February 2016
Volume 57, Issue 2
Open Access
Glaucoma  |   February 2016
Structure–Function Relationship in Glaucoma Patients With Parafoveal Versus Peripheral Nasal Scotoma
Author Affiliations & Notes
  • Kyoung In Jung
    Department of Ophthalmology and Visual Science Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Korea
  • Min Ku Kang
    Department of Ophthalmology and Visual Science Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Korea
  • Jin A. Choi
    St. Vincent's Hospital, Department of Ophthalmology, College of Medicine, Catholic University of Korea, Seoul, Korea
  • Hye-Young Shin
    Uijeongbu St. Mary's Hospital, Department of Ophthalmology, College of Medicine, Catholic University of Korea, Seoul, Korea
  • Chan Kee Park
    Department of Ophthalmology and Visual Science Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Korea
  • Correspondence: Chan Kee Park, Department of Ophthalmology and Visual Science, Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, 505 Banpo-dong, Seocho-ku, Seoul 137-701, Korea; ckpark@catholic.ac.kr
Investigative Ophthalmology & Visual Science February 2016, Vol.57, 420-428. doi:10.1167/iovs.15-18256
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      Kyoung In Jung, Min Ku Kang, Jin A. Choi, Hye-Young Shin, Chan Kee Park; Structure–Function Relationship in Glaucoma Patients With Parafoveal Versus Peripheral Nasal Scotoma. Invest. Ophthalmol. Vis. Sci. 2016;57(2):420-428. doi: 10.1167/iovs.15-18256.

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

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Abstract

Purpose: We evaluated whether the structure–function relationship in glaucoma patients with parafoveal scotoma or peripheral scotoma differs with the use of frequency doubling technology (FDT) or short-wavelength automated perimetry (SWAP) compared to standard automated perimetry (SAP).

Methods: Glaucoma patients with isolated parafoveal scotoma (PFS) within the central 10° of fixation in 1 hemifield and those with an isolated peripheral nasal step (PNS) within the nasal periphery outside 10° of fixation in one hemifield were studied. Peripapillary retinal nerve fiber layer (RNFL) thickness was measured using spectral-domain optical coherence tomography. The topographic relationships between structure and function were investigated.

Results: In the PNS group, superotemporal (r2 = 0.300, P = 0.001) and inferotemporal (r2 = 0.302, P = 0.001) RNFL thickness showed significant correlations with the corresponding visual field (VF) sensitivity using linear regression model in SAP. In the PFS group, temporal RNFL thickness was not correlated with nasal mean sensitivity (MS) on SAP (r2 = 0.103, P = 0.065). Using FDT, however, the temporal RNFL thickness was correlated with nasal MS in the PFS group (r2 = 0.277, P = 0.001). Using SWAP, the temporal RNFL thickness was not significantly associated with regional VF sensitivity in the PFS group (r2 = 0.052, P = 0.192).

Conclusions: In glaucoma with peripheral scotoma, the RNFL thickness was associated significantly with the corresponding VF loss in SAP, FDT, and SWAP. In eyes with PFS, however, the topographic structure–function relationships were not distinct with SAP or SWAP. Frequency doubling technology performed well in terms of structure–function correlation in glaucoma with PFS.

Structural damage is thought commonly to precede functional loss in glaucoma.1 Quigley et al.2,3 and Anderson4 suggested that many retinal ganglion cells (RGCs) could be lost before conventional visual field (VF) tests detect a defect. That is, standard automated perimetry (SAP) may detect the glaucoma only after the death of a large number of RGCs, even though SAP still is the gold standard for the functional analysis of glaucoma.57 
Several “unconventional” perimetry methods have been evaluated in many studies, which demonstrated their ability to detect the early glaucoma; for example, short-wavelength automated perimetry (SWAP) and frequency doubling technology perimetry (FDT).5 
Numerous studies have reported that the FDT shows good sensitivity and specificity for detecting glaucoma.68 Frequency doubling technology perimetry may detect the development of VF defects earlier and performs as well as, if not better than, SAP for detecting glaucomatous VF defects.915 The introduction of the second generation of FDT, Matrix FDT perimetry, enhanced the spatial resolution by using a 24-2 strategy similar to SAP.15 Test–retest variability of VF by SAP is greater within and near glaucomatous VF defects than to regions with normal sensitivity.1618 Increased variability with reductions in sensitivity is not present for frequency-doubling perimetry.1823 
Studies indicate that SWAP testing found early glaucomatous damage and that the test may indicate significant change in visual function before it is apparent on standard white-on-white VFs, although its weakness is greater long-term fluctuation and more learning effect artifact compared to SAP.5,2428 A new generation of SWAP techniques uses more efficient strategies, the Swedish interactive threshold algorithm (SITA), to reduce testing time. The SITA SWAP testing shows higher sensitivities than full-threshold SWAP dose, although there are controversies about that.2931 
Mean sensitivity (MS) of SAP is highest centrally and gradually decreases toward the periphery.32 Landers et al.32 reported that the topography of the FDT field is flatter than SAP fields, and that of the SWAP fields was steeper than SAP. Therefore, the structure–function relationship in glaucoma patients with parafoveal scotoma or peripheral scotoma may differ with the use of unconventional VF tests compared to SAP. 
A paracentral scotoma is important because central visual disturbance may put patients at greater risk of losing visual acuity, leading to lower driving performance.3335 Given the fact that central vision is clinically important, an accurate assessment of visual function in macular region is critical. In this study, we investigated whether the structure–function relationships in glaucoma patients with initial paracentral scotoma and initial peripheral scotoma differ among three types of perimetry; that is, SAP, FDT, and SWAP. Comparison of these types of perimetry in two distinct patterns of scotoma may be helpful in clarifying the structure–function relationship and appropriate clinical application of VF tests in glaucoma, especially with paracentral scotoma. 
Methods
This investigation was approved by the Institutional Review Board of the Catholic University of Korea, Seoul, Korea, and followed the tenets of the Declaration of Helsinki. Patients with glaucoma that met the inclusion criteria were consecutively included from patients examined for glaucoma at the glaucoma clinic of Seoul St. Mary's Hospital between March 2013 and December 2013. 
Inclusion criteria were best-corrected visual acuity of 20/40 or better, spherical equivalent within ±7 spherical diopters (D) and ±3 D cylinder. The inclusion criteria were eyes with a normal open angle, and the presence of a glaucomatous optic disc, such as diffuse or focal rim thinning, notching, optic disc hemorrhage, retinal nerve fiber layer (RNFL) defect with a corresponding VF defect meet our criteria for parafoveal scotoma (PFS) or peripheral nasal step (PNS). Patients with uveitis or diseases that may affect the peripapillary or macular area, or medication that may influence visual acuity were excluded. When both eyes met the inclusion criteria, one eye per subject was randomly selected for the study. 
All patients had performed complete ophthalmic examinations, including slit-lamp biomicroscopy, Goldmann applanation tonometry, gonioscopy, axial length measurement, central corneal thickness measurement, and dilated fundus biomicroscopy. All participants underwent stereoscopic optic disc photography. 
Optical Coherence Tomography
Using Cirrus spectral-domain optical coherence tomography (SD-OCT) version 6.0 (Carl Zeiss Meditec, Inc., Dublin, CA, USA), RNFL thickness was determined using optic Disc Cube 200 × 200 scan mode. The Cirrus SD-OCT automatically detects the center of the disc and then draws a circumpapillary circle (radius, 1.73 mm) from the cube data set for RNFL thickness analysis. Poor-quality images with a signal strength less than 6, misalignment, or overt decentration of the measurement circle location, were discarded. 
Average (360° measure), superonasal (91°–135°), nasal (136°–225°), inferonasal (226°–270°), inferotemporal (271°–315°), temporal (316°–45°), and superotemporal (46°–90°) RNFL thickness was used in the current study. Retinal nerve fiber layer thickness of each sector was estimated by integrating the clock hour RNFL thickness from the Cirrus OCT.36 We used these sectors in accordance with the structure–function correspondence map suggested by Garway-Heath et al.37 (Fig. 1). 
Figure 1
 
(A) Pattern deviation plot divided into two subfields of the Humphrey VF. The parafoveal scotoma group included abnormal points within 12 points of a central 10° radius (dashed line). The peripheral nasal step group had abnormal points within 12 nasal peripheral points (dotted line) in one hemifield. (B) Structure–function correspondence map according to Garway-Heath et al.18 (B-1) Visual field sectors (B-2) and peripapillary RNFL thickness. SN, superonasal; N, nasal: IN, inferonasal; IT, inferotemporal; T, temporal; ST, superotemporal.
Figure 1
 
(A) Pattern deviation plot divided into two subfields of the Humphrey VF. The parafoveal scotoma group included abnormal points within 12 points of a central 10° radius (dashed line). The peripheral nasal step group had abnormal points within 12 nasal peripheral points (dotted line) in one hemifield. (B) Structure–function correspondence map according to Garway-Heath et al.18 (B-1) Visual field sectors (B-2) and peripapillary RNFL thickness. SN, superonasal; N, nasal: IN, inferonasal; IT, inferotemporal; T, temporal; ST, superotemporal.
VF Testing
All participants performed SAP using 24-2, the SITA standard program with a Humphrey field analyzer (Carl Zeiss Meditec, Inc.). Goldmann size III targets with a diameter of 0.43° was presented for 200 ms. Frequency doubling technology perimetry was performed using the 24-2 strategy with 5° stimuli and a spatial frequency of 0.5 cycles/deg, with temporal frequency of 18 Hz with the FDT Humphrey Matrix (Carl Zeiss Meditec, Inc.). Short-wavelength automated perimetry was examined with the 24-2 SITA program of the Humphrey field analyzer. Each of the blue Goldmann size V targets was displayed on a 100 cd/m2 yellow background. 
In all types of VF testing, the mean deviation (MD) and pattern standard deviation (PSD) were evaluated. On the pattern deviation plot, the percentages of significantly depressed VF points at P < 0.05 and P < 0.01 were evaluated using SAP, FDT, and SWAP. Not included in the comparison of VF sensitivity were the one central point that was examined only by the FDT but not by SAP or SWAP, and two points just above and below the blind spot. A total of 52 VF points remained for the analysis. In SAP and SWAP, VF sensitivity was evaluated using the dB [10  ×  log(1/Lambert)] scale in 52 points. In FDT matrix perimetry, sensitivities are expressed as the dB [20  ×  log(1/Michelson contrast)].38,39 Global and sectoral MS were evaluated on threshold printout in VF tests. Global MS is calculated as the mean of VF sensitivities in 52 points and sectoral MS as those in the sectors according to the structure–function correspondence map suggested by Garway-Heath et al.37 (Fig. 1). A reliable test was defined as <15% fixation losses, false-positives, or false-negatives. Most patients had no prior experience of performing VF test. 
VF Criteria for PFS and PNS
The PFS and the PNS group were determined by one glaucoma specialist (KIJ) based on pattern deviation probability plots in SITA 24-2 test. A PFS included isolated glaucomatous VF defect within 12 points of a central 10° radius in 1 hemifield (Fig. 1). An isolated glaucomatous VF defect within the nasal periphery outside 10° of fixation in one hemifield is indicated as a PNS. A glaucomatous VF defect was defined as a cluster of three or more points with a P value of <5%, one of which had a P value of <1% on the pattern deviation plot. 
Data from subjects with VF defects in the central 10° and peripheral nasal fields, with VF defects other than the central or nasal periphery, or with scotoma in the superior and inferior hemifields, were excluded from analysis. 
Statistical Analysis
SPSS software (ver. 17.0; SPSS, Inc., Chicago, IL, USA) was used for statistical analyses. 
Differences between the PFS and PNS groups were analyzed by Student's t-test for continuous parameters and the χ2 test for categorical parameters. Differences between the different VF tests were evaluated by a paired t-test. The relationships between the RNFL thickness and VF sensitivity were evaluated by linear (y = ax + b) and nonlinear (second-order polynomial [y = ax2 + bx + c] and logarithmic [y = alog(x) + b]) regression analyses. The goodness-of-fit of regression models was reported as the coefficient of determination, R2. In all analyses, P < 0.05 was taken to indicate statistical significance. In the calculation of univariate correlations, the correction was not performed for multiple comparisons because this study was an explorative trial and to minimize the risk of type II errors. 
Results
Data from 34 patients with PFS and 33 with PNS were analyzed after exclusion of 1 patient with uveitis and 2 with unreliable VF tests. No significant differences in age, sex, spherical equivalent, and axial length were observed between the PFS and PNS groups (P = 0.131, 0.224, 0.192, 0.147, respectively; Table 1). Average RNFL thickness was not significantly different between the two groups (P = 0.573). Both groups had similar MD and PSD as evaluated by SAP (P = 0.331 and P = 0.325, respectively; Table 1). 
Table 1
 
Characteristics of Patients With PFS and PNS
Table 1
 
Characteristics of Patients With PFS and PNS
Comparisons Among SAP, FDT, and SWAP in the PFS and PNS Groups
When the MD was considered, FDT (−7.31  ±  3.88 dB) gave a larger defect than SAP (−2.38 ± 1.38 dB) or SWAP (−5.41  ±  3.06 dB) in the PFS group (P = 0.043; Table 2). Pattern standard deviation in FDT was significantly larger than SAP or SWAP in the PNS and PFS groups (all P < 0.05). 
Table 2
 
Mean Deviation and PSD of FDT and SWAP in PFS and PNS Groups
Table 2
 
Mean Deviation and PSD of FDT and SWAP in PFS and PNS Groups
The mean percentage of the total abnormal points in FDT was significantly greater than those in SAP and SWAP, for 5% and 1% in the PNS group (all P < 0.001; Fig. 2). Also in the PFS group, the mean percentage of the total abnormal points in FDT was greater than those in SAP and SWAP, for 5% (P = 0.005 and P < 0.001, respectively) and 1% (both P < 0.001). The mean percentage of the total abnormal points for 5 % and 1% was lesser in the PFS group than the PNS group in all VF tests (all P < 0.05). 
Figure 2
 
The percentage of total abnormal points among the total VF points significantly depressed <5% and <1% in the pattern deviation plot. The mean percentage of abnormal points in FDT was significantly greater than that in SAP and SWAP, for 5% and 1% in the PNS group (all P < 0.001). In the PFS group, the mean percentage of total abnormal points in FDT was greater than the mean percentages of abnormal points in SAP and SWAP, for 5% (P = 0.005, P < 0.001, respectively) and 1% (both P < 0.001).
Figure 2
 
The percentage of total abnormal points among the total VF points significantly depressed <5% and <1% in the pattern deviation plot. The mean percentage of abnormal points in FDT was significantly greater than that in SAP and SWAP, for 5% and 1% in the PNS group (all P < 0.001). In the PFS group, the mean percentage of total abnormal points in FDT was greater than the mean percentages of abnormal points in SAP and SWAP, for 5% (P = 0.005, P < 0.001, respectively) and 1% (both P < 0.001).
Overall Structure–Function Relationships
In the PNS group, MD and PSD in the SAP showed significant correlations with average RNFL thickness in linear regression analyses (r2 = 0.215, P = 0.007; r2 = 0.167, P = 0.018). With regard to FDT, PSD was correlated with average RNFL thickness (r2 = 0.137, P = 0.034) in the PNS group. In the PFS group, however, neither MD nor PSD on the SAP showed correlations with the average RNFL thickness (r2 = 0.019, P = 0.434 and r2 = 0.028, P = 0.346, respectively). In the FDT, MD but not PSD was significantly correlated with the average RNFL thickness in the PFS group (r2 = 0.171, P = 0.015 and r2 = 0.001, P = 0.855, respectively). Neither MD nor PSD measured by SWAP showed a significant correlation with the average RNFL thickness in either the PNS or PFS group. 
In the total patient population, linear regression analyses showed a significant relationship between the average RNFL thickness and global MS (dB) in SAP and FDT (r2 = 0.112, P = 0.006 and r2 = 0.142, P = 0.002, respectively), but not in SWAP (r = 0.043, P = 0.094). The similar results were observed in nonlinear regression analyses. In the PNS group, there was a significant relationship between the average RNFL thickness and the global MS in SAP (linear, r2 = 0.137, P = 0.034; logarithmic, r2 = 0.131, P = 0.038; Table 3; Fig. 3). In the PFS group, however, no significant correlation was observed between the average RNFL thickness and global MS in SAP (linear and nonlinear regression analyses, all P > 0.05). With regard to FDT, the relationship between the average RNFL thickness and overall MS was significant in the PFS group (linear, r2 = 0.239, P = 0.003; second-order polynomial, r2 = 0.240, P = 0.014; logarithmic, r2 = 0.239, P = 0.003). There was no significant correlation between RNFL thickness and global MS for SWAP in all regression analyses (P > 0.05). 
Table 3
 
Structure–Function Relationship Between Global Mean Sensitivity of VF and Average RNFL Thickness
Table 3
 
Structure–Function Relationship Between Global Mean Sensitivity of VF and Average RNFL Thickness
Figure 3
 
Scatterplots showing the relationships between the global MS (dB) of the VF and average RNFL thickness in patients with the PNS (A, C) and PFS (B, D). Global MS was measured by SAP (A, B) and FDT (C, D). *Regression analyses with P < 0.05.
Figure 3
 
Scatterplots showing the relationships between the global MS (dB) of the VF and average RNFL thickness in patients with the PNS (A, C) and PFS (B, D). Global MS was measured by SAP (A, B) and FDT (C, D). *Regression analyses with P < 0.05.
Topographic Structure–Function Relationships
Table 4 shows the topographic structure–function relationships between RNFL thickness and SAP or FDT, and SWAP parameters in six VF sectors. In the PNS group, superotemporal (r2 = 0.300, P = 0.001) and inferotemporal (r2 = 0.302, P = 0.001; Fig. 4) RNFL thicknesses showed a linear relationship with the corresponding VF sensitivities in SAP. Significant correlations (r2)  between superotemporal and inferotemporal RNFL thicknesses with regional VF sensitivity were found for FDT and SWAP. 
Table 4
 
Structure–Function Relationship Between Regional VF Sensitivity Measured With SAP or FDT or SWAP and the Corresponding Peripapillary RNFL Thickness
Table 4
 
Structure–Function Relationship Between Regional VF Sensitivity Measured With SAP or FDT or SWAP and the Corresponding Peripapillary RNFL Thickness
Figure 4
 
Structure–function relationship between sectoral VF sensitivity (dB) and the corresponding RNFL thickness in patients with the PNS (A, B, D, E) and PFS (C, F). *Regression analyses with P < 0.05.
Figure 4
 
Structure–function relationship between sectoral VF sensitivity (dB) and the corresponding RNFL thickness in patients with the PNS (A, B, D, E) and PFS (C, F). *Regression analyses with P < 0.05.
In the PFS group, however, the temporal RNFL thickness of the PFS group was not significantly correlated with the corresponding MS in SAP (r2 = 0.103, P = 0.065). With regard to FDT perimetry, the temporal sector showed a linear relationship with the corresponding VF sensitivity (r2 = 0.277, P = 0.001). In SWAP, the temporal RNFL thickness was not significantly associated with regional VF sensitivity (r2 = 0.052, P = 0.192). Nonlinear regression analyses (second-polynomial and logarithmic regression) showed a similar structure–function relationship to that in the linear regression analyses. 
Discussion
We demonstrated that global and sectoral structure–function relationships were comparable among SAP, FDT, and SWAP in glaucoma patients with peripheral scotoma. In glaucoma with PFS, however, the topographic structure–function relationship was poor in SAP or SWAP. The structure–function relationship was favorable with FDT in patients with PFS. 
In glaucoma patients with peripheral scotoma, the overall structure–function relationship was similar between SAP and FDT in this study corresponding to the study of Pinto et al.39 in which correlations between RNFL thickness and MS measured in dB were similar for SAP and the FDT. 
In the PFS group, no significant correlation was observed between the average RNFL thickness and overall MS in SAP (linear and nonlinear regression analyses, all P > 0.05). In addition, the temporal RNFL thickness of the PFS group showed no significant correlation with the corresponding MS in SAP (linear and nonlinear regression analyses, all P > 0.05). Poor correlations were found previously in the temporal sector between RNFL thickness measured using Spectralis OCT and the VF sensitivity measured using SAP in the corresponding area.39 In one study investigating the structure–function relationship using scanning laser polarimetry and SAP in glaucoma patients, the strongest correlation was shown in the superotemporal sector, followed by inferotemporal sectors, while the temporal sector showed no statistically significant results.40 In another study evaluating structure–function relationships using SD-OCT, weak correlations were detected between temporal RNFL thickness and the corresponding VF areas.41 Discrepancies were found among studies evaluating the structure–function relationships in the temporal sector. We assumed that the use of different imaging devices or proportion of PFS patients may affect the structure–function relationship in the temporal sector. 
In glaucoma with PFS, FDT performed well in the overall and temporal sector. These findings corresponded to those of Pinto et al.,39 who reported that temporal RNFL thickness was significantly related to the corresponding VF sensitivity measured using FDT, but not with that using SAP. In another study, temporal RNFL thickness measured by Heidelberg retina tomography (HRT) had a weak correlation with MS in the corresponding VF area in FDT and SAP.42 This was inconsistent with our findings and may be explained by differences in imaging device and their study population, including patients in the early to advanced stages of glaucoma or different proportion of PFS patients. The strength of the current study is that we observed the structure–function relationship between MS in parafoveal VF area and temporal RNFL sector especially in patients with initial PFS. 
The ganglion cell layer is approximately four to six layers thick in the parafoveal region and thins to approximately two cells thick in the peripheral retina.43 Approximately 50% of the RGCs are placed within 4.5 mm (16°) of the fovea, an area that comprises only 7.3% of the total retina with a peak ganglion density approximately 1 mm from the foveal center.43 Only four points of the 24-2 VF test fall within the central 8°, the region containing more than 30% of the RGCs.43,44 Therefore, early RGC loss often occurs in the central macular region, even in patients with VFs classified as normal.45 By using 24-2 SAP alone, clinicians can miss parafoveal changes occurring before peripheral defects are present.44 A growing body of evidence suggests that 10-2 VF is more sensitive than 24-2 VF for detecting subtle changes in glaucomatous VF defects within the central 10° because more closely spaced test points are used in 10-2 VF.44,46 However, 10-2 VF has limitations because it cannot test VF defects outside the central 10°. Thus, more sensitive 24-2 VF tests may be needed to detect paracentral VF defects. We assume that FDT using 24-2 strategy may be helpful not to miss paracentral VF defects. 
The favorable performance of FDT in glaucoma patients with PFS with regard to structure–function relationship may be explained by the topography of FDT perimetry. The topography of the FDT fields was considerably flatter than SAP or SWAP fields.32 In FDT, maintaining VF sensitivities with eccentricity may have a role in presenting the constant structure–function relationship in glaucoma patients with PFS and PNS. There are three other speculations for different structure–function relationship between SAP and FDT. First, SAP with a stimulus of 0.43° may skip a considerable retinal area because test points are spaced 6° apart. FDT with a target of 5° covers a larger area, and is less likely to leave retina untested. Second, Swanson et al.47 found that sensitivity was higher for the frequency-doubling stimulus than for the size III SAP stimulus for magnocellular cells and parvocellular cells. Higher sensitivity may lead to a good structure–function relationship in FDT. Third, receptive field radii of RGCs become smaller as the degree of eccentricity from fixation decreases.48 Therefore, VF testing may skip more RGCs in the paracentral retina composed of RGCs with a smaller receptive field. Frequency doubling technology with the larger target covers the greater retinal area with higher sensitivity than SAP. Therefore, the strength of FDT could be maximized in the paracentral retina. The further studies are required to investigate the exact underlying mechanism explaining the favorable performance of FDT in glaucoma patients with PFS with regard to structure–function relationship. 
Short-wavelength automated perimetry is one of the most common VF testing technologies used in clinical practice, along with SAP and FDT perimetry.15 Yamagishi et al.49 reported that in 14 patients having open-angle glaucoma with focal optic disc damage, structural damage evaluated with HRT was topographically related to visual loss on blue–yellow perimetry. Other studies indicated relatively good associations between RNFL defects and SWAP abnormalities.5,5052 However, the poorer relationship between RNFL thickness and SWAP sensitivity, compared to SAP sensitivity, was observed in some studies.52,53 We found that SWAP performed relatively well in glaucoma with peripheral scotoma, whereas it did not in that with paracentral scotoma. Our findings were corresponding to the previous study that the structure–function relationship between temporal RNFL thickness and the paracentral VF defects were not significant, although overall RNFL thinning was relatively well correlated with SWAP damage.52 The topography of SWAP is steeper than corresponding SAP, with VF sensitivity decreasing more rapidly with increasing eccentricity.32 In SWAP, higher range of VF sensitivities within the tested fields may explain the difference in the structure–function relationship between glaucoma patients with paracentral and peripheral scotoma. 
High reliability is one of important elements of good visual function test for glaucoma.54 Test–retest variability was lower with FDT compared to SAP using size III stimuli.1823 These variability properties of FDT could result from increased stimulus size or decreased stimulus range.18 Test–retest variability of VF by SAP is greater within and near glaucomatous VF defects than to regions with normal sensitivity.1618 Increased variability with reductions in sensitivity is not present for frequency-doubling perimetry.1823 Good reproducibility for FDT may also have a role in enhancement of structure–function relationships in glaucoma with PFS.42,54 Short-wavelength automated perimetry had a relatively high degree of variability than that for white-on-white perimetry, such as SAP.55,56 Less reproducibility of SWAP may be a factor for weak structure–function relationship in glaucoma. 
In the PFS group, there were significant correlations between superotemporal or inferotemporal RNFL thickness with regional VF sensitivity for SAP, FDT, and SWAP. Some points in the superotemporal or inferotemporal sector were within 10° in the VF in the structure–function correspondence map (Fig. 1). Parafoveal scotoma may include a part of glaucomatous damage in superotemporal or inferotemporal sector. In addition, glaucomatous damage occurs preferentially in the superotemporal or inferotemporal sectors of the optic nerve head.42,5759 That can be one of reasons for significant correlations in superotemporal or inferotemporal sector in glaucoma patients with PFS. Mansoori et al.60 reported that RNFL thickness measurements for temporal quadrants showed higher variability than superior and inferior quadrants in normal and glaucomatous eyes. Higher variability for temporal RNFL thickness measurements using SD-OCT may contribute to poor structure–function relationship in the temporal sector compared to the superotemporal or inferotemporal sector in patients with PFS. 
There are some limitations in the current study. One of them is the relatively small sample size. As far as we know, however, this is the first study to investigate the structure–function relationships with three types of perimetry in glaucoma patients with paracentral and peripheral scotoma. Second, the calculation of stimulus contrast for each perimetry is different. Stimulus contrast was expressed as Weber contrast (ΔL/L) in SAP or SWAP and as Michelson contrast (LmaxLmin/Lmax + Lmin) in Matrix FDT perimetry.15 Nevertheless, the comparison between different VF types with currently available techniques may be clinically significant. Third, the structure–function correspondence map suggested by Garway-Heath et al.37 was used in this study. This map relates VF tests location to regions of the optic disc. Corresponding sectors of the optic disc to VF test points may be changed if a different structure–function model is used. Application of the structure–function map using such as ganglion cell–inner plexiform layer thickness also may lead to different results. Further studies using different structure–function models in glaucoma patients with paracentral scotoma may be helpful. 
Because of the clinical significance of central visual disturbance, an accurate assessment of visual function in macular region is important.3335 In glaucoma patients with paracentral scotoma, favorable performance of FDT was found with regard to the structure–function relationship, even though good topographic correlations were found in glaucoma with peripheral scotoma using SAP, FDT, or SWAP. Therefore, FDT may be valuable to gain a better understanding of the structure–function relationships, and have a role as an additional tool for evaluation of visual function in glaucoma with paracentral scotoma. Further investigation of progression using FDT may be helpful in cases of glaucoma with PFS. 
Acknowledgments
Supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2014R1A1A2059143). The authors alone are responsible for the content and writing of the paper. 
Disclosure: K.I. Jung, None; M.K. Kang, None; J.A. Choi, None; H.-Y. Shin, None; C.K. Park, None 
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Figure 1
 
(A) Pattern deviation plot divided into two subfields of the Humphrey VF. The parafoveal scotoma group included abnormal points within 12 points of a central 10° radius (dashed line). The peripheral nasal step group had abnormal points within 12 nasal peripheral points (dotted line) in one hemifield. (B) Structure–function correspondence map according to Garway-Heath et al.18 (B-1) Visual field sectors (B-2) and peripapillary RNFL thickness. SN, superonasal; N, nasal: IN, inferonasal; IT, inferotemporal; T, temporal; ST, superotemporal.
Figure 1
 
(A) Pattern deviation plot divided into two subfields of the Humphrey VF. The parafoveal scotoma group included abnormal points within 12 points of a central 10° radius (dashed line). The peripheral nasal step group had abnormal points within 12 nasal peripheral points (dotted line) in one hemifield. (B) Structure–function correspondence map according to Garway-Heath et al.18 (B-1) Visual field sectors (B-2) and peripapillary RNFL thickness. SN, superonasal; N, nasal: IN, inferonasal; IT, inferotemporal; T, temporal; ST, superotemporal.
Figure 2
 
The percentage of total abnormal points among the total VF points significantly depressed <5% and <1% in the pattern deviation plot. The mean percentage of abnormal points in FDT was significantly greater than that in SAP and SWAP, for 5% and 1% in the PNS group (all P < 0.001). In the PFS group, the mean percentage of total abnormal points in FDT was greater than the mean percentages of abnormal points in SAP and SWAP, for 5% (P = 0.005, P < 0.001, respectively) and 1% (both P < 0.001).
Figure 2
 
The percentage of total abnormal points among the total VF points significantly depressed <5% and <1% in the pattern deviation plot. The mean percentage of abnormal points in FDT was significantly greater than that in SAP and SWAP, for 5% and 1% in the PNS group (all P < 0.001). In the PFS group, the mean percentage of total abnormal points in FDT was greater than the mean percentages of abnormal points in SAP and SWAP, for 5% (P = 0.005, P < 0.001, respectively) and 1% (both P < 0.001).
Figure 3
 
Scatterplots showing the relationships between the global MS (dB) of the VF and average RNFL thickness in patients with the PNS (A, C) and PFS (B, D). Global MS was measured by SAP (A, B) and FDT (C, D). *Regression analyses with P < 0.05.
Figure 3
 
Scatterplots showing the relationships between the global MS (dB) of the VF and average RNFL thickness in patients with the PNS (A, C) and PFS (B, D). Global MS was measured by SAP (A, B) and FDT (C, D). *Regression analyses with P < 0.05.
Figure 4
 
Structure–function relationship between sectoral VF sensitivity (dB) and the corresponding RNFL thickness in patients with the PNS (A, B, D, E) and PFS (C, F). *Regression analyses with P < 0.05.
Figure 4
 
Structure–function relationship between sectoral VF sensitivity (dB) and the corresponding RNFL thickness in patients with the PNS (A, B, D, E) and PFS (C, F). *Regression analyses with P < 0.05.
Table 1
 
Characteristics of Patients With PFS and PNS
Table 1
 
Characteristics of Patients With PFS and PNS
Table 2
 
Mean Deviation and PSD of FDT and SWAP in PFS and PNS Groups
Table 2
 
Mean Deviation and PSD of FDT and SWAP in PFS and PNS Groups
Table 3
 
Structure–Function Relationship Between Global Mean Sensitivity of VF and Average RNFL Thickness
Table 3
 
Structure–Function Relationship Between Global Mean Sensitivity of VF and Average RNFL Thickness
Table 4
 
Structure–Function Relationship Between Regional VF Sensitivity Measured With SAP or FDT or SWAP and the Corresponding Peripapillary RNFL Thickness
Table 4
 
Structure–Function Relationship Between Regional VF Sensitivity Measured With SAP or FDT or SWAP and the Corresponding Peripapillary RNFL Thickness
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