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1From the Departments of Ophthalmology, School of Medicine, and 2Epidemiology and International Health, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama.
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Abstract |
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METHODS. Data from 79 glaucomatous and 149 normal eyes of 228 subjects were included in the analysis. Three independent graders evaluated ONH stereophotographs. Receiver operating characteristic curves were constructed for each technique and sensitivity was estimated at 80% of specificity. Comparisons of areas under these curves (aROC) and agreement (
) were determined between stereophoto grading and best parameter from each technique.
RESULTS. Stereophotograph grading had the largest aROC and sensitivity (0.903, 77.22%) in comparison with the best parameter from each technique: HRT-II global cup-to-disc area ratio (0.861, 75.95%); GDx-VCC Nerve Fiber Indicator (NFI; 0.836, 68.35%); and StratusOCT retinal nerve fiber layer (RNFL) thickness (0.844, 69.62%), ONH vertical integrated rim area (VIRA; 0.854, 73.42%), and macular thickness (0.815, 67.09%). The between photograph grading and imaging parameters was 0.71 for StratusOCT-VIRA, 0.57 for HRT-II cup-to-disc area ratio, 0.51 for GDX-VCC NFI, 0.33 for StratusOCT RNFL, and 0.28 for StratusOCT macular thickness.
CONCLUSIONS. Similar diagnostic ability was found for all imaging techniques, but none demonstrated superiority to subjective assessment of the ONH. Agreement between disease classification with subjective assessment of ONH and imaging techniques was greater for techniques that evaluate ONH topography than with techniques that evaluate RNFL parameters. A combination of subjective ONH evaluation with RNFL parameters provides additive information, may have clinical impact, and deserves to be considered in the design of future studies comparing objective techniques with subjective evaluation by general eye care providers.
Since the earlier studies, significant modifications have occurred with each of these quantitative imaging techniques that have improved their ability to detect glaucomatous damage. With scanning laser polarimetry (GDx-VCC; Carl Zeiss Meditec, Inc., Dublin, CA), a conversion to variable corneal compensation that provides individualized adjustment of anterior segment birefringence has improved the sensitivity and specificity of this technique.6 7 The current generation of optical coherence tomography (StratusOCT; Carl Zeiss Meditec, Inc.) has increased scan rate and scan resolution and can also be used to obtain macular and ONH measurements.8 The most recent version of the confocal scanning laser ophthalmoscope (HRT II; Heidelberg Engineering, Heidelberg, Germany) has been modified significantly with automation of the examination procedure focused on optic disc topography, which has improved the reproducibility and efficacy of this instrument in the detection of glaucoma.2 4 9 10
A recent study by Medeiros et al.11 using the current version of these instruments has demonstrated that each performs with similar efficacy in the diagnosis of glaucoma. However, there was no comparison between these new versions of objective imaging methods with subjective ONH evaluation or objective evaluation of the optic nerve head with ONH analysis and macular thickness from StratusOCT. The purpose of this study was to compare the diagnostic ability of the confocal scanning laser ophthalmoscopy with the HRT II, scanning laser polarimetry with the GDX-VCC, and retinal nerve fiber layer thickness, ONH analysis and macular thickness measurements with the StratusOCT with subjective masked expert assessment of stereophotographs in the same study population.
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Methods |
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Normal participants were included if they had bilateral highest documented IOP of 
22 mm Hg; bilateral normal eye examination findings, including dilated fundus examination; and bilateral normal visual field results defined as pattern standard deviation (PSD) within the 95% normal limits and a glaucoma hemifield test (GHT) result within 99% limits. Glaucomatous visual field loss was defined as PSD outside 95% normal limits or GHT outside 99% normal limits, confirmed with a second visual field test. Patients with a mean defect of –15 dB were excluded. In addition, subjects were excluded if they had best corrected visual acuity worse than 20/40, spherical refraction outside ±5.0 D and cylinder refraction outside ± 3.0 D, or unreliable visual fields (fixation losses and false-positive and -negative responses exceeding 30%) or were using medications known to affect visual sensitivity at the time of visual field testing, those with comorbid ophthalmic or neurologic surgery or disease and those with inadequate imaging–photograph quality were also excluded.
Simultaneous ONH stereophotographs were obtained after dilation of the pupil with a fundus camera (3-Dx; Nidek Technology America, Inc., Greensboro NC). Three masked experienced observers (CAG, BEM, JED-O) independently graded the ONH photographs according to a 5-point scale similar to the method described by Greaney et al.3 and Girkin et al.12 The grade increases with the clinical impression of glaucoma (1, definitely normal; 2, probably normal; 3, unsure; 4, probably glaucomatous; and 5, definitely glaucomatous). Criteria for classification was on the basis of the observing typical ONH characteristics consistent with glaucomatous optic neuropathy including the presence of neuroretinal rim thinning, notching, or undermining, nerve fiber layer defects, and optic disc hemorrhages. An overall photograph grade score was developed by the summation of scores to produce a 15-point scale. Furthermore, to compare this grading scale with more commonly used forced-choice grading; the stereophotographs were also graded in a dichotomous manner (glaucoma or normal) by two of the graders (JED-O, BEM), while the third grader (CAG) adjudicated cases of disagreement. The quality of the stereophotograph was evaluated at the time of masked grading. One participant had suboptimal quality on the stereophotograph and stereophotography was repeated, improving its quality.
ONH topography was obtained with the confocal scanning laser ophthalmoscope (HRT II). Details of the HRT II operation have been described before.13 14 15 Experienced operators (JED-O, SNA) evaluated image quality and outlined the disc margin while viewing stereoscopic photographs of the optic disc. The HRT II software-determined parameters of RNFL thickness, RNFL cross-sectional area, rim area and volume, mean height contour, cup area and volume, cup shape, mean cup depth, maximum cup depth, optic disc area, and cup-to-disc area ratio and results from discriminant analysis formulas developed by Bathija et al.,16 Mardin et al.,17 and Mikelberg et al.18 were included in the analysis. Topographies with acquisition sensitivity above 90%, SD greater than 40 µm, ONH not centered, excessive movement during acquisition, floaters over or adjacent to the ONH, poor clarity of image or framing were excluded (21 subjects). Most were excluded because of inadequate scan sensitivity and poor clarity (possibly because of reduced media clarity). The remaining had vitreous floaters adjacent to the disc or inadequate framing.
RNFL thickness was evaluated with both the StratusOCT and the GDx VCC (both Carl Zeiss Meditec Inc.). Details of StratusOCT operation have been described elsewhere.1 8 13 19 20 RNFL thickness measurements consisted of four quadrants and 12 sectors around the ONH (in clock hours). On left eyes (and transposed data from right eyes), these sectors corresponded to superior (11–1 o’clock), temporal (2–4 o’clock), inferior (5–7 o’clock) and nasal (8–10 o’clock) quadrants. The landmark option was used, and images were excluded if the video image had a poor quality, if the scan beam was not centered on the ONH, and if the subject was unable to maintain stable fixation. Twelve subjects were excluded.
Details of the GDX operation have been described previously,20 6 21 and parameters included were TSNIT (temporal, superior, nasal, inferior, and temporal) average, superior average, inferior average, TSNIT SD, intereye symmetry, superior and inferior average, superior and inferior ratio, superior nasal, maximum, inferior and ellipse modulation, superior and inferior normalized area, and nerve fiber indicator (NFI). NFI is a support vector machine derived parameter indicating the likelihood that an eye has glaucoma.22 The mean of three images was calculated. Images were considered of good quality if there was good fixation, minimal eye movement, and good illumination on the reflectance image, with no artifacts on the retardance image. Ten subjects were excluded because of poor image quality.
Automated ONH measurements were obtained with the StratusOCT, using the ONH protocol of six 4-mm radial line scans centered on the ONH. The mean from three images was used for the analysis, and the parameters included were vertical integrated rim area, horizontal integrated rim width, cup and rim area, cup-to-disc area ratio, and vertical and horizontal cup-to-disc ratio. Images were excluded if the video image was of inadequate quality, the ONH was not properly centered, and fixation losses were present. Thirteen subjects were excluded because of poor image quality.
Macular thickness was obtained with the StratusOCT, using six 6-mm radial-line scans centered on the fovea. Three measurements were obtained, and the mean was determined for each of nine locations (fovea, temporal inner and outer macula, superior inner and outer macula, nasal inner and outer macula, and inferior inner and outer macula). Similar quality-control criteria as used in the ONH and RNFL protocols were implemented, and 12 subjects were excluded.
Including control subjects with previously normal eye examination results is likely to bias the results in favor of subjective assessment of the optic disc. Although classification of control eyes using visual field criterion alone and ignoring clinical examination results would be optimal in comparing stereophotos with quantitative imaging, this strategy may create some degree of misclassification bias with the inclusion of preperimetric glaucoma. To investigate, we explored the comparison in two separate analyses. One using control subjects defined by normal visual fields and a normal eye examination and a secondary analysis using control subjects defined by visual fields alone. For this secondary analysis, we added 29 additional eyes from 29 participants enrolled as control subjects during the same period. These subjects were added to the control group because they had reliable normal visual fields, but we ignored any information from the initial dilated fundus examination. During the screening interview, the subjects self-reported as having no ocular disease, as did the 149 control subjects originally enrolled.
Two-tailed t-tests were used to compare glaucomatous and normal eyes with respect to continuous variables with normal distribution based on histograms plots. Nonparametric (Wilcoxon) tests were used for continuous variables not distributed normally. Similar group comparisons were conducted for categorical variables by 
2 tests.
To compare the relative ability of each imaging technique in discriminating glaucomatous from normal eyes, the area under the receiver operating characteristic curve (aROC) adjusted for age was calculated for each of the quantitative imaging parameters and for the overall stereophotograph grade. The aROC provides an evaluation of the ability to discriminate between those who experience the outcome of interest and those who do not. A logistic regression model containing the stereophotograph grade was compared to a model contained the most efficient (i.e., largest aROC) imaging parameters for each instrument. Sensitivity was assessed fixed at 80% of specificity. Statistical comparisons of the aROC were performed using previously described methods,23 24 adjusting for multiple comparisons with Bonferroni correction.
To compare the agreement in disease classification between the techniques, upper and lower limits from the control group for each best parameter were defined as two standard deviations from the control population mean, if the data had a normal distribution as determined with histograms plots or within the 2.5 to 97.5 percentiles otherwise. Eyes that fell outside these normal limits were classified as glaucomatous and agreement with dichotomous classification from stereophotograph grading was evaluated with linear statistics. The strength of agreement was interpreted as follows: 0.0, no agreement; <0.40, fair agreement; 0.40 to 0.59, moderate agreement; 0.60 to 0.75, good agreement; >0.75 to 0.99, excellent agreement; and 1.0, perfect agreement.25 Statistical analyses were performed on computer (SAS and JMP; SAS Institute, Inc., Cary, NC).
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Results |
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The glaucoma group had an average mean deviation (MD ± SD) of –3.8 ± 3.6 dB and control group had an average MD of 0.2 ± 1.0 dB. Furthermore, 44 (55.7%) eyes had an early defect, 31 (39.2%) eyes had a moderate defect, and 4 (5.1%) eyes had a severe defect, according to the classification of severity of field loss by Hodapp et al..26 Thus, the cohort with glaucomatous eyes predominantly had early to moderate visual field defects.
The stereophotograph grading obtained from the 15-point likelihood score scale fell within a range of 3 to 10 for the control group (mean 5.2 ± 1.9 SD) and 75% of control eyes received a score from 3 to 6. In the glaucoma group, the range of score was from 3 to 15 (mean, 10.6 ± 3.7 SD) and 70% of glaucomatous eyes received a score from 9 to 15. The mean of scores significantly differed between the two study groups (P < 0.0001). The 15-point likelihood score for stereophotograph grading had an overall sensitivity of 77.2% fixed at 
80.0% specificity (aROC = 0.903; SE = 0.03), adjusted for age.
Significant differences were found between control and glaucomatous eyes in GDx VCC, HRT II, and StratusOCT measurements (Table 1 GDx VCC, Table 2 global HRT II, and Table 3 StratusOCT). Also shown are the aROC and sensitivities at fixed specificity of at least 80%. Data for sectoral HRT II parameters are not shown because of space limitations. To compare diagnostic methods, we selected the parameter with the largest aROC from each technique. For GDx, the NFI showed the largest aROC (0.836). For the HRT II, the best global parameter was cup-to-disc area ratio, with an aROC of 0.861 and the best sectoral HRT II parameter was temporal inferior cup volume with a comparable aROC (0.854). For the StratusOCT, the ONH analysis parameter with the largest aROC was the vertical integrated rim area (0.854). Similarly, the RNFL thickness at the inferior quadrant (6:00 sector) had the largest aROC (0.844). Last, for the macular thickness, the largest aROC was obtained from thickness at the superior outer macular location (0.815).
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Discussion |
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Compared with the previous study using the newer generation of these instruments,11 consistent results were found on some of the best parameters from each instrument. For example, the largest aROC found for GDx VCC was NFI and the largest aROC found for StratusOCT was RNFL thickness at inferior sector. For the HRT II, however, global parameters such as cup-to-disc area ratio gave the largest aROC. This is in contrast to the high aROC, sensitivity, and specificity reported for linear discriminant functions (Bathija et al.,16 Mikelberg et al.,18 and Mardin et al.17 ). These discrepancies may reflect differences between study populations in the present study and that in others and demonstrates the need to evaluate these discriminant functions in study populations independent from the study populations from which they were developed.
The aROCs, sensitivities, and specificities reported in the present study are lower than the ones reported by Greaney et al.3 These lower values may reflect differences in enrollment criteria for control subjects. The present study obtained control subjects from those seeking eye care from referring practices or from employees who obtain eye care services at our facility, which may better approximate the source population for the cases compared with other studies, which have demonstrated greater diagnostic performance. If so, this study would more accurately reflect the performance of these techniques in the screening setting.
Although expert consensus assessment of masked stereophotographs demonstrated the highest performance in discriminating glaucomatous and nonglaucomatous eyes, this result may not reflect optic nerve head assessment in clinical practice. Level of training has been shown to affect stereophotograph grading, where glaucoma experts performed better than optometrists, residents, and general ophthalmologists.27 In addition, the optic nerve head evaluation in clinical practice is often performed in the busy clinical setting with less time for thorough assessment. Thus, this study may overestimate the diagnostic performance of subjective optic nerve head assessment as reflected in the primary care setting. Furthermore, subjects recruited as part of the control group are likely to have nonglaucomatous optic disc appearance because of the low prevalence of glaucoma in the normal population,28 which was the source population for the control subjects.
Macular thickness had a significantly worse discriminatory ability than stereophotograph grading and the other imaging techniques. This finding is consistent with a study by Medeiros et al.29 A probable explanation is that most of our glaucoma eyes had early to moderate visual field loss, and more advanced cases may produce greater changes at the macular thickness than the changes observed in our study population.
A substantial agreement was found between stereophotograph grading and results from StratusOCT ONH analysis, suggesting these two techniques detect similar characteristics of the optic nerve head and further supports the usefulness of StratusOCT technique. Furthermore, a greater number of eyes were correctly classified by combining RNFL parameters (GDx VCC NFI and StratusOCT RNFL at the temporal inferior region) with subjective disc assessment than by combining ONH parameters (StratusOCT ONH analysis and HRT II global cup-to-disc area ratio) with subjective disc assessment. This finding probably reflects the higher level of agreement between subjective disc evaluation and ONH imaging methods. Thus, much of the information obtained from ONH imaging may be assessed subjectively, whereas the RNFL measurements may provide a greater degree of additive information when combined with subjective assessment. This further information obtained from the combination of subjective evaluation of ONH and objective quantitative evaluation of RNLF may have a clinical impact, and such combination should be considered in the design of future studies, particularly when the subjective evaluation is perform by general eye care providers.
Ideally, classification of control eyes using visual field criterion alone would be optimal in comparing the results of stereophotos with quantitative imaging results. However, this strategy may create some degree of misclassification bias with the inclusion of preperimetric glaucoma. Alternatively, including control subjects with previously normal eye examination results is likely to bias the results in favor of subjective assessment of the optic disc. To investigate, we explored the comparison using both control subjects defined by normal visual fields and a normal eye examination and those defined by normal visual fields alone, adding the subjects who were eliminated based on abnormal-appearing optic discs. Although the diagnostic performance was predictably worse with all techniques when the field alone defined control subjects, we found that subjective assessment of the optic disc performed with significantly greater efficacy than did quantitative optic disc imaging.
In conclusion, subjective assessment of the ONH provided the best diagnostic efficacy in the detection of glaucoma defined by visual field defects alone. After correcting for multiple comparisons, differences between subjective ONH assessment and StratusOCT (ONH analysis and RNFL thickness) and HRT II were of borderline significance, whereas GDx VCC and macular thickness performed significantly less well than subjective ONH assessment. However, the optimal parameters from these newer generations of quantitative imaging techniques to detect glaucoma did not differ significantly in their discriminatory ability when compared with each other. In addition, combining RNFL measurements with subjective optic nerve head assessment correctly diagnosed more subjects with glaucoma than did the combination of optic nerve head topography with subjective disc assessment. Studies comparing objective techniques with subjective evaluation by general eye care providers will help to determine the usefulness of these techniques in clinical settings.
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Footnotes |
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Submitted for publication September 19, 2005; revised January 10 and March 24, 2006; accepted May 25, 2006.
Disclosure: J.E. DeLeón-Ortega, None; S.N. Arthur, None; G. McGwin, Jr, None; A. Xie, None; B.E. Monheit, None; C.A. Girkin, None
The publication costs of this article were defrayed in part by page charge payment. This article must therefore be marked "advertisement" in accordance with 18 U.S.C. 
1734 solely to indicate this fact.
Corresponding author: Christopher A. Girkin, UAB Department of Ophthalmology, 700 South 18th Street, Suite 406, Birmingham, AL 35233; cgirkin{at}uab.edu.
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