Retinal Damage and Visual Network Reconfiguration Defines Visual Function Recovery in Optic Neuritis

Abstract

Background and objectives: Recovery of vision after acute optic neuritis (AON) is critical to improving the quality of life of people with demyelinating diseases. The objective of the study was to prospectively assess the changes in visual acuity, retinal layer thickness, and cortical visual network in patients with AON to identify the predictors of permanent visual disability.

Methods: We studied a prospective cohort of 88 consecutive patients with AON with 6-month follow-up using high and low-contrast (2.5%) visual acuity, color vision, retinal thickness from optical coherence tomography, latencies and amplitudes of multifocal visual evoked potentials, mean deviation of visual fields, and diffusion-based structural (n = 53) and functional (n = 19) brain MRI to analyze the cortical visual network. The primary outcome was 2.5% low-contrast vision, and data were analyzed with mixed-effects and multivariate regression models.

Results: We found that after 6 months, low-contrast vision and quality of vision remained moderately impaired. The thickness of the ganglion cell layer at baseline was a predictor of low-contrast vision 6 months later (ß = 0.49 [CI 0.11-0.88], p = 0.012). The structural cortical visual network at baseline predicted low-contrast vision, the best predictors being the betweenness of the right parahippocampal cortex (ß = -036 [CI -0.66 to 0.06], p = 0.021), the node strength of the right V3 (ß = 1.72 [CI 0.29-3.15], p = 0.02), and the clustering coefficient of the left intraparietal sulcus (ß = 57.8 [CI 12.3-103.4], p = 0.015). The functional cortical visual network at baseline also predicted low-contrast vision, the best predictors being the betweenness of the left ventral occipital cortex (ß = 8.6 [CI: 4.03-13.3], p = 0.009), the node strength of the right intraparietal sulcus (ß = -2.79 [CI: -5.1-0.4], p = 0.03), and the clustering coefficient of the left superior parietal lobule (ß = 501.5 [CI 50.8-952.2], p = 0.03).

Discussion: The assessment of the visual pathway at baseline predicts permanent vision disability after AON, indicating that damage is produced early after disease onset and that it can be used for defining vision impairment and guiding therapy.

Figure 1. Change in Retina Layer Thicknesses During the 6-Month Follow-Up Period

Graphs show the longitudinal changes (from baseline to month 6) in each patient on the thickness of the inner retina layers for the affected eye (ON) and the non-affected eye (no ON). The y-axis represents absolute retina thickness. The x axis represents the time (days) from clinical onset. (A) Ganglion cells plus inner plexiform layer (GCIPL); (B) peripapillary retinal nerve fiber layer (pRNFL); (C) macular retinal nerve fiber layer (mRNFL); (D) inner nuclear layer (INL).

Figure 2. Linear Spline Mixed-Effect Models of Retina Layer Thicknesses

Linear spline mixed-effect models with 2 knots at 26 and 71 days for the GCIPL (A) and pRNFL (B). The black points joined by a dashed line represent the individual trajectories of retinal thickness changes, the thicker curves represent the individual fit of the model, and the dark red line represents the population model.

Figure 3. Predictors of Permanent Visual Impairment After Acute Optic Neuritis Based on the Severity of Retina Damage at Presentation

Graphs show the significant models from linear regression analysis for 2.5% low-contrast visual acuity (LCVA) and color vision (HRR plates) with the ganglion cell inner plexiform layer thickness as the independent variable.

Figure 4. Structural and Functional Visual Network in Patients With AON Predicting Long-Term Visual Function

(A) The visual network as described by Wang et al., depicting the ventral-temporal nodes in blue, dorsoparietal nodes in green, and parietal-frontal nodes in orange; (B) the visual structural network predicting visual acuity; (C) the visual functional network nodes predicting visual acuity. Visual function is defined with 2.5% low-contrast visual acuity (2.5% LCVA), high-contrast vision using LogMAR (HVCA LogMAR), and color vision using the HRR plates 2.5% contrast. The network parameters are (a) betweenness centrality, (b) node strength, and (c) clustering coefficient.