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Updated: Jan 14, 2026

Bioluminescence and Near-infrared Imaging of Optic Neuritis and Brain Inflammation in the EAE Model of Multiple Sclerosis in Mice

Bioluminescence and Near-infrared Imaging of Optic Neuritis and Brain Inflammation in the EAE Model of Multiple Sclerosis in Mice

Published on: March 1, 2017

Imaging biomarkers in optic neuritis: current tools and future directions.

Ziwei Meng¹, Yuhong He¹, Kai Guo²

¹Department of Ophthalmology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.

Frontiers in Neurology

|October 20, 2025

Summary

Recent advances in neuroimaging and biomarkers offer improved diagnosis and personalized treatment for optic neuritis (ON), a CNS inflammatory disorder. This review highlights multimodal imaging, AI, and future directions for precision management.

Keywords:

artificial intelligence imaging biomarkers magnetic resonance imaging optic neuritis optical coherence tomography optical coherence tomography angiography

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Area of Science:

Neuroimmunology
Ophthalmology
Neuroscience

Background:

Optic neuritis (ON) is a key indicator of central nervous system (CNS) inflammatory conditions.
Advances in imaging technologies have significantly improved ON diagnosis and treatment strategies.

Purpose of the Study:

To systematically review recent high-quality literature on advanced imaging techniques for ON.
To explore the combined clinical value of multimodal imaging and immune biomarkers.
To discuss the role of artificial intelligence (AI) and deep learning (DL) in ON image analysis.

Main Methods:

Systematic literature review of optical coherence tomography (OCT), OCT angiography (OCTA), magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI) in ON.
Analysis of studies integrating multimodal imaging with immune biomarkers.
Review of AI and DL applications in analyzing ON imaging data.

Main Results:

Multimodal imaging approaches, including OCT, OCTA, MRI, and DTI, show significant progress in diagnosing and managing ON.
The integration of imaging data with immune biomarkers enhances diagnostic precision and therapeutic guidance.
AI and DL are emerging as powerful tools for objective and efficient image analysis in ON.

Conclusions:

Current innovations in neuroimaging and AI facilitate precision diagnostics for ON.
Future directions include developing standardized multicenter protocols for personalized ON management.
Advancements aim to accelerate clinical translation and enhance the field of neuroimmunological ophthalmology.