Retinal nerve fiber bundle tracing and analysis in human eye by polarization sensitive OCT

Area of Science:

• Ophthalmology
• Medical Imaging
• Biomedical Engineering

Background:

• Accurate tracing of retinal nerve fiber bundles is crucial for diagnosing and monitoring neurodegenerative and ocular diseases.
• Current methods for analyzing the nerve fiber layer (NFL) often lack precision or require extensive manual processing.
• Polarization-sensitive optical coherence tomography (PS-OCT) offers unique insights into tissue birefringence, relevant to NFL structure.

Purpose of the Study:

• To introduce a novel semi-automatic processing method for tracing retinal nerve fiber bundles using PS-OCT data.
• To create a combined nerve fiber orientation map by fusing polarization and thickness variation data.
• To demonstrate the utility of this method for generating along-trace maps of NFL properties.

Main Methods:

• A semi-automatic tracing method was developed utilizing nerve fiber orientation maps derived from PS-OCT datasets.
• Optic axis orientation from polarization data and local thickness variation from the NFL were combined to generate orientation maps.
• Fusion of these maps created a comprehensive fiber orientation map for tracing nerve fiber bundles.
• En face maps (retardation, thickness, unit-depth-retardation/birefringence) were transformed into along-trace maps.

Main Results:

• The method successfully generated nerve fiber bundle traces in healthy volunteers' eyes.
• Combined orientation maps effectively revealed fiber bundle structures around the fovea and optic nerve head (ONH).
• Transformed along-trace maps provided detailed visualization of NFL retardation, thickness, and birefringence gradients.

Conclusions:

• The presented semi-automatic PS-OCT method offers an efficient approach for retinal nerve fiber bundle tracing.
• This technique facilitates advanced analysis of NFL properties, aiding in the understanding of retinal structure and disease.
• The along-trace mapping capability provides valuable quantitative data for ophthalmological research and clinical applications.