Using digital technology to analyze kidney biopsies in lupus nephritis patients
Official title: Digital Pathology and Computational Image Analysis for Lupus Nephritis
Funded at University of Michigan at Ann Arbor · NIH-11049028 · Data updated 2026-11-12
This study is looking to make it easier and more accurate to diagnose and manage kidney problems caused by lupus, especially for patients of African ancestry, by using advanced technology to better understand kidney biopsies and help doctors catch issues early so they can provide better care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | March 5, 2024 |
| Project end | January 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $604,489 |
| NIH project number | 5R01AR080668-02 |
| Project ID | NIH-11049028 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include adults diagnosed with systemic lupus erythematosus who are experiencing or at risk for lupus nephritis.
✕Less likely to help
Patients with lupus nephritis who are not of African ancestry or those who do not meet the age criteria may not benefit from this research.
What this research studies
This research focuses on improving the diagnosis and management of lupus nephritis, a serious kidney condition associated with systemic lupus erythematosus. By utilizing digital pathology and advanced image analysis techniques, the study aims to enhance the accuracy and reliability of kidney biopsy interpretations. This innovative approach seeks to identify patients at risk of disease progression, potentially shifting treatment strategies from reactive to preventive care. The research will involve analyzing large cohorts of patients, particularly those of African ancestry, to ensure comprehensive and applicable findings.
Why it matters
Potential benefit: If successful, this research could lead to better identification of lupus nephritis patients at risk for severe kidney complications, allowing for earlier intervention and improved patient outcomes.
How similar studies have gone: Other research has shown promising results using digital pathology in various medical fields, indicating potential for success in this novel application for lupus nephritis.
Where this research is happening
-
University of Michigan at Ann Arbor
Ann Arbor, United States Active
Researchers
- Principal investigator: Hodgin, Jeffrey Benton — University of Michigan at Ann Arbor
- Study coordinator: Hodgin, Jeffrey Benton
Related research
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PTPRS and lupus nephritis: a new target to reduce kidney damage in lupus
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-
Objective classification of lupus nephritis using computer vision
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.
-
AI-powered look at lupus nephritis in humans and mice
Researchers will use artificial intelligence to compare kidney tissue from people with lupus nephritis to tissue from mouse models, aiming to understand why treatments work differently in humans.
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.