Ординатура / Офтальмология / Английские материалы / Optical Coherence Tomography in Age-Related Macular Degeneration_Coscas_2009

Horizontal, cross-sectional images of the normal human macula taken by conventional TD-OCT (Stratus OCT) and Spectral-Domain system (RTVue OCT) are shown (Figure 3).

Most intraretinal layers can be visualized with Stratus* (Figure 3A). However, SD-OCT (with RTVue*) provides enhanced visualization of the intraretinal layers (Figure 3B and 3C).

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The intraretinal layers

▬The first hyper-reflective layer is the nerve fiber layer

(NFL).

These interpretations are supported by studies comparing ultrahigh-resolution OCT images, and to histology, as well as the known optical properties of retinal layers in the animal retina (Huang 200512 Gloesmann

2003 13 ).

Three-Dimensional OCT Imaging

Improved resolution and scan speed provide comprehensive three-dimensional information that could not be previously obtained with conventional TD-OCT systems.

(INL), and Outer Nuclear Layer (ONL).

▬Less reflective layers are adjacent to these nuclear layers: the Inner Plexiform Layer (IPL) and the Outer Plexiform Layer (OPL).

Vue* consist of 101 B-scan images each associated with 512 A-scans equally spaced in a rectangular area with an axial length of 2 mm. Volume data acquisition of 4 x 4 x 2 mm can be completed in 2 seconds.

The ELM is not a physical membrane but is thought to be an alignment of structures between the photoreceptor cells and the Müller cells representing the inner border of the photoreceptor inner segment.

▬The hyper-reflective layer below the ELM corresponds to the Interface between photoreceptor inner segments and outer segments (IS/OS).

The back reflection signal arising from IS/OS junction is thought to originate from the abrupt boundary between structures of the IS and highly organized OS, which contains stacks of membranous discs that are rich in the visual pigment rhodopsin ( Gloesmann 200313 ).

prehensive view of the morphology of the entire foveal depression (Figure 4).

In addition to this 3D representation, a single crosssectional image can be extracted and analyzed separately to identify a specific site of interest.

All of these cross-sectional images can be used to analyze various pathologies in three dimensions or to detect more localized pathologies without missing any important retinal features in the zone studied.

Three-dimensional imaging consequently allows better evaluation of the entire retina. Thus, the 3D-OCT imaging protocol achieves improved retinal coverage.

The distance between the RPE and the IS/OS interface is consistent with the increase in length of the cone OS in this region.

Characteristic features of this central foveal area are the high hyper-reflective foveal pit at the deepest location of the depression and a focal elevation of the OLM and the IS/OS interface (IS/OS junction).

Clinical Applications of 3D SD-OCT

3D-OCT imaging data is useful for registration of OCT images of the fundus or to obtain features of segmentation of the various retinal layers, and to measure retinal thickness.

Registration

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The 3D-OCT data obtained with SD-OCT can be used to create virtual fundus images that are similar to those obtained with fundus photography.

This OCT fundus image enables precise registration of each cross-sectional OCT image of specific features of the fundus.

OCT fundus images consequently enable direct comparison of OCT data and clinical findings, such as fundus photographs, fluorescein angiography, fundus autofluorescence, and microperimetry.

An example of an OCT fundus image obtained with RTVueTM is shown (Figure 5). This OCT fundus image can be directly correlated to a fundus photograph.

The white arrow indicates the retinal vessels identified:

▬On the fundus photograph (Figure 5A), and

▬On the OCT fundus image (Figure 5B),

▬Corresponding to cross-sectional images (Figure 5C), and

▬Corresponding to 3D images, respectively (Figure 5D).

This example demonstrates the ability to precisely localize a specific lesion and to directly correlate this lesion with the finding on the fundus photograph and OCT images.

These OCT fundus images can be used for tracking of subtle or focal pathologic changes in retinal disease.

Image Segmentation

3D images allow automatic segmentation of the different retinal layers.

An automatic segmentation of the OLM and the RPE at the same time as retinal thickness mapping obtained by

the CirrusTM HD-OCT (Carl-Zeiss-Meditec) in a normal human macula is shown (Figure 6)

Segmentation can be performed using the software developed for the Cirrus*, designed to automatically delineate retinal and RPE layers.

This technique can provide realistic identification and delineation of choroidal neovascularization (CNV) and associated exudative changes in AMD.

In addition, automatic segmentation allows detailed quantitative and topographic analysis of CNV, RPE, and the overlying retina.

These various findings may improve the understanding of the pathophysiology of AMD and allow better followup of treatment.

Measuring and Mapping Retinal Thickness

The Stratus* OCT measures retinal thickness by radial scans (6 mm in length) centered on the fovea ( Chan 200614). However, the majority of the macular surface is represented by extrapolation of the 6 sections obtained.

Stratus* OCT also measures retinal thickness by identifying the most highly reflective anterior and posterior layers just anterior to the retinal RPE. Stratus* OCT may therefore underestimate true retinal thickness.

In contrast, RTVue* SD-OCT allows more comprehensive analysis of the retina with 11 horizontal and vertical lines (5 mm scan length and 0.5 mm interval) and 6 horizontal lines (3 mm scan length and 0.5 mm interval) (Figure 7).

SD-OCT is also able to differentiate the IS/OS interface as a distinct feature from the RPE.

RTVue* shows retinal thickness mapping that measures retinal thickness as the distance from the inner surface (corresponding to the RPE) to the vitreoretinal interface.

These measurements correspond more closely to the real anatomical retinal thickness.

The inner retinal thickness is also measured from the vitreoretinal interface to the inner plexiform layer.

Current Applications of SD-OCT in AMD

OCT analysis of AMD has become very useful in relation with PDT and anti-VEGF therapy.

Retinal thickness is an important parameter to analyze exudation, and the acquisition speed and high resolution obtained with SD-OCT allows new methods of visualization, mapping, and measurement of retinal thickness.

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Precise clinical measurements and measurements of various volumes such as CNV, cystoid spaces, subretinal fluid, and lesions underneath the RPE, are also possible.

Evaluation of the photoreceptor layer and its integrity is possible. These advances offer more sensitive diagnostic indicators of disease and methods to assess disease progression.

SD-OCT may become an essential tool for diagnosis and to guide treatment decisions.

SD-OCT Imaging and 3D Analysis in

Vitreoretinal Diseases

This chapter has described the basic concepts of TDOCT and the more recently developed SD-OCT.

Several examples of imaging in vitreoretinal diseases are demonstrated by various clinical cases, such as:

▬Idiopathic macular hole (Figure 8),

▬Vitreoretinal traction syndrome (Figure 9),

▬CNV in AMD (Figure 10),

▬Polypoidal choroidal vasculopathy (Figure 11)

▬Chorioretinal anastomosis (Figure 12).

Conclusion

TD-OCT provides useful information for the diagnosis of many vitreoretinal diseases. It has become a standard diagnostic instrument for vitreoretinal diseases, including AMD.

SD-OCT, a new generation of OCT, provides further progress and can be used to document even subtle changes in chorioretinal microstructures. In particular, the clinical use of SD-OCT will provide a wealth of information for the diagnosis and evaluation of AMD.

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