pp 1–8 | Cite as

Spectral domain optical coherence tomography based imaging biomarkers for diabetic retinopathy

  • Sandeep SaxenaEmail author
  • Martin Caprnda
  • Surabhi Ruia
  • Senthamizh Prasad
  • Ankita
  • Julia Fedotova
  • Peter KruzliakEmail author
  • Vladimir Krasnik
Original Article


To evaluate the role of central subfield thickness (CST), cube average thickness (CAT), and cube volume (CV) as imaging biomarkers for severity of diabetic retinopathy within the ETDRS-based grades of retinopathy using spectral domain optical coherence tomography (SD-OCT). This study aims to evaluate the role of macular CST, CAT, and CV on SD-OCT as imaging biomarkers for severity of DR. One hundred ninety-four consecutive cases of type 2 diabetes mellitus were divided according to ETDRS classification: diabetes mellitus without retinopathy (No DR; n = 65), nonproliferative diabetic retinopathy (NPDR; n = 66), and proliferative diabetic retinopathy (PDR; n = 63). Sixty-three healthy controls were included. CST, CAT, and CV were analyzed using SD-OCT. Data were analyzed statistically. Analysis of variance revealed a significant increase in levels of CST, CAT, CV, and LogMAR visual acuity with the increase in severity of DR. Independent t-test revealed significant difference in CST, CAT, and CV between cases with DME and cases without DME. On multivariate linear regression analysis, increase in CST, CAT, and CV were found to indicate the increase in severity of DR. SD-OCT-based imaging biomarkers CST, CAT, and CV are effective tools for documenting the severity of diabetic retinopathy. These imaging biomarkers serve as significant indicators of severity of disease.


Diabetic retinopathy Diabetic macular edema Central subfield thickness Cube average thickness Cube volume Spectral-domain optical coherence tomography 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.


  1. 1.
    H. King, R.E. Aubert, W.H. Herman, Global burden of diabetes, 1995–2025: prevalence, numerical estimates, and projections. Diabetes Care. 21, 1414–1431 (1998)CrossRefGoogle Scholar
  2. 2.
    D.S. Fong, L. Aiello, T.W. Gardner, G.L. King, G. Blankenship, J.D. Cavallerano, F.L. Ferris 3rd, American Diabetes Association, Retinopathy in diabetes. Diabetes Care. 27, 84–87 (2004)CrossRefGoogle Scholar
  3. 3.
    A.M. Joussen, V. Poulaki, W. Qin, B. Kirchhof, N. Mitsiades, S.J. Wiegand, J. Rudge, G.D. Yancopoulos, A.P. Adamis, Retinal vascular endothelial growth factor induces intercellular adhesion molecule-1 and endothelial nitric oxide synthase expression and initiates early diabetic retinal leukocyte adhesion in vivo. Am. J. Pathol. 160, 501–509 (2002)CrossRefGoogle Scholar
  4. 4.
    B.O. Boehm, S. Schilling, S. Rosinger, G.E. Lang, G.K. Lang, R. Kientsch-Engel, P. Stahl, Elevated serum levels of N ε-carboxymethyl-lysine, an advanced glycation end product, are associated with proliferative diabetic retinopathy and macular oedema. Diabetologia 47, 1376–1379 (2004)CrossRefGoogle Scholar
  5. 5.
    Ankita, S. Saxena, D.K. Nim, J. Stefanickova, P. Ziak, P. Stefanicka, P. Kruzliak, Retinal photoreceptor apoptosis is associated with impaired serum ionized calcium homeostasis in diabetic retinopathy: An in-vivo analysis. J. Diabetes Complicat. 33, 208–211 (2019)CrossRefGoogle Scholar
  6. 6.
    Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69, 89–95 (2001)CrossRefGoogle Scholar
  7. 7.
    W. Goebel, T. Kretzchmar-Gross, Retinal thickness in diabetic retinopathy: a study using optical coherence tomography (OCT). Retina 22, 759–767 (2002)CrossRefGoogle Scholar
  8. 8.
    P. Massin, A. Erginay, B. Haouchine, A.B. Mehidi, M. Paques, A. Gaudric, Retinal thickness in healthy and diabetic subjects measured using optical coherence tomography mapping software. Eur. J. Ophthalmol. 12, 102–108 (2001)CrossRefGoogle Scholar
  9. 9.
    Y. Oshima, K. Emi, S. Yamanishi, M. Motokura, Quantitative assessment of macular thickness in normal subjects and patients with diabetic retinopathy by scanning retinal thickness analyser. Br. J. Ophthalmol. 83, 54–61 (1999)CrossRefGoogle Scholar
  10. 10.
    Diabetic Retinopathy Clinical Research Network, D.J. Browning, A.R. Glassman, L.P. Aiello, R.W. Beck, D.M. Brown, D.S. Fong, N.M. Bressler, R.P. Danis, J.L. Kinyoun, Q.D. Nguyen, A.R. Bhavsar, J. Gottlieb, D.J. Pieramici, M.E. Rauser, R.S. Apte, J.I. Lim, P.H. Miskala, Relationship between optical coherence tomography-measured central retinal thickness and visual acuity in diabetic macular edema. Ophthalmology 114, 525–536 (2007)CrossRefGoogle Scholar
  11. 11.
    S. Ruia, S. Saxena, Targeted screening of macular edema by spectral domain optical coherence tomography for progression of diabetic retinopathy. Indian J. Ocul. Biol. 1, 102 (2016)Google Scholar
  12. 12.
    P. Phadikar, S. Saxena, S. Ruia, T.Y. Lai, C.H. Meyer, D. Eliott, The potential of spectral domain optical coherence tomography imaging based retinal biomarkers. Int. J. Retin. Vitreous. 3, 1 (2017)CrossRefGoogle Scholar
  13. 13.
    S. Ahuja, S. Saxena, C.H. Meyer, J.S. Gilhotra, L. Akduman, Central subfield thickness and cube average thickness as bioimaging biomarkers for ellipsoid zone disruption in diabetic retinopathy. Int. J. Retin. Vitreous. 4, 41 (2018)CrossRefGoogle Scholar
  14. 14.
    Early Treatment Diabetic Retinopathy Study Research Group, Grading diabetic retinopathy from stereoscopic color fundus photographs—an extension of the modified Airlie House classification: ETDRS report number 10. Ophthalmology 98, 786–806 (1991)CrossRefGoogle Scholar
  15. 15.
    A.C. Sull, L.N. Vuong, L.L. Price, V.J. Srinivasan, I. Gorczynska, J.G. Fujimoto, J.S. Schuman, J.S. Duker, Comparison of spectral/Fourier domain optical coherence tomography instruments for assessment of normal macular thickness. Retina 30, 235 (2010)CrossRefGoogle Scholar
  16. 16.
    H. Faghihi, S. Faghihi, F. Ghassemi, Measurement of normal macular thickness using cirrus optical coherence tomography instrument in Iranian subjects with normal ocular condition. Iran. J. Ophthalmol. 25, 107–114 (2013)Google Scholar
  17. 17.
    A. Pokharel, G.S. Shrestha, J.B. Shrestha, Macular thickness and macular volume measurements using spectral domain optical coherence tomography in normal Nepalese eyes. Clin. Ophthalmol. 10, 511–519 (2016)CrossRefGoogle Scholar
  18. 18.
    G. Virgili, F. Menchini, V. Murro, E. Peluso, F. Rosa, G. Casazza, Optical coherence tomography (OCT) for detection of macular oedema in patients with diabetic retinopathy. Cochrane Database Syst. Rev. 7, CD008081 (2011)Google Scholar
  19. 19.
    A. Jain, S. Saxena, V.K. Khanna, R.K. Shukla, C.H. Meyer, Status of serum VEGF and ICAM-1 and its association with external limiting membrane and inner segment-outer segment junction disruption in type 2 diabetes mellitus. Mol. Vis. 19, 176017–176068 (2013)Google Scholar
  20. 20.
    T. Otani, Y. Yamaguchi, S. Kishi, Correlation between visual acuity and foveal microstructural changes in diabetic macular edema. Retina 30, 774–780 (2010)CrossRefGoogle Scholar
  21. 21.
    H.J. Shin, S.H. Lee, H. Chung, H.C. Kim, Association between photoreceptor integrity and visual outcome in diabetic macular edema. Graefes Arch. Clin. Exp. Ophthalmol. 250, 61–70 (2012)CrossRefGoogle Scholar
  22. 22.
    N. Mishra, S. Saxena, R.K. Shukla, V. Singh, C.H. Meyer, P. Kruzliak, V.K. Khanna, Association of serum N ε-Carboxy methyl lysine with severity of diabetic retinopathy. J. Diabetes Complicat. 30, 511–517 (2016)CrossRefGoogle Scholar
  23. 23.
    S. Sharma, S. Saxena, K. Srivastav, R.K. Shukla, N. Mishra, C.H. Meyer, P. Kruzliak, V.K. Khanna, Nitric oxide and oxidative stress is associated with severity of diabetic retinopathy and retinal structural alterations. Clin. Exp. Ophthalmol. 43, 429–436 (2015)CrossRefGoogle Scholar
  24. 24.
    J. Liang, W. Lei, J. Cheng, Correlations of blood lipids with early changes in macular thickness in patients with diabetes. J. Fr. Ophtalmol. S0181-5512(18)30537-0 (2019).Google Scholar
  25. 25.
    S. Saxena, S. Ruia, S. Prasad, A. Jain, N. Mishra, S.M. Natu, C.H. Meyer, J.S. Gilhotra, P. Kruzliak, L. Akduman, Increased serum levels of urea and creatinine are surrogate markers for disruption of retinal photoreceptor external limiting membrane and inner segment ellipsoid zone in type 2 diabetes mellitus. Retina 37, 344–349 (2017)CrossRefGoogle Scholar
  26. 26.
    S. Saxena, K. Srivastav, L. Akduman, Spectral domain optical coherence tomography based alterations in macular thickness and inner segment ellipsoid are associated with severity of diabetic retinopathy. Int. J. Ophthalmol. Clin. Res. 2, 7 (2015)CrossRefGoogle Scholar
  27. 27.
    D.J. Browning, C.M. Fraser, S. Clark, The relationship of macular thickness to clinically graded diabetic retinopathy severity in eyes without clinically detected diabetic macular edema. Ophthalmology 115, 533–539 (2008)CrossRefGoogle Scholar
  28. 28.
    L. Pelosini, C.C. Hull, J.F. Boyce, D. McHugh, M.R. Stanford, J. Marshall, Optical coherence tomography may be used to predict visual acuity in patients with macular edema. Investig. Ophthalmol. Vis. Sci. 52, 2741–2748 (2011)CrossRefGoogle Scholar
  29. 29.
    H. Alkuraya, D. Kangave, A.M. Abu El-Asrar, The correlation between optical coherence tomographic features and severity of retinopathy, macular thickness and visual acuity in diabetic macular edema. Int. Ophthalmol. 26, 93–99 (2005)CrossRefGoogle Scholar
  30. 30.
    J. Olson, P. Sharp, K. Goatman, G. Prescott, G. Scotland, A. Fleming, S. Philip, C. Santiago, S. Borooah, D. Broadbent, V. Chong, P. Dodson, S. Harding, G. Leese, C. Styles, K. Swa, H. Wharton, Improving the economic value of photographic screening for optical coherence tomography-detectable macular oedema: a prospective, multicentre, UK study. Health Technol. Assess. 17, 1–142 (2013)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of OphthalmologyKing George’s Medical UniversityLucknowIndia
  2. 2.1st Department of Internal Medicine, Faculty of MedicineComenius University and University HospitalBratislavaSlovakia
  3. 3.Department of Community MedicineKing George’s Medical UniversityLucknowIndia
  4. 4.Laboratory of Neuroendocrinology, I.P. Pavlov Institute of PhysiologyRussian Academy of Sciences, StPetersburgRussia
  5. 5.Department of Chemistry and Molecular BiologyITMO University, StPetersburgRussia
  6. 6.Department of Internal MedicineBrothers of Mercy HospitalBrnoCzech Republic
  7. 7.2nd Department of Surgery, Faculty of MedicineMasaryk University and St. Anne´s University HospitalBrnoCzech Republic
  8. 8.Department of Ophthalmology, Faculty of MedicineComenius University and University HospitalBratislavaSlovakia

Personalised recommendations