Axel Petzold1, Laura J Balcer2, Peter A Calabresi3, Fiona Costello4, Teresa C Frohman5, Elliot M Frohman5, Elena H Martinez-Lapiscina6, Ari J Green7, Randy Kardon8, Olivier Outteryck9, Friedemann Paul10, Sven Schippling11, Patrik Vermersch12, Pablo Villoslada6, Lisanne J Balk13. 1. Moorfields Eye Hospital, London, UK; Department of Neurology, Amsterdam Neuroscience, VUmc MS Center Amsterdam and Dutch Expertise Centre for Neuro-ophthalmology, VU University Medical Center, Amsterdam, Netherlands; Institute of Neurology, University College London, London, UK. Electronic address: a.petzold@ucl.ac.uk. 2. Department of Neurology, Department of Ophthalmology, and Department of Population Health, New York University School of Medicine, New York, NY, USA. 3. Department of Neurology, Johns Hopkins Hospital, Baltimore, MD, USA. 4. Department of Clinical Neurosciences and Department of Surgery, University of Calgary, Calgary, AB, Canada. 5. Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA. 6. Center of Neuroimmunology, Institute of Biomedical Research August Pi Sunyer, Hospital Clinic of Barcelona, Barcelona, Spain. 7. Multiple Sclerosis Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA. 8. Iowa City VA Center for Prevention and Treatment of Visual Loss, Department of Veterans Affairs Hospital Iowa City, and Department of Ophthalmology and Visual Sciences, University of Iowa Hospital and Clinics, Iowa City, IA, USA. 9. Department of Neurology, University of Lille Nord de France, Lille, France. 10. NeuroCure Clinical Research Center, Charité, Department of Neurology, Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité Universitätsmedizin Berlin, Berlin, Germany. 11. Neuroimmunology and Multiple Sclerosis Research Section, University Hospital Zurich, Zurich, Switzerland. 12. Université Lille, CHRU Lille, LYRIC-INSERM U995, FHU Imminent, Lille, France. 13. Department of Neurology, Amsterdam Neuroscience, VUmc MS Center Amsterdam and Dutch Expertise Centre for Neuro-ophthalmology, VU University Medical Center, Amsterdam, Netherlands.
Abstract
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<0·0001) and in MSNON eyes (-7·41 μm, -8·98 to -5·83; p<0·0001). The macula showed RNFL thinning of -6·18 μm (-8·07 to -4·28; p<0·0001) in MSON eyes and -2·15 μm (-3·15 to -1·15; p<0·0001) in MSNON eyes compared with control eyes. Atrophy of the macular ganglion cell layer and inner plexiform layer (GCIPL) was -16·42 μm (-19·23 to -13·60; p<0·0001) for MSON eyes and -6·31 μm (-7·75 to -4·87; p<0·0001) for MSNON eyes compared with control eyes. A small degree of inner nuclear layer (INL) thickening occurred in MSON eyes compared with control eyes (0·77 μm, 0·25 to 1·28; p=0·003). We found no statistical difference in the thickness of the combined outer nuclear layer and outer plexiform layer when we compared MSNON or MSON eyes with control eyes, but we found a small degree of thickening of the combined layer when we compared MSON eyes with MSNON eyes (1·21 μm, 0·24 to 2·19; p=0·01). 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.
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<0·0001) and in MSNON eyes (-7·41 μm, -8·98 to -5·83; p<0·0001). The macula showed RNFL thinning of -6·18 μm (-8·07 to -4·28; p<0·0001) in MSON eyes and -2·15 μm (-3·15 to -1·15; p<0·0001) in MSNON eyes compared with control eyes. Atrophy of the macular ganglion cell layer and inner plexiform layer (GCIPL) was -16·42 μm (-19·23 to -13·60; p<0·0001) for MSON eyes and -6·31 μm (-7·75 to -4·87; p<0·0001) for MSNON eyes compared with control eyes. A small degree of inner nuclear layer (INL) thickening occurred in MSON eyes compared with control eyes (0·77 μm, 0·25 to 1·28; p=0·003). We found no statistical difference in the thickness of the combined outer nuclear layer and outer plexiform layer when we compared MSNON or MSON eyes with control eyes, but we found a small degree of thickening of the combined layer when we compared MSON eyes with MSNON eyes (1·21 μm, 0·24 to 2·19; p=0·01). 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.
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