Skip to main content

Advertisement

SpringerLink
Log in

Difference in correspondence between visual field defect and inner macular layer thickness measured using three types of spectral-domain OCT instruments

  • Clinical Investigation
  • Published:
Japanese Journal of Ophthalmology Aims and scope Submit manuscript

Abstract

Purpose

To compare the relationship between visual field sensitivity (VFS) and macular parameters measured using three spectral-domain optical coherence tomography (SD-OCT) instruments and to determine a base level (=floor effect) for macular parameters.

Methods

We imaged 127 glaucomatous eyes (1 eye per subject) using three different OCT instruments, i.e., the Cirrus, RTVue and 3D OCT devices; 76 normal eyes were evaluated as controls using the same instruments. The thicknesses of the macular retinal nerve fiber layer (mRNFL), ganglion cell layer+inner plexiform layer (GCL/IPL), and mRNFL+GCL/IPL (GCC) were analyzed. The VFS of the area analyzed by OCT was expressed in decibels and the 1/Lambert scale. For each parameter, the structure–function relationship and the base level were evaluated by regression analysis. The strength of the correlations between the instruments was compared by the bootstrapping method.

Results

All of the macular parameters evaluated exhibited statistically significant correlations with VFS. The average GCC measured by all three SD-OCT instruments and the average mRNFL thickness measured by the Cirrus and 3D OCT instruments had similar correlations with VFS. The average GCL/IPL thickness measured by the Cirrus OCT instrument was better correlated with VFS that was measured by the 3D OCT instrument (p = 0.031). The base level GCC thickness measured by all three instruments was approximately 65 % of that of normal eyes. The base level mRNFL thickness measured with the Cirrus and OCT instruments was 52  and 48 %, respectively, of that of normal eyes. The base level GCL/IPL thickness measured with the Cirrus and 3D instruments was 71 and 75 %, respectively, of that of normal eyes.

Conclusions

The three SD-OCT instruments evaluated showed similar structure–function relationships in terms of GCC and mRNFL measurements. The base levels of the macular parameters determined by the three instruments differed, due, at least partly, to the scanning area defined by each instrument.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Kass MA, Heuer DK, Higginbotham EJ, Johnson CA, Keltner JL, Miller JP, et al. The ocular hypertension treatment study: a randomized trial determines that topical ocular hypotensive medication delays or prevents the onset of primary open-angle glaucoma. Arch Ophthalmol. 2002;120:701–13 (discussion 829–30).

    Article  PubMed  Google Scholar 

  2. Hood DC, Kardon RH. A framework for comparing structural and functional measures of glaucomatous damage. Prog Retin Eye Res. 2007;26:688–710.

    Article  PubMed Central  PubMed  Google Scholar 

  3. Shah NN, Bowd C, Medeiros FA, Weinreb RN, Sample PA, Hoffmann EM, et al. Combining structural and functional testing for detection of glaucoma. Ophthalmology. 2006;113:1593–602.

    Article  PubMed  Google Scholar 

  4. Leung CK, Liu S, Weinreb RN, Lai G, Ye C, Cheung CY, et al. Evaluation of retinal nerve fiber layer progression in glaucoma a prospective analysis with neuroretinal rim and visual field progression. Ophthalmology. 2011;118:1551–7.

    Article  PubMed  Google Scholar 

  5. Leite MT, Rao HL, Weinreb RN, Zangwill LM, Bowd C, Sample PA, et al. Agreement among spectral-domain optical coherence tomography instruments for assessing retinal nerve fiber layer thickness. Am J Ophthalmol. 2011;151(85–92):e1.

    PubMed  Google Scholar 

  6. Kanamori A, Nakamura M, Tomioka M, Kawaka Y, Yamada Y, Negi A. Agreement among three types of spectral-domain optical coherent tomography instruments in measuring parapapillary retinal nerve fibre layer thickness. Br J Ophthalmol. 2012;96:832–7.

    Article  PubMed  Google Scholar 

  7. Lee JR, Jeoung JW, Choi J, Choi JY, Park KH, Kim YD. Structure–function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2010;51:6424–30.

    Article  PubMed  Google Scholar 

  8. Cho JW, Sung KR, Lee S, Yun SC, Kang SY, Choi J, et al. Relationship between visual field sensitivity and macular ganglion cell complex thickness as measured by spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2010;51:6401–7.

    Article  PubMed  Google Scholar 

  9. Aptel F, Sayous R, Fortoul V, Beccat S, Denis P. Structure-function relationships using spectral-domain optical coherence tomography: comparison with scanning laser polarimetry. Am J Ophthalmol. 2010;150:825–33.

    Article  PubMed  Google Scholar 

  10. Rao HL, Zangwill LM, Weinreb RN, Leite MT, Sample PA, Medeiros FA. Structure–function relationship in glaucoma using spectral-domain optical coherence tomography. Arch Ophthalmol. 2011;129:864–71.

    Article  PubMed  Google Scholar 

  11. Takagishi M, Hirooka K, Baba T, Mizote M, Shiraga F. Comparison of retinal nerve fiber layer thickness measurements using time domain and spectral domain optical coherence tomography, and visual field sensitivity. J Glaucoma. 2011;20:383–7.

    Article  PubMed  Google Scholar 

  12. Kanamori A, Nakamura M, Tomioka M, Kawaka Y, Yamada Y, Negi A. Structure–function relationship among three types of spectral-domain optical coherent tomography instruments in measuring parapapillary retinal nerve fibre layer thickness. Acta Ophthalmol. 2013;91:e196–202.

    Article  PubMed  Google Scholar 

  13. Ishikawa H, Stein DM, Wollstein G, Beaton S, Fujimoto JG, Schuman JS. Macular segmentation with optical coherence tomography. Invest Ophthalmol Vis Sci. 2005;46:2012–7.

    Article  PubMed Central  PubMed  Google Scholar 

  14. Curcio CA, Allen KA. Topography of ganglion cells in human retina. J Comp Neurol. 1990;300:5–25.

    Article  CAS  PubMed  Google Scholar 

  15. Tan O, Chopra V, Lu AT, Schuman JS, Ishikawa H, Wollstein G, et al. Detection of macular ganglion cell loss in glaucoma by Fourier-domain optical coherence tomography. Ophthalmology. 2009;116(2305–14):e1–2.

    Google Scholar 

  16. Schulze A, Lamparter J, Pfeiffer N, Berisha F, Schmidtmann I, Hoffmann EM. Diagnostic ability of retinal ganglion cell complex, retinal nerve fiber layer, and optic nerve head measurements by Fourier-domain optical coherence tomography. Graefes Arch Clin Exp Ophthalmol. 2011;249:1039–45.

    Article  PubMed  Google Scholar 

  17. Garas A, Vargha P, Hollo G. Diagnostic accuracy of nerve fibre layer, macular thickness and optic disc measurements made with the RTVue-100 optical coherence tomograph to detect glaucoma. Eye (Lond). 2011;25:57–65.

    Article  CAS  Google Scholar 

  18. Akashi A, Kanamori A, Nakamura M, Fujihara M, Yamada Y, Negi A. The ability of macular parameters and circumpapillary retinal nerve fiber layer by three SD-OCT instruments to diagnose highly myopic glaucoma. Invest Ophthalmol Vis Sci. 2013;54:6025–32.

    Article  PubMed  Google Scholar 

  19. Akashi A, Kanamori A, Nakamura M, Fujihara M, Yamada Y, Negi A. Comparative assessment for the ability of Cirrus, RTVue, and 3D-OCT to diagnose glaucoma. Invest Ophthalmol Vis Sci. 2013;54:4478–84.

    Article  PubMed  Google Scholar 

  20. Murata H, Hirasawa H, Aoyama Y, Sugisaki K, Araie M, Mayama C, et al. Identifying areas of the visual field important for quality of life in patients with glaucoma. PLoS One. 2013;8:e58695.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  21. Sumi I, Shirato S, Matsumoto S, Araie M. The relationship between visual disability and visual field in patients with glaucoma. Ophthalmology. 2003;110:332–9.

    Article  PubMed  Google Scholar 

  22. Kim NR, Lee ES, Seong GJ, Kim JH, An HG, Kim CY. Structure–function relationship and diagnostic value of macular ganglion cell complex measurement using Fourier-domain OCT in glaucoma. Invest Ophthalmol Vis Sci. 2010;51:4646–51.

    Article  PubMed  Google Scholar 

  23. Hood DC, Raza AS, de Moraes CG, Odel JG, Greenstein VC, Liebmann JM, et al. Initial arcuate defects within the central 10° in glaucoma. Invest Ophthalmol Vis Sci. 2011;52:940–6.

    Article  PubMed Central  PubMed  Google Scholar 

  24. Moura AL, Raza AS, Lazow MA, De Moraes CG, Hood DC. Retinal ganglion cell and inner plexiform layer thickness measurements in regions of severe visual field sensitivity loss in patients with glaucoma. Eye (Lond). 2012;26:1188–93.

    Article  Google Scholar 

  25. Na JH, Kook MS, Lee Y, Baek S. Structure-function relationship of the macular visual field sensitivity and the ganglion cell complex thickness in glaucoma. Invest Ophthalmol Vis Sci. 2012;53:5044–51.

    Article  PubMed  Google Scholar 

  26. Hood DC, Anderson SC, Wall M, Kardon RH. Structure versus function in glaucoma: an application of a linear model. Invest Ophthalmol Vis Sci. 2007;48:3662–8.

    Article  PubMed  Google Scholar 

  27. Leite MT, Zangwill LM, Weinreb RN, Rao HL, Alencar LM, Medeiros FA. Structure-function relationships using the Cirrus spectral domain optical coherence tomograph and standard automated perimetry. J Glaucoma. 2012;21:49–54.

    Article  PubMed Central  PubMed  Google Scholar 

  28. Anderson DR, Patella VM. Automated static perimetry. St. Louis: Mosby; 1999.

    Google Scholar 

  29. Omodaka K, Kunimatsu-Sanuki S, Morin R, Tsuda S, Yokoyama Y, Takahashi H, et al. Development of a new strategy of visual field testing for macular dysfunction in patients with open angle glaucoma. Jpn J Ophthalmol. 2013;57:457–62.

    Article  CAS  PubMed  Google Scholar 

  30. Matsumoto M, Nishimura T. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Trans Model Comput Simul. 1998;8:3–30.

    Article  Google Scholar 

  31. Mwanza JC, Durbin MK, Budenz DL, Girkin CA, Leung CK, Liebmann JM, et al. Profile and predictors of normal ganglion cell-inner plexiform layer thickness measured with frequency-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2011;52:7872–9.

    Article  PubMed  Google Scholar 

  32. Mwanza JC, Oakley JD, Budenz DL, Chang RT, Knight OJ, Feuer WJ. Macular ganglion cell-inner plexiform layer: automated detection and thickness reproducibility with spectral domain-optical coherence tomography in glaucoma. Invest Ophthalmol Vis Sci. 2011;52:8323–9.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Kotera Y, Hangai M, Hirose F, Mori S, Yoshimura N. Three-dimensional imaging of macular inner structures in glaucoma by using spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2011;52:1412–21.

    Article  PubMed  Google Scholar 

  34. Kim KE, Park KH, Jeoung JW, Kim SH, Kim DM. Severity-dependent association between ganglion cell inner plexiform layer thickness and macular mean sensitivity in open-angle glaucoma. Acta Ophthalmol. 2014;. doi:10.1111/aos.12438.

    Google Scholar 

  35. Shin HY, Park HY, Jung KI, Park CK. Comparative study of macular ganglion cell-inner plexiform layer and peripapillary retinal nerve fiber layer measurement: structure-function analysis. Invest Ophthalmol Vis Sci. 2013;54:7344–53.

    Article  PubMed  Google Scholar 

  36. Takahashi M, Omodaka K, Maruyama K, Yamaguchi T, Himori N, Shiga Y, et al. Simulated visual fields produced from macular RNFLT data in patients with glaucoma. Curr Eye Res. 2013;38:1133–41.

    Article  PubMed  Google Scholar 

  37. Harwerth RS, Wheat JL, Fredette MJ, Anderson DR. Linking structure and function in glaucoma. Prog Retin Eye Res. 2010;29:249–71.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. Hogan MJ, Alvarado JA, Weddell JE. Histology of the human eye : an atlas and textbook. 13th edn. Philadelphia: Saunders; 1971. p. 687.

    Google Scholar 

  39. Moura AL, Raza AS, Lazow MA, De Moraes CG, Hood DC. Retinal ganglion cell and inner plexiform layer thickness measurements in regions of severe visual field sensitivity loss in patients with glaucoma. Eye (Lond). 2012;26:1188–93.

    Article  Google Scholar 

  40. Le PV, Tan O, Chopra V, Francis BA, Ragab O, Varma R, et al. Regional correlation between ganglion cell complex, nerve fiber layer, and visual field loss in glaucoma. Invest Ophthalmol Vis Sci. 2013;54(6):4287–95. doi:10.1167/iovs.12-1138841.

    Article  PubMed Central  PubMed  Google Scholar 

  41. Dichtl A, Jonas JB, Naumann GO. Retinal nerve fiber layer thickness in human eyes. Graefes Arch Clin Exp Ophthalmol. 1999;237:474–9.

    Article  CAS  PubMed  Google Scholar 

  42. Drasdo N, Millican CL, Katholi CR, Curcio CA. The length of Henle fibers in the human retina and a model of ganglion receptive field density in the visual field. Vision Res. 2007;47:2901–11.

    Article  PubMed Central  PubMed  Google Scholar 

  43. Raza AS, Cho J, de Moraes CG, Wang M, Zhang X, Kardon RH, et al. Retinal ganglion cell layer thickness and local visual field sensitivity in glaucoma. Arch Ophthalmol. 2011;129:1529–36.

    Article  PubMed  Google Scholar 

  44. Hood DC, Raza AS, de Moraes CG, Liebmann JM, Ritch R. Glaucomatous damage of the macula. Prog Retin Eye Res. 2013;32:1–21. doi:10.1016/j.preteyeres.2012.08.003.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

These studies were supported by JSPS KAKENHI grant number 25462715 (A. Kanamori) from the Japanese Government.

Conflicts of interest

K. Ueda, None; A. Kanamori, Grant (The Mishima Memorial Foundation and the Santan Pharmaceutical Founder Commemoration Ophthalmic Research Fund); A. Akashi, None; Y. Kawaka, None; Y. Yamada, None; M. Nakamura, None.

Author information

Authors and Affiliations

  1. Division of Ophthalmology, Department of Surgery, Graduate School of Medicine, Kobe University, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan

    Kaori Ueda, Akiyasu Kanamori, Azusa Akashi, Yuki Kawaka, Yuko Yamada & Makoto Nakamura

Authors
  1. Kaori Ueda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akiyasu Kanamori
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Azusa Akashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuki Kawaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuko Yamada
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Makoto Nakamura
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Akiyasu Kanamori.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ueda, K., Kanamori, A., Akashi, A. et al. Difference in correspondence between visual field defect and inner macular layer thickness measured using three types of spectral-domain OCT instruments. Jpn J Ophthalmol 59, 55–64 (2015). https://doi.org/10.1007/s10384-014-0355-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10384-014-0355-z

Keywords

Search

Navigation