projects on the same topics.
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Deep learning to estimate kidney scarring from ultrasound
A new AI-based tool uses ultrasound images to estimate kidney scarring (interstitial fibrosis) without needing a biopsy, helping people with chronic kidney disease and their doctors track disease.
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Using AI to analyze kidney ultrasound images for fibrosis assessment
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Measuring liver scarring using MRI and advanced computer techniques
This study is looking for a gentle way to check for liver scarring in people with chronic liver disease using advanced MRI technology and smart computer programs, so you won’t need any painful biopsies.
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.