Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis

Summary Background Structural retinal imaging biomarkers are important for early recognition and monitoring of inflammation and neurodegeneration in multiple sclerosis. With the introduction of spectral domain optical coherence tomography (SD-OCT), supervised automated segmentation of individual retinal layers is possible. We aimed to investigate which retinal layers show atrophy associated with neurodegeneration in multiple sclerosis when measured with SD-OCT. Methods In this systematic review and meta-analysis, we searched for studies in which SD-OCT was used to look at the retina in people with multiple sclerosis with or without optic neuritis in PubMed, Web of Science, and Google Scholar between Nov 22, 1991, and April 19, 2016. Data were taken from cross-sectional cohorts and from one timepoint from longitudinal studies (at least 3 months after onset in studies of optic neuritis). We classified data on eyes into healthy controls, multiple-sclerosis-associated optic neuritis (MSON), and multiple sclerosis without optic neuritis (MSNON). We assessed thickness of the retinal layers and we rated individual layer segmentation performance by random effects meta-analysis for MSON eyes versus control eyes, MSNON eyes versus control eyes, and MSNON eyes versus MSON eyes. We excluded relevant sources of bias by funnel plots. Findings Of 25 497 records identified, 110 articles were eligible and 40 reported data (in total 5776 eyes from patients with multiple sclerosis [1667 MSON eyes and 4109 MSNON eyes] and 1697 eyes from healthy controls) that met published OCT quality control criteria and were suitable for meta-analysis. Compared with control eyes, the peripapillary retinal nerve fibre layer (RNFL) showed thinning in MSON eyes (mean difference −20·10 μm, 95% CI −22·76 to −17·44; p Interpretation The largest and most robust differences between the eyes of people with multiple sclerosis and control eyes were found in the peripapillary RNFL and macular GCIPL. Inflammatory disease activity might be captured by the INL. Because of the consistency, robustness, and large effect size, we recommend inclusion of the peripapillary RNFL and macular GCIPL for diagnosis, monitoring, and research. Funding None.