Brazilian and French researchers have developed an imaging-based AI tool to predict how multiple sclerosis patients will respond to natalizumab treatment.
Key Details
- 1Combines high-content cell imaging and machine learning to analyze patient blood samples before natalizumab therapy.
- 2Study used over 400 cell morphological features, with 130 key characteristics for prediction.
- 3Tool achieved 92% accuracy in discovery and 88% in validation cohorts for predicting drug response.
- 4Non-responders showed distinct actin remodeling and cell morphology (more elongated CD8+ T cells).
- 5Findings published in Nature Communications, suggesting potential for broader disease and drug applications.
Why It Matters
This research demonstrates how imaging AI and advanced cell analysis can enable more personalized and effective treatment strategies in neurology. Such approaches could optimize resource use, reduce side effects, and accelerate precision medicine adoption in radiology and adjacent fields.
Source
EurekAlert
Related News
•EurekAlert
Researchers Develop All-Optical Synapse for Neuromorphic Imaging Systems
A new artificial synapse, controlled entirely by light, enables in-sensor neuromorphic processing for more efficient and noise-resistant imaging systems.
•EurekAlert
Mayo Clinic Showcases Imaging AI and Early Cancer Detection Advances at ASCO 2026
Mayo Clinic researchers will present over 30 studies at ASCO 2026, highlighting new advances in imaging AI, data science, and early cancer detection.
•EurekAlert
AI-Simulation Approach Achieves 90% Faster Brain MRI with Minimal Data
A simulation-based AI method can reconstruct brain MRI scans with only 10% of the usual data, greatly reducing scan times.