Objective classification of lupus nephritis using computer vision
Official title: Objective Classification of Lupus Nephritis
Funded at University of Houston · NIH-11377551 · Data updated 2026-11-12
A new computer vision tool uses deep learning to classify lupus nephritis from kidney tissue images to help doctors predict outcomes for patients with lupus.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Houston NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | August 20, 2023 |
| Project end | May 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $605,010 |
| NIH project number | 5R01DK134055-04 |
| Project ID | NIH-11377551 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with systemic lupus erythematosus who undergo kidney biopsy for suspected lupus nephritis.
✕Less likely to help
If biopsy data are unavailable or image quality is poor, the AI tool may not offer added guidance.
What this research studies
This project will develop a deep learning model that analyzes biopsy images to assign lupus nephritis classes and identify key histological features. It will compare the AI model’s classifications with those of expert renal pathologists and aim to predict patient outcomes from baseline pathology. If successful, the tool could support faster, more consistent kidney disease diagnoses and informed treatment decisions for people with lupus. The study focuses on real patient tissue samples and established diagnostic criteria to enhance accuracy and reproducibility.
Why it matters
Potential benefit: If successful, it could improve diagnostic consistency and help tailor treatments to reduce progression to kidney failure in lupus patients.
How similar studies have gone: Prior studies show that AI-based image analysis can match or exceed human performance in pathology tasks, but clinical translation remains ongoing.
Where this research is happening
-
University of Houston
Houston, United States Active
Researchers
- Principal investigator: Mohan, Chandra — University of Houston
- Study coordinator: Mohan, Chandra
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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.