High resolution multi-depth quantification of the retinal nerve fiber layer

Thickness of the retinal nerve fiber layer, composed of axon bundles converging toward the optic nerve head, is a key biomarker for diagnosing and monitoring glaucoma and neurodegenerative diseases. High-resolution en face imaging of individual nerve fiber bundles offers morphological information beyond conventional optical coherence tomography, yet lacks automated analysis tools and normative data. Here, we develop image processing pipelines for automated quantification of bundle trajectory, tortuosity, orientation, and width, and establish a normative database from 18 healthy volunteers enrolled across three studies (n = 15, 11 and 11), imaged using adaptive optics scanning laser ophthalmoscopy and full-field optical coherence tomography. Trajectory analysis revealed systematic deviations from existing mathematical models, leading us to propose two refined models. Bundles were on average 12% wider at shallower retinal depths and bundle width decreased significantly with age. These results and toolkit provide a foundation for high-resolution biomarker extraction in retinal investigations.