|Year : 2016 | Volume
| Issue : 2 | Page : 65-72
Functional and anatomical assessment of retinal ganglion cells in glaucoma
Mona Abdelkader MD
Department of Ophthalmology, Mansoura Ophthalmic Center, Faculty of Medicine, Mansoura University, Mansoura, Egypt
|Date of Submission||02-Sep-2015|
|Date of Acceptance||11-Feb-2016|
|Date of Web Publication||30-Aug-2016|
Mansoura Ophthalmic Center, Faculty of Medicine, Mansoura University, Mansoura, P.O. 35516
Source of Support: None, Conflict of Interest: None
The aim of the study was to assess the ability of retinal ganglion cell (RGC) complex measurements obtained by optical coherence tomography (OCT) to detect glaucoma, to measure RGC loss by pattern electroretinogram (PERG), and to correlate the results of PERG with OCT for glaucoma detection.
Patients and methods
Fifty glaucoma suspects (100 eyes), 70 glaucoma patients (140 eyes), and 50 age-matched controls (100 eyes) were examined. Participants had clear ocular media, no or mild refractive errors, and no concomitant ocular or systemic diseases. Superior and inferior ganglion cell complex thickness and retinal nerve fiber layer (RNFL) thickness were measured by means of OCT. The amplitude and latency of PERG were elicited by counter-phase checks.
The mean RNFL thickness and mean RGC thickness were reduced in glaucoma patients compared with glaucoma suspects and controls. The mean RNFL thickness was 88 ± 9.9 µm in early glaucoma, 94 ± 12 µm in glaucoma suspects, and 99 ± 15.5 µm in controls. The total RGC thickness was 55 ± 6.2 µm in early glaucoma, 64.9 ± 3.8 µm in glaucoma suspects, and 65 ± 4.1 µm in controls. The mean PERG amplitude was decreased in both glaucoma suspects and glaucoma patients compared with controls. In glaucoma suspects, PERG amplitude did not correlate significantly with both RNFL thickness and RGC thickness, whereas in glaucoma patients PERG amplitude was positively correlated with both RNFL and RGC thickness.
OCT can assess the RGC anatomically, whereas PERG can functionally evaluate RGC loss. Lack of anatomical–functional relationship in glaucoma suspects suggests that at this stage PERG losses appear to affect primarily the retinal/optic nerve function. In glaucoma patients, PERG reflects both dysfunction and loss of ganglion cells.
Keywords: electroretinogram, GCL, nerve fiber layer, optical coherence tomography, pattern electroretinogram
|How to cite this article:|
Abdelkader M. Functional and anatomical assessment of retinal ganglion cells in glaucoma. Delta J Ophthalmol 2016;17:65-72
| Introduction|| |
Glaucoma is a neurodegenerative disease associated with progressive loss of retinal ganglion cells (RGCs) and their axons. RGC complex is defined as a set of neighboring ganglion cells in the RGC layer together with their axons forming a nerve fiber bundle in the retinal nerve fiber layer (RNFL) until their exit from the eye in the optic nerve head .
The goal of glaucoma management is to slow down the rate of progressive neural loss to preserve visual function throughout the patient’s life. Assessment of visual function in clinical practice is traditionally performed with standard automated perimetry (SAP). Although SAP testing has been widely used for diagnosis, staging, and monitoring of the disease, it has become increasingly evident that a substantial number of RGCs may be lost before damage to SAP becomes statistically significant ,.
The pattern electroretinogram (PERG) is a direct objective measure that reflects the electrical activity of RGCs and has been extensively used for detecting the loss of RGC function in glaucoma ,.
Optical coherence tomography (OCT) is a rapidly evolving robust technology that has profoundly changed the practice of ophthalmology. It involves the use of objective probes to investigate the structure of RGCs and RNFL thickness . It is generally accepted that structural damage precedes functional loss in glaucoma, suggesting the presence of RGC reserve or rebound . It is estimated that 25–50% of nerve fibers can be lost before a field defect is detected on perimetry . Kerrigan-Baumrind et al.  estimated that at least 25–35% of RGCs would need to be lost for statically significant abnormalities to appear on automated perimetry.
Studies comparing high-resolution imaging of anatomical structures with SAP have shown that OCT may detect a large number of glaucoma patients with early and/or progressive damage compared with SAP ,.
The aim of the present study was to evaluate the function and anatomy of RGCs in glaucoma and to assess the relationship between PERG amplitude and RGC thickness by OCT.
| Patients and methods|| |
This study was carried out on patients attending the outpatient clinic of Mansoura Ophthalmic Center during the period from February 2013 to February 2014.
A total 170 patients (340 eyes) were included in the study: 50 glaucoma suspects (100 eyes; 26 men and 24 women; mean ± SD age: 46 ± 10 years), 70 glaucoma patients (140 eyes; 35 men and 35 women; mean ± SD age: 48 ± 13 years), and 50 age-matched controls (100 eyes; 24 men and 26 women; mean ± SD age: 52 ± 12 years).
All patients underwent a full ophthalmic examination including visual acuity testing, slit-lamp biomicroscopy, stereoscopic optic nerve head photography, OCT, PERG, and perimetry.
The inclusion criteria for the control group were a corrected visual acuity of 6/12 or better and a pupil diameter of at least 2.5 mm without dilation, normal slit-lamp biomicroscopy including an open anterior chamber angle on gonioscopy, normal PERG, normal OCT, and a central corneal thickness between 520 and 570 μm measured using a pachymeter, normal intraocular pressure (IOP) measured with Goldmann applanation tonometry, normal ophthalmoscopy, normal visual field (VF), and no family history for glaucoma or retinal dystrophy.
Patients with refractive error exceeding ± 3 D, astigmatism more than ± 1 D, diabetes, previous cataract surgery or any other ocular disorders, neuro-ophthalmologic disease affecting the optic disc and VF, or low perimetric reliability were excluded. All patients had reliable VFs with fewer than 33% fixation losses, false positives, and false negatives.
Glaucoma patients had either elevated IOP (IOP > 21 mmHg on two separate occasions, mean ± SD IOP: 24.9 ± 2.1 mmHg) in both eyes, family history of glaucoma, normal SAP and clinically normal optic nerve head, or a normal IOP (IOP <20 mmHg, mean ± SD IOP: 12.6 ± 2.1 mmHg) in both eyes with an abnormal optic disc or abnormal SAP. Normal appearance of the optic disc on routine stereoscopic examination with slit-lamp biomicroscopy was defined as a vertical cup–disc ratio less than 0.2 with no asymmetry (≥0.2, unexplained by side differences in disc size), excavation, thinning of the rim, notching, hemorrhages, RNFL defects, or para papillary atrophy. Abnormal clinical appearance of the optic disc included at least one or more of the above-mentioned abnormalities.
The diagnosis of glaucoma required a confirmed VF defect on the Humphery 24-2 test and glaucomatous optic disc as judged by stereo disk photography. IOP was 22 mmHg or more on applantation tonometry. Glaucomatous eyes were subdivided according to mean deviation of SAP (Hodapp’s classification) into three subgroups: early glaucoma was defined as VF loss with an MD less than or equal to -6 dB; moderate glaucoma was defined as Mean deviation (MD) between -6 and −12 dB; and severe glaucoma was defined as an MD worse than −12 dB .
The evaluation of glaucomatous VF defects was made on the basis of liberal criteria (two or more contiguous points with pattern deviation sensitivity loss of P < 0.1 or three or more contiguous points with sensitivity loss of P < 0.05 in the superior or inferior arcuate areas or a 10-dB difference across the nasal horizontal midline at two or more adjacent locations and abnormal result in the glaucoma hemifield test) . Only patients who had more than two reliable consistent VF results were included. Both eyes were tested so that asymmetry analysis could be performed.
Informed consent was obtained for each participant after the aims and procedures of the study had been fully explained. The study was carried out in accordance with the tenets of the Declaration of Helsinki (1989) of the world medical association. The study was approved by Mansoura University Hospital Trust Ethics Committee.
Optical coherence tomography
OCT was performed using Topcon 3D OCT 1000 (Topcon Corporation, Tokyo, Japan). The scan protocol was the fast one. Two macula-centered and 2-ONH-centered scans were obtained. OCT volumes were acquired (2 × 2 volumes per patients). Each OCT volume was 200 × 200 × 1024 voxels, corresponding to a dimension of 6 × 6 × 2 mm2. Only patients with acceptable quality of both macular and peripapillary OCT images (with signal strength ≥50) were included in the study. The mean RGC thickness (software-defined region bound by the presumed internal limiting membrane and the inner plexiform layer) and RNFL thickness (software-defined region bound by anterior and posterior RNFL borders) were estimated from OCT volumes. The regional RGC thickness for all A-scans in a grid region and similarly the mean RNFL thickness were measured. Images with eye movements during scans, poor centration, poor focus, or high noise were excluded.
PERG was performed using RETI Port 21 (Electrophysiological Diagnostic System, Roland Consult; Brandenburg, Germany). PERG was undertaken according to the standards of the International Society for Clinical Electrophysiology of Vision (ISCEV). PERG was simultaneously recorded from both eyes according to a paradigm optimized for glaucoma detection, which has been reported to have low test–retest variability ,.
Responses were recorded by using a Dawson–Trick–Litzkow thread electrode, which was positioned on the inferior cornea along the lid margin and fixed temporarily. The pupils were dilated with tropicamide 1%. Gold cup reference and surface electrodes were applied to the participant’s temple and forehead, respectively. Stimuli were checks-modulated in counter-phase and electronically generated on high-resolution T-V stimuli (contrast: 98%, mean luminance: 80 cd/m2, field size: 31° width × 24 height, resolution: 1024 × 768). The Roland equipment provides LED stimulator to produce the stimulus pattern with homogenous luminance. The pattern reversal needs exchanging between the black and white checks on the checker board, and the numbers of black and white checks should be equal on the screen. Pattern check size was 0.48 min, modulating at a rate of three reversals per second. Patients fixated at the center of the stimulated field placed at a viewing distance of 30 cm with natural pupils (they did not receive dilating drops). The patients wore full refractive correction for test distance and were allowed to blink freely. Responses were amplified (100 000×), band pass filtered (1–30 Hz), sampled at 2 kHz, and averaged with automated artifact rejection. Two replications were obtained for each record to verify reproducibility. Peak-to-peak amplitude (μv) and implicit time (ms) were measured.
Static achromatic automated perimetry was performed using Humphery Field Analyser 640 (Carl Zeiss Co., San Leandro, California, USA). Patients were tested with undilated pupils using static automated white-on-white 24-2 stimulus presentation pattern and full threshold strategy. An optimal lens correction was used and the fellow eye was occluded with an eye patch. Global indices (MD, CSPD) were determined. Patients had previously performed Humphery 24-2 field tests on two or more occasions and had demonstrated reproducible field results.
A normal VF was one with less than 3 nonedge contiguous points identified significantly (P < 0.05) on the same side of the horizontal meridian in the pattern deviation plot and was graded as within normal limits in the glaucoma hemifield test.
Data were analyzed using the statistical package for the social sciences (SPSS; Microsoft Corporation, Chicago, Illinois, USA). PERG and OCT data obtained from the three groups of the study population were first analyzed by one-way analysis of variance (ANOVA; Microsoft Corporation) with post-hoc adjusted t-test (Bonferroni) to determine differences in the measurement values across the groups. The performance of RGC thickness to discriminate glaucoma from controls was compared with that of RNFL thickness. A standard method was used for including two correlated eyes of patients in the analysis. Especially, we nested eyes (included them as a random effect) within participants in the ANOVA model. This generated between-eye variance component estimates that were extracted from the analysis that did not contribute to an estimate of (in the present cases) the difference between the results of two eyes. Receiver operating characteristic (ROC) curves were used to describe the ability of each parameter to differentiate between groups. The parameter with the highest area of ROC had the best diagnostic performance. A perfect test would have ROC curve equal to 1 (100% sensitivity and 100% specificity), whereas a test with no diagnostic value would have an ROC of 0.5. The correlation among PERG amplitude, latency, and RGC and RNFL thickness was calculated by Pearson’s correlation and linear correlation analysis (R ≥ 5 indicated good correlation). P values less than 0.01 were accepted as being statistically significant.
Sensitivity was defined as the percentage of glaucomatous eyes that had an abnormality on the test. Specificity was defined as the percentage of eye with a normal optic disc structure that had a normal test result.
| Results|| |
The study included 170 patients (340 eyes).
There were reductions in retinal functions (PERG) in glaucoma patients compared with other groups [Table 1] and [Figure 1].
|Figure 1 Pattern electroretinogram (ERG). (a) Normal controls: there is normal latency and amplitude of P50. (b) Glaucoma suspects: there is delay in latency and normal amplitude. (c) Glaucoma patients: there is severe delay in latency and reduction in amplitude.|
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There were reductions in P50 amplitude and prolongation of implicit times of PERG in glaucoma suspects and glaucoma patients when compared with the age-matched control group (P = 0.01 and 0.002, respectively).
As regards RGC and RNFL thickness (measured by OCT), there were no statistically significant differences between glaucoma suspects and the control group (P = 0.3). There were significant reductions in both RGC and RNFL thickness in the glaucoma group when compared with the other groups (P = 0.005) [Table 2] and [Table 3] and [Figure 2], [Figure 3], [Figure 4].
|Table 3 Macular ganglion cell complex thickness and retinal nerve fiber layer thickness among groups|
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|Figure 2 (a) Optical coherence tomography (OCT) grid in glaucoma. Retinal ganglion cell–axonal complex connectivity maps for cell body segment in ganglion cell layer to the optic nerve head neural rim segment. It shows the following regions: macular grid (cyan), optic nerve head grid including optic cup (orange), optic nerve head wedge regions (green). (b) OCT in glaucoma suspects. It shows reduction of nerve fiber thickness and GCL thickness. NFL, nerve fiber layer.|
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|Figure 3 (a) Good positive correlation between pattern electroretinogram (PERG) amplitude and ganglion cell layer (GCL) in glaucoma. (b) Good negative correlation between PERG latency and GCL thickness in glaucoma. (c) Good positive correlation between PERG amplitude and nerve fiber layer thickness (NFLT) in glaucoma.|
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|Figure 4 (a) Nonsignificant correlation between pattern electroretinogram (PERG) amplitude and GCL thickness in glaucoma suspects. (b) Nonsignificant correlation between PERG latency and GCL in glaucoma suspects.|
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In glaucoma suspects, the widest parts of the ROC curves of RNFL (the areas with big values) were found in the inferior quadrants (0.811) followed by the average (ROC = 0.798). In early glaucoma, the widest areas of ROC curves of RNFL thickness were related to inferior quadrants (0.898).
In addition, in glaucoma suspects, RGC thickness with the widest ROC curves were correlated to total thickness (ROC = 0.685), followed by the inferior quadrant (0.651). In early glaucoma RGC thickness with the widest ROC curves were related to total thickness (ROC = 0.799), followed by the inferior quadrant (0.779) [Table 4].
|Table 4 Receiver operating characteristic curve areas of optical coherence tomography|
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The proportion with abnormal PERG ranged from 50 to 70% in glaucoma suspects, whereas by OCT the proportion with abnormal RNFL thickness (one sector red or two sectors yellow) ranged from 45 to 65% and the proportion with abnormal RGC thickness ranged between 42 and 63%.
Specificity in normal participants was 75% (25 eyes) in PERG, 95% (five eyes) in RNFL thickness, and 91% (nine eyes) in RGC thickness.
Sensitivity of RNFL thickness was 97% (three eyes), that of RGC thickness was 92% (eight eyes), that of P50 amplitude of PERG was 88% (12 eyes), and that of P50 implicit time of PERG was 90% (10 eyes).
There was a significant correlation between RGC and RNFL thickness (R = 0.5, P = 0.005). The reduction in RNFL thickness was accompanied by a reduction in RGC thickness in glaucoma. However, there was a statistically nonsignificant correlation between total RGCs and RNFL in glaucoma suspects (R = 0.2, P = 0.8).
There was a significant negative correlation between OCT abnormalities (RNFL, RGC reduction) and P50 implicit time of PERG in the glaucoma patient group (R = −0.8, P = 0.002; R = −0.7, P = 0.001, respectively). There was a delay in P50 implicit time with a decrease in both macular RGC and peripapillary RNFL thickness. In addition, there was a significant positive correlation between OCT parameters (both macular RGC and peripapillary RNFL thickness) and P50 amplitude (R = 0.5, P = 0.01, R = 0.51, P = 0.02).
| Discussion|| |
The PERG has long been considered an important indicator of RGC function in glaucoma ,.
In this study, there was a reduction in the amplitude and a delay in the implicit time of P50 with normal VF indices and normal RNFL and RGC complex thickness in glaucoma suspects.
PERG amplitude and implicit time represent different aspects of RGC function. Decease in PERG amplitude may occur because of lost RGCs, dysfunctional RGCs, or a combination of both conditions. The delay in response may mean that active RGCs respond in a slower manner ,. Fortune et al.  reported that RGC function abnormalities exist before thinning of the RNFL.
The reason for normal VF in the presence of abnormal PERG is that the PERG has a strong macular over-representation due to the highest RGC density in the macular region compared with that in the extramacular region . In contrast, for VF the macular region is relatively less represented .
Bode et al.  found a deterioration of PERG signal associated with normal VF in OHT patients. Similarly, Ventura et al.  found longitudinal loss of signal (amplitude reduction, phase delay, or both) in glaucoma suspects. Nakano et al. reported thinner macular inner retinal layers in glaucoma suspects compared with controls.
In this study, there was a reduction in RGC and RNFL thickness with a delay in implicit time and reduction of P50 amplitude of PERG in glaucoma. There was an RGC damage in glaucoma accompanied by a corresponding nerve fiber loss. Wolff et al.  found significant reduction in RNFL thickness and amplitude of PERG in glaucoma. Similarly, Schulze et al.  found significant reduction in RGC complex layer thickness compared with that of controls or patients with OHT. Kim et al.  found ganglion cell complex loss in open-angle glaucoma. In addition, Na et al.  found significant lower macular RGCs and peripapillary RNFL in glaucomatous eyes compared with healthy eyes.
In this study, the sensitivity of the RNFL parameter was 97% (three eyes), that of RGC was 92% (eight eyes), that of the P50 amplitude of PERG was 88% (12 eyes), and that of the P50 implicit time of PERG was 90% (10 eyes). The best parameter of RGC (ROC = 0.799) was the total RGC thickness and the best parameter of RNFL was the inferior quadrant (ROC = 0.898). Thus, RGC thickness is as useful in detecting glaucoma as is RNFL thickness. Wolf et al.  reported that the sensitivity of PERG was 70% and the specificity was 97.7%, whereas the OCT sensitivity was 50% and the specificity was 100%. Garas et al.  showed that RNFL and RGC variables have moderate sensitivity with high specificity for glaucoma detection. Bertuzzi et al.  reported that the best RNFL parameter was the average (sensitivity: 90%, ROC: 0.98) and the inferior–temporal (sensitivity: 89%, ROC: 0.97). In addition, they reported that the best RGC parameter was focal loss (sensitivity: 91%, ROC: 0.98) and global loss (sensitivity: 87%, ROC: 0.96). They emphasized that the diagnostic validity of RGC was comparable to that of the RNFL parameters and may be very useful in detecting RNFL thickness .
In the present study, there was a significant positive correlation between total RGC and RNFL thickness in glaucoma patients, whereas there was a statistically nonsignificant correlation between total RGC and RNFL thickness in glaucoma suspects. The most obvious explanation is that tissue loss and thinning progress as glaucoma advances, leading to increasing structural correlation as additional RGCs are damaged by the disease. Lee et al.  reported a strong correlation between RGC and RNFL in early glaucoma.
In the current study, there was a statistically nonsignificant correlation between OCT abnormalities (RNFL and RGC reduction) and P50 of the PERG in glaucoma suspects. There were significant PERG losses with no losses in RNFL and RGC thickness. The amount of PERG loss was greater than predicted by RNFL and RGC thickness loss. This means that in glaucoma suspects the loss of electrical responses does not reflect a numerical dropout of optic nerve axons but rather an RGC dysfunction. This is in agreement with the idea that there is a disease stage where RGC dysfunction may precede cellular and axonal numerical loss corresponding to functional losses in the presence of normal structures . In accordance with this, Weinreb et al.  mentioned that, in OHT, RGC dysfunction is prevalent with minimal anatomical loss. Similarly, Falsini et al.  found that PERG amplitude did not correlate significantly with RNFL thickness in OHT, whereas in early glaucoma, PERG amplitude was positively correlated with RNFL thickness. In contrast, Parisi et al. , observed a positive correlation between RNFL thickness and PERG in both OHT and glaucoma.
Bach et al.  followed glaucoma suspects and found that ROC increased over time. They concluded that PERG can help to predict stability or progression in OHT at least 1 year ahead of conversion. Bowd et al.  described the association between PERG and OCT and found that PERG amplitude is weakly associated with the RGC complex. They found a weak correlation between PERG parameters and macular RGCs. Banitt et al.  observed that, in glaucoma suspects, PERG signal anticipated an equivalent loss of OCT signal (RGCs and RNFL thickness) by several years.
In the present study, there was a significant negative correlation between OCT abnormalities (RNFL and RGC reduction) and P50 implicit time of PERG in glaucoma patients. There was a delayed P50 implicit time with a decrease in both macular RGC and peripapillary RNFL thickness. There was a significant positive correlation between OCT parameters (both macular RGC and peripapillary RNFL and P50 amplitude). Park HY and Park CK  detected stronger structure–function relationship in perimetric glaucoma and early glaucoma. They found strong correlation between circumpapillary RNFL thickness and mean retinal sensitivity of the corresponding field. However, Ventura et al.  showed that PERG amplitude losses in glaucoma suspects and glaucoma patients are greater than the corresponding losses in RNFL thickness.
In summary, in glaucoma, the loss of RGC body is accompanied by corresponding nerve fiber loss. OCT is a useful ancillary diagnostic tool for evaluation of early macular and circumpapillary structural changes in glaucomatous eyes. PERG is considered an important indicator of RGC function in glaucoma.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]