Retinal Nerve Fiber Layer

The retinal nerve fiber layer (RNFL) is a thin layer of nerve fibers originating from the ganglion cells in the retina and converging to form the optic nerve, which serves as a conduit for visual signals from the retina to the brain [1–3]. One of the earliest and most pathognomonic features of glaucoma is RNFL [2, 4, 5]. Structural loss of the RNFL layer precedes visual field damage by many years; this is crucial for diagnosing pre-perimetric glaucoma and monitoring disease progression [5, 6]. Thus, RNFL is an important biomarker for glaucoma diagnosis and monitoring disease progression. The RNFL thickness can be measured using a variety of techniques, including optical coherence tomography (OCT), scanning laser polarimetry (SLP), and confocal scanning laser ophthalmoscopy (CSLO) [2, 5–7]. While technological developments have improved the resolution and accuracy of imaging modalities used for RNFL measurements, artificial intelligence (AI) has emerged as a promising tool for detecting and measuring RNFL defects in glaucoma. This chapter will elaborate on the anatomical characterization of the RNFL and its relevance in glaucoma while detailing methods to assess them. This chapter will also discuss using AI-based tools for RNFL assessment using fundus imaging.