Determinants of Macular Ganglion Cell–Inner Plexiform Layer Thickness in Normal Chinese Adults

Abstract

Background

To determine the influences of multiple demographic and ocular factors on the measurements of macular ganglion cell–inner plexiform layer (GCIPL) thickness in normal Chinese adults.

Methods

This was a retrospective study conducted on 225 normal eyes from 225 healthy Chinese adults. GCIPL thickness were obtained using Cirrus high-definition optical coherence tomography (OCT). The age, gender, laterality, spherical equivalent (SE) refractive error, intraocular pressure (IOP), axial length (AL), central cornea thickness (CCT), circumpapillary retinal nerve fibre layer (pRNFL) thickness and OCT signal strength were recorded and their respective effect on GCIPL thickness parameters were evaluated.

Results

The mean (± SD) average, minimum, superotemporal, superior, superonasal, inferonasal, inferior, and inferotemporal GCIPL thickness was (84.56 ± 5.36), (81.32 ± 5.58), (83.08 ± 5.37), (85.70 ± 5.95), (87.15 ± 6.26), (85.07 ± 6.11), (82.46 ± 5.76), and (83.88 ± 5.59) µm, respectively. Determinants of thinner GCIPL thickness were older age (P = 0.001–0.117; effects enhanced if age over 40 years), thinner pRNFL (all P < 0.001), and weaker signal strength (all P < 0.001). No significant difference was found between males and females (P = 0.069–0.842), and between right eyes and the left eyes (P = 0.160–0.875) except that of superonasal GCIPL thickness (P < 0.001). There was no significant correlation between GCIPL thickness and SE, IOP, CCT, and AL (P = 0.135–0.968).

Conclusions

Individual determinants associated with thinner GCIPL thickness were older age (particularly over 40 years of age), thinner pRNFL, and weaker OCT signal strength. This is relevant in comprehensively understanding the normative data and differentiating normal aging from abnormalities.

Background

As the output neurons of the retina, retinal ganglion cells (RGCs) are the only part of the central nervous system that can be optically detected in vivo.(1) The hallmark of glaucoma, one of the leading causes of irreversible blindness worldwide, is progressive loss of RGCs in the inner retina and their axons in the optic nerve head (ONH).(2) Previous studies showed that structural glaucomatous changes primarily affect RGCs and their axons, followed by functional changes featured by characteristic glaucomatous visual field defect.(3, 4) There may be a 20–40% of RGC loss prior to detectable visual field defect,(5, 6) which indicates that early detection and monitoring of glaucoma could be benefit from the detailed evaluation of RGCs. The human retina contains an estimate of more than 1 million RGCs, over 50% of which are located in the macular.(7) The high density of the RGCs makes the macular the easiest region for calculating the RGC counts and detecting their loss. The thinning of macular ganglion cell layer (GCL) and peripapillary retinal nerve fiber layer (pRNFL) has been well recognized as biomarkers of optic nerve damage, which can be measured by optical coherence tomography (OCT) quantitatively in a non-invasive, precise, and reproducible way.

A number of studies have showed that the macular ganglion cell complex (GCC, the sum of RNFL, GCL, and inner plexiform layer) thickness, or the macular ganglion cell–inner plexiform layer (GCIPL) thickness has similar glaucoma discriminating performance with that of pRNFL.(8–13) Combining the measurements of GCC/GCIPL and pRNFL with optic disc parameters as well as psychophysics examinations and vasculature evaluations can help to improve the overall glaucomatous diagnostic ability and accuracy.(14, 15)

For clinical interpretation of GCC/GCIPL and pRNFL thickness readings, it is essential to know physiological factors that could influence the measurements. In normal eyes, age, sex, race, refractive power, axial length, optic disc size, and signal strength of OCT scanning are proven to be associated with GCC/GCIPL and/or pRNFL thickness; among these, the age is considered the most significant determinant by multiple studies.(16–24) However, some of the previous studies investigated multiple potential determinants with limited analysis deep into each determinant, and some emphasized on one or two determinants. Thus, an overall “big picture” is needed for better understanding which factors are impacting the OCT readings, how much the impacts are, and which should be taken into account in clinical interpretations despite normative database is used as a reference. The purpose of this study was to examine the influences of multiple demographic and ocular factors on the measurements of macular GCIPL thickness using Cirrus high-definition optical coherence tomography (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) in a cohort of normal Chinese adults with detailed, comprehensive analyses.

Methods

In this retrospective observational study, all participants were consecutively recruited from the Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China, from February 2013 to January 2016. The study followed the tenets of the Declaration of Helsinki and was approved by the Institutional Review Board (IRB). Written informed consent was obtained from all participants after explanation of the nature and possible consequences of the study.

Eligibility was determined via demographic characteristics recording and a comprehensive ophthalmologic evaluation including measurement of uncorrected and best-corrected visual acuity, measurement of refractive error (cycloplegic refraction test for participants younger than 30-year-old, and manifest refraction test for participants of 30 years or older), slit lamp biomicroscopy examination, intraocular pressure (IOP) measurement using a Goldman applanation tonometer (Haag-Streit, Bern, Switzerland), angle evaluation using gonioscopy, dilated fundus examination, stereo disc photography (Kowa nonmyd a-D III; Kowa Optimed Inc, Aichi, Japan), visual field testing (Humphrey Visual Field Analyzer II; Carl Zeiss Meditec, Dublin, CA) using the Swedish Interactive Thresholding Algorithm (SITA) standard 24 − 2 program, and OCT scanning (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA).

For inclusion, the criteria were: (1) generally healthy individuals of age ≥ 18 years; (2) best-corrected visual acuity 20/20 or better; (3) a spherical equivalent (SE) refractive error between − 5.00 diopters (D) and + 1.00 D; (4) intraocular pressure < 21 mmHg; (5) normal and wide anterior chamber angle; (6) normal optic nerve head appearance (cup-to-disc ratio < 0.5 in either eye, with the asymmetry of ≤ 0.2, no evidence of optic disc hemorrhage or focal thinning of the rim); (7) reliable and normal visual field results which was defined as: mean deviation (MD) with a P value of > 5%, pattern standard deviation (PSD) with a P value of > 5%, no more than 3 adjacent points in the pattern deviation plot with a P value of < 5%, and glaucoma hemifield test within the normal range; besides, the test should have a false-positive error, a false-negative error, and a fixation loss of less than 15%, simultaneously. The appearance of the optic disc on stereoscopic fundus photographs and visual field results were evaluated independently by two glaucoma specialists (XX and HX) who were masked to all other information about the eyes. Inconsistencies between these two doctors were decided by a senior glaucoma expert (XL). The data of the eye would not be used if the three doctors did not reach an agreement on the classification. The exclusion criteria were: (1) any known history of ocular disorders except mild or moderate refractive error; (2) history of ocular and/or brain trauma; (3) previous intraocular surgery; (4) optic media opacity; (5) medications usage that may cause IOP elevation or induce optic neuropathy; (6) neurological or systemic disorders that potentially affect visual field results and/or OCT readings; (7) unsatisfactory image acquisition; (8) inability to cooperatively complete all examinations. If both eyes of a participant met the inclusion criteria, only one randomly selected eye was enrolled.

Eligible participants underwent central cornea thickness (CCT) measurement using Ultrasonic Pachymetry (DGH-1000, Storz Inc, Louis, MO, USA) and the axial length (AL) measurement using IOLMaster (Carl Zeiss Meditec, Dublin, CA, USA).

OCT images were obtained after eyes were dilated with tropicamide 1% and phenylephrine 2.5% (Mydrin®-P, Santen Pharmaceutical Co. Ltd., Osaka, Japan) using the same OCT device by a well-trained glaucoma specialist (XX). Macular Cube 200 × 200 scan (200 horizontal B-scans comprising 200 A-scans per B-scan within a cube measuring 6 × 6 × 2 mm centered on the fovea) and Optic Disc Cube 200 × 200 scan (200 horizontal B-scans comprising 200 A-scans per B-scan within a cube measuring 6 × 6 × 2 mm centered on the optic disc center) were performed respectively at the same visit. Artificial tear was provided if the participants complained dryness or discomfort. Images with signal strength of less than 6 and those with visible motion or blinking artifacts and obvious segmentation failure were discarded immediately followed by repetition(s) of the scan.

The distance between the inner boundary of the GCL and the outer boundary of the IPL yields the combined thickness of the GCL and IPL (termed “GCIPL”) by the ganglion cell analysis (GCA) algorithm. The GCIPL thickness were analyzed within a 14.13 mm² elliptical annulus area with a horizontal inner and outer radius of 0.6 and 2.4 mm, respectively; and a vertical inner and outer radius of 0.5 mm and 2.0 mm, respectively. The average, minimum, and 6 sectoral (superior, superonasal, inferonasal, inferior, inferotemporal, and superotemporal) GCIPL thickness parameters were calculated. The minimum GCIPL thickness was defined as the lowest measured value of the 1-degree intervals among all the 360 spokes. Circumpapillary RNFL thickness parameters including the average RNFL thickness and quadrant RNFL thicknesses (superior, temporal, inferior and nasal) were calculated by the Cirrus analysis algorithm.

Participants were divided into 6 groups by age with an interval of 10 years. Participants were also divided into 2 groups based on refractive error: emmetropia group (SE between − 0.5D to + 1.0D) and myopia group (SE of <-0.5D and ≥ -5.0D).

Statistical analyses were performed using SPSS version 25.0 (SPSS Inc., Chicago, IL, USA). Shapiro-Wilk test and Levene test were applied to test the normality and the homogeneity of variance, respectively. Comparisons of GCIPL thickness between different gender and refractive groups were performed using independent-samples t-test. Paired-samples t-test was used to evaluate the GCIPL thickness between the right eye and the left eye of each subject. Comparisons of the GCIPL thickness and refraction between multiple age groups were performed using one-way analysis of variance (ANOVA) with Bonferroni adjustment for pairwise comparisons. Correlations between GCIPL thickness and the following factors were analyzed using Pearson correlation coefficient: age, SE refractive error, IOP, CCT, AL, and OCT signal strength. Univariate linear regression analyses were performed to assess how age and pRNFL thickness affected GCIPL thickness. A P value of < 0.05 was considered statistically significant. Except where stated otherwise, the data were presented as mean ± standard deviation (SD) values.

Results

A total of 225 participants (96 males and 129 females) were enrolled. The mean age of the study population was 46.3 ± 16.5 years (range from 18 to 75 years of age). The mean (± SD) average, minimum, superotemporal, superior, superonasal, inferonasal, inferior, and inferotemporal GCIPL thickness was (84.56 ± 5.36), (81.32 ± 5.58), (83.08 ± 5.37), (85.70 ± 5.95), (87.15 ± 6.26), (85.07 ± 6.11), (82.46 ± 5.76), and (83.88 ± 5.59) µm, respectively. Variability of GCIPL thickness were assessed upon the following possible determinants:

Discussion

In this study, we evaluated multiple determinants of macular GCIPL thickness in normal Chinese adults and demonstrated that the thinning of GCIPL thickness was associated with older age, thinner pRNFL, and weaker OCT scanning signal strength. In general, gender, laterality, refractive status (when the refractive error is between + 1D and − 5D), IOP, CCT, and AL had no significant impacts on macular GCIPL thickness.

Age is one of the most significant impact factors in determining macular GCIPL thickness. In this study, we found that the overall trend of GCIPL thickness changing with age was as follows: GCIPL thickness increased slowly with age in younger adults; after reaching the peak at 40–49 years of age, it decreased rapidly with age, which was consistent with the findings of Mwanza et al.(17) However, our previous findings in normal Chinese subjects indicated that pRNFL thickness was comparatively thicker in teenagers and reached its peak at 20–29 years of age, then gradually became thinner with age.(25) Similar results were found in studies in other Asian populations.(26, 27) These findings suggested that GCIPL and RNFL thickness changes may not necessarily be synchronized.

We found that for each additional year over 40 years of age, the average, minimum, superotemporal, superior, superonasal, inferonasal, inferior, and inferotemporal GCIPL thickness decreased by 0.229, 0.200, 0.127, 0.249, 0.273, 0.295, 0.273, and 0.173 µm, respectively. Animal experiments demonstrated that the age-related change of RGC predominately manifested as axon loss, while the RGC cell count is relatively constant.(28, 29) As the retina expands with age while the total cell counts retain, the RGC density decreases. The phenomenon of retina expansion with age was also found in human eyes, but the main difference with the animal eyes was that the number of RGC soma also declined with age in human.(30) Therefore, it is explainable that the GCIPL gets thinner with age in an OCT-based thickness evaluation, as shown in this study. It has been proven by multiple studies that the GCC or GCIPL thickness decreased with age, even though the age-related RGC loss varies in extent: Balazsi et al,(31) Repka et al,(32) Mikelberg et al,(33) Jonas et al,(34) Blanks et al,(35) Harman et al,(36) and Kerrigan-baumrind et al(37) respectively reported the annual RGC loss was between 0.07–0.61%, in studies with the sample size between 12 eyes to 72 eyes. In this study, we further approved that the age-dependent GCIPL thickness change was nonlinear with age. However, this age-related variability of the OCT measurements may not be completely attributed to inter-subject variability in retinal neurology, which is considerably significant even in normal human eyes. When ganglion cells reduce with age, the migrant amacrine cells and other non-neuronal components may partially compensate the space which is previously predominated by ganglion cells. As such, the actual cell loss may be masqueraded and the age-RGC loss correlation may become more unpredictable. Moreover, the RGC layered in the macular region, making it more complicated to evaluate the defined pattern of region- and eccentricity-associated, age-dependent RGC loss.

When evaluating the potential causative impacts of axial length on GCIPL thickness, just as the investigations concerning its impacts on RNFL thickness, contradictory conclusions were drawn. Some studies proposed that the GCIPL and RNFL thickness were negatively correlated to axial length.(38–41) Studies with a larger sample size and/or a wider range of refractive status, generally indicated that only less than 0.5% GCIPL thickness change was attributed to per millimeter axial length change.(16–18) Such minor changes could hardly reflect any practical clinical significance. Another reason that axial length may have some impacts on the GCIPL thickness measurement, but not necessarily the actual anatomic cell counts may be ascribed to the optical effects. Since the Cirrus OCT model eye adopts a calibrated value of 24.46 mm as the default axial length setting with a fixed measuring angular distance of approximately 12°, the actual scanning area would be larger than the “standard” retinal area due to the optical magnification effect in eyes longer than 24.46 mm. As the macular ganglion cell counts drop dramatically as the eccentricity increases outward from the foveal center, average ganglion cell estimates or GCIPL thickness in these eyes may therefore be underestimated for this reason. On the contrary, in eyes shorter than the set value, the actual scanning area is smaller than the preset area where the ganglion cells are more crowded and thus a thicker GCIPL measurement may be generated falsely.

Other studies declined the direct impacts of axial length on RGC growth or apoptosis and claimed that axial length had no significant correlation with macular GCIPL thickness,(42, 43) to which our findings was consistent with. The relatively small sample size could be one possible cause. Also, our inclusive criteria for spherical equivalent refractive error were − 5.00 D and + 1.00 D. The exclusion of highly myopic eyes restricted the variability of axial length, thus minimizing the interference of magnification effects on location of the retinal area being scanned that could potentially influence the GCIPL thickness measurements. Similarly, we didn’t find significant association between refractive error and GCIPL thickness. The difference of average, minimum, and most sectoral GCIPL thickness between the two refractive groups were not significantly different, except that in inferonasal and inferior sectors. Histological studies of both human and animals have found that the RGC were denser nasally than temporally, and superiorly than inferiorly, with distinct inter-subject variability, which might have indicated the discrepant anatomic distribution pattern in emmetropic and myopic eyes.(44) The thickest GCIPL was detected in the superonasal sector, in which no significant difference in emmetropic and myopic groups was found, suggesting that the density in this sector may have partially offset the difference caused by refractive error and/or axial length. This sector may have poorer performance in diagnosing glaucoma due to its least glaucomatous susceptibility.

The finding that pRNFL thickness had significant positive correlation with macular GCIPL thickness was not surprising and was consistent with previous studies.(17, 45) As the axon and soma of the ganglion cells, these two cellular components are closely related and both can be remarkably affected by glaucoma. Thus, these two parameters are both important and sensitive for early detection of glaucoma. The regression analysis showed that the mean RNFL thickness decreased by 0.901 µm for every 1 µm decrease in average GCIPL thickness. Overk et al(46) found that lesions in the axon may occur earlier than that in the soma in some neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, indicating a ‘reverse’ pathogenesis pathway for the primary causative factor of glaucoma. In the pathophysiological development process of glaucoma, whether GCIPL is affected primarily and causes changes in pRNFL, or vice versa, still needs further investigations.

The stronger the OCT signal strength, the deeper retinal tissue the light achieved.(47) As the reflection of the boundaries got enhanced, the segmentation of each layer was more accurate. The signal strength of Cirrus OCT was found to be positively correlated with RNFL thickness.(48) When the signal strength reaches 7 or more, the RNFL is less likely to measure thicker as the signal strength increases. In this study, although there was significant difference between the signal strength of the Macula Cube 512 × 128 scanning protocol and that of the 200 × 200 scanning protocol, all signal strength, as our inclusion criteria indicated, was ≥ 6. No significant difference was found in GCIPL thickness measured by the two scanning protocols, which may suggest that the GCIPL thickness measurement was stable and accurate when the signal strength is strong enough. The correlation between the signal strength of the 512 × 128 protocol and the GCIPL thickness was not as strong as that between the signal strength of the 200 × 200 protocol and the GCIPL thickness. This could be explained by the denser scan, which is more likely to generate better image quality, and the stronger signal strength of the former protocol.

There were several limitations of this study. First, it was a cross-sectional retrospective study with comparatively small sample size. Second, only ocular predictors were evaluated. Systemic predictors such as history of diabetes, cigarette smoking history, blood pressure, serum lipid levels should be taken into account. Third, there was a lack of a multivariable model synthesizing the effects of age and RNFL thickness, which were the two potential determinants found using univariable regression model. More comprehensive investigations are expected in future studies.

Conclusion

In conclusion, the GCIPL thickness measured by Cirrus OCT in normal Chinese subjects was associated with age, RNFL thickness, and scanning signal strength. No association was found between GCIPL thickness and gender, laterality, refractive status, intraocular pressure, axial length, and central corneal thickness. These should be taken into account to make comprehensive and objective clinical interpretation of GCIPL thickness in practical applications.

Abbreviations

Declarations

Ethics approval and consent to participate:

This study complied with the Declaration of Helsinki and was approved by the Institutional Review Board of Zhongshan Ophthalmic Center of Sun Yat-sen University. Written informed consent was obtained from all participants.

Consent for publication:

Consent for publication was obtained from all participants of this study.

Availability of data and material:

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests:

The authors declare that they have no competing interests.

Funding:

This project was supported by National Natural Science Foundation of China (81800879), Natural Science Foundation of Guangdong Province (2017A030310372); Fundamental Research Funds of the State Key Laboratory of Ophthalmology, China (2018KF04 & 2017QN05); Sun Yat-Sen University Clinical Research 5010 Program (2014016). None of the funding bodies played a role in the design of the study, collection, analysis, and interpretation of data, or in writing the manuscript.

Authors' contributions:

Conception and design (XL); data collection (XX, HX, JL); analysis and interpretation of data (XX, HX, KL, XG); statistical analysis (XX); literature search (XX); writing the article (XX); critical revision of the article (XX, HX, KL, XG, JL, XL). All authors reviewed and approved the final manuscript.

Acknowledgements:

Not applicable

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