Evaluation of Retinal Nerve Fiber Layer, Optic Nerve Head, And Macular Thickness Measurements for...

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Evaluation of Retinal Nerve Fiber Layer, OpticNerve Head, and Macular Thickness

Measurements for Glaucoma Detection Using

Optical Coherence Tomography

FELIPE A. MEDEIROS, MD, LINDA M. ZANGWILL, PHD, CHRISTOPHER BOWD, PHD,

ROBERTO M. VESSANI, MD, REMO SUSANNA JR, MD, AND ROBERT N. WEINREB, MD

PURPOSE: To compare the ability of optical coherence

tomography retinal nerve fiber layer (RNFL), optic nervehead, and macular thickness parameters to differentiatebetween healthy eyes and eyes with glaucomatous visual

field loss. DESIGN: Observational case-control study. METHODS: Eighty-eight patients with glaucoma and 78healthy subjects were included. All patients underwent

ONH, RNFL thickness, and macular thickness scanswith Stratus OCT during the same visit. ROC curves and

sensitivities at fixed specificities were calculated for eachparameter. A discriminant analysis was performed to

develop a linear discriminant function designed to iden-

tify and combine the best parameters. This LDF wassubsequently tested on an independent sample consistingof 63 eyes of 63 subjects (27 glaucomatous and 36

healthy individuals) from a different geographic area. RESULTS: No statistically significant difference was

found between the areas under the ROC curves (AUC)for the RNFL thickness parameter with the largest AUC

(inferior thickness, AUC 0.91) and the ONH param-eter with largest AUC (cup/disk area ratio, AUC

0.88) (P .28). The RNFL parameter inferior thick-ness had a significantly larger AUC than the macular

thickness parameter with largest AUC (inferior outer

macular thickness, AUC 0.81) (P

.004). A com-bination of selected RNFL and ONH parameters resultedin the best classification function for glaucoma detection

with an AUC of 0.97 when applied to the independent

sample. CONCLUSIONS: RNFL and ONH measurements had

the best discriminating performance among the several

Stratus OCT parameters. A combination of ONH and

RNFL parameters improved the diagnostic accuracy for

glaucoma detection using this instrument. (Am J Oph-

thalmol 2005;139:44-55. 2005 by Elsevier Inc. All

rights reserved.)

CHANGES IN THE STRUCTURAL APPEARANCE OF THE

optic nerve head (ONH) and retinal nerve fiber

layer (RNFL) have been reported to precede thedevelopment of visual field loss in glaucoma.13 Detection

of ONH and RNFL damage is, therefore, crucial for early

diagnosis of glaucoma. Recent attention has also been

directed to the role of macular thickness measurements for

glaucoma diagnosis. Retinal ganglion cells also are lost in

the posterior pole in glaucoma,4,5 where these cells may

constitute 30% to 35% of the retinal thickness in the

macular region.

Optical coherence tomography (OCT) is an optical

imaging technique that provides high resolution and re-

producible images of the RNFL that discriminate glauco-

matous from healthy subjects.611 Although OCT has beenused, for the most part, to evaluate RNFL thickness, recent

improvements in the software also have made possible the

evaluation of ONH topography and macular thickness for

glaucoma diagnosis and follow-up. A previous investiga-

tion demonstrated that OCT ONH measurements corre-

late well with topographic measurements obtained by

confocal scanning laser ophthalmoscopy, another imaging

technique that evaluates the ONH.12 Other studies have

also shown that OCT macular thickness measurements are

significantly thinner in glaucomatous compared with

healthy eyes.5,1315 Although the ability of OCT ONH and

Accepted for publication Aug 26, 2004.From the Hamilton Glaucoma Center and Department of Ophthal-

mology, University of California, San Diego, California ( F.A.M., L.M.Z.,C.B., R.N.W.); and Department of Ophthalmology, University of SoPaulo, So Paulo, Brazil (R.M.V., R.S. Jr.).

Supported in part by the Foundation for Eye Research (F.A.M.) andNIH Grant EY11008 (L.M.Z.).

Inquiries to Felipe A. Medeiros, MD, Hamilton Glaucoma Center,University of California, San Diego, 9500 Gilman Drive, La Jolla, CA92093-0946; e-mail: [email protected]

2005 BY ELSEVIER INC. ALL RIGHTS RESERVED.44 0002-9394/05/$30.00doi:10.1016/j.ajo.2004.08.069


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macular thickness measurements to differentiate glauco-

matous from healthy subjects has been reported to be lowerthan RNFL thickness parameters, no study has yet pro-

vided a comparison of these three methods in the samepopulation. Further, it is possible that ONH and macula

measurements provide complementary structural informa-tion that would increase diagnostic accuracy when com-

bined with RNFL evaluation.The purpose of this study was to compare the ability of

OCT RNFL, ONH, and macular thickness parameters todifferentiate between healthy eyes and eyes with glauco-

matous visual field loss in one study population. We alsoinvestigated whether a combination of these analytical

methods improved the accuracy of glaucoma diagnosis byOCT.

METHODS

THIS OBSERVATIONAL CROSS-SECTIONAL STUDY INCLUDED166 eyes of 166 patients (88 glaucomatous patients and 78

healthy control subjects). Mean age ( SD) of glaucoma

patients and healthy individuals was 68 11 years and 65 9 years, respectively (P .09; Students t test). Subjects

were evaluated at the Hamilton Glaucoma Center, Uni-versity of California, San Diego, from April 2002 to

January 2004. These patients were included in a prospec-tive longitudinal study designed to evaluate optic nerve

structure and visual function in glaucoma (DIGSDiag-nostic Innovations in Glaucoma Study). All patients who

met the inclusion criteria described were enrolled in the

current study. Informed consent was obtained from allparticipants. The University of California San DiegoHuman Subjects Committee approved all protocols, and

the methods described adhered to the tenets of theDeclaration of Helsinki.

Each subject underwent a comprehensive ophthalmologicexamination including review of medical history, best-cor-

rected visual acuity, slit-lamp biomicroscopy, intraocularpressure (IOP) measurement using Goldmann applanation

tonometry, gonioscopy, dilated fundoscopic examination us-ing a 78-diopter lens, stereoscopic optic disk photography,

and automated perimetry using 24-2 Swedish InteractiveThreshold Algorithm (Carl Zeiss Meditec Inc., Dublin, Cal-

ifornia, USA). To be included, subjects had to have best-corrected visual acuity of 20/40 or better, spherical refraction

within 5.0 diopters and cylinder correction within 3.0diopters, and open angles on gonioscopy. Eyes with coexisting

retinal disease, uveitis, or nonglaucomatous optic neuropathywere excluded from this investigation. One eye of each

patient was randomly selected for inclusion in the study.Normal control eyes had intraocular pressures of 21 mm

Hg or less with no history of increased IOP and a normalvisual field result. Normal visual field was defined as a

mean deviation and pattern standard deviation within95% confidence limits, and a Glaucoma Hemifield Test

(GHT) within normal limits. Normal control eyes also had

a healthy appearance of the optic disk and RNFL (nodiffuse or focal rim thinning, cupping, optic disk hemor-

rhage, or RNFL defects), as evaluated by clinical exami-nation.

Eyes were classified as glaucomatous if they had repeat-able (two consecutive) abnormal visual field test results,

defined as a PSD outside of the 95% normal confidencelimits or a Glaucoma Hemifield Test result outside normal

limits, regardless of the appearance of the optic disk.Average MD of the glaucomatous eyes on the visual field

test nearest the imaging date was 4.96 dB. According tothe Hodapp-Parrish-Anderson16 grading scale of severity of

visual field defects, 61 patients (69%) were classified ashaving early visual field defects, 15 patients (17%) had

moderate defects, and 12 patients (14%) had severe visualfield defects.

Although the appearance of the optic disk on stereo-photographs was not used as an inclusion criterion, the

results of stereophotograph assessment were used for com-parison with Stratus OCT ONH measurements. Simulta-

neous stereoscopic optic disk photographs (TRC-SS;

Topcon Instrument Corp of America, Paramus, NewJersey, USA) were evaluated by two experienced graders,

and each was masked to the subjects identity and to theother test results. The graders visually estimated the

horizontal and vertical cup/disk ratios based on the con-tour of the cup. The mean value of the two graders was

used as a final grading.Subjects underwent ocular imaging with dilated pupils

using the commercially available optical coherence tomo-

graph, Stratus OCT (Carl Zeiss Meditec, Dublin, Califor-nia, USA). All patients had optic nerve head, RNFLthickness, and macular thickness scans obtained during the

same visit. OCT employs the principles of low-coherenceinterferometry and is analogous to ultrasound B-mode

imaging but uses light instead of sound to acquire high-resolution images of ocular structures. In brief, a low-

coherence near-infrared (840 nm) light beam is directedonto a partially reflective mirror (beam splitter) that

creates two light beams, a reference and a measurementbeam. The measurement beam is directed onto the sub-

jects eye and is reflected from intraocular microstructuresand tissues according to their distance, thickness, and

different reflectivity. The reference beam is reflected fromthe reference mirror at a known, variable position. Both

beams travel back to the partially reflective mirror, recom-bine, and are transmitted to a photosensitive detector. The

pattern of interference is used to provide informationregarding distance and thickness of retinal structures.

Bidimensional images are created by successive longitudi-nal scanning in transverse direction.

Quality assessment of Stratus OCT scans was evaluatedby an experienced examiner masked to the subjects results

of the other tests. Good-quality scans had to have focusedimages from the ocular fundus, an adequate signal-to-noise

EVALUATION OF MEASUREMENTS FOR GLAUCOMA DETECTION USING OCTVOL. 139, NO. 1 45


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ratio (33 dB for RNFL and macula scans), and the

presence of a centered circular ring around the optic disk

(for RNFL scans). For macula and ONH scans, the radial

scans had to be centered on the fovea and optic disk,

respectively. RNFL scans were also evaluated as to the

adequacy of the algorithm for detection of the RNFL. Only

scans without overt algorithm failure in detecting the

retinal borders were included in the study. If one type ofscan was classified as unacceptable, the patient was ex-

cluded from the study. From an initial group of 189 eligible

patients, 23 (12%) had unacceptable Stratus OCT scans

and were excluded from further analysis.

RNFL THICKNESS MEASUREMENTS: The fast RNFL

algorithm was used to obtain RNFL thickness measure-

ments with Stratus OCT. Three images were acquired from

each subject, with each image consisting of 256 A-scans

along a 3.4-mm-diameter circular ring around the optic

disk. A mean image was automatically created by the

Stratus OCT software.Parapapillary RNFL thickness parameters automati-

cally calculated by existing Stratus OCT software (version

3.1) and evaluated in this study were average thickness

(360-degree measure), temporal quadrant thickness (316

degrees to 45 degrees), superior quadrant thickness (46

degrees to 135 degrees), nasal quadrant thickness (136

degrees to 225 degrees), inferior quadrant thickness (226

degrees to 315 degrees), and thickness for each of 12

clock-hour positions with the 3-oclock position as nasal,

6-oclock position as inferior, 9-oclock position as tempo-

ral, and 12-oclock position as superior. Other parameters

evaluated included superior maximum (Smaxthickestpoint in the superior quadrant), inferior maximum

(Imaxthickest point in the inferior quadrant), and rela-

tional parameters such as Imax/Smax, Smax/Imax, Imax/

Tavg (inferior maximum/temporal quadrant thickness),

Smax/Navg (Superior maximum/Nasal quadrant thick-

ness), and Max-min (difference between the thickest and

thinnest points along the measurement circle).

OPTIC NERVE HEAD MEASUREMENTS: The Fast Opti-

cal Disk scanning protocol was used to obtain ONH

measurements with Stratus OCT. The ONH scan consists

of six radial scans in a spoke like pattern centered on theONH. The OCT interpolates between the scans to provide

measurements throughout the ONH. In optic nerve head

scans, the device automatically determines the disk margin

as the end of the retinal pigment epithelium/choriocapil-

laris layer. One can manually adjust the demarcation of the

edge of the retinal pigment epithelium to improve the

outlining of the disk margin. However, to minimize sub-

jectivity, the automatically determined default disk margin

was used in this study. A straight line connects the edges

of the retinal pigment epithelium/choriocapillaris, and a

parallel line is constructed 150 m anteriorly. Structures

below this line are defined as the disk cup and above this

line as the neuroretinal rim.

ONH parameters automatically calculated by existing

Stratus OCT software (version 3.1) and evaluated in this

study were vertically integrated rim area (total volume of

rim tissue calculated by multiplying the average of indi-

vidual rim areas times the circumference of the disk),

horizontally integrated rim width (estimate of total rimarea calculated by multiplying the average of individual

rim widths times the circumference of the disk), disk area,

cup area, rim area, cup/disk area ratio (ratio of cup area to

disk area), horizontal cup/disk ratio (ratio of the longest

horizontal line across the cup to the longest horizontal line

across the disk), and vertical cup/disk ratio (ratio of the

longest vertical line across the cup to the longest vertical

line across the disk).

MACULAR THICKNESS MEASUREMENTS: The Fast

Macular Thickness protocol was used to obtain macular

thickness measurements with Stratus OCT. The macularscans consist of six radial scans in a spokelike pattern

centered on the fovea with each radial scan spaced 30

degrees from one to another. To fill the gaps between the

scans, OCT uses interpolation.

Stratus OCT software calculates retinal thickness as

the distance between the vitreoretinal interface and the

junction between the inner and outer segment of photo-

receptors, which is just above the retinal pigment epithe-

lium. Three concentric circles divide the macular

thickness map into three zones: fovea, inner macula, and

outer macula. The inner and outer zones are further

divided in four quadrants by two diagonal lines. Thus, atotal of nine areas (fovea, superior outer, superior inner,

inferior outer, inferior inner, temporal outer, temporal

inner, nasal outer, and nasal inner) are available for

analysis. For this study, concentric circles with default

diameters of 1 mm, 3 mm, and 6 mm were used to divide

the macular thickness map.

Macular thickness parameters automatically calculated

by existing Stratus OCT software (version 3.1) and eval-

uated in this study were foveal thickness, superior outer

macular thickness, inferior outer macular thickness (IOM),

temporal outer macular thickness, nasal outer macular

thickness, superior inner macular thickness, inferior innermacular thickness, temporal inner macular thickness, and

nasal inner macular thickness. Average macular thickness

was calculated as the weighted average of the sectoral

macular thickness measurements excluding the fovea.

STATISTICAL ANALYSIS: Student t tests were used to

evaluate optic nerve head, RNFL thickness, and macular

thickness measurement differences between glaucomatous

and healthy eyes. Results of statistical significance were

also provided after Bonferronis correction based on the

number of comparisons within each analysis. Pearsons

AMERICAN JOURNAL OF OPHTHALMOLOGY46 JANUARY 2005


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correlation coefficients were used to assess the correlations

between continuous variables. Bland and Altman plotswere constructed to assess agreement between optic disk

stereophotograph assessment and Stratus OCT ONHmeasurements.17,18

Receiver operating characteristic (ROC) curves wereused to describe the ability to differentiate glaucomatous

from healthy eyes of each Stratus OCT software-providedparameter. The ROC curve shows the trade-off between

sensitivity and 1-specificity. An area under the ROC curveof 1.0 represents perfect discrimination, whereas an area of

0.5 represents chance discrimination. The method ofDeLong and associates19 was used to compare areas under

the ROC curve.A discriminant analysis was performed to develop a

classification function (linear discriminant functionLDF) designed to identify and combine the best Stratus

OCT measures to differentiate glaucomatous from normaleyes. A principal component analysis was initially per-

formed to select a reduced set of variables that accountedfor most of the variance of the original data set.20,21 The

central idea of PCA is to reduce the dimensionality of a

data set consisting of a large number of interrelatedvariables while retaining as much as possible of the

variation present in the data set.20 Thirteen principalcomponents explaining 91% of the variance of the data set

were selected according to Jollifes criterion.22 After vari-max rotation, the variables with highest loadings in each

component were selected for further analysis and possibleinclusion in the discriminant function.21 LDFs were then

constructed using all possible subsets from the reduced set

of variables. The bias-corrected area under the ROC curvewas used as a measure of the performance of each LDF. Biascorrection was performed using 10-fold cross-validation.

The model that maximized the bias-corrected ROC curvearea was selected as best.

To evaluate model stability, 1,000 bootstrap randomsamples were drawn with replacement from the original

sample. The model selection procedure was then applied toeach of the 1,000 bootstrap resamples, and the best model

was selected in each resample. The frequency of inclusionof the variables in the selected models was reported.

Important variables should be included in most of thereplications, and the inclusion frequencies may be used as

a criterion for the importance of a variable.23

EXTERNAL VALIDATION ANALYSIS: To determinegeneralizability of the derived Stratus OCT LDF to new

patients, the final LDF was applied to an external inde-pendent sample from a different geographic area.24 Patients

in this sample were not used in any of the steps of modeldevelopment. This validation set included 63 eyes of 63

subjects (27 glaucomatous and 36 normals) evaluated atthe Glaucoma Center of the University of So Paulo,

Brazil. Informed consent was obtained from all subjects,and the appropriate regulatory and ethics committees

approved all protocols. The inclusion and exclusion crite-

ria were identical to those used for the derivation set.Mean age (SD) of glaucoma patients and healthy sub-

jects was 59 15 years and 56 10 years, respectively(P .36). Average MD of the glaucomatous eyes on the

visual field test nearest the imaging date was 6.58 dB.According to the Hodapp-Parrish-Anderson16 grading

scale of severity of visual field defects, 16 patients (59%)were classified as having early visual field defects, 4

patients (15%) had moderate defects, and 7 patients(26%) had severe visual field defects.

A P value less than .05 was considered statisticallysignificant. Statistical analyses were performed using soft-

ware SPSS v.10.0 (SPSS Inc., Chicago, Illinois, USA) andS-PLUS 2000 (Mathsoft Inc., Seattle, Washington, USA).

RESULTS

RNFL THICKNESS MEASUREMENTS: Table 1 showsmean values of Stratus OCT RNFL parameters in glauco-

matous and normal eyes. After Bonferronis correction ( 0.002; 25 comparisons), statistical significant differenceswere found for all parameters except thickness at 9-oclock,

Imax/Smax, Smax/Tavg, and Smax/Navg. Table 1 alsoshows ROC curve areas and sensitivities at fixed specific-

ities. The 3 Stratus OCT RNFL parameters with largestareas under the ROC curves were inferior thickness (0.91),

average thickness (0.91), and inferior maximum (0.90).There were no statistically significant differences in the

ROC curve areas for these parameters (P .05 for all

comparisons).

OPTIC NERVE HEAD MEASUREMENTS: Table 2 shows

mean values of Stratus OCT ONH parameters in glauco-matous and normal eyes. After Bonferronis correction ( 0.006; 8 comparisons), statistical significant differenceswere found for all parameters except disk area. Table 2 also

shows ROC curve areas and sensitivities at fixed specific-ities. The 3 Stratus OCT ONH parameters with largest

areas under the ROC curves were cup/disk area ratio(0.88), vertical cup/disk ratio (0.88), and HIRW (0.88).

Vertical and horizontal cup/disk ratio measurementsobtained by the Stratus OCT also were compared with

those obtained by stereophotograph assessment. There wasno statistically significant difference between mean Stratus

OCT vertical cup/disk ratio and stereophotograph verticalcup/disk ratio [0.59 0.20 vs 0.58 0.24; P .59, paired

t test). There was a statistically significant correlationbetween the two measurements (r .87; P .001). Figure

1 shows a Bland and Altman plot of the agreement invertical cup/disk ratio between Stratus OCT and stereo-

photograph assessment. The difference (stereophotographvertical cup/disk ratioStratus OCT vertical cup/disk

ratio) was plotted against the average of the two measure-ments. Although no significant fixed bias was observed, a



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statistically significant proportional bias was detected (r

.34; P .001). For lower values of vertical cup/disk ratio,Stratus OCT measurements tended to be higher than

stereophotograph measurements; whereas for higher valuesof vertical cup/disk ratio, Stratus OCT measurements

tended to be lower than stereophotograph measurements.For the horizontal cup/disk ratio, Stratus OCT measure-

ments were significantly larger than stereophotograph-basedsubjective assessment (0.64 0.22 vs 0.54 0.22; P .001;

paired t test). A significant correlation was obtained between

the two measures (r .84; P .001). The Bland and Altmanplot (Figure 2) showed the presence of fixed bias, but no

proportional bias was detected (r .01; P .87).

MACULAR THICKNESS MEASUREMENTS: Table 3shows mean values of Stratus OCT macular thickness

parameters in glaucomatous and normal eyes. AfterBonferronis correction ( 0.005; 10 comparisons),

TABLE 1. Mean ( SD) Values of Stratus OCT Retinal Nerve Fiber Layer Parameters With Areas Under the Receiver Operating

Characteristic (ROC) Curves and Sensitivities (Sn) at Fixed Specificities (Sp)

Parameter

Glaucoma

(n 88)

Normal

(n 78) P* ROC (SE)

Sn/Sp

(Sp 95%)

Sn/Sp

(Sp 80%)

Inferior thickness (m) 84.6 23.2 123.8 16.5 .0001 0.91 (0.02) 65/96 89/80

Average thickness (m) 74.2 13.3 96.5 9.90 .0001 0.91 (0.02) 71/95 86/80Imax (m) 112.3 30.5 159.3 21.1 .0001 0.90 (0.03) 63/95 85/80

Thickness at 6-oclock (m) 90.2 29.6 133.8 24.5 .0001 0.87 (0.03) 56/95 78/80


Max-min (m) 94.0 25.1 124.5 18.6 .0001 0.85 (0.03) 55/95 81/80

Superior thickness (m) 92.2 22.5 118.6 16.0 .0001 0.83 (0.03) 52/96 73/81

Smax (m) 120.4 26.6 149.8 19.5 .0001 0.81 (0.03) 50/95 68/80


Imax/Tavg 1.92 0.54 2.43 0.51 .0001 0.76 (0.04) 38/95 50/81


Nasal thickness (m) 59.5 15.8 76.1 19.6 .0001 0.76 (0.04) 13/95 61/80






Smax/Tavg 2.08 0.61 2.28 0.48 .019 0.64 (0.04) 27/96 43/80


Imax/Smax 0.97 0.31 1.08 0.17 .004 0.65 (0.04) 33/95 44/81


Temporal thickness (m) 60.5 15.2 67.6 13.1 .002 0.65 (0.04) 22/95 38/81


Smax/Navg 2.16 1.01 2.10 0.63 .634 0.48 (0.05) 5/95 17/80

Smax/Imax 1.15 0.39 0.95 0.15 .0001 0.35 (0.04) 7/95 16/80

TABLE 2. Mean ( SD) Values of Stratus OCT Optic Nerve Head Parameters With Areas Under the Receiver OperatingCharacteristic (ROC) Curves and Sensitivities (Sn) at Fixed Specificities (Sp)

Parameter

Glaucoma

(n 88)

Normal

(n 78) P* ROC (SE)

Sn/Sp

(Sp 95%)

Sn/Sp

(Sp 80%)

Cu p/disk:are a ratio 0.55 0.19 0.26 0.14 .0001 0.88 (0.03) 69/95 80/80

Vertical C/D ratio 0.70 0.14 0.45 0.16 .0001 0.88 (0.03) 65/95 81/80

HIRW (mm2) 1.23 0.28 1.69 0.28 .0001 0.88 (0.03) 55/95 77/80

Rim area (mm2) 1.02 0.42 1.74 0.45 .0001 0.88 (0.03) 51/95 81/80

VIRA (mm2) 0.17 0.16 0.48 0.34 .0001 0.87 (0.03) 58/95 82/80

Horizontal C/D rat io 0.76 0.16 0.50 0.19 .0001 0.86 (0.03) 59/95 74/80

Cup area (mm2) 1.31 0.60 0.61 0.39 .0001 0.84 (0.03) 50/95 74/80

Disk area (mm2) 2.34 0.47 2.35 0.51 .847 0.51 (0.05) 6/95 19/80

*HIRW horizontal integrated rim width; VIRA vertical integrated rim area.



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statistically significant differences were found for allparameters except NIM thickness and foveal thick-

ness. Table 3 also shows ROC curve areas and sensitiv-ities at fixed specificities. The 3 Stratus OCT macular

thickness parameters with the largest areas under theROC curves were IOM thickness (0.81), Macular thick-

ness average (0.75), and TOM thickness (0.75). Therewere no statistically significant differences in the ROC

curve areas for these parameters (P .05 for allcomparisons).

COMPARISON OF RNFL, ONH, AND MACULAR THICK-

NESS MEASUREMENTS: No statistically significant differ-ence was found between the areas under the ROC curves

(AUC) for the RNFL thickness parameter with largestAUC (inferior thickness; AUC 0.91) and the ONH

parameter with largest AUC (cup/disk area ratio; AUC 0.88) (P .28). The RNFL parameter inferior thickness

had a significantly larger AUC than the macular thicknessparameter with largest AUC (IOM; AUC 0.81) (P

.004). The AUC of the ONH parameter cup/disk area ratiowas higher than that of the macular thickness parameter

IOM, but the difference did not reach statistical signifi-cance (P .09).

We evaluated whether a combination of Stratus OCTmeasures improved the discrimination between glaucoma

and healthy subjects. The best discriminant functionresulting from the combination of Stratus OCT parameters

had the following formula:LDF 3.023 (2.659 cup/disk area ratio)

(0.035 average thickness) (0.013 thickness at7-oclock) (0.011 thickness at 11-oclock) (0.031 thickness at 9-oclock)

This LDF had an AUC of 0.97 (SE 0.01) with an

estimated bias of 0.011. The AUC of the LDF wassignificantly larger than that of the single Stratus OCT

software-provided parameter with largest AUC (inferiorthickness) (0.97 vs 0.91; P .012). Figure 3 shows the

ROC curves for the two parameters of RNFL, ONH, andmacular analyses with largest AUCs and also for the

Stratus OCT LDF. For specificity at 95%, the LDF hada sensitivity of 90% (cut-off of 0.284). For specificity at

81%, the LDF had a sensitivity of 94% (cut-off of0.683).

Although there were several LDFs that were competi-tive with the above formula, the variables included in the

final LDF had the highest frequencies of inclusion in themodels selected in the bootstrap samples. Figure 4 illus-

FIGURE 1. Bland and Altman plot of the agreement on vertical cup/disk ratio between stereophotograph assessment and Stratus

OCT measurements. The difference (stereophotograph Stratus OCT) is plotted vs the average (stereophotograph Stratus

OCT)/2. The existence of proportional bias is indicated by the significant slope of the line regressing the difference on the average

(r .34; P < .001). The regression line is shown with 95% individual confidence limits bands.



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trates the frequency of inclusion of the variables in the

final models selected in the 1,000 bootstrap replications.The variables included in the final LDF were selected in

59% to 88% of the final models, whereas the othervariables were included in no more than 32% of the

models. The full model containing all 13 variables had abias-corrected AUC of 0.96.

When applied to the independent validation sample

(n 63), the LDF had an AUC of 0.97 (SE 0.02).Figure 5 shows the ROC curves for the LDF when

applied to the independent sample and for the twoparameters with largest AUC for RNFL (average thick-

ness; AUC 0.93 and RNFL thickness at 6-oclock;AUC 0.92), ONH (VIRA; AUC 0.92 and cup/disk

FIGURE 2. Bland and Altman plot of the agreement on horizontal cup/disk ratio between stereophotograph assessment and Stratus

OCT measurements. The difference (stereophotograph Stratus OCT) is plotted vs the average (stereophotograph Stratus

OCT)/2. The continuous line represents the mean difference and 95% limits of agreement. The existence of fixed bias is indicated

by the significant deviation from zero of the mean difference between stereophoto and Stratus OCT measurements.

TABLE 3. Mean ( SD) Values of Stratus OCT Macular Thickness Parameters With Areas Under the Receiver Operating

Characteristic (ROC) Curves and Sensitivities (Sn) at Fixed Specificities (Sp)

Parameter

Glaucoma

(n 88)

Normal

(n 78) P* ROC (SE)

Sn/Sp

(Sp 95%)

Sn/Sp

(Sp 80%)

Inferior outer macula (m) 205 16 224 16 .0001 0.81 (0.03) 47/95 73/82

Macula average (m) 216 13 231 15 .0001 0.75 (0.04) 35/95 50/80

Temporal outer macula (m) 202 15 218 18 .0001 0.75 (0.04) 32/95 51/80

Superior outer macula (m) 220 18 236 17 .0001 0.73 (0.04) 36/95 48/80

Nasal outer macula (m) 235 18 247 18 .0001 0.68 (0.04) 21/95 39/80

Temporal inner macula (m) 246 18 257 19 .0001 0.67 (0.04) 22/95 42/80

Inferior inner macula (m) 254 19 265 19 .0001 0.65 (0.04) 26/96 34/80

Superior inner macula (m) 259 21 269 19 .002 0.63 (0.04) 18/95 34/80

Nasal inner macula (m) 264 21 269 21 .12 0.55 (0.05) 14/95 31/80

Fovea (m) 202 25 201 28 .83 0.47 (0.05) 6/95 18/80

*Macula average thickness is calculated from the weighted average of all sectors excluding the fovea. SE standard error.



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area ratio; AUC 0.91), and macular thickness anal-yses (IOM; AUC 0.79 and SOM; AUC 0.78) on

the independent sample.

DISCUSSION

THE ANALYSIS OF STRATUS OCT SOFTWARE-PROVIDED PA-

rameters showed that parapapillary RNFL measures and

ONH topographic parameters had the highest power todiscriminate glaucomatous from healthy eyes. Areas under

the ROC curves and sensitivities at moderate and highspecificities were similar for the best parameters from each

of these two methods of analysis. We also found that acombination of selected RNFL and ONH parameters in a

linear discriminant function resulted in further improve-ment of the diagnostic accuracy of OCT.

The ROC curve areas for the Stratus OCT RNFLmeasurements were similar to those obtained with the

previous versions of this technology. The areas under theROC curves for the earlier OCT models have been

reported to range from 0.79 to 0.94, depending on the

parameter and characteristics of the population evaluat-

ed.911,15,2527 In studies evaluating the diagnostic ability of

several OCT parameters, the RNFL thickness in the

inferior region often had the best performance to discrim-

inate healthy eyes from eyes with early to moderate

glaucoma with sensitivities between 67% and 79% for

specificities 90%.9,11,26 In our study, the parameter

inferior thickness also had the highest area under the

ROC curve, with sensitivity of 65% for specificity at95%. The parameter average thickness also had a similar

performance.

The RNFL thicknesses at 7-oclock and at 11-oclock

were included as RNFL parameters in our discriminant

function, along with RNFL thickness at 9-oclock and

average thickness. The high discriminating ability of

RNFL thickness at 7- and 11-oclock is readily understand-

able, as these variables represent the inferior temporal and

superior temporal sectors of the optic disk, respectively,

which are the sectors most commonly affected in glauco-

ma.28 The inclusion of these variables may also be related

FIGURE 3. Receiver operating characteristic (ROC) curves of the two parameters with largest areas under the ROC curves from

the Stratus OCT retinal nerve fiber layer (inferior thickness and average thickness), optic nerve head (cup/disk area ratio and

vertical cup/disk ratio), macular thickness analysis (inferior outer macular thickness [IOM] and macula average), and of the lineardiscriminant function (LDF) obtained from the combination of selected parameters.



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to the detection of localized nerve fiber layer defects that

are most commonly seen in these sectors.29 The average

RNFL thickness is a measurement of global thickness ofthe RNFL and, therefore, is presumably important in thedifferentiation of glaucoma from healthy eyes. The inclu-

sion of the RNFL thickness at 9-oclock in the discrimi-nant function is more difficult to explain. This variable

corresponds to the thickness at the most temporal sector,in the region of the papilomacular bundle. No significant

difference was observed in the mean RNFL thicknessvalues at 9-oclock between glaucomatous and healthy

eyes. This is in agreement with previous studies demon-strating that the RNFL is usually preserved in the region of

the papilomacular bundle until late in the course of thedisease. It is well known that RNFL thickness can vary

widely among healthy subjects limiting the usefulness ofabsolute thickness values to separate glaucomatous from

healthy subjects. Conversely, the evaluation of the modu-lation of the RNFL thickness may provide a useful tool for

detection of relative loss of nerve fibers in glaucoma.30 Themodulation represents the difference between the thickest

and the thinnest parts of the RNFL around the optic disk.The RNFL thickness difference between the 9-oclock

sector and the 7- and 11-oclock sectors could provide anindication of the modulation of RNFL thickness around

the optic disk. The negative sign of this variable in theLDF formula indicates that, all other variables being equal,

a subject with thicker RNFL at 9-oclock (and lower

modulation) will have a higher chance of having glauco-

matous visual field loss than a subject with thinner RNFLin this sector (and higher modulation). In a recent study,Nouri-Mahdavi27 and associates found that the thickness

at 7-, 10-, and 11-oclock provided the best combination ofOCT RNFL parameters to discriminate patients with

glaucomatous visual field loss from healthy subjects. Intheir study, the thickness at 10-oclock had a positive

correlation with the presence of glaucomatous visual fieldloss, that is, higher values indicated a higher chance of

glaucoma. Thus, it is possible that the RNFL thickness at10-oclock in their discriminant function had the same role

as the RNFL thickness at 9-oclock in our study. This issupported by the high correlation existing between these

two variables (r .77, P .001 in our study).Stratus OCT ONH parameters also performed well for

glaucoma detection in our study. Areas under the ROCcurves were similar for all ONH parameters except disk

area. The parameter cup/disk area ratio had the highestsensitivity with specificity at 95%, and this parameter was

also included in the final LDF developed in our study.Highly significant correlations were found between Stratus

OCT and stereophotograph assessment of vertical andhorizontal cup/disk ratios. However, important disagree-

ments were detected between these two methods whenBland and Altman plots (Figures 1 and 2) were analyzed,

FIGURE 4. Frequency of inclusion of the 13 different variables in the best models selected in each of the 1,000 bootstrap

replications.



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indicating the low utility of correlation coefficients toassess agreement between methods of measurement, an

issue that has already been extensively acknowledged inthe literature.17,18,31 The limited agreement with stereo-

photographic assessment does not preclude the use ofStratus OCT ONH parameters for glaucoma diagnosis.

Stereophotographic assessment of cup/disk ratio is a sub-jective measure and has a large interobserver variability.32

In contrast, Stratus OCT ONH assessment provides ob-jective measures of optic disk topography using an auto-

mated process of optic disk edge detection and cupdelimitation, and a recent study has found these measures

to be highly reproducible.33 In fact, the discriminatingabilities of Stratus OCT ONH parameters were similar to

those of the best RNFL measures, and the combination ofan ONH parameter (cup/disk area ratio) with RNFL

thickness parameters resulted in the best discriminantfunction for glaucoma detection in our study.

The utility of the topographical evaluation of the ONHwith OCT for glaucoma diagnosis still needs further

evaluation. As the automatic algorithm for detection ofthe disk margin is based on the determination of the end

of the retinal pigment epithelium/choriocapillaris layer, itis possible that the evaluation of the disk margin will be

influenced by changes in these layers such as with progres-sive parapapillary atrophy in glaucoma.34 A manual algo-

rithm for disk margin determination is also available.However, we did not use the manual algorithm to avoid

introducing a subjective component to our analysis. Fur-thermore, the manual and automatic algorithms have been

demonstrated to have comparable performance in a previ-ous work.12

Stratus OCT macular thickness measurements had alimited ability to differentiate glaucomatous from healthy

eyes in our investigation. Although mean macular thick-ness parameters of glaucomatous eyes were significantly

lower than that of normal control eyes, the macularthickness parameter with largest AUC had a sensitivity of

only 47% for a specificity set at 95%, with an AUC of 0.81.This agrees with a previous investigation where a maxi-

FIGURE 5. Receiver operating characteristic (ROC) curve of the linear discriminant function when applied to the independent

sample and of the two parameters with the largest areas under the ROC curves for RNFL (average thickness and RNFL thicknessat 6 oclock), ONH (vertically integrated rim area [VIRA] and cup/disk area ratio), and macular thickness analyses (inferior outer

macula thickness [IOM] and superior outer macula thickness [SOM]) on the independent sample.



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mum ROC curve area of 0.77 for macular thickness

parameters was obtained for the discrimination betweenearly glaucoma and normal subjects, whereas peripapillary

RNFL thickness parameters had maximum ROC curvearea of 0.94 in the same situation.15 In contrast to RNFL

and ONH measures, macular thickness parameters werenot included in the final LDF developed in our study. The

low frequency of inclusion of macular thickness parameterswhen the model building process was replicated in the

bootstrap samples provides an indication that these vari-ables had at most a weak influence on the discrimination

between glaucomatous and healthy eyes when severalStratus OCT parameters were combined. However, it

should be noted that we have only investigated the currentmacular thickness parameters provided by the standard

Stratus OCT printout, and it is possible that advances inthe software designed to extract data from the macular area

would improve detection of retinal ganglion cell loss in theposterior pole.

Our study has limitations. Although the generalizabilityof the discriminant function combining several Stratus

OCT parameters was good when applied to an indepen-

dent population, the size of the validation sample wasrelatively small. However, the sample size of the validation

group provided 79% power to detect a decrease in perfor-mance of 0.05 in the ROC curve area in the validation

sample compared with the performance in the develop-ment sample.35 The validation sample contained a higher

proportion of moderate and advanced cases compared withthe development sample. However, even when patients

with moderate and advanced glaucomatous visual field loss

were excluded from the validation sample, the LDF stillperformed well, with an area under the ROC curve of 0.96.Another limitation of our study was that the inclusion

criteria for normal subjects required a normal optic nerveappearance at the clinical examination. This was required

to avoid the inclusion of subjects with glaucomatous opticneuropathy but normal visual fields in the control group. It

might be argued that these inclusion criteria could haveoverestimated the diagnostic accuracy of OCT parameters,

especially of ONH parameters. However, this is a limita-tion common to case-control studies of this type, and no

practical solution to this problem is available at this time.In conclusion, RNFL and ONH measurements had the

best performance for glaucoma detection among the sev-eral Stratus OCT parameters examined in our study. A

combination of ONH and RNFL parameters seems to bepromising for glaucoma diagnosis using OCT.

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