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Matrix perimetry is a new iteration of frequency‐doubling technology (FDT) which uses a smaller target size in the standard achromatic perimetry presentation pattern.
To compare the performance of matrix and Swedish interactive thresholding algorithm (SITA) perimetry in detecting glaucoma diagnosed by structural assessment.
Prospective cross‐sectional study.
76 eyes from 15 healthy subjects and 61 consecutive glaucoma suspects and patients with glaucoma were included. All patients underwent optic nerve head (ONH) photography, SITA and matrix perimetries, and optical coherence tomography (OCT) within a 6‐month period. Glaucoma diagnosis was established by either glaucomatous optic neuropathy or OCT by assessing retinal nerve fibre layer (RNFL) thickness. Mean deviation (MD), pattern standard deviation (PSD), glaucoma hemifield test and cluster of abnormal testing locations were recorded from matrix and SITA perimetries.
Similar correlations were observed with matrix and SITA perimetry MD and PSD with either cup‐to‐disc ratio or OCT mean RNFL. The area under the receiver operating characteristic (AROC) curves of MD and PSD for discriminating between healthy and glaucomatous eyes ranged from 0.69 to 0.81 for matrix perimetry and from 0.75 to 0.77 for SITA perimetry. There were no significant differences among any corresponding matrix and SITA perimetry AROCs.
Matrix and SITA perimetries had similar capabilities for distinguishing between healthy and glaucomatous eyes regardless of whether the diagnosis was established by ONH or OCT–RNFL assessment.
Glaucoma is an optic neuropathy characterised by a gradual loss of retinal ganglion cells and thinning of the retinal nerve fibre layer (RNFL).1,2 Previous studies have shown that the glaucomatous abnormality is detectable on achromatic perimetry only when significant RNFL loss has already occurred.3 Moreover, considerable short‐ and long‐term fluctuations were observed with visual field (VF) in healthy subjects4 and to a greater extent in patients with glaucoma,5 which further delay glaucoma detection.
Frequency‐doubling technology (FDT) uses low spatial frequency sinusoidal grating in a high temporal frequency counterphase flicker to test the VF. The stimulus creates an illusion of doubling the spatial frequency. Several studies have reported high sensitivity and specificity of the commercially available FDT for glaucoma detection.6,7 FDT was also found to predict the appearance of standard achromatic perimetry (SAP) defect in glaucoma suspects 8 and to predict the progression of SAP defect in patients with glaucoma.9
SAP uses 0.43°‐sized stimuli (Goldman III) to quantify visual sensitivity at each test location. The conventional FDT device uses 10°×10° square stimuli. A new iteration of FDT (Matrix; Carl Zeiss Meditec, Dublin, California, USA), which was recently released for commercial use, utilises smaller stimuli of 5°×5° squares. The smaller targets allow a spatial testing distribution that is similar to conventional SAP with a spacing of 6° between the centres of adjacent points. The greater stimulus sampling density of matrix perimetry in comparison with conventional FDT might improve the ability to detect and map early VF defects.10
In a previous study, we tested the performance of matrix preimetry as compared with Swedish interactive thresholding algorithm (SITA) perimetry at a pointwise level in subjects with VF glaucomatous defects.11 The purpose of this study was to compare the ability of matrix perimetry and conventional SAP in differentiating between healthy and glaucomatous eyes. The classification of the eyes in this study was based on structural findings.
Sixty‐one eyes from 61 consecutive subjects evaluated on the Glaucoma Service at UPMC Eye Center, Pittsburgh, Pennsylvania, USA were enrolled in this cross‐sectional study. Fifteen eyes from 15 healthy volunteers were also included. One eye was randomly selected if both eyes were eligible for the study.
Inclusion criteria were best‐corrected visual acuity20/40 and refractive error within ±6.00 Diopters (spherical equivalent) of emmetropia. Eyes were excluded if they had signs of retinal or optic nerve head (ONH) pathologies other than glaucoma, when media opacities interfered with fundus imaging, or if the patient was using medications that are known to affect retinal thickness. Patients were also excluded if they had systemic diseases that might affect the retina or VF or if they had any previous operation in the study eye except for uneventful cataract extraction.
All subjects had comprehensive ophthalmic evaluation, and all tests were completed within 6 months. The evaluation included medical history, best‐corrected visual acuity, manifest refraction, intraocular pressure (IOP) measurements by Goldmann applanation tonometry, slit‐lamp examination before and after pupil dilation, colour ONH photography, VF testing with standard 24–2 SITA perimetry, (Carl Zeiss Meditec) and 24–2 matrix perimetry, and optical coherence tomography (OCT) scanning of peripapillary RNFL. To eliminate the possible effect of IOP on the perimetry, all IOPs were maintained at <21 mm Hg at the time of the testing.
The study was approved by the institutional review board ethics committee, and adhered to Declaration of Helsinki and Health Insurance Portability and Accountability Act regulations. Informed consent was obtained from all participants.
For both perimetry devices, a reliable VF test was with <30% fixation losses, false positive or false negative responses. The order of perimetric testing was randomly determined and both SITA and matrix perimetries were performed on a single day. To represent a typical glaucoma population, the study group included subjects with (n=47) and without (n=29) previous experience with automated perimetry.
For both perimetry methods, glaucomatous VF loss was defined as a glaucoma hemifield test (GHT) outside normal limits (GHT definition), mean deviation (MD) probability <5% (MD definition), pattern standard deviation (PSD) probability <5% (PSD definition), or a cluster of three or more adjacent non‐edge points in typically glaucomatous locations, all of which were depressed on the pattern deviation plot at a p <5% level and one of which was depressed at a p <1% level (cluster definition).
Two independent structural methods were used as gold standards in defining the diagnosis: glaucoma expert assessment of stereoscopic ONH photographs and OCT.
All participants had stereoscopic ONH photographs taken using a Nidek 3‐Dx camera (Nidek, Fremont, California, USA). The photos were taken after pupillary dilation with 1% tropicamide and 2.5% phenylephrine hydrochloride. Three glaucoma experts independently evaluated the ONH photographs and were blinded to any clinical information. ONH photograph assessment was conducted using a stereoviewer (Screen‐UV stereoscope; PSMfg, Portland, Oregon) and each observer estimated the vertical cup‐to‐disc (C/D) ratio and the average among the observers was used for the analysis. Glaucomatous optic neuropathy (GON) was defined as global or localised neuroretinal rim thinning, disc haemorrhages or RNFL defect. Glaucoma diagnosis was established if GON was observed by two or more experts. In addition, quantitative evaluation was established by averaged C/D ratio among the three experts.
All OCT scans were performed using fast RNFL scanning method of Stratus OCT V.4.0 (Carl Zeiss Meditec). Poor‐quality scans were defined as those with signal strength <6 and/or the presence of overt misalignment of the surface‐detection algorithm of at least 15 consecutive or 20 cumulative per cent of the scan.
Two diagnostic criteria were used to define glaucomatous OCT changes: (1) global mean RNFL outside normal limits which corresponds to measurements <1% for age‐matched normative database (OCT criterion 1); and (2) in the presence of at least one of the clock hour, quadrantic or global mean RNFL thickness measurements <1% for age‐matched normative database as defined by Stratus OCT (OCT criterion 2). These criteria were chosen as OCT criterion 1 simulates the criteria commonly used in clinical practice and OCT criterion 2 was reported to provide the highest specificity and sensitivity to differentiate between healthy and glaucomatous eyes.12
As this study evaluated the performance of functional assessment as determined by perimetry, the classification of eyes as glaucomatous was made with the presence of any one of three structural criteria: GON; OCT criterion 1; or OCT criterion 2.
The entire cohort included patients with a wide range of perimetric abnormalities with or without previous VF testing experience. A subset analysis was performed for patients who had previous experience with SAP to determine the influence of experience on outcome parameters.
The R language and environment for statistical computing was used to perform the statistical analyses.13 Correlation analysis was performed with Spearman's rank order correlations. The differences between dependent Spearman's correlations were tested with William's t test. Sensitivity and specificity of the perimetric devices were compared using marginal logistic regression models based on generalised estimating equations. Bonferroni's correction was used to account for multiple comparisons of specificity and sensitivity. The differences between areas under the receiver operating characteristic (AROC) curves were calculated using the method of DeLong et al.14 The level of significance was set to 0.05.
The average age of the entire group was 52.8 (14.8) years. Twenty‐three eyes did not show any VF abnormality, 69 eyes had SITA perimetry MD>−6 dB, 6 had MD between −6 and −12 dB and 2 had MD<−12 dB.
Using the GON criteria, 35 eyes were defined as abnormal and 41 eyes were defined as normal. In all, 62 eyes were defined as abnormal by OCT criterion 2 (14 normals), 15 of them were also labelled as abnormal based on OCT criterion 1 (61 normals). In all, 47 subjects had previous experience with automated perimetry. The mean (SD) SITA perimetry MDs of the experienced and non‐experienced groups were −2.56 (4.95) dB and −0.54 (1.56) dB, respectively (p=0.01). SITA perimetry PSDs were 1.79 (0.59) dB and 3.31 (3.37) dB (p=0.004), respectively, for the two subgroups.
Eight of the 30 eyes (26.7%) that were defined as having glaucoma by SITA (either GHT, PSD or cluster definition) were judged to be normal by matrix perimetry. Among the 46 subjects with normal SITA perimetry, 15 (32.6%) had abnormal matrix perimetry.
FiguresFigures 1 and 22 shows the scatter plots of matrix and SITA perimetry MD and PSD with the degree of structural abnormality by ONH and OCT evaluation. Overall, moderate correlation coefficients were found between both MD and PSD of the perimetric devices and between the C/D ratio and OCT by assessing mean RNFL (table 11).). When analysing the perimetry‐experienced subgroup separately, there was an improved correlation for both devices. None of the differences between corresponding correlations for the two perimetric devices were significant in either the entire group or in the perimetry‐experienced subgroup.
TablesTables 2 and 33 present the AROC curves for matrix and SITA perimetry MD and PSD for differentiating between healthy and glaucomatous eyes as defined by the structural diagnostic criteria: GON, OCT criterion 1 and OCT criterion 2. None of the differences between any corresponding matrix and SITA perimetry AROC were significant either in the entire study group or in the experienced subgroup.
AROCs for discriminating between eyes based on the structural criteria and using matrix and SITA perimetry MD and PSD were compared between subjects with (n=47) and without (n=29) previous experience in perimetry. There was a trend for improvement in AROCs for the various parameters when using GON and OCT criterion 2 definitions in subjects with previous experience, which did not reach the level of significance except for PSD and OCT criterion 2 definition (experienced 0.904, non‐experienced 0.529; p=0.03). An opposite trend was observed (higher AROC for non‐experienced than experienced VF taker) for matrix perimetry with both MD and PSD when using the definition of OCT criterion 1, but it did not reach a significant level. AROCs for SITA petrimetry with both MD and PSD when using the definition of OCT criterion 1 were not significantly different between experienced and non‐experienced groups.
Sensitivities and specificities for discriminating between healthy and glaucomatous eyes (as defined by structural assessment) were calculated for matrix and SITA parameters based on GHT, the probability values for MD and PSD, or by the presence of clusters (fig 33).). Overall, matrix perimetry sensitivities ranged from 0.31 to 0.87 with specificities between 0.59 and 0.93 for the various parameters and criteria. SITA perimetry sensitivities for the various parameters ranged from 0.36 to 0.73 with specificities between 0.6 and 1.00. In the VF‐experienced subgroup (fig 44),), there were similar ranges for sensitivity and specificity for both devices as those reported for the entire group. To assess if the difference between the devices for sensitivity and specificity was significant, we modelled sensitivity and specificity as a function of age, device and VF experience allowing for possible interactions among the factors. Two of the marginal regression models showed a significant difference between the devices after Bonferroni correction. Specificity was higher for the SITA perimetry GHT compared with matrix perimetry GHT when using the OCT criterion 2 (adjusting for VF experience). Specificity was also higher for SITA perimetry MD compared with matrix perimetry MD when using the OCT criterion 2 (adjusting for VF experience and age).
Matrix perimetry uses the same technology as FDT, but with a smaller stimulus, and with a number and pattern of testing points similar to conventional SAP. The larger number of testing points allows a higher spatial resolution VF assessment, potentially making matrix perimetry a better tool for quantification of functional glaucomatous damage. Although the threshold values reported by matrix perimetry are derived from physical properties that are substantially different from SAP, the results of matrix perimetry are given in decibels adjusted to approximate the values provided by SAP. In a previous study we demonstrated that matrix perimetry delineated significantly smaller and deeper scotomas as compared with SITA perimetry.11 However, in 36% of eyes that showed SITA–VF defects there was a completely normal matrix perimetry. Using various structural diagnostic criteria that are common in the clinical setting (glaucomatous optic neuropathy and OCT mean RNFL) or a sensitive method to detect structural glaucomatous abnormality (OCT criterion 2), we could not find any significant difference between matrix and SITA perimetries in their ability to discriminate between healthy and glaucomatous eyes. This was evidenced by using the global index values (MD and PSD; PSD;tablestables 2, 33),), the probability of abnormality for MD and PSD ((figsfigs 3, 44)) and the classification criteria commonly used in clinical practice (GHT and cluster; cluster;figsfigs 3, 44).). As margin blending was not used in the present study, it is possible that edge contrast effects could have influenced sensitivity. Sensitivity might have been affected further by fatigue, as both VF tests were performed on the same day. However, as the order of testing was randomised, the fatigue factor would be expected to have had an equal effect on both types of perimetric testing. Nevertheless, because matrix perimetry testing might be more sensitive to fatigue effects, the effect of fatigue on sensitivity could have been greater on matrix perimetry testing than on SITA perimetry.15,16
This study included a wide range of glaucomatous abnormalities with predominantly early‐to‐moderate perimetric changes (87% of the glaucoma subjects had MD>−6 dB). The subgroup without previous perimetric experience included subjects with early functional damage (SITA MD=−0.54 dB, SITA PSD=1.79 dB), and, yet, no difference was observed in AROCs for differentiating between diseased and healthy eyes between matrix and SITA perimetries. Although previous studies have indicated that FDT is especially beneficial in detecting early glaucoma changes,9,17 we did not find any advantage in detecting disease with matrix procedures compared with SITA perimetry.
We intentionally included subjects with and without experience of perimetry tests to simulate the common situation in a glaucoma service. The results of automated perimetry were reported to improve with experience in perimetry in both healthy subjects and patients with glaucoma.18,19,20 A learning effect was also noted with FDT,21,22 and was evident in patients with glaucoma with previous SAP experience.23,24 To estimate the performance in experienced subjects, we performed a subset analysis in subjects with previous experience in perimetry testing. In the differentiation between diseased and healthy eyes, experienced subjects had higher AROCs as compared with non‐experienced subjects, however, except for one parameter these differences were not significant. A trend of worse performance in experienced subjects, as judged by AROCs, appeared for matrix perimetry when using the OCT criterion 1 for glaucoma diagnosis. This difference in AROCs was not significant. The reason for the inverted trend with this criterion is not clear. The majority of the subjects in this subgroup had previous experience with SITA, but not with FDT; therefore, this disproportionate experience with one of the technologies could have biased the findings.
The study was also limited by the use of accepted levels of false positives and false negatives in the inclusion/exclusion criteria.25,26 However, a recent study suggests that the acceptable level of false positives and false negatives previously accepted in clinical practice and large‐scale studies might underestimate the actual level of occurrences of false positives and false negatives in VF examinations.27 The use of previously accepted standards could have caused us to underestimate subjects' errors, there by introducing an inaccurate determination of the severity of VF loss.
Both matrix and SITA perimetries had moderate correlation with either C/D ratio or OCT mean RNFL (table 11,, ,figsfigs 1, 22),), similar to those reported previously for SAP.28,29 We could not detect any significant difference in the correlation between matrix and SITA perimetries, and structural measurements and, therefore, neither of the devices provided an advantage in terms of structure–function agreement. Recent case studies suggested that glaucomatous neuropathy might extend throughout the visual system including the lateral geniculate nucleus and visual cortex.30 This in turn might cause the moderate correlation between structure and function that is observed in this study.
Using MD and PSD as continuous variables, the AROC curves for discriminating between healthy and glaucomatous eyes for matrix and SITA perimetries were similar to those reported previously ((tablestables 2, 33).31 In the present study, none of the AROC comparisons between matrix and SITA perimetries were significant.
The specificities and sensitivities of functional parameters (probability of abnormality of the global indexes, GHT and cluster criteria) in eyes diagnosed by structural criteria were similar for both devices. Two significant differences were observed when using the OCT criterion 2. SITA perimetry had higher sensitivity, as compared with matrix perimetry, for the MD and GHT functional parameters.
In summary, we compared the abilities of matrix and SITA perimetries to discriminate between healthy eyes and glaucomatous eyes as defined by structural assessment. Matrix perimetry was found to be comparable to SITA perimetry in glaucoma detection.
AROC - area under the receiver operating characteristic
C/D - cup‐to‐disc
FDT - frequency‐doubling technology
GHT - glaucoma hemifield test
GON - glaucomatous optic neuropathy
IOP - intraocular pressure
MD - mean deviation
OCT - optical coherence tomography
ONH - optic nerve head
PSD - pattern standard deviation
RNFL - retinal nerve fibre layer
SAP - standard achromatic perimetry
SITA - Swedish interactive thresholding algorithm
VF - visual field
Funding: This study is supported in part by National Institute of Health grants RO1‐EY013178‐6, P30‐EY008098 (Bethesda, Maryland, USA), The Eye and Ear Foundation (Pittsburgh, Pennsylvania, USA) and an unrestricted grant from Research to Prevent Blindness, (New York, New York, USA).
Competing interests: JSS receives royalties for intellectual property licensed to Carl Zeiss Meditec, Dublin, California, USA.