Assessments of vessel density and foveal avascular zone metrics in multiple sclerosis: an optical coherence tomography angiography study



To investigate optical coherence tomography angiography (OCT-A) findings of foveal avascular zone (FAZ) metrics and macular & peripapillary vessel densities (VD) in subjects with multiple sclerosis (MS).


The study design was prospective and cross-sectional. FAZ metrics and VDs of the superficial capillary plexus (SCP), deep capillary plexus (DCP), retinal peripapillary capillary plexus (RPCP) along with the structural OCT measurements were scanned by using the Nidek’s RS-3000 Advance in MS patients and healthy controls. All subject also underwent an assessment of visual evoked potentials (VEPs). The relationships between the OCT-A parameters with other clinical findings were analysed.


Forty-seven MS patients (94 eyes) and 61 healthy volunteers (122 eyes) were included in this study. Thirty-five eyes of the MS patients had an ON history. The structural OCT measurements were significantly differed between the groups (P < 0.001). All FAZ metrics were inversely correlated with central foveal thickness (CFT) (P< 0.001). The FAZ area and perimeter were inversely correlated with the VD of both SCP and DCP (P< 0.05). The VDs of SCP and DCP were significantly differed between the study groups (P< 0.001). The VEP latency was inversely correlated with the retinal nerve fibre layer, macular and ganglion cell layer thicknesses, the VD of SCP, and the VD of the DCP (P< 0.001).


Based on OCT angiography, VDs of macular and peripapillary area may be useful in detecting damage from ON in patients with MS.

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Fig. 1: Vessel density of SCP(B1, C1, D1), DCP(B2, C2, D2), and RPCP(B3, C3, D3).


  1. 1.

    Britze J, Frederiksen JL. Optical coherence tomography in multiple sclerosis. Eye. 2018;32:884–8.

  2. 2.

    DI Maggio G, Santangelo R, Guerrieri S, Bianco M, Ferrari L, Medaglini S, et al. Optical coherence tomography and visual evoked potentials: which is more sensitive in multiple sclerosis? Mult Scler. 2014;20:1342–7.

  3. 3.

    Kerrison JB, Flynn T, Green WR. Retinal pathologic changes in multiple sclerosis. Retina. 1994;14:445–51.

  4. 4.

    Petzold A, Balcer L, Calabresi PA, Costello F, Frohman T, Frohman E, et al. Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol. 2017;16:797–812.

  5. 5.

    Oertel FC, Zimmermann HG, Brandt AU, Paul F. Novel uses of retinal imaging with optical coherence tomography in multiple sclerosis. Expert Rev Neurother. 2019;19:31–43.

  6. 6.

    Galetta SL, Villoslada P, Levin N, Shindler K, Ishikawa H, Parr E, et al. Acute optic neuritis: unmet clinical needs and model for new therapies. Neurol Neuroimmunol NeuroInflammation. 2015;2:1–11.

  7. 7.

    Oberwahrenbrock T, Traber GL, Lukas S, Gabilondo I, Nolan R, Songster C, et al. Multicenter reliability of semiautomatic retinal layer segmentation using OCT. Neurol Neuroimmunol Neuroinflammation. 2018;5:1–7.

  8. 8.

    Petzold A, Wattjes MP, Costello F, Flores-Rivera J, Fraser CL, Fujihara K, et al. The investigation of acute optic neuritis: a review and proposed protocol. Nat Rev Neurol. 2014;10:447–58.

  9. 9.

    Lanzillo R, Cennamo G, Criscuolo C, Carotenuto A, Velotti N, Sparnelli F, et al. Optical coherence tomography angiography retinal vascular network assessment in multiple sclerosis. Mult Scler J. 2018;24:1706–14.

  10. 10.

    Wang L, Murphy O, Caldito NG, Calabresi PA, Saidha S. Emerging applications of optical coherence tomography angiography (OCTA) in neurological research. Eye Vis. 2018;5:1–11.

  11. 11.

    Spain RI, Liu L, Zhang X, Jia Y, Tan O, Bourdette D, et al. Optical coherence tomography angiography enhances the detection of optic nerve damage in multiple sclerosis. Br J Ophthalmol. 2018;102:520–4.

  12. 12.

    Wang X, Jia Y, Spain R, Potsaid B, Liu JJ, Baumann B, et al. Optical coherence tomography angiography of optic nerve head and parafovea in multiple sclerosis. Br J Ophthalmol. 2014;98:1368–73.

  13. 13.

    Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria. Ann Neurol. 2011;69:292–302.

  14. 14.

    Odom JV, Bach M, Brigell M, Holder GE, McCulloch DL, Tormene AP, et al. ISCEV standard for clinical visual evoked potentials (2009 update). Doc Ophthalmol. 2010;120:111–9.

  15. 15.

    Cruz-Herranz A, Balk LJ, Oberwahrenbrock T, Saidha S, Martinez-Lapiscina EH, Lagreze WA, et al. The APOSTEL recommendations for reporting quantitative optical coherence tomography studies. Neurology. 2016;86:1–7.

  16. 16.

    Yilmaz H, Karakurt Y, Icel E, Ugurlu A, Ucak T, Tasli NG, et al. Normative data assessment of vessel density and foveal avascular zone metrics using AngioScan software. Curr Eye Res. 2019;0:1–8.

  17. 17.

    Tewarie P, Balk L, Costello F, Green A, Martin R, Schippling S, et al. The OSCAR-IB consensus criteria for retinal OCT quality assessment. PLoS ONE. 2012;7:1–7.

  18. 18.

    Schippling S, Balk LJ, Costello F, Albrecht P, Balcer L, Calabresi PA, et al. Quality control for retinal OCT in multiple sclerosis: validation of the OSCAR-IB criteria. Mult Scler J. 2015;21:163–70.

  19. 19.

    Ayadi N, Dörr J, Motamedi S, Gawlik K, Bellmann-Strobl J, Mikolajczak J, et al. Temporal visual resolution and disease severity in MS. Neurol Neuroimmunol NeuroInflammation. 2018;5:1–8.

  20. 20.

    Ying Gshuang, Maguire MG, Glynn R, Rosner B. Tutorial on biostatistics: statistical analysis for correlated binary eye data. Ophthalmic Epidemiol. 2018;25:1–12.

  21. 21.

    Lanzillo R, Cennamo G, Moccia M, Criscuolo C, Carotenuto A, Frattaruolo N, et al. Retinal vascular density in multiple sclerosis: a 1-year follow-up. Eur J Neurol. 2019;26:198–201.

  22. 22.

    Corvi F, Pellegrini M, Erba S, Cozzi M, Staurenghi G, Giani A. Reproducibility of vessel density, fractal dimension, and foveal avascular zone using 7 different optical coherence tomography angiography devices. Am J Ophthalmol. 2018;186:25–31.

  23. 23.

    Tang FY, Ng DS, Lam A, Luk F, Wong R, Chan C, et al. Determinants of quantitative optical coherence tomography angiography metrics in patients with diabetes. Sci Rep. 2017;7:1–10.

  24. 24.

    Allen NB, Lichtman JH, Cohen HW, Fang J, Brass LM, Alderman MH. Vascular disease among hospitalized multiple sclerosis patients. Neuroepidemiology. 2008;30:234–8.

  25. 25.

    Doche E, Lecocq A, Maarouf A, Duhamel G, Soulier E, Confort-Gouny S, et al. Hypoperfusion of the thalamus is associated with disability in relapsing remitting multiple sclerosis. J Neuroradiol. 2017;44:158–64.

  26. 26.

    Narayana PA, Zhou Y, Hasan KM, Datta S, Sun X, Wolinsky JS. Hypoperfusion and T1-hypointense lesions in white matter in multiple sclerosis. Mult Scler J. 2014;20:363–73.

  27. 27.

    D’Haeseleer M, Hostenbach S, Peeters I, El Sankari S, Nagels G, De Keyser J, et al. Cerebral hypoperfusion: a new pathophysiologic concept in multiple sclerosis? J Cereb Blood Flow Metab. 2015;35:1406–10.

  28. 28.

    Feucht N, Maier M, Lepennetier G, Pettenkofer M, Wetzlmair C, Daltrozzo T, et al. Optical coherence tomography angiography indicates associations of the retinal vascular network and disease activity in multiple sclerosis. Mult Scler J. 2018;20:224–34.

  29. 29.

    Kumar RS, Anegondi N, Chandapura RS, Sudhakaran S, Kadambi SV, Rao HL, et al. Discriminant function of optical coherence tomography angiography to determine disease severity in glaucoma. Investig Ophthalmol Vis Sci. 2016;57:6079–88.

  30. 30.

    Holló G. Relationship between optical coherence tomography sector peripapillary angioflowdensity and Octopus visual field cluster mean defect values. PLoS ONE. 2017;12:1–12.

  31. 31.

    Bojikian KD, Chen PP, Wen JC. Optical coherence tomography angiography in glaucoma. Curr Opin Ophthalmol. 2019;30:110–6.

  32. 32.

    Moghimi S, Hou H, Rao H, Weinreb RN. Optical coherence tomography angiography and glaucoma: a brief review. Asia-Pac J Ophthalmol. 2019;8:115–25.

  33. 33.

    Holló G. Influence of removing the large retinal vessels-related effect on peripapillary vessel density progression analysis in glaucoma. J Glaucoma. 2018;27:e137–9.

  34. 34.

    Leocani L, Rovaris M, Boneschi FM, Medaglini S, Rossi P, Martinelli V, et al. Multimodal evoked potentials to assess the evolution of multiple sclerosis: a longitudinal study. J Neurol Neurosurg Psychiatry. 2006;77:1030–5.

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Yilmaz, H., Ersoy, A. & Icel, E. Assessments of vessel density and foveal avascular zone metrics in multiple sclerosis: an optical coherence tomography angiography study. Eye (2019) doi:10.1038/s41433-019-0746-y

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