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TITLE-

THE ABILITY TO DIFFERENTIATE GLAUCOMATOUS FROM

NORMATIVE EYES USING RETINAL NERVE FIBRE LAYER THICKNESS

VERSUS GANGLION CELL THICKNESS USING OPTICAL FOURIER

COHERENCE TOMOGRAPHY

DR CYRES KEIKI MEHTA MS(OPHTH) ,FSVH(GER) ,FASCRS(USA)

2011 OCTOBER

INTERNATIONAL EYE CENTRE

MEHTA INTERNATIONAL EYE INSTITUTE

MUMBAI

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THESIS ON:

THE ABILITY TO DIFFERENTIATE GLAUCOMATOUS FROM

NORMATIVE EYES USING OF RETINAL NERVE FIBRE LAYER

THICKNESS VERSUS GANGLION CELL THICKNESS USING OPTICAL

FOURIER COHERENCE TOMOGRAPHY

ABSTRACT

Aim: To differentiate between glaucomatous and normal eyes by the evaluation of

Retinal nerve fiber layer and ganglion cell thickness by Fourier Domain Optical

Coherence Tomography (FD-OCT) .

Materials and methods: This Observational cross sectional study included 30 normal

(30 subjects) and 30 glaucoma (30 subjects) that underwent reliable standard

automated perimetry (24-2) testing and Fourier Domain Optical Coherence (FD-OCT)

Tomography imaging Retinal Nerve Fibre layer (RNFL) and Ganglion Cell Thickness

(GCC) along with complete ophthalmic examinations. Receiver operating

characteristic curves (ROC) were studied for all parameters.

Results: The highest AROCs for distinguishing between groups were overall nerve

fibre layer (NFL) thickness followed by overall GCC thickness .There was a

significant difference in both RNFL and GGC thickness between normal and all

glaucoma subgroups (P <0.001).Both mean deviation (MD) and corrected pattern

standard deviation (CPSD) showed a significant correlation with all the parameters in

eyes with glaucoma (P < 0.001).

Conclusion: Ganglion cell complex thickness, as measured by OCT, was capable of

detecting glaucomatous damage and corresponded with RNFL thickness; however,

RNFL thickness had higher sensitivity and specificity for the detection of glaucoma.

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Contents

1. Acknowledgement

2. Introduction

3. Material & Methods

4. Results

5. Discussion

6. Conclusions

7. References

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ACKNOWLEDGEMENT

Special thanks to Dr. Farhana Koya and Dr Ali Azhar who helped in the

design and execution of this study and to all my Patients who co-operated with

me to bring this study to fruition

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INTRODUCTION:

OPTICAL COHERENCE TOMOGRAPHY (OCT) is a high-resolution noncontact

imaging modality. The ocular application of this technology provides quantitative

measurements of the macular retinal thickness, peripapillary nerve fiber layer (NFL)

thickness, and topographical measurements of the optic nerve head (ONH). Cross-

sectional studies have shown that measurements obtained from each of these regions

can be used to differentiate between normal and glaucomatous eyes. 1-8

Each of the

ocular scanning regions has theoretical advantages that make it the preferable scanning

area. ONH and peripapillary regions are the locations where nerve fibers from

throughout the eye are represented. The retinal ganglion cell (RGC) layer in the

macula is more than one cell thick, and RGC bodies have 10 to 20 times the diameter

of their axons. Because the RGC layer and the NFL are layers prone to glaucomatous

damage, macular scanning has been suggested as a sensitive scanning region for

glaucoma detection. 9-12

The aim of this study was to identify the best OCT scanning

region for distinguishing between normal and glaucomatous eyes.

Optical coherence tomography (OCT) was first introduced in 1995 as an imaging

technique for glaucoma diagnosis. 13

Studies have been conducted to investigate the

reproducibility of OCT RNFL thickness measurements, to assess the value of OCT as

a clinical tool for distinguishing between healthy and glaucomatous eyes. 14-20

However, in all previous studies, conventional time-domain OCT was used for testing

the reproducibility of RNFL thickness measurements. Time-domain OCT uses a

scanning interferometer and an 820-nm infrared light source that is split into two

separate beams. One beam is scanning a tissue being analyzed, and the other one acts

as a reference beam that is reflected by a reference mirror. The distance of the

reference mirror can be adjusted, and therefore the time it takes for the reference beam

to reach the sensor can be changed. By comparing the two light beams, time-domain

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OCT measures the optical backscattering of light to generate a cross-sectional image

of the tested tissue. Recently, improvements in OCT technology have been introduced.

21-22 Fourier-domain (FD)-OCT provides increased resolution and scanning speed by

recording the interferometric information with a Fourier-domain spectrometric method

instead of adjusting the position of a reference mirror. Resolution is up to five times

higher, and imaging speed is 60 times faster than in conventional time-domain OCT.

23-24 In addition to high image quality, it is important to have reliable and reproducible

software programs to analyze the data acquired by FD-OCT. A previous investigation

demonstrated that OCT ONH measurements correlate well with topographic

measurements obtained by confocal scanning laser ophthalmoscopy, another imaging

technique that evaluates the ONH. 25

Other studies have also shown that OCT macular

thickness measurements are significantly thinner in glaucomatous compared with

healthy eyes26-28

. Although the ability of OCT ONH and macular thickness

measurements to differentiate glaucomatous from healthy subjects has been reported

to be lower than RNFL thickness parameters, no study has yet provided a comparison

of these three methods in the same population. Further, it is possible that ONH and

macula measurements provide complementary structural information that would

increase diagnostic accuracy when combined with RNFL evaluation.

METHODS:

THIS OBSERVATIONAL CROSS-SECTIONAL STUDY INCLUDED 120 eyes (30

glaucomatous patients and 30 healthy control subjects). Subjects were evaluated at the

International Eye Centre, Mumbai. All participants had comprehensive ocular

examination, reliable Swedish Interactive Thresholding Algorithm standard 24–2

perimetry and good-quality OCT scanning of the RNFL, GCC, and ONH regions at

the same visit. All had best-corrected visual acuity of 20/60 or better, refractive error

between -6.00 and +3.00 diopters, no media opacities that would preclude OCT

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scanning, and no retinal pathologies other than those attributed to glaucoma. Patients

with diabetes, any medical condition that might affect visual field (VF) other than

glaucoma, or treatment with medications that might affect retinal thickness were

excluded from the study. Normal subjects were healthy volunteers with normal ocular

examination and VF glaucoma hemifield test within normal limits. Glaucoma subjects

were defined by the presence of GHT outside normal limits with reproducible VF

defects at the same location on two consecutive visits.

The participants were classified based on their perimetric findings, and ONH

appearance did not form part of the inclusion criteria.

Visual Field Testing:

All subjects underwent SITA Standard 24-2 perimetry (Carl Zeiss Meditec Inc.,

Dublin, California, USA). A reliable visual field test was defined as one with fewer

than 20% fixation losses, false positives or false negatives. A field defect was defined

as having three or more significant (P < 0.05) non–edge-contiguous points with at

least one at the P <0.01 level on the same side of the horizontal meridian in the pattern

deviation plot, classified as outside normal limits in the glaucoma hemifield test

(GHT) and confirmed with at least two VF examinations. The glaucoma patients were

divided into 3 subgroups: early, moderate, and severe. The severity of the glaucoma

was determined by the Hodapp-Parrish-Anderson (HAP) classification based on

the mean defect (MD) index of visual fields. Early glaucoma was defined by a visual

field loss with MD <6 dB, moderate glaucoma with MD <6 dB but >12 dB, and severe

glaucoma with MD >12 dB. The Global indices like Mean deviation (MD) and Pattern

Standard Deviation (PSD) were also analyzed.

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FD-OCT:

All subjects were scanned using the RT-Vue FD-OCT system (Optovue, INC.,

Fremont, CA) It takes 26,000 A-scans per second, with a frame rate of 256 to 4,096 A-

scans per frame. It has a depth resolution of 5 µm and a transverse resolution of 15

µm. The scan range is 2 mm to 2.3 mm in depth and 2 mm to 12 mm in transverse

direction. The scan beam wavelength is 840 ± 10 nm, and the exposure power at the

pupil is 750 µW.

RNFL and GCC thickness were measured using FD-OCT. FD-OCT imaging was

performed through undilated pupils using a 3.45mm diameter circular scan acquisition

protocol. This imaging protocol provides an average of four peripapillary scans

acquired in 76 milliseconds (999 A-scans per 360-degree circular path with each A-

scan corresponding to a 0.36 degree arc) centered on the optic disc. Images with

failure of the RNFL segmentation algorithm were excluded, as well as images

obtained during eye movement, images that were unfocused, poorly centered or had a

scan score index (SSI) of < 30. The average of two high quality images was used for

the FD-OCT analysis.

Mean, superior, and inferior RNFL thicknesses were calculated. The GCC scan was

centered 1-mm temporal to the fovea and covered a square grid (7 X 7 mm) on the

central macula. GCC thickness was measured from the internal limiting membrane to

the outer inner plexiform layer boundary, and mean, superior, and inferior GCC

thicknesses were calculated.

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Statistical analysis:

The SPSS 15.0 program was used for statistical analysis (SPSS Inc., Chicago, IL,

USA). An ANOVA test was used to compare the measured parameter values between

the patient groups. Sensitivity, specificity for OCT parameters were determined. P-

values of 0.05 were considered as statistically significant. Student t tests were used to

evaluate optic nerve head, RNFL thickness, and macular thickness measurement

differences between glaucomatous and healthy eyes. The relationships between mean

RNFL/GCC thickness and MD were evaluated with linear and nonlinear regression

analyses. Pearson’s correlation coefficients were used to assess the correlations

between continuous variables. Receiver operating characteristic (ROC) curves were

used to describe the ability to differentiate glaucomatous from healthy eyes of each of

the FD-OCT parameter.

RESULTS:

30 normal and glaucoma subjects each were included in this study. The mean age of the

study group was 53.40 (10.4) years, 55.47% of the overall study population were males

and 44.23% were females (Figure1). The difference in mean age among the groups was

not significant.

According to (HAP) criteria 53.85% were early glaucomatous subjects, 30.77% were

moderate glaucomatous and 15.38% were severe glaucomatous patients (Figure 2).

9.62% showed borderline and 90.38% as Outside normal limits in GHT (Figure 3).

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Figure 1: Gender distribution

Fig 2: Classification of glaucoma group by HAP Fig 3: Classification of glaucoma

group Classification. by GHT.

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RNFL thickness shows significance difference from Glaucoma and normal’s where

RNFL thickness is significantly thinner in glaucomatous groups compared to control

subjects. RNFL thickness showed significant difference with Mean deviation (MD) of

visual field in glaucoma subjects (p= 0.01) and RNFL thickness showed a negative

correlation with Pattern Standard deviation (PSD) (p= 0.01).

GCC overall thickness shows significance difference from Glaucoma and normal’s

where GCC overall thickness is significantly thinner in glaucomatous groups

compared to control subjects.

GCC overall thickness showed significant difference with Mean deviation (MD) of

visual field in glaucoma subjects (p= 0.01) and GCC overall thickness showed a

negative correlation with Pattern Standard deviation (PSD) (p= 0.01) .GCC overall

thickness decreases with increasing severity of Visual Fields (Glaucoma Hemifield

parameter & HAP classification) (Graph 1,2). RNFL overall thickness decreases with

increasing severity of Visual Fields (Glaucoma Hemifield parameter & HAP

classification) (Graph 3,4).

Graph 1: GCC overall thickness with Fields Glaucoma Hemifield.

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Graph 2: GCC overall thickness with HAP classification

Graph 3: RNFL overall thickness with Fields Glaucoma Hemifield.

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Graph 4: RNFL overall thickness with HAP classification

Receiver operator characteristic (ROC) curves were drawn for RNFL and GCC

parameters. The area under the ROC (AROC) curve for average RNFL was 0.901

(95% CI, 0.85 to 0.96). With a cut off value of 98.5 microns, there was 86% sensitivity

and 80% specificity. For inferior RNFL thickness, the AROC curve was 0.876 (95%

CI, 0.80 to 0.94), and a cut off of 94 microns gave 92% sensitivity and 75%

specificity. The AROC curve for superior RNFL was 0.872 (95% CI, 0.80 to 0.93) and

a cut off of 99microns gave sensitivity of 84% and specificity of 75%.

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Graph 5: ROC curve for RNFL parameters.

The area under the ROC (AROC) curve for average GCC was 0.875 (95% CI, 0.81 to

0.94). With a cut off value of 89.70 microns, there was 88% sensitivity and 80%

specificity. For inferior GCC thickness, the AROC curve was 0.866(95% CI, 0.79 to

0.93), and a cut off of 90.73 microns gave 84% sensitivity and 80% specificity. The

AROC curve for superior GCC thickness was 0.876 (95% CI, 0.80 to 0.94) and a cut

off of 89.32 microns gave sensitivity of 84% and specificity of 80%.

Graph 6: ROC curve for GCC parameters.

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DISCUSSION:

In this study population the RNFL showed the highest AROC among all of the

parameters followed by GCC parameter. These findings are in accordance to previous

study both with frequency-domain OCT and time-domain OCT though most of the

RNFL thickness parameters obtained from these two devices are quite different. 29-40

The superior and inferior sectors gather most of the RNFL and have the priority of

glaucomatous damage and in early stage glaucoma, RNFL damage can occur either in

superior or inferior region (or both) in a focal or diffuse way.

Chen et al. 41

showed that average RNFL was the best parameter for differentiating

early glaucoma from normal eyes with ROC curve area of 0.793, Kanamori et al. 42

showed an AROC of 0.93 with inferior RNFL as the best parameter for such a

differentiation. We found that the average RNFL thickness followed by the inferior

and superior RNFL thickness had the highest power to discriminate between early

glaucoma and normal eyes, with an area under the ROC of 0.901, 0.876 and 0.872,

respectively. Galvao Filho et al 43

showed that superior and inferior quadrant RNFL

thickness was significantly different between healthy and early glaucoma subgroups,

but not between early and moderate glaucoma subgroups, by using scanning laser

polarimetry. Sihota et al 44

evaluated the role and ability of OCT to detect differences in

RNFL thickness between normal and glaucomatous eyes and also between different

severities of glaucoma and found that inferior quadrant and average RNFL parameters

are among the most efficient parameters for making such a differentiation.

Reduced macular thickness was initially described by Zeimer et al45

using the slit-

scanning Retinal Thickness Analyzer (Talia Technology Ltd, Neve- Ilan, Israel),

hypothesizing that macular thickness could be a measure of glaucoma damage.

Ishikawa et al46

developed a macular segmentation algorithm to measure sublayer

thickness for glaucoma diagnosis: they showed that macular inner retinal complex

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(ganglion cell layer, inner plexiform layer, inner nuclear layer) was thinner in eyes

with perimetric glaucoma. Leung et al47

used the Stratus TD-OCT (Carl Zeiss, Dublin,

CA) to evaluate macular nerve fiber layer thinning in glaucoma. They reported a

reduction in macular nerve fiber layer thickness in glaucomatous eyes compared with

normal eyes.

In other studies, it has been reported that peripapillary RNFL measurements are

significantly more accurate in glaucoma detection than is GCC thickness. 48-50

In a few

studies, the diagnostic value of RNFL and GCC measurements has been compared

with that of FD-OCT and the results have shown that diagnosis using macular GCC

parameters is comparable with diagnosis using circumpapillary RNFL measurements.

51,52

We found that RNFL thickness and GCC thickness had almost similar diagnostic

values for glaucoma detection. The GCC parameters (Mean, superior, and inferior

thickness and FLV, GLV) readily identified glaucoma patients. Mean GCC thickness

appeared to be a better predictor of early glaucoma than inferior and superior GCC

thickness, but the difference was not significant.

Tan et al53

showed that macular GCC thickness has glaucoma discrimination ability

comparable with papillary RNFL thickness. They also found that FLV and GLV have

higher diagnostic accuracy than the GCC average. Kim et al54

observed that macular

GCC thickness and RNFL thickness showed similar diagnostic performance for

detecting early glaucoma.

On studying the correlation between the visual field indices (MD and CPSD) and the

average RNFL thickness and GCC thickness, we found a significant positive

correlation with MD because the MD is negative value, higher the MD poorer is the

disease and a significant negative correlation with CPSD on standard humphery

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perimetry because the PSD is positive value, higher the PSD poorer is the disease.

This observation is in agreement with previous studies. 55-56

In a study of 30 patients

with glaucoma and 14 control subjects, Parisi et al.57

showed a highly significant linear

regression (r= 0.663, P <0.001) between overall NFL thickness and CPSD, the

correlation with MD having been less significant (r =0.393, P< 0.031). 57

Conclusion:

In conclusion, FD-OCT were able to show the significant differences of thickness of

RNFL and GCC between glaucoma patients and normal subjects. At present, there is

no consensus on which is the best structure parameter for early glaucoma diagnosis,

and it is still unknown whether one or several of these diagnostic parameters should be

used in the clinical diagnosis of early glaucoma. Our study showed that the RNFL and

GCC thickness are lower in early glaucoma than in normal eyes. The average RNFL

thickness is a measurement of global thickness of the RNFL and, therefore, is

presumably important in the differentiation of glaucoma from healthy eyes. Ganglion

cell complex thickness, as measured by OCT, was capable of detecting glaucomatous

damage and corresponded with RNFL thickness; however, RNFL thickness had higher

sensitivity and specificity for the detection of glaucoma.

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