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Der Ophthalmologe

, Volume 116, Issue 1, pp 5–13 | Cite as

Strukturelle Endpunkte für Glaukomstudien

  • A. Popa-Cherechenau
  • D. Schmidl
  • G. Garhöfer
  • L. SchmettererEmail author
Leitthema
  • 131 Downloads

Zusammenfassung

Hintergrund

Strukturelle Endpunkte wurden als Surrogatendpunkte für die Zulassung neuroprotektiver Substanzen bei Glaukom diskutiert.

Fragestellung

Ist die Evidenz stark genug, um strukturelle Endpunkte als Surrogatendpunkte zu etablieren?

Material und Methode

Es erfolgt eine Zusammenfassung des Verständnisses zwischen Struktur und Funktion bei Glaukom.

Ergebnisse

Die Einführung der optischen Kohärenztomographie hat die Bildgebung bei Glaukom revolutioniert. Klinisch können sowohl die retinale Nervenfaserschichtdicke entlang eines in der Papille zentrierten Kreises als auch die Ganglienzellschichtdicke im Bereich der Makula gemessen werden, wobei man Letztere in Kombination mit anderen retinalen Schichten quantifiziert. Auf mikroskopischer Ebene gibt es eine starke Korrelation zwischen dem Verlust von Struktur und Funktion. Diese ist aber mit den klinischen Methoden nur ungenügend etabliert. Das gilt insbesondere für den longitudinalen Verlauf der Erkrankung. Zukünftige bildgebende Verfahren, die heute noch nicht klinisch zur Verfügung stehen, könnten das Potenzial haben, ein klareres Verständnis zum Zusammenhang zwischen Struktur und Funktion zu etablieren.

Diskussion

Die derzeitige Evidenz lässt die Verwendung struktureller Endpunkte als Surrogatendpunkte für Phase-3-Studien bei Glaukom nicht zu. Neuroprotektive Medikamente müssen auf Basis von Gesichtsfelduntersuchungen zugelassen werden, da es sich dabei um den patientenrelevanten Endpunkt handelt. Strukturelle Endpunkte könnten aber in der Zukunft eine wichtige Rolle bei Phase-2-Studien oder Proof-of-concept-Studien spielen.

Schlüsselwörter

Zulassungsstudien Retinale Bildgebung Optische Kohärenztomographie Neuroprotektive Substanzen Surrogatendpunkte 

Structural endpoints for glaucoma studies

Abstract

Background

Structural endpoints have been discussed as surrogate endpoints for the approval of neuroprotective drugs in glaucoma.

Objective

Is the evidence strong enough to establish structural endpoints as surrogate endpoints?

Material and methods

Review of current understanding between structure and function in glaucoma.

Results

The introduction of optical coherence tomography has revolutionized imaging in glaucoma patients. Clinically either the nerve fiber layer thickness can be measured along a circle centered in the optic nerve head or the ganglion cell layer thickness can be assessed in the macular region, the latter being quantified in combination with other inner retinal layers. On a microscopic level there is a strong correlation between structural and functional loss but this relation can only partially be described with currently available clinical methods. This is particularly true for longitudinal course of the disease in glaucoma patients. Novel imaging techniques that are not yet used clinically may have the potential to increase our understanding between structure and function in glaucoma but further research in this field is required.

Conclusion

The current evidence does not allow the establishment of structural endpoints as surrogate endpoints for phase 3 studies in glaucoma. Neuroprotective drugs have to be approved on the basis of visual field data because this is the patient-relevant endpoint. Structural endpoints can, however, play an important role in phase 2 and proof of concept studies.

Keywords

Approval studies Retinal imaging Optical coherence tomogaphy Neuroprotective substances Surrogate endpoints 

Notes

Danksagung

Finanzielle Unterstützung durch folgende Projekte wurde gewährt: Fonds zur Förderung der wissenschaftlichen Forschung (FWF): KLI 250, KLI 340, KLI 529, P26157.

Einhaltung ethischer Richtlinien

Interessenkonflikt

A. Popa-Cherechenau, D. Schmidl, G. Garhöfer und L. Schmetterer geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Literatur

  1. 1.
    Alencar LM, Zangwill LM, Weinreb RN et al (2010) A comparison of rates of change in neuroretinal rim area and retinal nerve fiber layer thickness in progressive glaucoma. Invest Ophthalmol Vis Sci 51:3531–3539PubMedPubMedCentralGoogle Scholar
  2. 2.
    Aptel F, Aryal-Charles N, Giraud JM et al (2015) Progression of visual field in patients with primary open-angle glaucoma – ProgF study 1. Acta Ophthalmol 93:e615–e620PubMedGoogle Scholar
  3. 3.
    Aref AA, Budenz DL (2017) Detecting visual field progression. Ophthalmology 124:S51–S56PubMedGoogle Scholar
  4. 4.
    Baumann B, Potsaid B, Kraus MF et al (2011) Total retinal blood flow measurement with ultrahigh speed swept source/Fourier domain OCT. Biomed Opt Express 2:1539–1552PubMedPubMedCentralGoogle Scholar
  5. 5.
    Burgoyne CF, Downs JC (2008) Premise and prediction-how optic nerve head biomechanics underlies the susceptibility and clinical behavior of the aged optic nerve head. J Glaucoma 17:318–328PubMedPubMedCentralGoogle Scholar
  6. 6.
    Bussel II, Wollstein G, Schuman JS (2014) OCT for glaucoma diagnosis, screening and detection of glaucoma progression. Br J Ophthalmol 98(Suppl 2):ii15–ii19PubMedGoogle Scholar
  7. 7.
    Caprioli J, Mock D, Bitrian E et al (2011) A method to measure and predict rates of regional visual field decay in glaucoma. Invest Ophthalmol Vis Sci 52:4765–4773PubMedGoogle Scholar
  8. 8.
    Cettomai D, Hiremath G, Ratchford J et al (2010) Associations between retinal nerve fiber layer abnormalities and optic nerve examination. Neurology 75:1318–1325PubMedPubMedCentralGoogle Scholar
  9. 9.
    Chauhan BC, Garway-Heath DF, Goni FJ et al (2008) Practical recommendations for measuring rates of visual field change in glaucoma. Br J Ophthalmol 92:569–573PubMedPubMedCentralGoogle Scholar
  10. 10.
    Chen CL, Wang RK (2017) Optical coherence tomography based angiography [Invited]. Biomed Opt Express 8:1056–1082PubMedPubMedCentralGoogle Scholar
  11. 11.
    Cherecheanu AP, Garhofer G, Schmidl D et al (2013) Ocular perfusion pressure and ocular blood flow in glaucoma. Curr Opin Pharmacol 13:36–42PubMedPubMedCentralGoogle Scholar
  12. 12.
    Cheung CY, Ong YT, Hilal S et al (2015) Retinal ganglion cell analysis using high-definition optical coherence tomography in patients with mild cognitive impairment and Alzheimer’s disease. J Alzheimers Dis 45:45–56PubMedGoogle Scholar
  13. 13.
    Chung JK, Hwang YH, Wi JM et al (2017) Glaucoma diagnostic ability of the optical coherence tomography angiography vessel density parameters. Curr Eye Res 42:1458–1467PubMedGoogle Scholar
  14. 14.
    Cordeiro MF, Guo L, Luong V et al (2004) Real-time imaging of single nerve cell apoptosis in retinal neurodegeneration. Proc Natl Acad Sci USA 101:13352–13356PubMedPubMedCentralGoogle Scholar
  15. 15.
    Cordeiro MF, Normando EM, Cardoso MJ et al (2017) Real-time imaging of single neuronal cell apoptosis in patients with glaucoma. Brain 140:1757–1767PubMedPubMedCentralGoogle Scholar
  16. 16.
    Costa VP, Harris A, Anderson D et al (2014) Ocular perfusion pressure in glaucoma. Acta Ophthalmol 92:e252–e266PubMedGoogle Scholar
  17. 17.
    Dehghani C, Srinivasan S, Edwards K et al (2017) Presence of peripheral neuropathy is associated with progressive thinning of retinal nerve fiber layer in type 1 diabetes. Invest Ophthalmol Vis Sci 58:Bio234–Bio239PubMedGoogle Scholar
  18. 18.
    Den Haan J, Verbraak FD, Visser PJ et al (2017) Retinal thickness in Alzheimer’s disease: a systematic review and meta-analysis. Alzheimers Dement (Amst) 6:162–170Google Scholar
  19. 19.
    Doblhoff-Dier V, Schmetterer L, Vilser W et al (2014) Measurement of the total retinal blood flow using dual beam Fourier-domain Doppler optical coherence tomography with orthogonal detection planes. Biomed Opt Express 5:630–642PubMedPubMedCentralGoogle Scholar
  20. 20.
    Dong ZM, Wollstein G, Wang B et al (2017) Adaptive optics optical coherence tomography in glaucoma. Prog Retin Eye Res 57:76–88PubMedGoogle Scholar
  21. 21.
    Downs JC, Girkin CA (2017) Lamina cribrosa in glaucoma. Curr Opin Ophthalmol 28:113–119PubMedPubMedCentralGoogle Scholar
  22. 22.
    Fischer MD, Synofzik M, Kernstock C et al (2013) Decreased retinal sensitivity and loss of retinal nerve fibers in multiple system atrophy. Graefes Arch Clin Exp Ophthalmol 251:235–241PubMedGoogle Scholar
  23. 23.
    Fondi K, Wozniak PA, Howorka K et al (2017) Retinal oxygen extraction in individuals with type 1 diabetes with no or mild diabetic retinopathy. Diabetologia 60:1534–1540PubMedPubMedCentralGoogle Scholar
  24. 24.
    Garcia-Martin E, Garcia-Campayo J, Puebla-Guedea M et al (2016) Fibromyalgia is correlated with retinal nerve fiber layer thinning. PLoS ONE 11:e161574PubMedPubMedCentralGoogle Scholar
  25. 25.
    Garway-Heath DF, Caprioli J, Fitzke FW et al (2000) Scaling the hill of vision: the physiological relationship between light sensitivity and ganglion cell numbers. Invest Ophthalmol Vis Sci 41:1774–1782PubMedGoogle Scholar
  26. 26.
    Garway-Heath DF, Crabb DP, Bunce C et al (2015) Latanoprost for open-angle glaucoma (UKGTS): a randomised, multicentre, placebo-controlled trial. Lancet 385:1295–1304PubMedGoogle Scholar
  27. 27.
    Garway-Heath DF, Poinoosawmy D, Fitzke FW et al (2000) Mapping the visual field to the optic disc in normal tension glaucoma eyes. Ophthalmology 107:1809–1815PubMedGoogle Scholar
  28. 28.
    Gill R, Foster AC, Woodruff GN (1987) Systemic administration of MK-801 protects against ischemia-induced hippocampal neurodegeneration in the gerbil. J Neurosci 7:3343–3349PubMedGoogle Scholar
  29. 29.
    Gracitelli CP, Abe RY, Tatham AJ et al (2015) Association between progressive retinal nerve fiber layer loss and longitudinal change in quality of life in glaucoma. JAMA Ophthalmol 133:384–390PubMedPubMedCentralGoogle Scholar
  30. 30.
    Han M, Zhao C, Han QH et al (2016) Change of retinal nerve layer thickness in non-arteritic anterior ischemic optic neuropathy revealed by Fourier domain optical coherence tomography. Curr Eye Res 41:1076–1081PubMedGoogle Scholar
  31. 31.
    Harwerth RS, Wheat JL, Fredette MJ et al (2010) Linking structure and function in glaucoma. Prog Retin Eye Res 29:249–271PubMedPubMedCentralGoogle Scholar
  32. 32.
    He S, Stankowska DL, Ellis DZ et al (2017) Targets of neuroprotection in glaucoma. J Ocul Pharmacol Ther.  https://doi.org/10.1089/jop.2017.0041 CrossRefPubMedGoogle Scholar
  33. 33.
    Hood DC (2017) Improving our understanding, and detection, of glaucomatous damage: an approach based upon optical coherence tomography (OCT). Prog Retin Eye Res 57:46–75PubMedGoogle Scholar
  34. 34.
    Hood DC, Kardon RH (2007) A framework for comparing structural and functional measures of glaucomatous damage. Prog Retin Eye Res 26:688–710PubMedPubMedCentralGoogle Scholar
  35. 35.
    Hood DC, Raza AS, De Moraes CG et al (2013) Glaucomatous damage of the macula. Prog Retin Eye Res 32:1–21PubMedGoogle Scholar
  36. 36.
    Hu R, Marin-Franch I, Racette L (2014) Prediction accuracy of a novel dynamic structure-function model for glaucoma progression. Invest Ophthalmol Vis Sci 55:8086–8094PubMedPubMedCentralGoogle Scholar
  37. 37.
    Jansonius NM, Nevalainen J, Selig B et al (2009) A mathematical description of nerve fiber bundle trajectories and their variability in the human retina. Vision Res 49:2157–2163PubMedPubMedCentralGoogle Scholar
  38. 38.
    Jansonius NM, Schiefer J, Nevalainen J et al (2012) A mathematical model for describing the retinal nerve fiber bundle trajectories in the human eye: average course, variability, and influence of refraction, optic disc size and optic disc position. Exp Eye Res 105:70–78PubMedGoogle Scholar
  39. 39.
    Jonas JB, Aung T, Bourne RR et al (2017) Glaucoma. Lancet 390:2183–2193PubMedGoogle Scholar
  40. 40.
    Jutley G, Luk SM, Dehabadi MH et al (2017) Management of glaucoma as a neurodegenerative disease. Neurodegener Dis Manag 7:157–172PubMedGoogle Scholar
  41. 41.
    Kim KE, Park KH (2017) Macular imaging by optical coherence tomography in the diagnosis and management of glaucoma. Br J Ophthalmol.  https://doi.org/10.1136/bjophthalmol-2017-310869 CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Kiyota N, Kunikata H, Shiga Y et al (2017) Relationship between laser speckle flowgraphy and optical coherence tomography angiography measurements of ocular microcirculation. Graefes Arch Clin Exp Ophthalmol 255:1633–1642PubMedGoogle Scholar
  43. 43.
    Kupersmith MJ, Garvin MK, Wang JK et al (2016) Retinal ganglion cell layer thinning within one month of presentation for non-arteritic anterior ischemic optic neuropathy. Invest Ophthalmol Vis Sci 57:3588–3593PubMedPubMedCentralGoogle Scholar
  44. 44.
    Lee EK, Yu HG (2015) Ganglion cell-inner plexiform layer and peripapillary retinal nerve fiber layer thicknesses in age-related macular degeneration. Invest Ophthalmol Vis Sci 56:3976–3983PubMedGoogle Scholar
  45. 45.
    Lee YH, Kim KN, Heo DW et al (2017) Difference in patterns of retinal ganglion cell damage between primary open-angle glaucoma and non-arteritic anterior ischaemic optic neuropathy. PLoS ONE 12:e187093PubMedPubMedCentralGoogle Scholar
  46. 46.
    Leitgeb RA, Werkmeister RM, Blatter C et al (2014) Doppler optical coherence tomography. Prog Retin Eye Res 41:26–43PubMedPubMedCentralGoogle Scholar
  47. 47.
    Leske MC, Heijl A, Hussein M et al (2003) Factors for glaucoma progression and the effect of treatment: the early manifest glaucoma trial. Arch Ophthalmol 121:48–56PubMedGoogle Scholar
  48. 48.
    Leung CK, Yu M, Weinreb RN et al (2012) Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography: patterns of retinal nerve fiber layer progression. Ophthalmology 119:1858–1866.  https://doi.org/10.1016/j.ophtha.2011.10.010 CrossRefPubMedGoogle Scholar
  49. 49.
    Leung CK, Yu M, Weinreb RN et al (2012) Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography: a prospective analysis of age-related loss. Ophthalmology 119:731–737PubMedGoogle Scholar
  50. 50.
    Li F, Huang W, Zhang X (2017) Efficacy and safety of different regimens for primary open-angle glaucoma or ocular hypertension: a systematic review and network meta-analysis. Acta Ophthalmol (Copenh).  https://doi.org/10.1111/aos.13568 CrossRefGoogle Scholar
  51. 51.
    Lin SC, Singh K, Jampel HD et al (2007) Optic nerve head and retinal nerve fiber layer analysis: a report by the American Academy of Ophthalmology. Ophthalmology 114:1937–1949PubMedPubMedCentralGoogle Scholar
  52. 52.
    Malik R, Swanson WH, Garway-Heath DF (2012) ‘Structure-function relationship’ in glaucoma: past thinking and current concepts. Clin Experiment Ophthalmol 40:369–380PubMedPubMedCentralGoogle Scholar
  53. 53.
    Medeiros FA, Leite MT, Zangwill LM et al (2011) Combining structural and functional measurements to improve detection of glaucoma progression using Bayesian hierarchical models. Invest Ophthalmol Vis Sci 52:5794–5803PubMedPubMedCentralGoogle Scholar
  54. 54.
    Medeiros FA, Weinreb RN, Moore G et al (2012) Integrating event- and trend-based analyses to improve detection of glaucomatous visual field progression. Ophthalmology 119:458–467PubMedPubMedCentralGoogle Scholar
  55. 55.
    Medeiros FA, Zangwill LM, Alencar LM et al (2009) Detection of glaucoma progression with stratus OCT retinal nerve fiber layer, optic nerve head, and macular thickness measurements. Invest Ophthalmol Vis Sci 50:5741–5748PubMedPubMedCentralGoogle Scholar
  56. 56.
    Medeiros FA, Zangwill LM, Anderson DR et al (2012) Estimating the rate of retinal ganglion cell loss in glaucoma. Am J Ophthalmol 154:814–824.e811PubMedPubMedCentralGoogle Scholar
  57. 57.
    Medeiros FA, Zangwill LM, Bowd C et al (2012) The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change. Invest Ophthalmol Vis Sci 53:6939–6946PubMedPubMedCentralGoogle Scholar
  58. 58.
    Mukherjee N, Mcburney-Lin S, Kuo A et al (2017) Retinal thinning in amyotrophic lateral sclerosis patients without ophthalmic disease. PLoS ONE 12:e185242PubMedPubMedCentralGoogle Scholar
  59. 59.
    Mwanza J‑C, Budenz DL, Warren JL et al (2015) Retinal nerve fibre layer thickness floor and corresponding functional loss in glaucoma. Br J Ophthalmol 99:732–737PubMedGoogle Scholar
  60. 60.
    Nadler Z, Wang B, Schuman JS et al (2014) In vivo three-dimensional characterization of the healthy human lamina cribrosa with adaptive optics spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci 55:6459–6466PubMedPubMedCentralGoogle Scholar
  61. 61.
    Nakazawa T (2016) Ocular blood flow and influencing factors for glaucoma. Asia Pac J Ophthalmol (Phila) 5:38–44Google Scholar
  62. 62.
    Ng DS, Chiang PP, Tan G et al (2016) Retinal ganglion cell neuronal damage in diabetes and diabetic retinopathy. Clin Experiment Ophthalmol 44:243–250PubMedGoogle Scholar
  63. 63.
    Nguyen TD, Ethier CR (2015) Biomechanical assessment in models of glaucomatous optic neuropathy. Exp Eye Res 141:125–138PubMedPubMedCentralGoogle Scholar
  64. 64.
    Nouri-Mahdavi K, Brigatti L, Weitzman M et al (1997) Comparison of methods to detect visual field progression in glaucoma. Ophthalmology 104:1228–1236PubMedGoogle Scholar
  65. 65.
    Ohnell H, Heijl A, Anderson H et al (2017) Detection of glaucoma progression by perimetry and optic disc photography at different stages of the disease: results from the Early Manifest Glaucoma Trial. Acta Ophthalmol 95:281–287PubMedGoogle Scholar
  66. 66.
    Osborne NN (2010) Mitochondria: their role in ganglion cell death and survival in primary open angle glaucoma. Exp Eye Res 90:750–757PubMedGoogle Scholar
  67. 67.
    Osborne NN (2009) Recent clinical findings with memantine should not mean that the idea of neuroprotection in glaucoma is abandoned. Acta Ophthalmol 87:450–454PubMedGoogle Scholar
  68. 68.
    Otarola F, Chen A, Morales E et al (2016) Course of glaucomatous visual field loss across the entire perimetric range. JAMA Ophthalmol.  https://doi.org/10.1001/jamaophthalmol.2016.0118 CrossRefPubMedGoogle Scholar
  69. 69.
    Palkovits S, Lasta M, Told R et al (2014) Retinal oxygen metabolism during normoxia and hyperoxia in healthy subjects. Invest Ophthalmol Vis Sci 55:4707–4713PubMedGoogle Scholar
  70. 70.
    Palkovits S, Told R, Schmidl D et al (2014) Regulation of retinal oxygen metabolism in humans during graded hypoxia. Am J Physiol Heart Circ Physiol 307:H1412–H1418PubMedGoogle Scholar
  71. 71.
    Peters D, Bengtsson B, Heijl A (2015) Threat to fixation at diagnosis and lifetime risk of visual impairment in open-angle glaucoma. Ophthalmology 122:1034–1039PubMedGoogle Scholar
  72. 72.
    Pircher M, Zawadzki RJ (2017) Review of adaptive optics OCT (AO-OCT): principles and applications for retinal imaging [Invited. Biomed Opt Express 8:2536–2562PubMedPubMedCentralGoogle Scholar
  73. 73.
    Quigley HA (2012) Clinical trials for glaucoma neuroprotection are not impossible. Curr Opin Ophthalmol 23:144–154PubMedGoogle Scholar
  74. 74.
    Raza AS, Hood DC (2015) Evaluation of the structure-function relationship in glaucoma using a novel method for estimating the number of retinal ganglion cells in the human retina. Invest Ophthalmol Vis Sci 56:5548–5556PubMedPubMedCentralGoogle Scholar
  75. 75.
    Rossi EA, Granger CE, Sharma R et al (2017) Imaging individual neurons in the retinal ganglion cell layer of the living eye. Proc Natl Acad Sci USA 114:586–591PubMedPubMedCentralGoogle Scholar
  76. 76.
    Rufa A, Pretegiani E, Frezzotti P et al (2011) Retinal nerve fiber layer thinning in CADASIL: an optical coherence tomography and MRI study. Cerebrovasc Dis 31:77–82PubMedGoogle Scholar
  77. 77.
    Russell RA, Malik R, Chauhan BC et al (2012) Improved estimates of visual field progression using bayesian linear regression to integrate structural information in patients with ocular hypertension. Invest Ophthalmol Vis Sci 53:2760–2769PubMedPubMedCentralGoogle Scholar
  78. 78.
    Schmetterer L, Garhofer G (2007) How can blood flow be measured? Surv Ophthalmol 52(Suppl 2):S134–S138PubMedGoogle Scholar
  79. 79.
    Schmidl D, Werkmeister R, Garhofer G et al (2015) Ocular perfusion pressure and its relevance for glaucoma. Klin Monbl Augenheilkd 232:141–146PubMedGoogle Scholar
  80. 80.
    Schonfeldt-Lecuona C, Kregel T, Schmidt A et al (2016) From imaging the brain to imaging the retina: Optical Coherence Tomography (OCT) in schizophrenia. Schizophr Bull 42:9–14PubMedGoogle Scholar
  81. 81.
    Schwartz M, Belkin M, Yoles E et al (1996) Potential treatment modalities for glaucomatous neuropathy: neuroprotection and neuroregeneration. J Glaucoma 5:427–432PubMedGoogle Scholar
  82. 82.
    Sehi M, Goharian I, Konduru R et al (2014) Retinal blood flow in glaucomatous eyes with single-hemifield damage. Ophthalmology 121:750–758PubMedGoogle Scholar
  83. 83.
    Seth NG, Kaushik S, Kaur S et al (2017) 5‑year disease progression of patients across the glaucoma spectrum assessed by structural and functional tools. Br J Ophthalmol.  https://doi.org/10.1136/bjophthalmol-2017-310731 CrossRefPubMedGoogle Scholar
  84. 84.
    Shin HY, Park HY, Jung KI et al (2014) Glaucoma diagnostic ability of ganglion cell-inner plexiform layer thickness differs according to the location of visual field loss. Ophthalmology 121:93–99PubMedGoogle Scholar
  85. 85.
    Svrcinova T, Mares J, Chrapek O et al (2017) Changes in oxygen saturation and the retinal nerve fibre layer in patients with optic neuritis – a pilot study. Acta Ophthalmol.  https://doi.org/10.1111/aos.13571 CrossRefPubMedGoogle Scholar
  86. 86.
    Vianna JR, Danthurebandara VM, Sharpe GP et al (2015) Importance of normal aging in estimating the rate of glaucomatous neuroretinal rim and retinal nerve fiber layer loss. Ophthalmology 122:2392–2398PubMedGoogle Scholar
  87. 87.
    Wanek J, Blair NP, Chau FY et al (2016) Alterations in retinal layer thickness and reflectance at different stages of diabetic retinopathy by en face optical coherence tomography. Invest Ophthalmol Vis Sci 57:Oct341–Oct347PubMedPubMedCentralGoogle Scholar
  88. 88.
    Weinreb RN, Kaufman PL (2011) Glaucoma research community and FDA look to the future, II: NEI/FDA glaucoma clinical trial design and endpoints symposium: measures of structural change and visual function. Invest Ophthalmol Vis Sci 52:7842–7851PubMedPubMedCentralGoogle Scholar
  89. 89.
    Weinreb RN, Kaufman PL (2009) The glaucoma research community and FDA look to the future: a report from the NEI/FDA CDER glaucoma clinical trial design and endpoints symposium. Invest Ophthalmol Vis Sci 50:1497–1505PubMedGoogle Scholar
  90. 90.
    Werkmeister RM, Dragostinoff N, Palkovits S et al (2012) Measurement of absolute blood flow velocity and blood flow in the human retina by dual-beam bidirectional Doppler fourier-domain optical coherence tomography. Invest Ophthalmol Vis Sci 53:6062–6071PubMedGoogle Scholar
  91. 91.
    Werkmeister RM, Schmidl D, Aschinger G et al (2015) Retinal oxygen extraction in humans. Sci Rep 5:15763PubMedPubMedCentralGoogle Scholar
  92. 92.
    Wickstrom K, Moseley J (2017) Biomarkers and surrogate endpoints in drug development: a European regulatory view. Invest Ophthalmol Vis Sci 58:Bio27–Bio33PubMedGoogle Scholar
  93. 93.
    Yarmohammadi A, Zangwill LM, Diniz-Filho A et al (2016) Relationship between optical coherence tomography angiography vessel density and severity of visual field loss in glaucoma. Ophthalmology 123:2498–2508PubMedPubMedCentralGoogle Scholar
  94. 94.
    Yu JG, Feng YF, Xiang Y et al (2014) Retinal nerve fiber layer thickness changes in Parkinson disease: a meta-analysis. PLoS ONE 9:e85718PubMedPubMedCentralGoogle Scholar
  95. 95.
    Zhang Y, Wen W, Sun X (2016) Comparison of several parameters in two optical coherence tomography systems for detecting glaucomatous defects in high myopia. Invest Ophthalmol Vis Sci 57:4910–4915PubMedGoogle Scholar
  96. 96.
    Zhao L, Wang Y, Chen CX et al (2014) Retinal nerve fibre layer thickness measured by spectralis spectral-domain optical coherence tomography: The Beijing Eye Study. Acta Ophthalmol 92:e35–e41PubMedGoogle Scholar
  97. 97.
    Zhu H, Crabb DP, Schlottmann PG et al (2010) Predicting visual function from the measurements of retinal nerve fiber layer structure. Invest Ophthalmol Vis Sci 51:5657–5666PubMedGoogle Scholar
  98. 98.
    Zmyslowska A, Fendler W, Waszczykowska A et al (2017) Retinal thickness as a marker of disease progression in longitudinal observation of patients with Wolfram syndrome. Acta Diabetol 54:1019–1024PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2018

Authors and Affiliations

  • A. Popa-Cherechenau
    • 1
    • 2
    • 3
  • D. Schmidl
    • 1
  • G. Garhöfer
    • 1
  • L. Schmetterer
    • 1
    • 4
    • 5
    • 6
    • 7
    Email author
  1. 1.Universitätsklinik für Klinische PharmakologieMedizinische Universität WienWienÖsterreich
  2. 2.Medizinische und Pharmazeutische Universität Carol DavilaBukarestRumänien
  3. 3.Abteilung für OphthalmologieNotfallzentrum der Universitätsklinik BukarestBukarestRumänien
  4. 4.Singapore Eye Research Institute, SERI (Augenforschungszentrum Singapur)SingapurSingapur
  5. 5.Lee Kong Chian Medical SchoolsNanyang Technological University (NTU)SingapurSingapur
  6. 6.Klinisches Fortbildungszentrum Ophthalmologie und Visual SciencesDuke-NUS Medical SchoolSingapurSingapur
  7. 7.Ophthalmology and Visual Sciences Academic Clinical ProgramDuke-NUS Medical SchoolSingapurSingapur

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