in nearly all eyes and the NFL to be measured in a thicker area, thus permitting a higher sensitivity to subtle NFL defects (Schuman et al., 1996).

It is important to emphasize that Fast RNFL scan is the only peripapillary RNFL scan type available in the Stratus OCT software that has a normative database analysis. The values obtained can be compared against a normative database of age-matched controls to derive percentile values. The four percentile values included in the OCT software are the top 5th percentile, top 95th percentile, bottom 5th percentile, and bottom 1st percentile. The normative data used in the software were collected by studying approximately

350 normal individuals equally distributed into decades between the ages of 20 and 80 years. In the Fast scan program, subject values are compared with values obtained in the normative database. There is no correction for other demographic factors, such as ethnicity or gender, because these factors have not been demonstrated to affect RNFL thickness to date (Budenz et al., 2005).

Evaluation of optic disc

Changes in optic nerve head are a well-established marker for glaucoma. Determining whether

changes have occurred in the optic disc remains one of the most important and challenging aspects of glaucoma management. Structural changes that are most clinically recognized include generalized or localized thinning of the neuroretinal rim (Airaksinen and Drance, 1985) and deepening of the optic cup. These changes reflect a loss or alteration of retinal ganglion cell axons and/or the structures that support them (Quigley, 1999). Optic disc size can be estimated roughly by disc photographs, with correction for ocular parameters such as corneal curvature and axial length (Balazsi et al., 1984). Modern imaging devices are able to document optic disc morphology and quantify reduction of retinal fiber thickness. Stratus OCT can readily provide accurate estimates of optic disc size. Cup and rim area estimates are also valuable in determining the degree and rate of change. Expert algorithms can also be used to perform OCT image analysis in order to assess the optic nerve head and measure cup and disc parameters.

The Stratus OCT 3 uses two protocols. The optical disc protocol consists of a series of 6–24 equally spaced line scans through a common center. The default pattern has six lines that are 4 mm in length. The scans created with this protocol are used with the optic nerve head analysis protocol. The fast optical disc protocol

compresses the six optical disc scans into one scan. This protocol consists of six 4 mm radial line scans. The resolution of fast protocols is lower, but the chance of error from patient movement is less.

As shown in Fig. 3, the boundary of the disc can be determined from each OCT image by the point at which the photoreceptor layer, RPE, and choriocapillaris terminate at the laminar cribrosa. This point can be located automatically by expert image processing algorithms and then viewed and confirmed by the operator. The disc diameter can be determined by measuring the distance between the disc boundaries on opposite sides of the disc. The cup diameter can be measured by constructing a line parallel to and offset anteriorly by a standard amount to the line that defines the disc diameter.

Optic disc topography measured by OCT has shown to be in agreement with other disc-measuring instruments (Bowd et al., 2001; Zangwill et al., 2001; Bowd et al., 2002; Williams et al., 2002; Aydin et al., 2003; Guedes et al., 2003; Schuman et al., 2003).

OCT in glaucoma management

Visual field examination can be considered the gold standard in glaucomatous patient

management, and any new technique, such as OCT imaging, must be compared to it.

Typical visual field abnormalities reliably establish glaucomatous nerve atrophy. Visual fields can be preceded by significant loss of retinal ganglion cells. In the early seventies, Hoyt (Hoyt et al., 1973) correlated slit-like defects in the appearance of the nerve fiber layer with early clinically detectable manifestations of glaucomatous damage. Since Hoyt’s initial report, numerous experimental and observational studies suggested that in glaucomatous eyes, the atrophy of the retinal fiber layer is primarily related to the degeneration of ganglion cell axons, followed by NFL thinning (Quigley et al., 1977; Sommer et al., 1984; Airaksinen et al., 1985).

Subsequent reports correlate abnormalities in the RNFL to an arcuate loss of visual field, and in doing so, these reports emphasize the importance of examining the RNFL in glaucoma. Several authors affirm that visual field defects are anticipated by loss of RNFL, and furthermore, early glaucoma cannot be excluded without excluding the presence of RNFL defects (Quigley et al., 1982; Caprioli and Miller, 1990; Mikelberg et al., 1995). Of note, Sommer (Sommer et al., 1991) observed that in 60% of eyes, NFL layer loss appears approximately 6 years before any detectable visual field defects.

The RNFL assessment with a slit lamp and a handheld lens requires experience and offers only subjective and qualitative data that is difficult to compare over time. When attempting to detect early glaucomatous optic nerve damage, it would be useful to supplement qualitative observations of RNFL defects with objective quantitative measurements of the NFL thickness.

According to Soliman (Soliman et al., 2002), there is a nonlinear relationship between RNFL loss (measured by OCT RNFL) and visual field damage, and it can be better approximated using an exponential model represented by the curved line showing relationship between OCT RNFL and standard achromatic perimetry (SAP) pattern standard deviation. The graphic shows that a considerable amount of RNFL is lost before the development of observable visual field damage. In early glaucoma, RNFL loss can occur without

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visual field changes and can be easily detected with OCT. However, in late stages, the progress of glaucomatous damage can be better detected with visual fields, as the variation in RNFL thickness is too small to be detected, while the variation in visual field is larger and easily detectable.

Measurements of retinal NFL with the OCT have demonstrated a reproducible difference between normal eyes and eyes with open-angle glaucoma, as defined by abnormal achromatic visual fields (Pieroth et al., 1998).

Schumann (Schumann et al., 1995) showed that the diagnosis of glaucoma was associated with a significantly thinner RNFL, especially in the inferior quadrant, as compared with measurements in normal eyes. In 2007, Johnson (Johnson et al., 2007) clearly stated that subjective biomicroscopic examination of the fundus is the current gold standard for detecting glaucomatous structural damage, but it relies on the examiner’s experience. OCT, one of the several imaging technologies introduced to measure RNFL thickness, has been proposed as a diagnostic tool for the detection of glaucoma because of its ability to provide quantitative, reproducible, and objective data. Patients with early glaucoma provide a diagnostic challenge, and it is this group for whom it is hoped that OCT can provide useful information. Using quality assessment for the diagnostic accuracy of OCT in glaucoma, Johnson concluded that reporting on this subject is ‘‘suboptimal.’’ Keeping this ‘‘warning’’ in mind, the following representative data from ‘‘milestone’’ papers describe the use of OCT in the diagnosis of glaucoma.

Nouri-Madhavi in 2004 (Nouri-Madhavi et al., 2004) found that OCT effectively differentiates early perimetric glaucoma from normal eyes, while its discriminating power in glaucoma suspects (eyes with suspicious optic disc cupping and normal achromatic visual fields) is less adequate. This study confirmed earlier reports by the same group: Greaney (Greaney et al., 2002) compared various quantitative optic nerve imaging methods [OCT, confocal scanning laser ophthalmoscopy (CSLO), SLP] with the qualitative disc assessment by experienced observers (ONHP: optic nerve head photographs). None of these quantitative techniques, when used alone, was sufficiently

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able to discriminate between normal eyes and early to moderate glaucoma. Only after combining parameters from four different optic nerve imaging techniques, the authors were able to improve this diagnostic ability.

Recently, Parikh et al. (2007) compared their data with data from international literature and affirmed that OCT has moderate sensitivity with high specificity. Data from inferior hemi-meridian showed the best combination between sensitivity and specificity compared to superior hemimeridian.

Although it is clear that further scientific evidence is needed to clarify the role of OCT in glaucoma, we can state that OCT at the present time is a good instrument to diagnose early glaucoma but cannot be used to exclude it.

New perspective

Improvements in OCT technology have recently been introduced.

Podoleanu and Jackson in 1997 (Podoleanu et al., 1997) introduced a transverse scanning technique (parallel to the retina surface) to capture real-time coronal planes (C-scans) or sagittal planes (B-scans) simultaneous with confocal SLO images (OCT/ SLO). The distance between scans is four times less in transverse scan than in A-scan. Transverse retinal scanning follows retinal layers, allowing better imaging of the outer retinal region. Coronal OCT scans visualize details that are often lost in B-scan with a more complex interpretation. Moreover, SLO channel maintains multifunctional capabilities of angiography, microperimetry and mfERG.

Ultra-high resolution (UHR) OCT introduced by Drexel and Fujimoto in 2001 (Drexel et al., 2001) provided a better axial resolution (up to 2 mm) using an improved super luminescent diode. The enhanced anatomical details were limited by slow time acquisition (4–5 s) and alignment dependence on macular fixation.

Wojtkoswki in 2002 (Wojtkoswki et al., 2002) first used spectrometers with high-speed cameras to capture sets of axial scans to allow multiple signal (up to 200) returns. The use of this spectral domain technique accelerated data collection from

400 A-scans/s of one conventional OCT to 27 A-scans/s. With a faster acquisition, there is a more stable image that is not affected by patient motion. A stack of one hundred or more crosssectional scans (high-density scan) can be acquired in the same time that it takes for six cross-sectional scans (low-density scan) with conventional timedomain OCT, thus allowing for a three-dimen- sional representation of images.

The use of the improved super luminescent diode, coupled with the spectral domain OCT (SDOCT) technique, allows us to acquire, in vivo, cross-sectional retinal images with an axial resolution up to five times higher and an imaging speed that is 60 times faster than conventional OCT.

This increase in resolution and scanning speed permits high-density faster scanning of retinal tissue while minimizing eye motion artifacts.

By combining high resolution OCT, SDOCT, and SLO, it is finally possible to obtain a device with the ability to generate high-speed (200 frame per second) B-scan OCT/SLO, and to reveal internal three-dimensional anatomic details along with surface features with a 35 degree image field. All of these properties are reached without losing the multifunctionality of SLO.

Using this new device, it is possible to detect and segment the RNFL in each faster OCT image and use these data to construct a detailed RNFL thickness map. In particular, UHR/SDOCT/SLO has shown that RNFL thickness is generally inversely related to the distance from the ONH center in the peripapillary region of healthy subjects. Aside from the nasal segment, all areas show an initial increase in RNFL, followed by a peak and gradual linear decrease.

Like any other technology that has not yet completed the ascending phase of its cycle of use, at the moment UHR/SDOCT/SLO and, in general, OCT have many drawbacks. First of all, normative data are required for the new system. Moreover, large datasets need a plan for storage and backup, faster image processing, and integration with conventional images. Because a large number of new SDOCT systems (Table 1) are now commercially available, it is difficult to integrate data across different clinics, thus creating a challenge for new clinical trials.