AI-enhanced MRI predictors of recovery after stroke

Global Brain Health Predictors of Post-Stroke Sensorimotor Recovery using AI-Enhanced Clinical MRIs

NIH-funded research University of Southern California · NIH-11227811

This project uses routine hospital brain MRIs, basic patient information, and AI to predict how well people will regain movement and thinking at 3, 6, and 12 months after a stroke.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionUniversity of Southern California NIH-funded
Lab location1 site (Los Angeles, UNITED STATES)
Project IDNIH-11227811 on NIH RePORTER

What this research studies

This work will use your routine clinical brain MRI taken soon after a stroke, along with age and simple behavior tests, to train AI models that forecast motor and cognitive recovery at 3, 6, and 12 months. The team combines measures of global brain health—like ‘brain age,’ white matter changes, and enlarged fluid spaces—with lesion damage and clinical scores to make more accurate predictions. They are building and testing the models using large, existing patient datasets and follow-up visits. The aim is to give clearer, individualized recovery forecasts that can help tailor rehabilitation plans.

Who could benefit from this research

Good fit: Ideal candidates are adults who recently had a stroke and who have routine clinical brain MRIs plus follow-up motor and cognitive assessments.

Not a fit: People without clinical MRI scans, those with non-stroke neurological disorders, or those lacking follow-up data at the specified time points are unlikely to benefit directly.

Why it matters

Potential benefit: If successful, this could provide patients and clinicians clearer, personalized recovery forecasts to inform safer and more targeted rehabilitation choices.

How similar studies have performed: Previous studies, including the team's earlier R01 work, showed that global brain health markers on MRI help predict stroke outcomes, but combining these markers with AI for multi-timepoint forecasts 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.
Last reviewed 2026-06-15 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.