Patients from this study were included in a prospective longitudinal study designed to evaluate optic nerve structure and visual function in glaucoma (Diagnostic Innovations in Glaucoma Study) conducted at the Hamilton Glaucoma Center, University of California, San Diego. Patients in the Diagnostic Innovations in Glaucoma Study were longitudinally evaluated according to a preestablished protocol that included regular follow-up visits in which patients underwent clinical examination and several other imaging and functional tests. All the data were entered in a computer database. All patients from the Diagnostic Innovations in Glaucoma Study who met the inclusion criteria described below were enrolled in the current study. Informed consent was obtained from all participants. The University of California San Diego Human Subjects Committee approved all protocols, and the methods described adhered to the tenets of the Declaration of Helsinki.
Each subject underwent a comprehensive ophthalmologic examination including review of medical history, best-corrected visual acuity (BCVA), slit-lamp biomicroscopy, IOP measurement using Goldmann applanation tonometry, gonioscopy, dilated fundoscopic examination using a 78-diopter (D) lens, stereoscopic optic disc photography, and standard automated perimetry using the 24-2 Swedish Interactive Threshold Algorithm (Carl Zeiss Meditec Inc., Dublin, CA). To be included, subjects had to have BCVA of 20/40 or better, spherical refraction within ±5.0 D and cylinder correction within ±3.0 D, and open angles on gonioscopy. Eyes with coexisting retinal disease, uveitis, or nonglaucomatous optic neuropathy were also excluded from this investigation.
A cohort of patients suspected of having glaucoma was selected from our database. These patients were selected based on the presence of abnormal or suspicious appearance of the optic nerve from cross-sectional evaluation of stereophotographs at the time of imaging by 2 independent masked graders. Features characteristic of glaucomatous appearance of the optic disc were neuroretinal rim thinning, cupping, or suspicious/abnormal RNFL defects. A third grader reviewed the photographs in case of disagreement. All patients had normal VFs at time of imaging. A normal VF was defined as a mean deviation (MD) and pattern standard deviation within 95% confidence limits and a glaucoma hemifield test result within normal limits. Additionally, participants could not have had repeatable glaucomatous standard automated perimetry VF loss before the date of their examination with imaging instruments. All patients had been observed for at least 5 years before their imaging session.
These patients were then classified based on history of documented evidence of progressive glaucomatous change in the appearance of the optic disc occurring before the imaging sessions. Patients with documented evidence of progressive glaucomatous nerve damage at any time before both imaging sessions with SLP and CSLO were considered as having glaucoma. Progressive glaucomatous change in the appearance of the optic disc was assessed by simultaneous stereoscopic optic disc photographs (TRC-SS, Topcon Instrument Corp. of America, Paramus, NJ). Stereoscopic sets of slides were examined using a stereoscopic viewer (Asahi, Pentax, Tokyo, Japan). The photographs were evaluated by 2 experienced graders, and each was masked to the subject's identity and to the other test results. For inclusion, photographs needed to be graded adequate or better. For each patient, the most recent stereophotograph was compared with the oldest available one, to maximize the chance of detecting progressive optic disc change. Each observer was masked to the temporal sequence of the photographs. Definition of change was based on focal or diffuse thinning of the neuroretinal rim, increased excavation, or enlargement of RNFL defects. Changes in rim color, presence of disc hemorrhage, or progressive parapapillary atrophy was not sufficient for characterization of progression. Discrepancies between the 2 graders were resolved by either consensus or adjudication of a third experienced grader. Initial agreement between graders was obtained in 88% of cases (93% of agreement for judging no-progression and 83% of agreement for judging progression). When both eyes of the same patient showed progressive optic disc changes and met the inclusion criteria, one eye was randomly selected for inclusion in the study.
A total of 40 eyes with progressive glaucomatous optic disc change and no VF loss before the imaging sessions were included in the glaucoma group. These patients were observed for an average of 8.21±3.26 years.
Patients without any evidence of progressive change in the appearance of the optic disc or VF loss in both eyes, observed without any history of IOP-lowering treatment, were considered to be normal and used as the control group. One eye of each subject was randomized for analysis. A total of 42 eyes of 42 subjects were included in the normal group. These subjects were observed untreated for an average time of 8.97±3.08 years without showing any evidence of progressive damage to the optic nerve, providing reasonable confidence that they had only suspicious findings of disease but no glaucomatous damage.
Mean (± standard deviation [SD]) ages of glaucoma and normal subjects were 66.1±12.8 years and 62.5±13.1 years (P = 0.21). Medians (first quartile, third quartile) of MD of the VF closest to the imaging session were −1.28 decibels (−2.79, 0.09) and −0.54 decibels (−1.01, 0.26), respectively (P = 0.006).
Scanning Laser Polarimetry with Variable Corneal Compensation
Patients were imaged using a commercially available scanning laser polarimeter with variable corneal compensation (GDx VCC, software version 5.5.1, Carl Zeiss Meditec, Dublin, CA). The general principles of SLP and the algorithm used for variable corneal compensation have been described in detail elsewhere.1,12,13
Because corneal polarization axis and magnitude affect scanning laser polarimetry measurements and are not similar in all eyes, GDx VCC employs a variable corneal polarization compensator that allows eye-specific compensation of anterior chamber birefringence. After determining the axis and magnitude of corneal polarization in each eye by macular scanning,13
3 appropriately compensated retinal polarization images per eye were automatically obtained and combined to form each mean image used for analysis.
Assessment of GDx VCC image quality was performed by an experienced examiner masked to the subject's identity and results of the other tests. The assessment was based on the appearance of the reflectance image, presence of residual anterior segment retardation, and presence of an atypical pattern of retardation. To be classified as good, an image had to be focused and have evenly illuminated reflectance with a centered optic disc. To be acceptable, the mean image also had to have residual anterior segment retardation ≤ 15 nm and a typical scan score > 25. The typical scan score is a measure provided by the GDx VCC standard software that indicates the presence of atypical patterns of retardation that can generate spurious RNFL thickness measurements.14
GDx VCC parameters provided in the standard printout of the instrument and investigated in this study were superior average, inferior average, temporal–superior–nasal–inferior–temporal (TSNIT) average, TSNIT SD, and nerve fiber indicator (NFI). The NFI is calculated using a support vector machine algorithm based on several RNFL measures and assigns a number from 0 to 100 to each eye.15
The higher the NFI, the greater the likelihood the patient has glaucoma.
Confocal Scanning Laser Ophthalmoscopy
The HRT II (software version 3.0, Heidelberg Engineering, Dossenheim, Germany) was used to acquire CSLO images in the study. It uses confocal scanning laser principles to obtain a 3-dimensional topographic image of the optic nerve. Its working principles have been described in detail elsewhere.16
For each patient, 3 topographical images were obtained, combined, and automatically aligned to make a single mean topography for analysis. Magnification errors were corrected using patients' corneal curvature measurements. An experienced examiner outlined the optic disc margin on the mean topographic image while viewing stereoscopic photographs of the optic disc. Good images required a focused reflectance image with a standard deviation not greater than 50 μ
Topographical parameters included with HRT software and investigated in this study were disc area, cup area, rim area, cup-to-disc (C/D) area ratio, rim-to-disc area ratio, cup volume, rim volume, mean cup depth, maximum cup depth, mean height contour, height variation contour, cup shape measure, mean RNFL thickness, RNFL cross-sectional area, linear C/D ratio, and a linear discriminant function, from Mikelberg et al.17
The software on HRT II also incorporates Moorfields regression analysis (MRA), which is a comparison of the subject's rim area to a predicted rim area for a given disc area and age, based on confidence limits of a regression analysis derived from healthy subjects included in the instrument's normative database.18
This database contains information from 733 eyes of Caucasian subjects, 215 eyes of African subjects, and 104 eyes from Indian subjects. These subjects were selected based on the presence of normal IOP (<23 mmHg), normal VFs, no family history of glaucoma, and no history of ocular disease. Each sector is classified as within normal limits if the measurement falls within a 95% confidence interval (CI), borderline if the measurement falls in the 95% to 99.9% CI, and outside normal limits if the measurement falls below the 99.9% CI. Moorfields regression analysis also provides results for the global rim area (MRA global) and a final classification (MRA classification). A normal MRA classification requires the MRA analysis of all sectors and the global rim area to be within normal limits. A borderline MRA classification occurs when at least one of the sectors or the global rim area is borderline, and an outside normal limits result occurs when at least one sector or the global rim area is outside normal limits.
The HRT 3.0 software utilizes manufacturer-developed automated analysis for the detection of glaucomatous damage, the glaucoma probability score (GPS), which is independent of the contour line traced by the examiner around the optic disc margin.19
It is based on a 3-dimensional model of the entire topographical image, including the optic disc and surrounding parapapillary RNFL. Five shape-based parameters are used in the model to characterize the shape of the optic disc and RNFL. Three parameters are used to characterize the optic disc: cup size (width), cup depth (depth), and rim steepness (slope). Two parameters are used to characterize the RNFL: vertical RNFL curvature (superior to inferior curvature) and horizontal RNFL curvature (nasal to temporal curvature). A 3-dimensional model incorporating information from the 5 parameters described above is then constructed for the optic disc being examined. The values of the parameters are then fed into a machine learning classifier analysis called a relevance vector machine, which compares a patient's results to previously defined healthy and glaucomatous models. According to the manufacturer, the final GPS result is the probability or likelihood that the scan has structural characteristics that are consistent with glaucoma.
Descriptive statistics included mean and SD for normally distributed variables and median, first quartile, and third quartile values for non–normally distributed variables. Student's t tests or Mann–Whitney U tests were used to evaluate demographic and clinical differences between glaucoma and normal subjects.
Receiver operating characteristic (ROC) curves were used to describe the ability of SLP and CSLO to differentiate glaucoma from normal subjects. The ROC curve shows the tradeoff between sensitivity and 1 − specificity.20
An ROC curve area of 1.0 represents perfect discrimination, whereas an area of 0.5 represents chance discrimination. Receiver operating characteristic curve areas were compared using the method of DeLong et al.21
Sensitivities at fixed specificities of 70% and 95% were also reported for each parameter of each instrument.
Statistical analyses were performed using STATA (version 9.0, StataCorp, College Station, TX) and SPSS (version 13.0, SPSS Inc., Chicago, IL). The α level (type I error) was set at 0.05.