Free
Glaucoma  |   November 2012
Structure-Function Relationship between FDF, FDT, SAP, and Scanning Laser Ophthalmoscopy in Glaucoma Patients
Author Affiliations & Notes
  • Julia Lamparter
    From the Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; the
    National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital National Health Service Foundation Trust, London, United Kingdom; and the
  • Richard A. Russell
    National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital National Health Service Foundation Trust, London, United Kingdom; and the
    Department of Optometry and Visual Science, City University London, London, United Kingdom.
  • Andreas Schulze
    From the Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; the
  • Ann-Christin Schuff
    From the Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; the
  • Norbert Pfeiffer
    From the Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; the
  • Esther M. Hoffmann
    From the Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; the
  • Corresponding author: Esther M. Hoffmann, Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University, Langenbeckstrasse 1, 55131 Mainz, Germany; ehoffman@uni-mainz.de
Investigative Ophthalmology & Visual Science November 2012, Vol.53, 7553-7559. doi:10.1167/iovs.12-10892
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Julia Lamparter, Richard A. Russell, Andreas Schulze, Ann-Christin Schuff, Norbert Pfeiffer, Esther M. Hoffmann; Structure-Function Relationship between FDF, FDT, SAP, and Scanning Laser Ophthalmoscopy in Glaucoma Patients. Invest. Ophthalmol. Vis. Sci. 2012;53(12):7553-7559. doi: 10.1167/iovs.12-10892.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose.: Flicker defined form perimetry (FDF) and frequency doubling technology perimetry (FDT) are alleged to detect glaucoma at an earlier stage than standard automated perimetry (SAP). It is the purpose of this study to investigate the structure-function relationship between FDF, FDT, SAP, and confocal scanning laser ophthalmoscopy (cSLO) in patients with glaucoma.

Methods.: Seventy-six patients with glaucoma were included in the study. Patients were tested with SAP, Matrix-FDT, FDF perimetry, and cSLO. Structure-function relationships between global and sectoral cSLO parameters and global and sectoral mean sensitivity (MS) of SAP, Matrix-FDT, and FDF were calculated using Spearman's rank correlation and linear regression.

Results.: Overall, FDF perimetry showed the strongest structure-function relationship (global correlation with rim area: 0.44; range of significant sectoral FDF values: 0.23–0.69), followed by FDT (global correlation with rim area: 0.35; range of significant sectoral FDT values: 0.25–0.60). SAP presented with the weakest structure-function relationship and fewer statistically significant results (global correlation with rim volume: 0.32; range of significant sectoral SAP values: 0.23–0.58). Sector-by-sector, the structure-function relationship was greatest in the superotemporal and inferotemporal regions. Weakest correlations were found in the inferonasal and nasal sectors.

Conclusions.: The correlation between structure and function is stronger in FDF and FDT compared with SAP. Correlations are strongest in temporal areas where glaucomatous damage tends to occur first. A better understanding of the structure-function relationship should allow for improved detection and management of glaucoma patients.

Introduction
Structural measurements of the optic nerve head (ONH) and functional measurements of the visual field represent two main pillars of glaucoma diagnosis and management. 1 The relationship between structure and function has been actively investigated since the invention of the direct ophthalmoscope by von Helmholtz in 1850. 2 Since then, there has been a long history of analysis of this topic 3 and numerous studies have reported a moderate relationship between the appearance of the ONH, the retinal nerve fiber layer (RNFL), and visual field changes in glaucomatous patients. 48 Structure-function maps have been developed in order to establish the anatomical relationship between visual field areas and regions of the ONH. 912  
Today, structural measures of ONH topography and RNFL thickness can be obtained using optical imaging techniques including scanning laser ophthalmoscopy (SLO), confocal scanning laser polarimetry (cSLP), and optical coherence tomography (OCT), 13,14 while standard automated perimetry (SAP) remains the gold standard for functional assessment of glaucoma. 15 SAP is considered a nonselective test for glaucoma, since all subtypes of retinal ganglion cells are sensitive to its achromatic stimulus. 
Frequency doubling technology perimetry (FDT) was introduced to clinical practice in the late 1990s. 16,17 It measures contrast sensitivity of a low spatial frequency sinusoidal grating, which undergoes high temporal frequency counterphase flicker and causes the perception of a frequency-doubling illusion (FDI). 18 Several investigations have affirmed promising results in detecting early, moderate and advanced visual field loss in patients with glaucoma. 1922 In addition, studies have shown that there is a smaller increase in variability in damaged areas of the visual field for FDT in comparison to SAP. 2325  
Flicker defined form perimetry (FDF) uses a new stimulus, which was specifically designed for the detection of functional loss due to early glaucoma. 2628 Randomly positioned stimuli of black and white dots flicker at high temporal frequency in counterphase. The spots reverse polarity without changing their positions, which means that white dots are replaced with black dots and black dots are replaced with white dots. At high temporal frequencies subjects can not see the difference between the flickering dots but they can perceive an illusory circular edge contour, which looks like a gray patch against the mean luminance background. 
To date, no studies on FDF perimetry in glaucomatous patients have been published in peer reviewed journals. It is the aim of this study to evaluate the structure-function relationship between SAP, Matrix-FDT, FDF, and SLO in glaucomatous patients. 
Materials and Methods
Patients and Selection Criteria
Seventy-six patients with early (n = 26) or moderate to advanced glaucoma (n = 50) were included in this prospective cross-sectional study. One eye of each participant was randomly selected for the study, except in cases in which only one eye met the inclusion criteria. Inclusion criteria were a minimum best-corrected logMar visual acuity of 0.2 and spherical equivalent within ± 6 diopters (D). Participants with previous intraocular surgery, patients with history of diabetes, or neurological disorders that might affect the visual field were not included in the study. 
Subjects were consecutively recruited from patients attending the Ophthalmology department of the University of Mainz between October 2009 and April 2011. All patients were diagnosed with POAG prior to study involvement. Most of the study patients were treated with IOP lowering eye drops. To be included in the study, glaucoma diagnosis had to be confirmed on the basis of characteristic structural changes of the ONH or RNFL observed with clinical stereo-biomicroscopic slitlamp examination (one or several of the following: rim thinning, notching, glaucomatous excavation, nerve fiber layer defects) and scanning laser polarimetry. Before inclusion, patients were examined by at least two independent glaucoma specialists. SAP visual field test results were not used for diagnosis but were used to classify patients into groups with early, moderate or advanced glaucoma according to the Hodapp-Anderson-Parrish visual field severity score. 29  
All participants signed informed consent prior to any examination and the study followed the tenets of the Declaration of Helsinki. The study was approved by the Medical Ethical Committee of Rhineland Palatinate in Mainz, Germany. 
Examinations
All participants underwent medical and ocular history, complete ophthalmic examination including best corrected visual acuity testing, slit lamp biomicroscopy, Goldmann applanation tonometry, stereoscopic fundus biomicroscopy using a superfield-lens (Volk Optical, Inc., Mentor, Ohio), and laser interference pachymetry (4optics AG, Lübeck, Germany). They were tested with SAP, Matrix-FDT, and FDF perimetry within a period of one month. Patients also received scanning laser ophthalmoscopy (HRT III; Heidelberg Engineering, Heidelberg, Germany) and scanning laser polarimetry (GDxPro; Carl Zeiss Meditec AG, Dublin, CA). 
Structural and Functional Measurements
SAP was performed with the automated Humphrey Visual Field Analyzer II (HFA II, model 750; Carl Zeiss Meditec AG). The 24-2 Swedish Interactive Threshold Algorithm (SITA) Standard program was used with a size III visible light stimulus, a maximum intensity of 10.000 apostilbs (asb), stimulus duration of 200 ms on a background illumination of 31.5 asb (10 cd/m2). FDT perimetry was performed with the Humphrey Matrix-FDT (Welch Allyn Inc., and Carl Zeiss Meditec AG, Dublin, CA), using the 24-2 Zippy Estimation by Sequential Testing (ZEST) strategy with a stimulus duration of 300 ms and a background illumination of 100 cd/m2. Each target subtends 5° of visual angle and has a spatial frequency of 0.5 cycles/deg and a temporal frequency of 18 Hz. FDF perimetry was performed with the Heidelberg Edge Perimeter ([HEP]; Heidelberg Engineering), using the central 24-2 program and standard Adaptive Staircase Thresholding Algorithm (ASTA), with a stimulus size of 5° × 5°, a stimulus duration of 400 ms, a frequency of 15 Hz, and a mean luminance background of 50 cd/m2. Further details about the recently developed HEP device have been described elsewhere. 30  
Although most participants were familiar with visual field testing (SAP only), instructions about how to perform the visual field test were given before any testing, and the test was started after a brief demonstration. SAP testing was performed with regular trial lenses. Near addition was added to the subject's refractive correction. Subjects were tested using their own distance glasses or contact lenses for FDF and FDT perimetry as recommended by the manufacturers. The built in automatic fixation control systems were used to measure the patient's gaze direction during the stimulus presentation. Additionally, fixation was controlled by the examiner during the entire test. If the tests were done on the same day, no specific test order was followed, and an adequate rest of at least 10 minutes was offered between the tests. Reliability indices for SAP and FDT were set to false positive, false negative, and fixation loss errors less than 30%. As there are no generally accepted values for FDF reliability indices yet, all examinations carried out were included in the study. Scanning laser ophthalmoscopy was performed with the Heidelberg Retina Tomograph (HRT III; Heidelberg Engineering). HRT image quality and contour lines were checked and, if necessary, re-assessed by an experienced glaucoma specialist (EMH). Only well-focused, evenly illuminated, centered HRT scans with SD less than 30 were included. 
Analysis
Structure-function relationships between global and sectoral HRT parameters and global and sectoral mean sensitivity (MS) of SAP, Matrix-FDT, and FDF were calculated using Spearman's correlation coefficient and linear regression. Spearman's correlation coefficient was used instead of Pearson's because variables were not normally distributed and so the assumptions of normality, associated with Pearson's correlation coefficient, were not met. Furthermore, studies of structure-function associations consistently report a nonlinear relationship between visual function measurements scaled in decibels and structural measurements scaled in linear units 31,32 ; Pearson's correlation coefficient is strongly biased toward linear trends, whereas Spearman's correlation coefficient can detect a general monotonic trend. 
Each visual field was divided into six sectors, corresponding to the six HRT sectors in the Moorfields Regression Analysis. The analysis was based on the structure-function map developed by Garway-Heath et al., 9 which was accordingly transformed to correspond to the HRT sectors 8 ; this is shown in the Figure (top part). For simplification, sectors were only named according to their structural location on the ONH (e.g., the visual-field (VF)-temporal/ HRT-nasal pair was given the name “nasal sector”). HRT sectoral raw data were exported in order to evaluate the correlations for each of the six sectors. Matrix-FDT provides three additional visual field points which are not assessed in the pattern deviation plot of Humphrey-SAP and HEP: one central point and two points just above and below the blind spot. These points as well as the blind spot were excluded and 52 visual field points remained for the analysis. Visual field sensitivity was recorded using the dB [10*log(1/Lambert)] scale. As FDF and FDT are proposed to be selective tests alleged to detect functional damage associated with early glaucoma, a subanalysis was carried out in order to assess the structure-function relationship in the early glaucoma patient group (based on the Hodapp-Anderson-Parrish criteria). 
Structure-function correlation coefficients were compared between SAP, FDF, and FDT perimeters using a statistical procedure that accounts for differences between two “overlapping” correlations. Standard tests for comparing correlations assume that the measurements are independent. In this study, this assumption is not true as the correlations share a common (“overlapping”) variable. For example, if we wish to compare the correlation between global MS of SAP and global rim area against the correlation between global MS of FDT and global rim area, the correlations are not independent since global rim area is common to both tests. Therefore, we used a technique described by Zou in order to adjust the confidence interval to account for this overlap. 33 In summary, the technique adjusts the sampling variances of the correlations using a form of the variance sum law. All analyses were performed using the software R. 34 A P value less than 0.05 was considered statistically significant. 
Results
Seventy-six eyes of 76 patients with early (26 eyes) and moderate to advanced (n = 50) glaucoma were included in the analysis. The Table shows mean patient age ± SD at enrolment, mean spherical refractive error, mean logMAR visual acuity, mean IOP, and mean corneal thickness (CCT) for the entire group and the two subgroups. Furthermore, mean deviation (MD) and pattern standard deviation (PSD) are shown for all three instruments (FDF, FDT, SAP). 
The Figure shows Spearman's correlation coefficients between HRT sectoral parameters (rim area, rim volume, mean RNFL thickness, and cup-disc-area-ratio) and mean sectoral visual field sensitivity (dB) for all three visual field tests. Data for global correlation coefficients and additional HRT parameters (mean RNFL cross-sectional area, cup volume, cup area, cup-shape-measure, disc area, rim-disc-area-ratio, mean and maximum cup depth, and height variation contour) as well as the complete dataset for the early glaucoma group can be found in the online supplement (see Supplementary Material and Supplementary Tables S1, S2). 
The structure-function relationship between FDF perimetry and HRT parameters in the overall group of 76 patients showed significant correlations in five visual field sectors (all sectors except the nasal sector) and 11 HRT parameters (all parameters except disc area, and height variation contour). In general, FDF perimetry showed the strongest correlation coefficients (strongest global correlation for rim area: 0.44; range of all significant FDF values: 0.23–0.69), followed by FDT (strongest global correlation for rim area: 0.35; range of all significant FDT values: 0.25–0.60). SAP presented with the weakest correlation coefficients and fewer statistically significant results (strongest global correlation for rim volume: 0.32; range of all significant SAP values: 0.23–0.58). 
When comparing global RNFL thickness, rim volume, and cup-disc-area-ratio, FDF and FDT presented with significant correlations for all three parameters, while SAP was only significant for RNFL thickness and rim volume. Interestingly, FDT and SAP had stronger correlation coefficients for RNFL thickness (0.30 compared with 0.27 in FDF), while FDF presented with stronger correlations for rim volume and cup-disc-area-ratio (rim volume: FDF = 0.37, FDT = 0.33, SAP = 0.22, and cup-disc-area-ratio: FDF = −0.38, FDT = −0.32, and SAP = −0.19). 
Sector-by-sector, correlation coefficients for FDF were largest in magnitude in the superotemporal sector (rim area: 0.69), followed by the inferotemporal (rim area: 0.55), superonasal (cup-disc-area-ratio/rim-disc area ratio: ±0.53), temporal (rim volume: 0.40), and inferonasal (rim volume: 0.30) sectors. No significant correlation was found in the nasal sector. For FDT and SAP, correlation coefficients were also found to be greatest in the superotemporal (cup-disc-area-ratio/ rim disc area ratio for FDT ±0.60 and for SAP ±0.58), and infero-temporal sectors (mean RNFL thickness/RNFL cross-sectional area for FDT 0.54 and rim volume for SAP 0.55). In contrast to FDF, correlations in the temporal sector were stronger than in the superonasal sector for both FDT and SAP (cup-disc-area ratio/rim-disc-area-ratio for FDT ±0.43 and rim volume for SAP 0.39). Weakest correlations were found in the superonasal (cup-disc-area-ratio/rim-disc-area-ratio ±0.41 for FDT and rim area/ cup-shape-measure ±0.27 for SAP), inferonasal (rim volume 0.32 for FDT and 0.27 for SAP) and nasal (only cup area and disc area for FDT) sectors. Like FDF, SAP did not show any significant correlation in the nasal sector. 
Comparing correlation coefficients among the three perimeters, a statistically significant difference could be shown between FDF/FDT and FDF/SAP for rim area in both, superotemporal and superonasal sectors (P < 0.05, respectively) as presented in the Figure. With regard to rim volume, FDF had significantly stronger correlation coefficients compared with FDT and SAP in the superonasal sector. For cup-disc-area-ratio both, FDF and FDT showed a significantly stronger correlation than SAP in the superonasal sector. 
In the early glaucoma group, less than one third of the correlation coefficients were statistically significant. Most of the significant values were found for FDF perimetry, followed by FDT and SAP. Interestingly, amongst the different tests, SAP exhibited the strongest correlation in the inferotemporal sector (rim area 0.61) but presented with the weakest structure-function relationship in all other sectors. Looking at global correlation coefficients, significant values were only found in FDF perimetry, which also exhibited the strongest correlation coefficient (cup-shape-measure: −0.57). Correlations were significantly stronger for FDF compared with FDT for rim area and cup-disc-area-ratio in the superotemporal sector. For RNFL thickness, the difference between SAP and FDF reached statistical difference in the inferotemporal sector and also globally. 
Discussion
The aim of this study was to evaluate the relationship between retinal light sensitivity and structural measures of the ONH in topographically related areas of three visual field tests (FDF, Matrix-FDT, and SAP) and confocal scanning laser ophthalmoscopy (cSLO). This is the first study evaluating the structure-function relationship with FDF perimetry. 
Improving the magnitude of the structure-function relationship in glaucoma patients is important. Recently, the Food and Drug Administration Center for Drug Development and Research announced that it is open to using structural endpoints in clinical trials of new glaucoma drugs provided that the structural measures exhibit a strong correlation between predictability of either current visual function or future visual function. 35  
FDF perimetry presented with the strongest correlation coefficients and the strongest structure-function relationship; it was followed by FDT, while SAP presented with the weakest structure-function relationship. 
In general, the strongest relationship between structure and function could be found in the temporal hemisphere (superotemporal, inferotemporal, and temporal sectors) and the superonasal sector. The weakest correlation was found in the inferonasal and nasal areas. Given the fact that glaucomatous damage preferentially affects the superotemporal and inferotemporal areas of the ONH, a stronger structure-function relationship in these areas is what we expected. 3638 Interestingly, FDF was stronger than FDT and SAP in the superotemporal and superonasal sector (where also statistically significant differences were evident among the three instruments) but weakest in the inferotemporal sector (where differences between instruments were only small and not significant). 
Our results are in slight contrast to the results by Danesh-Meyer et al. 39 who evaluated the regional correlation between structure and function, based on HRT and SAP results. They reported the strongest correlation for the inferior/inferotemporal structural regions while the superior regions had weaker coefficients. However, our studies are not entirely comparable as theirs was based on a mixed population of subjects, glaucomatous patients and normal controls, using MD instead of mean sensitivity. 
The structure-function relationship has also been investigated for FDT and HRT. 40,41 Iester and colleagues 40,41 found HRT cup-shape-measure as the strongest predictor for FDT and sectoral HRT parameters better correlating to SAP than to FDT. This is in disagreement to our findings and may be explained by a difference in methodologies; instead of matching the visual field to the ONH, based on a structure-function map, they calculated correlations between visual field quadrants and superotemporal, superonasal, inferotemporal, and inferonasal HRT sectors. In accordance to our results, temporal areas showed a stronger correlation than nasal areas. Looking at the structure-function relationship between additional structural tests and SAP, Bowd and colleagues 42 evaluated the structure-function relationships using cSLO, OCT, and SLP in glaucomatous patients, glaucoma suspects and healthy controls. The correlation between RNFL thickness and visual sensitivity was generally strongest in the inferotemporal sector for SLP and OCT. For cSLO, strongest correlations for RNFL thickness and rim area were found in the inferotemporal and superotemporal sectors, comparable to our findings. The weakest correlation was found in the nasal but also in the temporal sector. Miglior and colleagues 43 evaluated the relationship between retinal light sensitivity, measured with the Humphrey Field Analyzer (HFA II; Carl Zeiss Meditec AG) and RNFL thickness obtained with spectral domain optical coherence tomography (SD-OCT). In glaucoma patients, they found a significant correlation between structure and function in all of the sectors except for the VF temporal/OCT nasal pair which corresponds to the nasal sector in this study. Similar results for SD-OCT could be shown by Aptel et al., 44 who found the highest correlation between SD-OCT RNFL thickness and SAP retinal light sensitivity in the superotemporal sector, while the nasal sector was the only one without any significant correlation. This is in accordance with our results obtained with FDF and FDT (significant correlation for HRT mean RNFL thickness in all sectors but the nasal sector for FDF and in all sectors, but the nasal and superonasal sectors for FDT). In contrast to their results, significant correlation between SAP and HRT RNFL thickness could only be shown in three of the six sectors (superotemporal, inferotemporal, and temporal). Lee et al. 45 evaluated the structure-function relationship using scanning laser polarimetry and SAP in POAG patients. Again, the strongest correlation was found in the superotemporal sector, followed by the superonasal and inferotemporal sectors, while the temporal and nasal sectors did not show statistically significant results. 
When analyzing the early glaucoma subgroup, we found less significant results than in the entire group of glaucomatous patients. This might be due to the small sample size of only 26 patients. It could also be related to the early stage of the disease as studies investigating the structure-function relationship in ocular hypertensive patients and normal controls could not find any significant results, either. However, it is notable that FDF is still showing the strongest correlation in both, statistically significant and non significant cases, and it is remarkable that the overall trend in the early glaucoma group is generally better for FDF and FDT compared with SAP. 
FDT and FDF are tests which were supposed to preferentially stimulate magnocellular M cells. 22,27,46 For a long time, magnocellular M cells were thought to be primarily damaged in early glaucoma. 47 However, there is controversy about the exact mechanisms underlying FDT (and, hence, FDF) and the impact of the magnocellular pathway in glaucoma: Crawford and Yücel have shown that the effect of glaucoma does not seem to be any greater for the magnocellular, rather than the parvocellular pathway. 48,49 Swanson et al. 50 recently discovered that Goldmann Size III stimuli (as used in conventional perimetry) were superior to the frequency doubling stimulus in preferentially stimulating magnocellular versus parvocellular cells in primates. In addition to this, White et al. 17 demonstrated that the nonlinearity of spatial summation gives a doubled response in time but not across space. The appearance of fractional spatial frequency percepts was demonstrated by Zeppieri et al., 51 who proposed that there is no well defined spatiotemporal region within which “frequency doubling” occurs, questioning the idea that frequency-doubling is exclusively generated by spatially nonlinear magnocellular ganglion cells. 
On the basis of these findings it is important to underline that the exact differences between the principal mechanisms used by SAP, FDT, and FDF remain unclear and a more thorough understanding of the underlying processes is needed. 
We speculate that any differences in the structure-function relationship are not driven primarily by preferentially targeting different cellular pathways, but instead are possibly due to the reduced variability associated with FDT and FDF in damaged areas of the VF. This reduced variability leads to an increase in the signal-to-noise ratio of the measurements, which in turn, may result in a stronger correlation with structural measurements. 
It is important to underline that the strength of correlation between structure and function can vary according to patient factors, stage and definition of the disease, or variability of measurements and instruments used. Small differences in study design (such as a different range of refractive error or visual acuity) can influence the results and make direct comparisons among different structure-function investigations difficult or even impossible. 
For structural techniques, strongest correlations were reported for OCT, while strongest correlations for functional tests have been found for FDF perimetry in this study. 42 For future investigations it might therefore be interesting to investigate the relationship between both, FDF and OCT. Another potential reason for weaker structure-function relationships might be explained by the nature of current structure-function maps, which do not account for individual patient's variability in structure-function topography; correlation between structural and functional parameters in a given patient may be improved by using an ‘individualized' structure-function map rather than a ‘global' mapping system. 
In summary, the strength of the structure-function relationship in FDF perimetry was greatest amongst the three instruments investigated. The strongest relationship between structure and function was mainly found in the superotemporal and inferotemporal sectors of the ONH, statistically significant differences between the instruments were reached in the superonasal and superotemporal sectors. Weaker or even non significant correlations are found for the nasal part of the disc. Our results suggest that FDF may be an effective visual field test for detecting glaucoma and integrating structural and functional measurements. 
Figure. 
 
Structure-function relationship between flicker defined form perimetry, Matrix frequency doubling technology perimetry, standard automated perimetry, and confocal scanning laser ophthalmoscopy (rim area, rim volume, cup-disc-area-ratio, and RNFL thickness). Shown are sectoral Spearman correlation coefficients for ST, superotemporal; SN, superonasal; N, nasal; IN, inferonasal; IT, inferotemporal; and T, temporal sectors. The map is based on the structure-function map developed by Garway-Heath and colleagues, showing the relationship between areas in the visual field and regions on the optic nerve head. 8,9 X, statistically significant difference between correlations for FDF and SAP; †, statistically significant difference between correlations for FDF and FDT; ▪, statistically significant difference between correlations for FDT and SAP.
Figure. 
 
Structure-function relationship between flicker defined form perimetry, Matrix frequency doubling technology perimetry, standard automated perimetry, and confocal scanning laser ophthalmoscopy (rim area, rim volume, cup-disc-area-ratio, and RNFL thickness). Shown are sectoral Spearman correlation coefficients for ST, superotemporal; SN, superonasal; N, nasal; IN, inferonasal; IT, inferotemporal; and T, temporal sectors. The map is based on the structure-function map developed by Garway-Heath and colleagues, showing the relationship between areas in the visual field and regions on the optic nerve head. 8,9 X, statistically significant difference between correlations for FDF and SAP; †, statistically significant difference between correlations for FDF and FDT; ▪, statistically significant difference between correlations for FDT and SAP.
Table. 
 
Demographic Data of the Entire Study Group, the Early Glaucoma Group and the Moderate/Advanced Glaucoma Group
Table. 
 
Demographic Data of the Entire Study Group, the Early Glaucoma Group and the Moderate/Advanced Glaucoma Group
Entire Group (n = 76) Early Glaucoma Group (n = 26) Moderate/ Advanced Glaucoma Group (n = 50) P Value
Age 65.47 ± 8.23 (43.21; 80.68) 65.56 ± 8.22 (43.21; 80.68) 65.42 ± 8.24 (43.93; 79.84) 0.94
Mean RE 0.21 ± 1.97 (−4.75; +4.25) 0.35 ± 2.11 (−4.50; +4.25) 0.15 ± 1.88 (−4.75; 3.25) 0.68
Mean cylinder −0.67 ± 0.60 (−2.75; +0.75) −0.65 ± 0.60 (−2.25; +0.50) −0.68 ± 0.60 (−2.75; 0.75) 0.86
Mean SE −0.12 ± 1.97 (−5.63; 3.75) 0.20 ± 2.17 (−5.13; 3.75) −0.19 ± 1.85 (−5.63; 3.00) 0.66
logMAR VA 0.09 ± 0.08 (−0.10; +0.20) 0.10 ± 0.08 (0.00; +0.20) 0.08 ± 0.08 (−0.10; 0.20) 0.27
IOP 16.22 ± 3.02 (10.0; 27.0) 16.81 ± 2.90 (10.0; 22.0) 15.92 ± 3.03 (10.0; 27.0) 0.23
Mean CCT 524.33 ± 38.07 (441; 635) 523.50 ± 33.23 (441.00; 582.00) 524.76 ± 40.35 (460.0; 635.0) 0.89
MD SAP −7.92 ± 4.65 (−22.0; −0.25) −3.63 ± 1.94 (−8.07; −0.25) −9.79 ± 4.00 (−22.0; −3.12) <0.001
MD FDT −9.41 ± 4.25 (−19.50; −0.36) −6.61 ± 3.78 (−18.37; −0.36) −10.86 ± 3.80 (−19.50; −2.57) <0.001
MD FDF −13.69 ± 4.19 (−21.97; −3.38) −11.33 ± 4.32 (−20.03; −3.38) −14.92 ± 3.63 (−21.97; −6.50) <0.01
PSD SAP 8.41 ± 4.06 (1.62; 15.00) 4.48 ± 2.95 (1.62; 12.06) 10.46 ± 2.92 (4.60; 15.00) <0.001
PSD FDT 6.70 ± 2.06 (1.98; 11.05) 5.78 ± 1.88 (2.41; 10.12) 7.18 ± 2.03 (1.98; 11.05) 0.02
PSD FDF 5.52 ± 2.04 (1.07; 10.26) 6.17 ± 1.67 (3.12; 9.06) 5.19 ± 2.17 (1.07; 10.26) 0.062
Supplementary Materials
References
Gupta N Weinreb RN. New definitions of glaucoma. Curr Opin Ophthalmol . 1997;8:38–41. [CrossRef] [PubMed]
Schumann WP. One hundred years of the ophthalmoscope–Von Helmholtz, the man, his life and work. Am J Optom Arch Am Acad Optom . 1951;28:357–368. [CrossRef] [PubMed]
Johnson CA Cioffi GA Liebmann JR Sample PA Zangwill LM Weinreb RN. The relationship between structural and functional alterations in glaucoma: a review. Semin Ophthalmol . 2000;15:221–233. [CrossRef] [PubMed]
Drance SM. Doyne Memorial Lecture, 1975. Correlation of optic nerve and visual field defects in simple glaucoma. Trans Ophthalmol Soc U K . 1975;95:288–296. [PubMed]
Read RM Spaeth GL. The practical clinical appraisal of the optic disc in glaucoma: the natural history of cup progression and some specific disc-field correlations. Trans Am Acad Ophthalmol Otolaryngol . 1974;78:OP 255–OP 274.
Goldberg I. Optic disc and visual field changes in primary open angle glaucoma. Aust J Ophthalmol . 1981;9:223–229. [CrossRef] [PubMed]
Johnson CA Sample PA Zangwill LM Structure and function evaluation (SAFE): II. Comparison of optic disk and visual field characteristics. Am J Ophthalmol . 2003;135:148–154. [CrossRef] [PubMed]
Garway-Heath DF Holder GE Fitzke FW Hitchings RA. Relationship between electrophysiological, psychophysical, and anatomical measurements in glaucoma. Invest Ophthalmol Vis Sci . 2002;43:2213–2220. [PubMed]
Garway-Heath DF Poinoosawmy D Fitzke FW Hitchings RA. Mapping the visual field to the optic disc in normal tension glaucoma eyes. Ophthalmology . 2000;107:1809–1815. [CrossRef] [PubMed]
Zhu H Crabb DP Schlottmann PG Predicting visual function from the measurements of retinal nerve fiber layer structure. Invest Ophthalmol Vis Sci . 2010;51:5657–5666. [CrossRef] [PubMed]
Strouthidis NG Vinciotti V Tucker AJ Gardiner SK Crabb DP Garway-Heath DF. Structure and function in glaucoma: the relationship between a functional visual field map and an anatomic retinal map. Invest Ophthalmol Vis Sci . 2006;47:5356–5362. [CrossRef] [PubMed]
Gardiner SK Johnson CA Cioffi GA. Evaluation of the structure-function relationship in glaucoma. Invest Ophthalmol Vis Sci . 2005;46:3712–3717. [CrossRef] [PubMed]
Townsend KA Wollstein G Schuman JS. Imaging of the retinal nerve fibre layer for glaucoma. Br J Ophthalmol . 2009;93:139–143. [CrossRef] [PubMed]
Medeiros FA Zangwill LM Bowd C Weinreb RN. Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and stratus OCT optical coherence tomograph for the detection of glaucoma. Arch Ophthalmol . 2004;122:827–837. [CrossRef] [PubMed]
San Laureano J. When is glaucoma really glaucoma? Clin Exp Optom . 2007;90:376–385. [CrossRef] [PubMed]
Anderson AJ Johnson CA. Frequency-doubling technology perimetry. Ophthalmol Clin North Am . 2003;16:213–225. [CrossRef] [PubMed]
White AJ Sun H Swanson WH Lee BB. An examination of physiological mechanisms underlying the frequency-doubling illusion. Invest Ophthalmol Vis Sci . 2002;43:3590–3599. [PubMed]
Kelly DH. Frequency doubling in visual responses. J Opt Soc Am . 1966;56:1628–1633. [CrossRef]
Medeiros FA Sample PA Weinreb RN. Frequency doubling technology perimetry abnormalities as predictors of glaucomatous visual field loss. Am J Ophthalmol . 2004;137:863–871. [CrossRef] [PubMed]
Kim TW Zangwill LM Bowd C Sample PA Shah N Weinreb RN. Retinal nerve fiber layer damage as assessed by optical coherence tomography in eyes with a visual field defect detected by frequency doubling technology perimetry but not by standard automated perimetry. Ophthalmology . 2007;114:1053–1057. [CrossRef] [PubMed]
Soliman MA de Jong LA Ismaeil AA van den Berg TJ de Smet MD. Standard achromatic perimetry, short wavelength automated perimetry, and frequency doubling technology for detection of glaucoma damage. Ophthalmology . 2002;109:444–454. [CrossRef] [PubMed]
Cello KE Nelson-Quigg JM Johnson CA. Frequency doubling technology perimetry for detection of glaucomatous visual field loss. Am J Ophthalmol . 2000;129:314–322. [CrossRef] [PubMed]
Artes PH Hutchison DM Nicolela MT LeBlanc RP Chauhan BC. Threshold and variability properties of matrix frequency-doubling technology and standard automated perimetry in glaucoma. Invest Ophthalmol Vis Sci . 2005;46:2451–2457. [CrossRef] [PubMed]
Spry PG Johnson CA McKendrick AM Turpin A. Variability components of standard automated perimetry and frequency-doubling technology perimetry. Invest Ophthalmol Vis Sci . 2001;42:1404–1410. [PubMed]
Chauhan BC Johnson CA. Test-retest variability of frequency-doubling perimetry and conventional perimetry in glaucoma patients and normal subjects. Invest Ophthalmol Vis Sci . 1999;40:648–656. [PubMed]
Goren D Flanagan JG. Is flicker-defined form (FDF) dependent on the contour? J Vis . 2008;8:1–11. [CrossRef] [PubMed]
Quaid PT Flanagan JG. Defining the limits of flicker defined form: effect of stimulus size, eccentricity and number of random dots. Vision Res . 2005;45:1075–1084. [CrossRef] [PubMed]
Quaid PT Simpson TL Flanagan JG. Frequency doubling illusion: detection vs. form resolution. Optom Vis Sci . 2005;82:36–42. [PubMed]
Budenz DL Rhee P Feuer WJ McSoley J Johnson CA Anderson DR. Comparison of glaucomatous visual field defects using standard full threshold and Swedish interactive threshold algorithms. Arch Ophthalmol . 2002;120:1136–1141. [CrossRef] [PubMed]
Lamparter J Schulze A Schuff AC Berres M Pfeiffer N Hoffmann EM. Learning curve and fatigue effect of flicker defined form perimetry. Am J Ophthalmol . 2011;151:1057–1064. e1051. [CrossRef] [PubMed]
Swanson WH Felius J Pan F. Perimetric defects and ganglion cell damage: interpreting linear relations using a two-stage neural model. Invest Ophthalmol Vis Sci . 2004;45:466–472. [CrossRef] [PubMed]
Reus NJ Lemij HG. The relationship between standard automated perimetry and GDx VCC measurements. Invest Ophthalmol Vis Sci . 2004;45:840–845. [CrossRef] [PubMed]
Zou GY. Toward using confidence intervals to compare correlations. Psychol Methods . 2007;12:399–413. [CrossRef] [PubMed]
R Core Development Team. R: A Language and Environment for Statistical Computing . Vienna: Austria; 2009.
Weinreb RN Kaufman PL. Glaucoma research community and FDA look to the future, II: NEI/FDA Glaucoma Clinical Trial Design and Endpoints Symposium: measures of structural change and visual function. Invest Ophthalmol Vis Sci . 2011;52:7842–7851. [CrossRef] [PubMed]
Jonas JB Gusek GC Naumann GO. Optic disc morphometry in chronic primary open-angle glaucoma. II. Correlation of the intrapapillary morphometric data to visual field indices. Graefes Arch Clin Exp Ophthalmol . 1988;226:531–538. [CrossRef] [PubMed]
Jonas JB Fernandez MC Sturmer J. Pattern of glaucomatous neuroretinal rim loss. Ophthalmology . 1993;100:63–68. [CrossRef] [PubMed]
Tuulonen A Airaksinen PJ. Initial glaucomatous optic disk and retinal nerve fiber layer abnormalities and their progression. Am J Ophthalmol . 1991;111:485–490. [CrossRef] [PubMed]
Danesh-Meyer HV Ku JY Papchenko TL Jayasundera T Hsiang JC Gamble GD. Regional correlation of structure and function in glaucoma, using the Disc Damage Likelihood Scale, Heidelberg Retina Tomograph, and visual fields. Ophthalmology . 2006;113:603–611. [CrossRef] [PubMed]
Iester M Traverso CE De Feo F Correlation between frequency doubling technology and heidelberg retina tomograph. J Glaucoma . 2005;14:368–374. [CrossRef] [PubMed]
Iester M Sangermani C De Feo F Sector-based analysis of frequency doubling technology sensitivity and optic nerve head shape parameters. Eur J Ophthalmol . 2007;17:223–229. [PubMed]
Bowd C Zangwill LM Medeiros FA Structure-function relationships using confocal scanning laser ophthalmoscopy, optical coherence tomography, and scanning laser polarimetry. Invest Ophthalmol Vis Sci . 2006;47:2889–2895. [CrossRef] [PubMed]
Miglior S Riva I Guareschi M Retinal sensitivity and retinal nerve fiber layer thickness measured by optical coherence tomography in glaucoma. Am J Ophthalmol . 2007;144:733–740. [CrossRef] [PubMed]
Aptel F Sayous R Fortoul V Beccat S Denis P. Structure-function relationships using spectral-domain optical coherence tomography: comparison with scanning laser polarimetry. Am J Ophthalmol . 2010;150:825–833. [CrossRef] [PubMed]
Lee PJ Liu CJ Wojciechowski R Bailey-Wilson JE Cheng CY. Structure-function correlations using scanning laser polarimetry in primary angle-closure glaucoma and primary open-angle glaucoma. Am J Ophthalmol . 2010;149:817–825. e811. [CrossRef] [PubMed]
Ramachandran VS Rogers-Ramachandran DC. Phantom contours: a new class of visual patterns that selectively activates the magnocellular pathway in man. Bull Soc Psychonomic . 1991;29:391–394. [CrossRef]
Quigley HA Sanchez RM Dunkelberger GR L'Hernault NL Baginski TA. Chronic glaucoma selectively damages large optic nerve fibers. Invest Ophthalmol Vis Sci . 1987;28:913–920. [PubMed]
Crawford ML Harwerth RS Smith EL III Shen F Carter-Dawson L. Glaucoma in primates: cytochrome oxidase reactivity in parvo- and magnocellular pathways. Invest Ophthalmol Vis Sci . 2000;41:1791–1802. [PubMed]
Yucel YH Zhang Q Weinreb RN Kaufman PL Gupta N. Atrophy of relay neurons in magno- and parvocellular layers in the lateral geniculate nucleus in experimental glaucoma. Invest Ophthalmol Vis Sci . 2001;42:3216–3222. [PubMed]
Swanson WH Sun H Lee BB Cao D. Responses of primate retinal ganglion cells to perimetric stimuli. Invest Ophthalmol Vis Sci . 2011;52:764–771. [CrossRef] [PubMed]
Zeppieri M Demirel S Kent K Johnson CA. Perceived spatial frequency of sinusoidal gratings. Optom Vis Sci . 2008;85:318–329. [CrossRef] [PubMed]
Footnotes
 Supported by grants in part from Heidelberg Engineering, Heidelberg, (EMH) Germany, the Department of Health's National Institute for Health Research (NIHR) Biomedical Research Centre for Ophthalmology at Moorfields Eye Hospital National Health Service Foundation Trust (RAR), and the University College London Institute of Ophthalmology (RAR).
Footnotes
 Disclosure: J. Lamparter, None; R.A. Russell, None; A. Schulze, None; A.-C. Schuff, None; N. Pfeiffer, None; E.M. Hoffmann, Heidelberg Engineering (F)
Figure. 
 
Structure-function relationship between flicker defined form perimetry, Matrix frequency doubling technology perimetry, standard automated perimetry, and confocal scanning laser ophthalmoscopy (rim area, rim volume, cup-disc-area-ratio, and RNFL thickness). Shown are sectoral Spearman correlation coefficients for ST, superotemporal; SN, superonasal; N, nasal; IN, inferonasal; IT, inferotemporal; and T, temporal sectors. The map is based on the structure-function map developed by Garway-Heath and colleagues, showing the relationship between areas in the visual field and regions on the optic nerve head. 8,9 X, statistically significant difference between correlations for FDF and SAP; †, statistically significant difference between correlations for FDF and FDT; ▪, statistically significant difference between correlations for FDT and SAP.
Figure. 
 
Structure-function relationship between flicker defined form perimetry, Matrix frequency doubling technology perimetry, standard automated perimetry, and confocal scanning laser ophthalmoscopy (rim area, rim volume, cup-disc-area-ratio, and RNFL thickness). Shown are sectoral Spearman correlation coefficients for ST, superotemporal; SN, superonasal; N, nasal; IN, inferonasal; IT, inferotemporal; and T, temporal sectors. The map is based on the structure-function map developed by Garway-Heath and colleagues, showing the relationship between areas in the visual field and regions on the optic nerve head. 8,9 X, statistically significant difference between correlations for FDF and SAP; †, statistically significant difference between correlations for FDF and FDT; ▪, statistically significant difference between correlations for FDT and SAP.
Table. 
 
Demographic Data of the Entire Study Group, the Early Glaucoma Group and the Moderate/Advanced Glaucoma Group
Table. 
 
Demographic Data of the Entire Study Group, the Early Glaucoma Group and the Moderate/Advanced Glaucoma Group
Entire Group (n = 76) Early Glaucoma Group (n = 26) Moderate/ Advanced Glaucoma Group (n = 50) P Value
Age 65.47 ± 8.23 (43.21; 80.68) 65.56 ± 8.22 (43.21; 80.68) 65.42 ± 8.24 (43.93; 79.84) 0.94
Mean RE 0.21 ± 1.97 (−4.75; +4.25) 0.35 ± 2.11 (−4.50; +4.25) 0.15 ± 1.88 (−4.75; 3.25) 0.68
Mean cylinder −0.67 ± 0.60 (−2.75; +0.75) −0.65 ± 0.60 (−2.25; +0.50) −0.68 ± 0.60 (−2.75; 0.75) 0.86
Mean SE −0.12 ± 1.97 (−5.63; 3.75) 0.20 ± 2.17 (−5.13; 3.75) −0.19 ± 1.85 (−5.63; 3.00) 0.66
logMAR VA 0.09 ± 0.08 (−0.10; +0.20) 0.10 ± 0.08 (0.00; +0.20) 0.08 ± 0.08 (−0.10; 0.20) 0.27
IOP 16.22 ± 3.02 (10.0; 27.0) 16.81 ± 2.90 (10.0; 22.0) 15.92 ± 3.03 (10.0; 27.0) 0.23
Mean CCT 524.33 ± 38.07 (441; 635) 523.50 ± 33.23 (441.00; 582.00) 524.76 ± 40.35 (460.0; 635.0) 0.89
MD SAP −7.92 ± 4.65 (−22.0; −0.25) −3.63 ± 1.94 (−8.07; −0.25) −9.79 ± 4.00 (−22.0; −3.12) <0.001
MD FDT −9.41 ± 4.25 (−19.50; −0.36) −6.61 ± 3.78 (−18.37; −0.36) −10.86 ± 3.80 (−19.50; −2.57) <0.001
MD FDF −13.69 ± 4.19 (−21.97; −3.38) −11.33 ± 4.32 (−20.03; −3.38) −14.92 ± 3.63 (−21.97; −6.50) <0.01
PSD SAP 8.41 ± 4.06 (1.62; 15.00) 4.48 ± 2.95 (1.62; 12.06) 10.46 ± 2.92 (4.60; 15.00) <0.001
PSD FDT 6.70 ± 2.06 (1.98; 11.05) 5.78 ± 1.88 (2.41; 10.12) 7.18 ± 2.03 (1.98; 11.05) 0.02
PSD FDF 5.52 ± 2.04 (1.07; 10.26) 6.17 ± 1.67 (3.12; 9.06) 5.19 ± 2.17 (1.07; 10.26) 0.062
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×