AI-enhanced MRI for detecting and classifying fatty liver disease

Quantitative MRI and Deep Learning Technologies for Classification of NAFLD

['FUNDING_U01'] · UNIVERSITY OF CALIFORNIA LOS ANGELES · NIH-11325723

This project uses faster, motion-robust MRI together with artificial intelligence to improve detection and classification of non-alcoholic fatty liver disease (NAFLD) for patients who need liver evaluation.

Quick facts

Phase['FUNDING_U01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF CALIFORNIA LOS ANGELES (nih funded)
Locations1 site (LOS ANGELES, UNITED STATES)
Trial IDNIH-11325723 on ClinicalTrials.gov

What this research studies

You would get quicker liver MRI scans designed to be easier to tolerate and less affected by breathing motion. The team will apply advanced image reconstruction and deep learning to remove artifacts and extract measures of liver fat, iron, and stiffness. They plan to compare those MRI measures with biopsy and clinical information to teach the AI how to recognize early signs of NASH. The aim is to make MRI more reliable and to spot disease earlier so doctors can treat it sooner.

Who could benefit from this research

Good fit: Adults with known or suspected NAFLD/NASH—for example those with fatty liver on ultrasound or abnormal liver tests—who can travel for MRI scans at the study site.

Not a fit: People with non-NAFLD causes of liver disease, those who cannot undergo MRI (such as patients with incompatible implants or severe claustrophobia), or those with end-stage liver disease may not benefit from this project.

Why it matters

Potential benefit: This could reduce the need for invasive liver biopsies and help catch and treat progressive NASH earlier.

How similar studies have performed: Quantitative MRI and elastography already help measure liver fat and stiffness noninvasively, but combining motion-robust scans with deep learning for early NASH classification is a newer approach.

Where this research is happening

LOS ANGELES, 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.

View on NIH RePORTER →

Last reviewed 2026-05-15 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.