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Glaucoma  |   April 2013
Correlation Between the Ganglion Cell-Inner Plexiform Layer Thickness Measured With Cirrus HD-OCT and Macular Visual Field Sensitivity Measured With Microperimetry
Author Notes
  • Department of Ophthalmology, Kagawa University Faculty of Medicine, Miki, Kagawa, Japan 
  • Correspondence: Kazuyuki Hirooka, Department of Ophthalmology, Kagawa University Faculty of Medicine, 1750-1 Ikenobe, Miki, Kagawa 761-0793, Japan; kazuyk@med.kagawa-u.ac.jp
Investigative Ophthalmology & Visual Science April 2013, Vol.54, 3046-3051. doi:10.1167/iovs.12-11173
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      Shino Sato, Kazuyuki Hirooka, Tetsuya Baba, Kaori Tenkumo, Eri Nitta, Fumio Shiraga; 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;54(4):3046-3051. doi: 10.1167/iovs.12-11173.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: To evaluate relationships between the macular visual field (VF) mean sensitivity and the ganglion cell and inner plexiform layer (GCA) thicknesses.

Methods.: Seventy-one glaucoma patients and 29 healthy subjects were included in this cross-sectional study. At each visit, GCA thicknesses were measured by Cirrus HD-OCT and static threshold perimetry was performed using Macular Integrity Assessment (MAIA). The relationship between the VF sensitivity and GCA thickness was examined globally, and in the superior hemiretina, inferior hemiretina, and six VF sectors with both VF and optical coherence tomography (OCT) in retinal view. Regression analysis was used to investigate the relationship between the GCA thickness and macular sensitivity.

Results.: Macular VF sensitivity (dB) and GCA thickness relationships were statistically significant in each sector (R = 0.365–0.706, all P < 0.001). The highest correlation observed was between the inferotemporal average mean sensitivity and the inferotemporal average GCA thickness (R = 0.706) with both VF and OCT in retinal view. Strength of the structure–function relationship for each of the corresponding inferior sectors was higher than those for the corresponding superior sectors. The strength of the structure–function relationship of the temporal sector was higher than that of the nasal sector.

Conclusions.: GCA thickness measured by Cirrus HD-OCT showed statistically significant structure–function associations with central VF. Inferotemporal central VF had the strongest association.

Introduction
Advances of optical coherence tomography (OCT) have enabled assessment of retinal ganglion cell (RGC) axons by measuring the thickness of the peripapillary retinal nerve fiber layer (RNFL) and the macular area. More recent advances in segmentation algorithms have it made possible to use OCT to visualize and measure individual retinal layers in the macular region. 13 RTVue-100 OCT (Optovue, Inc., Fremont, CA) incorporates a ganglion cell complex (GCC) scan mode that measures the inner macular retinal layer thickness from the internal limiting membrane to the inner plexiform layer (IPL), which is composed of ganglion cell axons, cell bodies, and dendrites. Previous studies have shown that the macular GCC thickness measurements derived from GCC scan data are significantly lower in glaucomatous eyes with visual field (VF) defects than in healthy eyes, and have a good glaucoma discriminating power that is comparable to that of the RNFL. 47 The thickness of the RGC or RGC + IPL (GCA: ganglion cell analysis) in the macula has also been measured by OCT. 2,8 Mwanza et al. 9,10 recently showed that the Cirrus HD-OCT GCA algorithm (Carl Zeiss Meditec, Dublin, CA) can successfully detect and measure the inner macular layers (the GCA; an area that contains the ganglion cell layer and the IPL) with excellent intervisit reproducibility. 
Microperimetry, which is known as fundus controlled perimetry or fundus perimetry, assesses retinal sensitivity during the direct examination of the ocular fundus. Microperimetry data are independent of eye movements and exactly related to the stimulated area. In addition, VF sensitivity can also be measured by microperimetry with improved spatial localization. 
A number of studies have used spectral-domain OCT to focus on the relationship between structural and functional damage as a way to improve our ability to detect the presence and progression of glaucomatous damage. Results of these studies have demonstrated there are high correlations between the global VF sensitivity and the peripapillary RNFL/GCC thickness. 5,11,12 The macular VF, including the central vision, is very important if a glaucoma patient is to enjoy normal daily life. Therefore, preservation of the macular VF is the key concern in glaucoma management. Wang et al. 2 found that local thickness of the RGC + IPL (GCA) could be obtained from frequency-domain OCT scans, with these measurements showing qualitative agreement with local VF sensitivity. Raza et al. 8 recently showed a strong relationship between losses in standard automated perimetry (SAP) sensitivity and decreases in local RGC + IPL thicknesses (GCA). 
The purpose of the current study was to evaluate the correlation between the GCA thickness and the local VF sensitivity obtained when using microperimetry, Macular Integrity Assessment (MAIA; CenterVue, Padova, Italy), in each sector of the macula. 
Materials and Methods
All patients were examined at Kagawa University Hospital from November 2011 through May 2012. At each visit, the GCA algorithm was used to detect the macular inner structure thickness, while MAIA was used to determine the static threshold perimetry. All eligible subjects received a detailed explanation of the study and signed an informed consent form in accordance with the principles embodied in the Declaration of Helsinki. The study protocol was approved by the institutional review board of the Kagawa University Faculty of Medicine. Healthy control subjects were either subjects attending the outpatients clinics, spouses and friends of the recruited patients, or volunteers from the hospital staff. 
All subjects underwent a complete ophthalmic examination that included visual acuity testing with refraction, IOP, gonioscopy examinations, and dilated fundus examination with stereoscopic biomicroscopy of the optic nerve head using slit lamp and indirect ophthalmoscopy. To be included in the study, all subjects had to have a best-corrected visual acuity of 20/40 or better, a spherical error within a range between +4.0 and −6.0 diopters (D), a cylinder within ± 2.0 D, and open angles (grade 3 and 4 according to the Shaffer grading system). Exclusion criteria included a history of any kind of retinal pathology or neurologic disease, retinal laser procedure, or either retinal or intraocular surgery. One eye in each subject was randomly chosen for inclusion in the study. To be enrolled as a control in the study, subjects had to have an IOP less than or equal to 21 mm Hg, no history of retinal pathology, and a normal visual field. Glaucomatous eyes were defined as eyes exhibiting structural glaucomatous changes (vertical cup-disc asymmetry between fellow eyes of ≥ 0.2, a cup-to-disc ratio of ≥ 0.6, and neuroretinal rim narrowing, notches, localized pallor, or RNFL defects with glaucomatous VF loss in the corresponding hemifield). A glaucomatous VF was defined as a glaucoma hemifield test (GHT) outside normal limits on at least two consecutive baseline tests and the presence of at least three contiguous test points within the same hemifield on the pattern deviation plot at P less than 1%, with at least one at P less than 0.5% excluding points on the edge of the field or those directly above and below the blind spot. 
Cirrus HD-OCT Imaging
All eyes were scanned by the Cirrus HD-OCT system. Only good-quality scans were used for the analyses. To be included, scans had to have a signal strength less than or equal to 6, be without RNFL discontinuity or misalignment, involuntary saccade or blinking artifacts, and show an absence of algorithm segmentation failure during a careful visual inspection. The GC analysis algorithm was used to automatically measure the macular GCA thickness. Software version 6.0 of the GCA algorithm was used to process the data in this study, as it was able to detect and measure the thickness of the macular ganglion cell-inner plexiform layer within a 14.13 mm2 elliptical annulus area centered on the fovea. The protocol carries out 200 horizontal B-scans, which are comprised of 200 A-scans per B-scan that are performed 1024 times within a cube measuring 6 × 6 × 2 mm. These scans were designed to allow analysis of the retinal topography. 8,9 The GCA algorithm is able to process data from either of the three-dimensional (3D) volume scans performed by the Cirrus HD-OCT. Both of these scan patterns cover the same physical field of view, namely an area that is 6 × 6 × 2 mm. However, the dimensionality of the image data is either 512 × 128 × 1024 or 200 × 200 × 1024. The input image data are initially segmented using the existing Cirrus inner limiting membrane (ILM) and RPE segmentation algorithms in order to create a region of interest that lies within the intraretinal layers. 9,10 The algorithm identifies the RNFL layer, the GCA layer (an area that ranges from the outer boundary of the RNFL to the outer boundary of the IPL, and that includes both the RGC layer and the IPL), and the outer retinal layer. The segmentation procedure operates in three dimensions and uses a graph-based algorithm to identify each layer. A detailed description of how the algorithm operates has been previously presented in detail. 9,10 There are nine thicknesses measured within the annular area that is centered on the fovea. These include the average, superior average, inferior average, and six sectoral (superotemporal, superior, superonasal, inferotemporal, inferior, inferonasal) values of the respective layers. 
Microperimetry Examinations
In all subjects, MAIA was used to measure the retinal sensitivity. MAIA was performed in a dim room without any dilation of the pupil. The following parameters were used in the current study: a 68-stimuli grid covering the central 10° of the retina, a 4 to 2 threshold strategy, a fixation target that consisted of a red circle with a 1° diameter, stimulus size Goldmann III, background luminance set at 4 apostilb (asb), maximum luminance of 1000 asb, and a stimulus dynamic range of 36 dB. Use of the MAIA device made it possible to determine which of the fixation stabilities were stable. Only stable fixation tests were included in the analysis. 
Mapping Structure to Function
For analysis of functional measurements, VF sensitivity was obtained for each subject. According to the criteria described earlier, 8 of 108 eyes that qualified for initial inclusion were excluded. Seven of these eyes had a signal strength less than 6, while one eye showed unstable fixation. Therefore, a total of 100 eyes were included in the final analysis. When comparing the GCA thickness to the local loss in VF sensitivity, it is important that the displacement of the RGCs in the macula be taken into consideration. 13 The average location of the RGCs associated with each MAIA test point was approximated using equations that were derived from the histologic analysis-based work of Drasdo et al. 14 Figure 1 shows the location of the visual field MAIA test points, while Figure 2A shows the location after adjusting for the RGC displacement. Structure-function relationships were determined from each of the six sectors with both VF and OCT in retinal view (Fig. 2B). Since fundus perimetry data are exactly related to the stimulated area, functional measurements of MAIA were correlated with the structural measurements of the OCT in the same hemifield. 
Figure 1. 
 
Detection of macular sensitivity. Right eye fundus image of a 50-year-old patient with primary open-angle glaucoma (POAG). Figure shows microperimetry results with differential light threshold values color-coded from 0 to 36 dB.
Figure 1. 
 
Detection of macular sensitivity. Right eye fundus image of a 50-year-old patient with primary open-angle glaucoma (POAG). Figure shows microperimetry results with differential light threshold values color-coded from 0 to 36 dB.
Figure 2. 
 
Representative example showing the six sectors of the ganglion cell analyzer thickness and the adjustment for retinal ganglion cell displacement. (A) The 10 to 2 VF displaced points corresponding to the RGC locations based on a model derived from histologic analysis. 5 (B) GCA thickness areas were divided into six sectors, with the corresponding VF regions then obtained using MAIA.
Figure 2. 
 
Representative example showing the six sectors of the ganglion cell analyzer thickness and the adjustment for retinal ganglion cell displacement. (A) The 10 to 2 VF displaced points corresponding to the RGC locations based on a model derived from histologic analysis. 5 (B) GCA thickness areas were divided into six sectors, with the corresponding VF regions then obtained using MAIA.
Statistical Analysis
To determine the association between the local VF mean sensitivity and the relative GCA thickness, we based this study on previous work that related the SAP sensitivity to peripapillary RNFL thickness 1517 or RGC + IPL thickness (GCA) in the macula. 8 Briefly, the assumptions for this model were as follows: the measured GCA thickness R consists of two components, the thickness S, which is due to portions of the IPL and RGC layer (GCA) that is affected by glaucoma, and the residual B, which includes portions of the IPL and RGC layer (GCA) not affected by glaucoma. These areas may include glial cells, blood vessels, bipolar cell axons, and amacrine cell projections. Thus, overall R = S + B. As the MAIA field sensitivity changes, the value of S will decrease, while B will remain constant. As the VF sensitivity decreases, the signal portion S of the local GCA thickness R will decrease linearly when the VF sensitivity is expressed in linear units. Thus, R = (S 0B) T + B for T less than or equal to 1.0, where S 0 is the median of the control GCA thickness at a particular eccentricity, T is the relative sensitivity (defined as 100.1D), and D is the VF sensitivity minus the mean value of healthy subjects. T equals 1.0 when there is no loss (0 dB difference from normal) and approaches 0 when there are large losses in the sensitivity. The variable B was calculated for each zone as the median of the GCA data when the local VF sensitivities were less than 20 dB. 
Correlations of the GCA thickness with the corresponding VF mean sensitivity were examined by using Spearman rank order correlations. Differences between the control and glaucoma groups were assessed by an independent Student's t-test and the χ2 test for categorical parameters. All statistical values are presented as the mean ± SD, with P values less than 0.05 considered to be statistically significant. Statistical analyses were performed using SPSS version 19.0 (IBM, New York, NY). Comparisons of the strength structure–function association were evaluated by tests of equality of dependent correlation coefficients. 
Results
A total of 71 glaucoma patients (32 POAG, 37 normal-tension, and 2 exfoliative) and 29 healthy subjects were enrolled in the study. The demographic characteristics are presented in Table 1. Since the healthy control participants were selected based on age- and refractive error-matching, there was no significant difference noted in the mean age between the healthy subjects and glaucoma patients. Based on the standard VF severity grading scale, 18 the grade of the disease in the glaucomatous eyes of the 71 patients ranged from early to moderate, with 29 (41%) classified as early, 24 (34%) classified as moderate, and 18 (25%) classified as severe. 
Table 1. 
 
Clinical Characteristics of the Study Population
Table 1. 
 
Clinical Characteristics of the Study Population
Glaucoma Normal
Age, y 62.5 ± 11.0 64.3 ± 12.2 0.71
Sex (M/F) 40/31 17/12 0.83
Diagnosis
 POAG 32
 NTG 37
 EG  2
Refraction (D) −1.6 ± 2.3  −0.7 ± 1.9   0.10
Table 2 lists the GCA thickness, while Table 3 presents the macular sensitivity. GCA thickness and macular sensitivity were significantly different between the glaucoma and healthy subject groups. 
Table 2. 
 
GCA Thickness for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
Table 2. 
 
GCA Thickness for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
GCA Thickness, μm
Glaucoma Normal
Average 65.1 ± 7.7 79.8 ± 5.2 <0.01
Superior hemifield 67.1 ± 9.2 80.8 ± 5.5 <0.01
Inferior hemifield 63.1 ± 8.0 78.8 ± 5.5 <0.01
Superotemporal 63.9 ± 9.8 79.6 ± 5.1 <0.01
Superior 67.5 ± 9.6 81.0 ± 6.5 <0.01
Superonasal 70.9 ± 10.0 81.7 ± 6.3 <0.01
Inferotemporal 59.6 ± 9.0 80.4 ± 6.1 <0.01
Inferior 62.0 ± 8.4 76.6 ± 5.9 <0.01
Inferonasal 67.7 ± 9.2 79.4 ± 5.7 <0.01
Table 3. 
 
Macular Sensitivity for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
Table 3. 
 
Macular Sensitivity for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
Mean Sensitivity, dB
Glaucoma Normal
Average 21.4 ± 6.3 26.9 ± 1.5 <0.01
Superior hemifield 23.4 ± 6.0 26.9 ± 1.6 <0.01
Inferior hemifield 19.4 ± 8.4 26.9 ± 1.5 <0.01
Superotemporal 21.4 ± 8.3 26.9 ± 1.7 <0.01
Superior 23.6 ± 6.8 26.8 ± 2.0 0.02
Superonasal 25.1 ± 5.6 27.1 ± 1.7 0.07
Inferotemporal 17.5 ± 10.3 27.0 ± 1.7 <0.01
Inferior 16.8 ± 11.1 26.4 ± 1.6 <0.01
Inferonasal 24.2 ± 6.5 27.1 ± 1.8 0.02
Figure 3 shows the structure–function relationship between the GCA thickness and the corresponding VF mean sensitivity with both OCT and VF in retinal view. To check the goodness of fit, we calculated the number of points falling outside the 95% confidence boundary. For the global GCA thickness–VF mean sensitivity, seven eyes fell outside of the 95% confidence boundary. Although the difference in the structure–function relationship was not significant among six sectors, the highest Spearman correlation coefficient was 0.706 in the inferotemporal sector. Strength of the structure–function relationship of each of the corresponding inferior sectors (R = 0.546–0.706) were higher than those of the corresponding superior sectors (R = 0.365–0.601). In addition, the strength of the structure–function relationship of the temporal sector was higher than that of the nasal sector (inferonasal [R = 0.546] versus inferotemporal [R = 0.706] [P = 0.02], superonasal [R = 0.365] versus superotemporal [R = 0.601] [P = 0.002]). 
Figure 3. 
 
Scatters plots showing the association between the Cirrus HD-OCT thickness parameters and the corresponding retinal sensitivity. (A) Average thickness of the GCA versus the macular mean sensitivity. (B) Superior average thickness of the GCA versus the superior macular mean sensitivity. (C) Inferior average thickness of the GCA versus the inferior macular mean sensitivity. (D) Superotemporal thickness of the GCA versus the superotemporal mean sensitivity. (E) Superior thickness of the GCA versus the superior mean sensitivity. (F) Superonasal thickness of the GCA versus the superonasal mean sensitivity. (G) Inferotemporal thickness of the GCA versus the inferotemporal mean sensitivity. (H) Inferior thickness of the GCA versus the inferior mean sensitivity. (I) Inferonasal thickness of the GCA versus the inferonasal mean sensitivity. Spearman correlation coefficients, *P < 0.001.
Figure 3. 
 
Scatters plots showing the association between the Cirrus HD-OCT thickness parameters and the corresponding retinal sensitivity. (A) Average thickness of the GCA versus the macular mean sensitivity. (B) Superior average thickness of the GCA versus the superior macular mean sensitivity. (C) Inferior average thickness of the GCA versus the inferior macular mean sensitivity. (D) Superotemporal thickness of the GCA versus the superotemporal mean sensitivity. (E) Superior thickness of the GCA versus the superior mean sensitivity. (F) Superonasal thickness of the GCA versus the superonasal mean sensitivity. (G) Inferotemporal thickness of the GCA versus the inferotemporal mean sensitivity. (H) Inferior thickness of the GCA versus the inferior mean sensitivity. (I) Inferonasal thickness of the GCA versus the inferonasal mean sensitivity. Spearman correlation coefficients, *P < 0.001.
Discussion
The pathology of glaucoma is characterized by the death of RGCs and their axons. Although there is substantial individual variability, the average retina contains 1.07 million RGCs, with approximately 50% of the RGCs located within 4.5 mm of the fovea. 19,20 It has been demonstrated in humans that the RGC loss is evident around the fovea during the early stages of the disease. 21 Therefore, we selected the central macular VF as the local functional target in the current study and then assessed its structure–function relationship by using the GCA thickness. Although SAP is able to show the functioning of individual retinal locations in the macula, reliable test results can be difficult to obtain because of unstable fixation in some cases. When using an autotracking system, MAIA is able to automatically record the fixation behavior during the test while the autotracking system makes it possible to adjust the stimulus points to predefined retinal positions and perform reliable field testing, even in eyes with unstable fixation. Because of these advantages, this study used MAIA to measure the macular VF sensitivity. 
The current study examined structure–function relationships in smaller regions, which to the best of our knowledge, has not been previously investigated. The determination of which region has a stronger structure–function association has clinical implications, as use of the stronger region could provide better detection and follow up in glaucoma patients who may present with an early stage of macular VF defects. Thus, our current results indicate the importance of studying the relationship patterns in smaller regions. The strength of the structure–function relationship is related to the individual anatomy and its variation in the subject, the stage of glaucoma present in the study sample, the VF scale, and the regression model used. During the previous examinations of the correlations between the VF sensitivity and the early glaucomatous stages, healthy individuals, and the glaucoma suspect eyes, the correlations were shown to be weaker than those observed in moderate-to-severe glaucoma. 22,23 The reason for this is because the range of VF is narrow in healthy and glaucoma suspect eyes. Thus, the strength of a structure–function relationship may be dependent upon both the actual retinal and VF areas in which the association is assessed and the specific imaging device that is used in the study. In addition, histologic studies in human 24,25 and monkey eyes 26 have shown that in the central retina, there are more ganglion cells in the nasal and superior sectors than in the temporal and inferior sectors, respectively. These differences in the distribution of the ganglion cells might affect the strength of the structure–function relationship. 
Raza et al. 8 recently reported finding that the local RGC + IPL thickness (GCA) correlated well with the local sensitivity loss obtained with the 10 to 2 SAP setting in the central 7.2° of the 14 patients with glaucoma and in the 19 healthy subjects. The differences between the current and previous study were as follows: our study showed that the strength of the correlation between the VF mean sensitivity and the GCA thickness varied within the macular region. In addition, our study measured the VF sensitivity with microperimetry in an attempt to improve the spatial localization. We also examined a total of 100 eyes, as it was hoped this larger sample size would result in a greater statistical power. 
In the past, relationships between RNFL losses and VF defects have been studied using different theoretical curves to fit the data. 1517,27,28 Results have shown that a complete loss in sensitivity does not result in a RNFL thickness of zero, but instead, is actually associated with a finite RNFL thickness. In the early stage of glaucoma, the decline in RNFL thickness is rapid, and there is a lag in the visual sensitivity loss. However, as the glaucoma becomes severe, RNFL thicknesses reach a base level beyond which only the visual sensitivity declines. For these reasons, we decided to evaluate the structure–function relationship using the model proposed by Hood et al. 15,16 Our results showed that their linear model fit the structure–function data quite well. 
With regard to potential limitations, we were not able to observe any overall age effect, the number of subjects in this study was relatively small; however, a further study with a larger number of subjects should be able to address this issue. We also did not notice any obvious difference in the structure-function agreement for patients with POAG, normal-tension glaucoma, or exfoliation glaucoma. Additional studies that more closely examine the different types of glaucoma will need to be undertaken. 
In conclusion, although the GCA thickness measured by Cirrus HD-OCT was significantly correlated with the macular retinal sensitivity assessed by MAIA, the strength of the correlation varied from region to region. Combining GCA thickness with macular VF sensitivity may provide a better understanding of the amount of glaucomatous damage that occurs in the macula region. 
Acknowledgments
Disclosure: S. Sato, None; K. Hirooka, None; T. Baba, None; K. Tenkumo, None; E. Nitta, None; F. Shiraga, None 
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Figure 1. 
 
Detection of macular sensitivity. Right eye fundus image of a 50-year-old patient with primary open-angle glaucoma (POAG). Figure shows microperimetry results with differential light threshold values color-coded from 0 to 36 dB.
Figure 1. 
 
Detection of macular sensitivity. Right eye fundus image of a 50-year-old patient with primary open-angle glaucoma (POAG). Figure shows microperimetry results with differential light threshold values color-coded from 0 to 36 dB.
Figure 2. 
 
Representative example showing the six sectors of the ganglion cell analyzer thickness and the adjustment for retinal ganglion cell displacement. (A) The 10 to 2 VF displaced points corresponding to the RGC locations based on a model derived from histologic analysis. 5 (B) GCA thickness areas were divided into six sectors, with the corresponding VF regions then obtained using MAIA.
Figure 2. 
 
Representative example showing the six sectors of the ganglion cell analyzer thickness and the adjustment for retinal ganglion cell displacement. (A) The 10 to 2 VF displaced points corresponding to the RGC locations based on a model derived from histologic analysis. 5 (B) GCA thickness areas were divided into six sectors, with the corresponding VF regions then obtained using MAIA.
Figure 3. 
 
Scatters plots showing the association between the Cirrus HD-OCT thickness parameters and the corresponding retinal sensitivity. (A) Average thickness of the GCA versus the macular mean sensitivity. (B) Superior average thickness of the GCA versus the superior macular mean sensitivity. (C) Inferior average thickness of the GCA versus the inferior macular mean sensitivity. (D) Superotemporal thickness of the GCA versus the superotemporal mean sensitivity. (E) Superior thickness of the GCA versus the superior mean sensitivity. (F) Superonasal thickness of the GCA versus the superonasal mean sensitivity. (G) Inferotemporal thickness of the GCA versus the inferotemporal mean sensitivity. (H) Inferior thickness of the GCA versus the inferior mean sensitivity. (I) Inferonasal thickness of the GCA versus the inferonasal mean sensitivity. Spearman correlation coefficients, *P < 0.001.
Figure 3. 
 
Scatters plots showing the association between the Cirrus HD-OCT thickness parameters and the corresponding retinal sensitivity. (A) Average thickness of the GCA versus the macular mean sensitivity. (B) Superior average thickness of the GCA versus the superior macular mean sensitivity. (C) Inferior average thickness of the GCA versus the inferior macular mean sensitivity. (D) Superotemporal thickness of the GCA versus the superotemporal mean sensitivity. (E) Superior thickness of the GCA versus the superior mean sensitivity. (F) Superonasal thickness of the GCA versus the superonasal mean sensitivity. (G) Inferotemporal thickness of the GCA versus the inferotemporal mean sensitivity. (H) Inferior thickness of the GCA versus the inferior mean sensitivity. (I) Inferonasal thickness of the GCA versus the inferonasal mean sensitivity. Spearman correlation coefficients, *P < 0.001.
Table 1. 
 
Clinical Characteristics of the Study Population
Table 1. 
 
Clinical Characteristics of the Study Population
Glaucoma Normal
Age, y 62.5 ± 11.0 64.3 ± 12.2 0.71
Sex (M/F) 40/31 17/12 0.83
Diagnosis
 POAG 32
 NTG 37
 EG  2
Refraction (D) −1.6 ± 2.3  −0.7 ± 1.9   0.10
Table 2. 
 
GCA Thickness for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
Table 2. 
 
GCA Thickness for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
GCA Thickness, μm
Glaucoma Normal
Average 65.1 ± 7.7 79.8 ± 5.2 <0.01
Superior hemifield 67.1 ± 9.2 80.8 ± 5.5 <0.01
Inferior hemifield 63.1 ± 8.0 78.8 ± 5.5 <0.01
Superotemporal 63.9 ± 9.8 79.6 ± 5.1 <0.01
Superior 67.5 ± 9.6 81.0 ± 6.5 <0.01
Superonasal 70.9 ± 10.0 81.7 ± 6.3 <0.01
Inferotemporal 59.6 ± 9.0 80.4 ± 6.1 <0.01
Inferior 62.0 ± 8.4 76.6 ± 5.9 <0.01
Inferonasal 67.7 ± 9.2 79.4 ± 5.7 <0.01
Table 3. 
 
Macular Sensitivity for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
Table 3. 
 
Macular Sensitivity for the Average, Superior Average, Inferior Average, and in Each of the Six Sectors
Mean Sensitivity, dB
Glaucoma Normal
Average 21.4 ± 6.3 26.9 ± 1.5 <0.01
Superior hemifield 23.4 ± 6.0 26.9 ± 1.6 <0.01
Inferior hemifield 19.4 ± 8.4 26.9 ± 1.5 <0.01
Superotemporal 21.4 ± 8.3 26.9 ± 1.7 <0.01
Superior 23.6 ± 6.8 26.8 ± 2.0 0.02
Superonasal 25.1 ± 5.6 27.1 ± 1.7 0.07
Inferotemporal 17.5 ± 10.3 27.0 ± 1.7 <0.01
Inferior 16.8 ± 11.1 26.4 ± 1.6 <0.01
Inferonasal 24.2 ± 6.5 27.1 ± 1.8 0.02
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