Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects

English version

Autoři: Alfonso Casado ^aff001; Andrea Cerveró ^aff001; Alicia López-de-Eguileta ^aff001; Raúl Fernández ^aff001; Soraya Fonseca ^aff001; Juan Carlos González ^aff001; Gema Pacheco ^aff001; Elena Gándara ^aff001; Miguel Á. Gordo-Vega ^aff001
Působiště autorů: Department of Ophthalmology, Hospital Universitario Marqués de Valdecilla-IDIVAL, Santander, Spain ^aff001
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0222347

Souhrn

Purpose

To evaluate the accuracy of the measurement of the ganglion cell layer (GCL) of the posterior pole analysis (PPA) software of the Spectralis spectral-domain (SD) optical coherence tomography (OCT) device (Heidelberg Engineering, Inc., Heidelberg, Germany), the asymmetry of paired GCL sectors, the total retinal thickness asymmetry (RTA), and the peripapillary retinal nerve fiber layer (pRNFL) test to discriminate between healthy, early and advanced glaucoma eyes.

Methods

Three hundred eighteen eyes of 161 individuals with reliable visual fields (VF) were enrolled in this study. All participants were examined using the standard posterior pole and the pRNFL protocols of the Spectralis OCT device. VF impairment was graded in hemifields, and the GCL sectors were correlated with this damage. Thicknesses of each GCL, the GCL map deviation asymmetry and the pRNFL were compared between control and glaucomatous eyes. The area under the receiver operating characteristic curve (AUC) of these analyses was assessed.

Results

Fourteen of the 16 sectors of the GCL and pRNFL were significantly thinner in eyes with glaucoma than in control eyes (p<0.006). Similarly, the GCL map deviation showed a significant difference between these eyes and both the control eyes as well as the eyes with early glaucoma (p = 0.001 and p = 0.039, respectively). The highest values of AUC to diagnose both early and advanced glaucoma corresponded to the average pRNFL analysis and the GCL map deviation (AUC>0.823, p<0.040 and AUC>0.708, p<0.188, respectively).

Conclusions

Although 16 central sectors of the GCL observed with PPA showed good correlation with VF damage, the pRNFL and the GCL map deviation were more effective for discrimination of glaucomatous damage.

Klíčová slova:

Medicine and health sciences – Ophthalmology – Eye diseases – Glaucoma – Visual impairments – Scotoma – Eyes – Ocular system – Ocular anatomy – Optic disc – Diagnostic medicine – Diagnostic radiology – Tomography – Radiology and imaging – Biology and life sciences – Anatomy – Head – Cell biology – Cellular types – Animal cells – Ganglion cells – Neuroscience – Cellular neuroscience – Neurons – Nerve fibers – Research and analysis methods – Imaging techniques

Zdroje

1. Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90:262–267 doi: 10.1136/bjo.2005.081224 16488940

2. Levkovitch-Verbin H. Retinal ganglion cell apoptotic pathway in glaucoma: Initiating and downstream mechanisms. Prog Brain Res. 2015;220:37–57. doi: 10.1016/bs.pbr.2015.05.005 26497784

3. Weinreb RN, Aung T, Medeiros FA. The pathophysiology and treatment of glaucoma: a review. JAMA. 2014;311:1901–1911. doi: 10.1001/jama.2014.3192 24825645

4. Price DA, Swanson WH, Horner DG. Using perimetric data to estimate ganglion cell loss for detecting progression of glaucoma: a comparison of models. Ophthalmic Physiol Opt. 2017 Jul;37(4):409–419. doi: 10.1111/opo.12378 28439944

5. Wollstein G, Schuman JS, Price LL, Aydin A, Beaton SZ, Stark PC, et al. Optical coherence tomography (OCT) macular and peripapillary retinal nerve fiber layer measurements and automated visual fields. Am J Ophthalmol. 2004;138:218–225. 15289130

6. Medeiros FA, Zangwill LM, Bowd C, Vessani RM, Susanna R Jr, Weinreb RN. Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography. Am J Ophthalmol. 2005;139:44–55. 15652827

7. Schuman JS, Pedut-Kloizman T, Hertzmark E, Hee MR, Wilkins JR, Coker JG, et al. Reproducibility of nerve fiber layer thickness measurements using optical coherence tomography. Ophthalmology. 1996;103: 1889–1898. 8942887

8. Garvin MK, Abramoff MD, Wu X, Russell SR, Burns TL, Sonka M. Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images. IEEE Trans Med Imaging. 2009;28:1436–1447. doi: 10.1109/TMI.2009.2016958 19278927

9. Fabritius T, Makita S, Miura M, Myllyl¨a R, Yasuno Y. Automated segmentation of the macula by optical coherence tomography. Opt Express. 2009;17:15659–15669. doi: 10.1364/OE.17.015659 19724565

10. Kajic V, Povazay B, Hermann B, Hofer B, Marshall D, Rosin PL, et al. Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based on texture and shape analysis. Opt Express. 2010;18:14730–14744. doi: 10.1364/OE.18.014730 20639959

11. Wang M, Hood DC, Cho JS, Ghadiali Q, De Moraes CG, Zhang X, et al. Measurement of local retinal ganglion cell layer thickness in patients with glaucoma using frequency-domain optical coherence tomography. Arch Ophthalmol. 2009;127:875–881. doi: 10.1001/archophthalmol.2009.145 19597108

12. Shin JW, Sung KR, Lee GC, Durbin MK, Cheng D. Ganglion Cell-Inner Plexiform Layer Change Detected by Optical Coherence Tomography Indicates Progression in Advanced Glaucoma. Ophthalmology. 2017 Oct;124(10):1466–1474. doi: 10.1016/j.ophtha.2017.04.023 28549518

13. Kim HJ, Jeoung JW, Yoo BW, Kim HC, Park KH. Patterns of glaucoma progression in retinal nerve fiber and macular ganglion cell-inner plexiform layer in spectral-domain optical coherence tomography. Jpn J Ophthalmol. 2017 Jul;61(4):324–333. doi: 10.1007/s10384-017-0511-3 28374270

14. Kim YK, Ha A, Na KI, Kim HJ, Jeoung JW, Park KH. Temporal Relation between Macular Ganglion Cell-Inner Plexiform Layer Loss and Peripapillary Retinal Nerve Fiber Layer Loss in Glaucoma. Ophthalmology. 2017 Jul;124(7):1056–1064. doi: 10.1016/j.ophtha.2017.03.014 28408038

15. Hammel N, Belghith A, Weinreb RN, Medeiros FA, Mendoza N, Zangwill LM. Comparing the Rates of Retinal Nerve Fiber Layer and Ganglion Cell-Inner Plexiform Layer Loss in Healthy Eyes and in Glaucoma Eyes. Am J Ophthalmol. 2017 Jun;178:38–50. doi: 10.1016/j.ajo.2017.03.008 28315655

16. 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;51:6401–6407. doi: 10.1167/iovs.09-5035 20631238

17. Kim NR, Lee ES, Seong GJ, et al. Structure-function relationship and diagnostic value of macular ganglion cell complex measurement using Fourier-domain OCT in glaucoma. Invest Ophthalmol Vis Sci. 2010;51:4646–4651. doi: 10.1167/iovs.09-5053 20435603

18. Takagishi M, Hirooka K, Baba T, Mizote M, Shiraga F. Comparison of retinalnerve fiber layer thickness measure ments using time domain and spectral domain optical coherence tomography, and visual field sensitivity. J Glaucoma. 2011;20:383–387. doi: 10.1097/IJG.0b013e3181efb371 20717050

19. 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;129:1529–1536. doi: 10.1001/archophthalmol.2011.352 22159673

20. Seo JH, Kim T-W, Weinreb RN, Park KH, Kim SH, Kim DM. Detection of localized retinal nerve fiber layer defects with posterior pole asymmetry analysis of spectral domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2012; 53:4347±53. doi: 10.1167/iovs.12-9673 22577076

21. Curcio CA, Allen KA. Topography of ganglion cells in human retina. J Comp Neurol. 1990; 300:5–25. 2229487

22. Sullivan-Mee M, Ruegg CC, Pensyl D, Halverson K, Qualls C. Diagnostic precision of retinal nerve fiber layer and macular thickness asymmetry parameters for identifying early primary open-angle glaucoma. Am J Ophthalmol. 2013; 156:567–77.e1. doi: 10.1016/j.ajo.2013.04.037 23810475

23. Sato S, Hirooka K, Baba T, Tenkumo K, Nitta E, Shiraga F. Correlation between the ganglion cell-inner plexiform layer thickness measured with cirrus HD-OCT and macular visual field sensitivity measured with microperimetry. Invest Ophthalmol Vis Sci. 2013 Apr 30;54(4):3046–51. doi: 10.1167/iovs.12-11173 23580483

24. Sankar PS, O'Keefe L, Choi D, Salowe R, Miller-Ellis E, Lehman A, et al. The SCHEIE Visual Field Grading System. J Clin Exp Ophthalmol. 2017 Jun;8(3). doi: 10.4172/2155-9570.1000651 28932621

25. Mandrekar J. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010;5: 1315–1316. doi: 10.1097/JTO.0b013e3181ec173d 20736804

26. Zhang C, Tatham AJ, Weinreb RN, Zangwill LM, Yang Z, Zhang JZ, et al. Relationship between ganglion cell layer thickness and estimated retinal ganglion cell counts in the glaucomatous macula. Ophthalmology 2014;121(12):2371–2379. doi: 10.1016/j.ophtha.2014.06.047 25148790

27. 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 22995953

28. Hood DC, Raza AS, de Moraes CG, Johnson CA, Liebmann JM, Ritch R. The Nature of Macular Damage in Glaucoma as Revealed by Averaging Optical Coherence Tomography Data. Transl Vis Sci Technol. 2012 May 25;1(1):3. doi: 10.1167/tvst.1.1.3 23626924

29. Grewal DS, Tanna AP. Diagnosis of glaucoma and detection of glaucoma progression using spectral domain optical coherence tomography. Curr Opin Ophthalmol. 2013;24(2):150–161. doi: 10.1097/ICU.0b013e32835d9e27 23328662

30. Lee EJ, Yang HK, Kim TW, Hwang JM, Kim YH, Kim CY. Comparison of the Pattern of Retinal Ganglion Cell Damage Between Patients With Compressive and Glaucomatous Optic Neuropathies. Invest Ophthalmol Vis Sci. 2015 Nov;56(12):7012–20. doi: 10.1167/iovs.15-17909 26523385

31. Ishikawa H, Stein DM, Wollstein G, Beaton S, Fujimoto JG, Schuman JS. Macular segmentation with optical coherence tomography. Invest Ophthalmol Vis Sci. 2005;46:2012–2017. doi: 10.1167/iovs.04-0335 15914617

32. Yaqoob Z, Wu J, Yang C. Spectral domain optical coherence tomography: a better OCT imaging strategy. Biotechniques. 2005;39(6 suppl):S6–S13. doi: 10.2144/000112090 20158503

33. Yamashita T, Sakamoto T, Kakiuchi N, Tanaka M, Kii Y, Nakao K. Posterior pole asymmetry analyses of retinal thickness of upper and lower sectors and their 638 association with peak retinal nerve fiber layer thickness in healthy young eyes. 639 Invest Ophthalmol Vis Sci. 2014 Aug 12;55(9):5673–8. doi: 10.1167/iovs.13-13828 25118262

34. Kim YK, Yoo BW, Kim HC, Park KH. Automated Detection of Hemifield Difference across Horizontal Raphe on Ganglion Cell—Inner Plexiform Layer Thickness Map. Ophthalmology. 2015 Nov;122(11):2252–60. doi: 10.1016/j.ophtha.2015.07.013 26278860

35. Um TW, Sung KR, Wollstein G, Yun SC, Na JH, Schuman JS. Asymmetry in hemifield macular thickness as an early indicator of glaucomatous change. Invest 647 Ophthalmol Vis Sci. 2012; 53:1139–44.

36. Yamada H, Hangai M, Nakano N, Takayama K, Kimura Y, Miyake M, et al. Asymmetry analysis of macular inner retinal layers for glaucoma diagnosis. Am J Ophthalmol. 2014; 158:1318x–29.e3. doi: 10.1016/j.ajo.2014.08.040 25194230

37. Kuang TM, Zhang C, Zangwill LM, Weinreb RN, Medeiros FA. Estimating Lead Time Gained by Optical Coherence Tomography in Detecting Glaucoma before Development of Visual Field Defects. Ophthalmology. 2015 Oct;122(10):2002–9. doi: 10.1016/j.ophtha.2015.06.015 26198809

38. Hood DC, Salant JA, Arthur SN, Ritch R, Liebmann JM. The location of the inferior and superior temporal blood vessels and interindividual variability of the retinal nerve fiber layer thickness. J Glaucoma. 2010;19:158–166. doi: 10.1097/IJG.0b013e3181af31ec 19661824

Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects

Souhrn

Purpose

Methods

Results

Conclusions

Klíčová slova:

Zdroje

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