Using Enhanced Depth Imaging Optical Coherence Tomography-Derived Parameters to Discriminate between Eyes with and without Glaucoma: A Cross-Sectional Comparative Study.

Journal: Ophthalmic Research
Published:
Abstract

Background: New technologies have been developed in order to decrease interpersonal influence and subjectivity during the glaucoma diagnosis process. Enhanced depth imaging spectral-domain OCT (EDI OCT) has turned up as a favorable tool for deep optic nerve head (ONH) structures assessment.

Objective: A prospective cross-sectional study was conducted to compare the diagnostic performance of different EDI OCT-derived parameters to discriminate between eyes with and without glaucoma.

Methods: The following ONH parameters were measured: lamina cribrosa (LC) thickness and area; prelaminar neural tissue (PLNT) thickness and area; average Bruch's membrane opening - minimum rim width (BMO-MRW), superior BMO-MRW, and inferior BMO-MRW. Peripapillary retinal nerve fiber layer (pRNFL) thickness was also obtained.

Results: Seventy-three participants were included. There were no significant differences between AUCs for average BMO-MRW (0.995), PLNT area (0.968), and average pRNFL thickness (0.975; p ≥ 0.089). However, AUCs for each of these 3 parameters were significantly larger than LC area AUC (0.701; p ≤ 0.001). Sensitivities at 80% specificity were: PLNT area = 92.3%, average BMO-MRW = 97.4%, and average pRNFL thickness = 94.9%.

Conclusions: Comparing the diagnostic performance of different EDI OCT ONH parameters to discriminate between eyes with and without glaucoma, we found better results for neural tissue-based indexes (BMO-MRW and PLNT area) compared to laminar parameters. In this specific population, these neural tissue-based parameters (including PLNT area, which was investigated by the first time in the present study) had a diagnostic performance comparable to that of the conventional pRNFL thickness protocol.

Authors
Flavio Siqueira Lopes, Igor Matsubara, Izabela Almeida, Carolina Pelegrini Gracitelli, Syril Dorairaj, Roberto Vessani, Augusto Paranhos, Tiago Prata