**Purpose**:
We tested the hypothesis that the macular ganglion cell layer (GCL) thickness demonstrates a stronger structure-function (SF) relationship and extends the useful range of macular measurements compared with combined macular inner layer or full thickness.

**Methods**:
Ninety-eight glaucomatous eyes and eight normal eyes with macular spectral domain optical coherence tomography (SD-OCT) volume scans and 10-2 visual fields were enrolled. Inner plexiform layer (IPL), GCL, macular retinal nerve fiber layer (mRNFL), ganglion cell-inner plexiform layer (GCIPL), ganglion cell complex (GCC), and full thickness (FT) measurements were calculated for 8 × 8 arrays of 3° superpixels. Main outcome measures were local structure-function relationships between macular superpixels and corresponding sensitivities on 10-2 fields after adjusting for ganglion cell displacement, dynamic range of measurements, and the change point (total deviation value where macular parameters reached measurement floor).

**Results**:
Median (interquartile range [IQR]) mean deviation was −7.2 (−11.6 to −3.2) dB in glaucoma eyes. Strength of SF relationships was highest for GCIPL, GCL, GCC, and IPL (ρ = 0.635, 0.627, 0.621, and 0.577, respectively; *P* ≤ 0.046 for comparisons against GCIPL). Highest SF correlations coincided with the peak of GCL thickness, where the dynamic range was widest for FT (81.1 μm), followed by GCC (65.7 μm), GCIPL (54.9 μm), GCL (35.2 μm), mRNFL (27.5 μm), and IPL (20.9 μm). Change points were similar for all macular parameters (−7.8 to −8.9 dB).

**Conclusions**:
GCIPL, GCL, and GCC demonstrated comparable SF relationships while FT, GCC, and GCIPL had the widest dynamic range. Measurement of GCL did not extend the range of useful structural measurements. Measuring GCL does not provide any advantage for detection of progression with current SD-OCT technology.

^{1,2}although more research is needed to better understand its limitations and the appropriate circumstances for its application. Some recent investigations have demonstrated the utility and added value of macular SD-OCT imaging for detecting glaucoma, but its role remains less well defined with respect to progression.

^{3–10}

^{3,11,12}These include single layer measurements such as ganglion cell (GCL), inner plexiform (IPL), or retinal nerve fiber layer, combination of inner retinal layers such as the ganglion cell-inner plexiform layer (GCIPL) and the ganglion cell complex (GCC), which includes the combined thickness of the GCIPL and macular RNFL (mRNFL), or the full retinal thickness. The comparative utility of these various thickness parameters for detection of glaucoma progression is unknown. To this aim, the strength of the corresponding structure-function relationships and the comparative dynamic range of these parameters need to be compared. Another issue of interest is the point of change on structure-function plots at which each parameter reaches its measurement floor.

*P*<5% on the pattern deviation plot, both confirmed at least once.

^{13}An eye was considered to have preperimetric glaucoma if the visual field did not meet the criteria for abnormality but the optic nerve was considered glaucomatous on review of the optic disc photographs by one of the authors (KNM). Patients were also required to meet the following criteria: less than 3 diopters (D) of astigmatism and no significant retinal or neurological disease. The normal subjects had a normal eye exam, open angles, normal appearing optic discs, no RNFL wedge defects, and 24-2 SAP visual fields that did not meet the criteria for an abnormal field.

^{14}and as demonstrated in Figure 2. Only the superpixels and the corresponding visual field (VF) test locations within the central 18° of the macula were further analyzed since the thickness values for the inner retinal layers significantly decrease and reach a plateau beyond this eccentricity.

^{15,16}Visual field data from the 10-2 fields were exported as XML files and total deviation values extracted. The central 24 superpixels and the corresponding test locations were divided into three circles or subfields according to eccentricity located at a distance of 3.4, 5.6, and 6.8° from the foveal center for circles 1 through 3, respectively (Fig. 2).

*x*-axis and various macular thickness parameters (in microns) on the

*y*-axis. Nonparametric correlations were estimated (Spearman's ρ) between macular parameters and visual field total deviation values. A bootstrap method was used to compare the Spearman correlation coefficients between various macular parameters and VF data in a pairwise manner.

*a*is the intercept in μm, an estimate of the measurement floor for macular parameters;

*b*is the slope in μm/dB, and

*C*is the threshold sensitivity at the point of change.

*b*) was calculated. The intercept for the flat linear model was considered the measurement floor. To calculate the ceiling of macular measurements, the 90th percentile measurement for each macular parameter in normal eyes was determined. The dynamic range was considered to be the difference between the intercept for the broken stick model and the 90th percentile normal thickness measure for each macular parameter.

^{17}All statistical analyses were performed with statistical software, Stata (version 14.0; StataCorp, College Station, TX, USA).

*P*< 0.001), but had similar axial lengths (median [IQR]: 24.7 [23.9–26.0] versus 24.1 [23.7–24.6] mm;

*P*= 0.236).

*P*values for pairwise comparisons of the correlation coefficients for structure-function relationships between various macular parameters and the corresponding TD values with a bootstrap method for all data (Table 3) and as a function of eccentricity (Table 4). Although the SF relationships for GCIPL were significantly larger than all the other parameters (Table 3,

*P*< 0.046 for all pairwise comparisons), the magnitude of such differences was not clinically relevant. When categorized according to eccentricity, the results remained unchanged for circles 1 and 2, whereas the magnitude of the Spearman's ρ for the IPL decreased for superpixels furthest from the fovea (circle 3). The highest SF correlations coincided with the peak of the GCL thickness on circle 2 (

*ρ*= 0.654, 0.641, 0.669, 0.638, 0.549 for IPL, GCL, GCIPL, GCC, and FT, respectively) except for mRNFL (0.282). For the latter, the highest correlation was observed closer to the fovea on circle 1 (

*ρ*= 0.458). Scatter plots showing local SF relationships between various macular parameters and the TD values for the corresponding VF locations confirmed the simple linear model as proposed by Hood and Kardon.

^{18}Figure 3 demonstrates local structure-function scatter plots for the six macular outcomes of interest versus VF total deviation values for all data regardless of eccentricity. It can be observed that macular measurements display a region of linear relationship with TD values beyond which they reach a floor. These scatter plots are similar in shape to those reported for sectoral RNFL thickness against the corresponding average sectoral MD values as reported by Hood and Kardon.

^{18}

*y*'s or

*ŷ*'s, superpixel values here), as predicted by the model versus TD values at corresponding individual test locations, based on the broken stick model, for four inner retinal parameters (IPL, GCL, GCIPL, and GCC) and separately for full thickness measurements against visual field TD values for circle 2 (5.6° eccentricity). The full thickness plot is shown separately given its much higher thickness values. Results for all data regardless of eccentricity and for circles 1 and 3 (3.4° and 6.8° eccentricities) were similar. It can be observed that: (1) the GCL had a higher dynamic range and lower floor compared to IPL; this finding was consistent across all eccentricities (data not shown); (2) the dynamic range of measurements increased as the thickness of the (combined) layers of interest increased (i.e., it was highest for the FT, GCC and GCIPL in that order); (3) the change point where the structural outcomes reached their measurement floor was very consistent among all parameters as follows: −7.8 dB for IPL, −8.4 dB for GCL, −8.9 dB for mRNFL, −8.0 dB for GCIPL, −8.3 dB for GCC, and −7.9 dB for full thickness measurements regardless of eccentricity; and (4) the largest dynamic range measurements belonged to circle 2 superpixels; the measurements for that eccentricity were as follows: FT (81.1 μm), followed by the GCC (65.7 μm), GCIPL (54.9 μm), GCL (35.2 μm), mRNFL (27.5 μm), and IPL (20.9 μm) (Fig. 5).

*y*-axis (superpixel thickness) to 0 below the change point. We formally tested this hypothesis by performing a linear regression analysis for each of the macular parameters against TD values after excluding superpixels with corresponding TD values greater than the change point for each macular parameter. We hypothesized that if the regression coefficient (i.e., the slope) for these equations was >0 μm/dB in a statistically significant manner for any given macular parameter, that particular parameter could be useful for detection of change in more advanced stages of the disease. We found that only the slope for the full macular thickness, GCIPL, and GCL were significantly positive (regression coefficient = 0.383, 0.077, and 0.076 μm/dB;

*P*< 0.001,

*P*= 0.025, and

*P*= 0.001, respectively). However the

*R*

^{2}values for all the models were very low (

*R*

^{2}= 0.03, 0.009, and 0.02). This means that a very small amount of variability in the outcome (superpixel thickness) could be explained by the independent variable (TD values at individual test locations).

^{19}This constitutes half of the retinal ganglion cell population critical to human visual function.

^{15}With the improvements in OCT image quality and more accurate segmentation of these images, individual layers of the macula can be measured.

^{11,12}There is preliminary evidence that macular measurements may be valuable for identifying disease deterioration in glaucoma. Reproducibility of macular SD-OCT measurements has been demonstrated to be very good to excellent.

^{3,20–23}We recently found that intrasession variability of various macular measures was excellent at the level of 3 × 3° superpixels.

^{24}A few studies have explored structure-function relationships between various macular outcome measures and threshold sensitivity in the central 10-2 fields

^{25,26}; these studies have shown correlations with visual fields that are comparable to those of the RNFL. Sung and colleagues

^{7}found that full macular thickness measurements showed statistically significant rates of change in patients deteriorating based on stereoscopic disc photographs or visual fields, as compared to RNFL thickness measurements, in a group of advanced glaucoma eyes (average baseline mean deviation: −14.3 dB). Lee et al.

^{8}found that event analyses based on full macular thickness measures detected a higher percentage of progressing eyes in a group of mostly normal-tension glaucoma eyes.

^{15,16}

^{27}reaching a plateau after a certain point beyond which they hardly changed. The strength of SF relationships was comparable for GCL, GCIPL, and GCC and was lowest for mRNFL and full macular thickness measurements regardless of eccentricity. Interestingly, the IPL thickness demonstrated as strong a correlation with VF data as those of GCL, GCIPL, and GCC closest to the fovea but its correlation diminished with increasing distance from the fovea. Prior clinical and histologic measurements of the IPL and GCL have demonstrated that the IPL layer thickness reaches a peak at the same distance from the fovea as the GCL but then plateaus until it actually exceeds GCL thickness.

^{28,29}This may explain the lower correlation of IPL thickness with VF sensitivity measurements farther from the fovea.

^{17}However, since the macular RGC axonal complex is less affected until the later stages of glaucoma, such measurements effectively extend the utility of structural outcome measures, notwithstanding that the inherent relationship of macular structural parameters with VF sensitivities is similar to RNFL measures. The other interesting finding of our study was that the dynamic range for the GCC or GCIPL was greater than that for the GCL or IPL; the dynamic range for the GCIPL was almost as large as the sum of the dynamic range for the GCL and IPL. We recently found that the intrasession variability of all macular parameters was quite low and did not exceed ±3 μm for all parameters after excluding a small percentage of outliers.

^{24}This could mean that GCIPL or GCC measurements may be more suitable for detecting smaller amounts of change over time compared with GCL thickness. In other words, because of the similar variability for all macular outcomes, the magnitude of a step change required to define a significant worsening event is comparable for all such outcomes; hence due to the larger dynamic range of the GCIPL or GCC thickness measurements, they may detect change sooner. This is despite the fact that no macular parameter extends the utility of such measures beyond 10 dB loss of VF sensitivity, or approximately 1 logarithmic unit. A higher dynamic range for GCIPL or GCC could translate into the possibility of detecting change sooner or detecting many more steps of change before the measurement floor is reached. However, this is based on the assumption that steps of change in GCIPL or GCC could be potentially as small as those for GCL. This is an issue that only longitudinal data can adequately address. We must emphasize, however, that our findings should not be understood as a complete lack of utility of macular parameters once the mean deviation for central 10-2 VF has reached a threshold of approximately −10 dB. Rather, macular damage can be more or less localized in glaucoma and while in some areas of the macula, the RGC/axonal complex may have reached its measurement floor, in other areas adequate thickness may be preserved that could be valuable to detect worsening. This issue needs to be further investigated.

*R*

^{2}= 0.02, 0.009, and 0.03, respectively). One caveat, however, is that the conclusions of this study are based on cross-sectional data and hence, the large interindividual variability of structural measurements could result in a lower performance of these parameters than that of same parameters from truly longitudinal data. Therefore, macular structural measurements, especially FT measures, might be helpful for monitoring disease progression in areas of the macula where most other inner retinal measurements have reached their floor. We found that the measurement's floor level was significantly lower for the FT measurements in circle 3. There is no clear explanation for this finding; however, this may be related to changes in the outer retinal layer thickness since this finding was not observed with any of the inner retinal parameters. This will need to be explored in longitudinal studies.

**A. Miraftabi**, None;

**N. Amini**, None;

**E. Morales**, None;

**S. Henry**, None;

**F. Yu**, None;

**A. Afifi**, None;

**A.L. Coleman**, None;

**J. Caprioli**, Allergan (C);

**K. Nouri-Mahdavi**, Allergan (C), Heidelberg Engineering (R)

*Curr Opin Ophthalmol*. 2014; 25: 104–111.

*Br J Ophthalmol*. 2014; 98 (suppl 2): ii15–19.

*Ophthalmology*. 2009; 116: 2305–2314.

*Invest Ophthalmol Vis Sci*. 2011; 52: 8323–8329.

*Am J Ophthalmol*. 2013; 156: 1297–1307.

*Invest Ophthalmol Vis Sci*. 2012; 53: 5044–5051.

*Ophthalmology*. 2012; 119: 308–313.

*Invest Ophthalmol Vis Sci*. 2013; 54: 1941–1949.

*Ophthalmology*. 2013; 120: 1388–1395.

*Invest Ophthalmol Vis Sci*. 2015; 56: 5477–5484.

*Invest Ophthalmol Vis Sci*. 2011; 52: 8769–8779.

*Invest Ophthalmol Vis Sci*. 2015; 56: 2254–2268.

*Am J Ophthalmol*. 2002; 134: 177–185.

*Vision Res*. 2007; 47: 2901–2911.

*J Comp Neurol*. 1990; 300: 5–25.

*Invest Ophthalmol Vis Sci*. 2011; 52: 7872–7879.

*Invest Ophthalmol Vis Sci*. 2015; 56: 6344–6351.

*Prog Retin Eye Res*. 2007; 26: 688–710.

*Invest Ophthalmol Vis Sci*. 2015; 56: 259–271.

*Ophthalmology*. 2010; 117: 738–746.

*Invest Ophthalmol Vis Sci*. 2005; 46: 2012–2017.

*Invest Ophthalmol Vis Sci*. 2014; 55: 6536–6546.

*Invest Ophthalmol Vis Sci*. 2015; 56: 4857–4764.

*Trans Vis Sci Tech*. 2016; 5 (4): 5.

*Invest Ophthalmol Vis Sci*. 2014; 55: 5269–5277.

*Invest Ophthalmol Vis Sci*. 2015; 56: 8063–8068.

*Invest Ophthalmol Vis Sci*. 2007; 48: 3662–3668.

*Invest Ophthalmol Vis Sci*. 2011; 52: 3943–3954.

*Eye (Lond)*. 2012; 26: 1188–1193.