PURPOSE. To investigate the relationship between visual function, measured by standard automated perimetry (SAP), and retinal nerve fiber layer (RNFL) thickness, measured by optical coherence tomography (OCT), in patients with multiple sclerosis (MS). METHODS. SAP and RNFL thickness were measured in patients with MS in 28 eyes with the last optic neuritis (ON) ≥6 months prior (ON group) and 33 eyes without ON history (non-ON group). Abnormal overall or quadrant RNFL thickness was defined by measured values below 5% of the norm. A whole visual field or a sector of the field was classified as abnormal by using cluster criteria on total-deviation plots. Agreement between SAP and OCT results in classifying eyes/sectors was presented as a percentage of observed agreement, along with the AC1 statistic, which corrects for chance agreement. Regression analyses were performed relating several SAP parameters and RNFL thickness in the ON group. RESULTS. ON eyes showed more loss of visual sensitivity (MD, P = 0.02) and more loss of RNFL thickness (P < 0.0001) than did non-ON eyes. SAP and OCT agreed in 86% (AC1 = 0.78) of eyes and 69% (AC1 = 0.38) of sectors in the ON group and 61% (AC1 = 0.33) of eyes and 66% (AC1 = 0.48) of sectors in the non-ON group. Overall RNFL thickness was related to MD (dB) by a simple exponential function (R2 = 0.48), supporting a linear relationship between these measures when both are expressed on linear scales. Absolute Pearson correlation coefficients for overall RNFL thickness and several SAP parameters ranged from 0.51 to 0.69. CONCLUSIONS. Good agreement between SAP and OCT was found in ON eyes but not in non-ON eyes or in individual sectors in either group. The findings in this study provide further support for the utility of combining structural and functional testing in clinical research on patients with MS, as well as in future neuroprotection trials for which the anterior visual pathways in patients with MS and optic neuritis may be used as a model.
ASJC Scopus subject areas
- Sensory Systems
- Cellular and Molecular Neuroscience