Using advanced MRI and deep learning to improve diagnosis of fatty liver disease
Official title: Quantitative MRI and Deep Learning Technologies for Classification of NAFLD
Funded at University of California Los Angeles · NIH-11086152 · Data updated 2026-11-12
This study is looking at new ways to use advanced MRI technology and deep learning to help doctors better diagnose non-alcoholic fatty liver disease (NAFLD) without needing invasive procedures, making it easier for patients to get accurate results and better care.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | August 1, 2022 |
| Project end | April 30, 2027 |
| Funding year | 2025 |
| Award (this year) | $610,185 |
| NIH project number | 5U01EB031894-04 |
| Project ID | NIH-11086152 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with non-alcoholic fatty liver disease or those at risk of developing it.
✕Less likely to help
Patients with liver diseases unrelated to non-alcoholic fatty liver disease may not benefit from this research.
What this research studies
This research focuses on enhancing the diagnosis of non-alcoholic fatty liver disease (NAFLD) through advanced magnetic resonance imaging (MRI) techniques and deep learning technologies. By developing non-invasive methods to accurately assess liver fat, iron overload, and fibrosis, the project aims to overcome the limitations of traditional liver biopsies, which can be invasive and prone to errors. The study will utilize innovative imaging approaches to improve the accuracy and reproducibility of liver assessments, ultimately facilitating earlier diagnosis and better management of the disease.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and non-invasive diagnostic methods for fatty liver disease, improving patient outcomes.
How similar studies have gone: Previous research has shown promise in using advanced imaging techniques for liver assessment, indicating potential success for this novel approach.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Wu, Holden H — University of California Los Angeles
- Study coordinator: Wu, Holden H
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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.