Retinal Nerve Fibre Layer Assessment in Glaucoma and Glaucoma Suspect by Optical Coherence Tomography (OCT)

Abstract

G laucoma is a progressive optic neuropathy characterized by structural changes in the optic nerve head, retinal nerve fiber layer (RNFL) defect, and accompanying visual field damage (VFD). In glaucoma management, detecting progression is essential in both early and late stages of the disease. In patients with an established diagnosis of glaucoma, evidence of progression will influence a clinician’s decision whether to modify glaucoma therapy. In patients who are suspected of having the disease, progression detection can confirm the diagnosis, and help decide how to manage the patient. Although standard automated perimetry has been the most commonly used test to monitor glaucomatous progression, evidence suggests that in some eyes substantial structural damage can be detected before the development of clinically detectable VFD. Structural assessment of optic nerve head and RNFL with imaging devices is a promising alternative. Many studies have reported the usefulness of event-based analyses, trend based analyses, and other statistical analyses of change in optic nerve head or RNFL over time, using optical coherence tomography (OCT).

Our results showed that; There was highly Significant difference as regards OCT parameters of the patients (p <0.001 for all). As the mean value of Cup/disc ratio was lower in Glaucoma Suspect cases, while Total RNFL, RNFL Superior and RNFL Inferior was higher in Glaucoma Suspected cases than patients with Moderate glaucoma. This study showed that; by using ROC-curve analysis, cup to disc ratio (CDR) at a cutoff point (>0.59) detected patients with glaucoma, with excellent accuracy, sensitivity= 95% and specificity= 100%. Also, by using ROC-curve analysis, superior RNFL at a cutoff point (≤116) detected patients with glaucoma, with fair accuracy, sensitivity= 66% and specificity= 91%. While inferior RNFL at a cutoff point (≤113) detected patients with glaucoma, with good accuracy, sensitivity= 70% and specificity= 95%.