Glaucoma is a progressive disease which can lead to blindness. Early detection is crucial to prevent further damage. 25-30% of ganglion cell loss happens before it can be detected on field test. Thinning of the neuroretinal rim and RNFL loss predicts glaucoma damage. To document disease progression requires both structural and functional assessment. Imaging techniques are objective and allows quantitative measurement. There are different modalities to image RNFL including OCT, HRT and SLP. This article describes interpretation of the OCT. It also discusses the limitations of OCT and artifacts affecting image quality.
INTERPRETATION OF OPTICAL COHERENCE TOMOGRAPHY
There are four types of spectral-domain optical coherence tomography (OCT) machine available commercially: Zeiss Cirrus, Heidelberg Spectralis, Optovue Avanti TRVue, and Topcon. We describe how to interpret the Cirrus OCT reports; however, the same principle applies to most devices. Due to differences in the measurement protocols in different machines, OCT machine data should be compared interchangeably. Cirrus OCT has superior image quality than time-domain OCT due to faster scanning speed and better image resolution.
Steps in assessment are as follows:
- Type of scan [Table 1]
- Assess the quality of the scan: Signal strength, centration of the disc, OCT image, and artifacts [Figures 1234567]
- Interpret the printout
RNFL deviation map: This compares the clusters of pixels in the test image with the normative database and color codes the areas accordingly. It is important to carefully assess this map because small localized defects may sometimes be seen only on this printout. Look specifically for the measurement circle and motion artifacts
- Age: Important because an inaccurately entered age will result in comparison with the wrong normative data age group. In normal eyes, a 2-μm retinal nerve fiber layer (RNFL) loss/decade and 0.2 μm/year has been reported
- RNFL thickness map: It shows the thickness of the RNFL – it is coded from blue (thin) to white (thickest). It normally shows an hourglass pattern. It can give you a gross idea of the RNFL thickness. The superior RNFL and inferior RNFL are the thickest whereas the nasal and temporal are less thick. Small optic discs, long axial length, and older age are associated with thinner RNFL. Every 1-mm increase in the axial length is associated with an approximately 2.2-μm decrease in RNFL thickness
- Look for artifacts in this map. Compare with the other eye [Table 2]; interocular difference >9 μm is unusual in normal eyes and glaucoma should be ruled out.
- [Figures 891011121314151617].
The normative database is based on 284 healthy adults with an age range of 18–84 years, refractive error of − 12 to + 8D; ethnicity includes Caucasians 43%, Asians 24%, African America 18%, Hispanic 12%, mixed ethnicity 6%, and Indian 1%. There were six groups based on age 18–29, 30–39, 40–49, 50–59, 60–69, and 70 years [Figure 18]. The average RNFL thickness in Indian eye reported in the literature is 104.8 ± 38.81 μm. Superior RNFL is 138.2 ± 21.74 μ, inferior RNFL 129.1 ± 25.6 μ, nasal 85.71 ± 21, and temporal 66.38 ± 17.37. Caucasians had thinner mean RNFL values 98.1 ± 10.9 μm than Asians 105.8 ± 9.2 μm.
MACULA OPTICAL COHERENCE TOMOGRAPHY
The macula has 50% of ganglion cells, which has been reported to help detect early glaucoma. It uses macular cube of 512 × 128 pixels with six linear scans in a spoke configuration. The inner boundary is formed by vitreous-retinal interface and outer boundary by retinal pigment epithelium. Yellow, green, and red represent thicker retina and blue represents thinner retina. It has thickness map, deviation map, sectoral value and average ganglion cell layer (GCL) + inner plexiform layer (IPL), and minimum GCL + IPL [Figures 19202122].
[Figures 23 and 24] illustrate clinical examples that depict the structure–function correlation of the optic nerve head and the retina in the diagnosis of glaucoma.
Lower vessel densities have been reported in glaucoma as compared to healthy adults and have shown good discriminatory abilities. Enhanced depth imaging allows lamina cribrosa imaging which is a proposed site for retinal ganglion cell injury. Lamina cribrosa deformation in response to IOP changes may play a role in pathophysiology of glaucoma and the OCT may help analyze this.
The OCT provides excellent opportunity to study the RNFL objectively which adds to diagnostic evidence to help in clinical assessment and to quantify glaucoma progression; however, limitations related to normative database and imaging artifacts should be kept in mind. Glaucoma should never be diagnosed in isolation based on the OCT only; clinical correlation is essential.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
1. Kerrigan-Baumrind LA, Quigley HA, Pease ME, Kerrigan DF, Mitchell RS. Number of ganglion cells in glaucoma eyes compared with threshold visual field tests in the same persons Invest Ophthalmol Vis Sci. 2000;41:741–8
2. Quigley H, Arora K, Idrees S, Solano F, Bedrood S, Lee C, et al Biomechanical responses of lamina cribrosa to intraocular pressure change assessed by optical coherence tomography in glaucoma eyes Invest Ophthalmol Vis Sci. 2017;58:2566–77
3. Mansouri K, Leite MT, Medeiros FA, Leung CK, Weinreb RN. Assessment of rates of structural change in glaucoma using imaging technologies Eye (Lond). 2011;25:269–77
4. Ramkrishnan R, Mittal S, Ambatkar S, Kader MA. Retinal nerve fiber layer thickness measurement in normal Indian population by optical coherence tomography Indian J Opthalmolo. 2006;54:11–5
5. Asrani S, Essaid L, Alder BD, Santiago-Turla C. Artifacts in spectral-domain optical coherence tomography measurements in glaucoma JAMA Ophthalmol. 2014;132:396–402
6. Budenz DL, Anderson DR, Varma R, Schuman J, Cantor L, Savell J, et al Determinants of normal retinal nerve fiber layer thickness measured by stratus OCT Ophthalmology. 2007;114:1046–52
7. Mwanza JC, Oakley JD, Budenz DL, Anderson DRCirrus Optical Coherence Tomography Normative Database Study Group.. Ability of cirrus HD-OCT optic nerve head parameters to discriminate normal from glaucomatous eyes Ophthalmology. 2010;118:241–8 e1
8. Medeiros FA, Zangwill LM, Bowd C, Weinreb RN. Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and stratus OCT optical coherence tomograph for the detection of glaucoma Arch Ophthalmol. 2004;122:827–37
9. Mwanza JC, Budenz DL, Godfrey DG, Neelakantan A, Sayyad FE, Chang RT, et al Diagnostic performance of optical coherence tomography ganglion cell-inner plexiform layer thickness measurements in early glaucoma Ophthalmology. 2014;121:849–54
10. Kansal V, Armstrong JJ, Pintwala R, Hutnik C. Optical coherence tomography for glaucoma diagnosis: An evidence based meta-analysis PLoS One. 2018;13:e0190621
11. Shin JW, Seong M, Lee JW, Hong EH, Uhm KB. Diagnostic ability of retinal nerve fiber layer thickness deviation map for localized and diffuse retinal nerve fiber layer defects J Ophthalmol. 2017;2017:8365090
12. Vazirani J, Kaushik S, Pandav SS, Gupta P. Reproducibility of retinal nerve fiber layer measurements across the glaucoma spectrum using optical coherence tomography Indian J Ophthalmol. 2015;63:300–5
13. Asrani S, Essaid L, Alder BD, Santiago-Turla C. Artifacts in spectral-domain optical coherence tomography measurements in glaucoma JAMA Ophthalmol. 2014;132:396–402
14. Rolle T, Dallorto L, Tavassoli M, Nuzzi R. Diagnostic ability and discriminant values of OCT-angiography parameters in early glaucoma diagnosis Ophthalmic Res. 2018:1–10 [Epub ahead of print].
15. Sigal IA, Wang B, Strouthidis NG, Akagi T, Girard MJ. Recent advances in OCT imaging of the lamina cribrosa British J Ophthalmol. 2014;98:ii34–9
16. Schuman JS. Optical coherence tomography in high myopia JAMA Ophthalmol. 2016;134:1040