- •Foreword
- •Preface
- •Contents
- •Contributors
- •Chapter 1
- •1.1 Introduction
- •1.2 Limitations of Time-Domain OCT
- •1.4 Conclusion
- •References
- •Chapter 2
- •2.1 Background
- •2.3 Clinical Application
- •2.4 Conclusions
- •References
- •Chapter 3
- •Fluorescein Angiography
- •3.1 Principles of Fluorescein Angiography
- •3.2 Procedures for Fluorescein Angiography
- •3.4 Time Course of Fluorescein Angiography
- •3.5 Interpretation of Fluorescein Angiography
- •3.5.1 Hypofluorescent Lesions
- •3.5.2 Hyperfluorescent Lesions
- •3.6 Fluorescein Angiography Today
- •References
- •Chapter 4
- •Wide-Field Imaging and Angiography
- •4.1 Introduction
- •4.2 History of Fundus Imaging
- •4.3.1 Fluorescein Angiography with a Scanning Laser Ophthalmoscope
- •4.3.2 Advantages of Imaging with a Scanning Laser Ophthalmoscope
- •4.4 Clinical Use of Wide-Field Imaging
- •4.4.1 Wide-Field Imaging in Uveitis
- •4.4.4 Wide-Field Imaging of Choroidal Tumors
- •4.5 Future Directions for Fundus Imaging
- •4.6 Conclusion
- •References
- •Chapter 5
- •Autofluorescence Imaging
- •5.1 Introduction
- •5.2 What is Fundus Autofluorescence?
- •5.3 Identification of Early Disease Stages
- •5.4 Phenotyping
- •5.5 Disease Markers
- •5.6 Monitoring of Disease Progression
- •5.7 Disease Mapping
- •5.8 Functional Correlation
- •References
- •Chapter 6
- •Imaging the Macular Pigment
- •6.1 Macular Pigment
- •6.1.1 Characteristics and Potential Functions
- •6.1.3 Spatial Distribution
- •6.1.4 Modifying the Macular Pigment
- •6.1.5 MPOD and Age
- •6.2 Measurement Techniques
- •6.2.1 Heterochromatic Flickerphotometry
- •6.2.2 Fundus reflectance
- •6.2.3 Autofluorescence
- •6.2.4 Raman spectroscopy
- •6.2.5 How do different techniques compare
- •6.3 Imaging
- •6.3.1 Heterochromatic Flickerphotometry
- •6.3.2 Fundus Reflectance
- •6.3.3 Autofluorescence
- •6.3.4 Raman spectroscopy
- •References
- •Chapter 7
- •7.1 Introduction
- •7.2 Origin of Near-Infrared Autofluorescence
- •7.3 RPE Melanin: Role and Aging
- •7.4 Clinical Cases
- •7.4.1 Age-Related Macular Degeneration
- •7.4.2 Retinal Dystrophies
- •7.4.2.1 Stargardt’s Disease
- •7.4.2.2 Best’s Disease
- •7.4.2.3 Retinitis Pigmentosa
- •7.5 Conclusion
- •References
- •Chapter 8
- •8.1 Introduction
- •8.3.1.1 Classic Choroidal Neovascularization
- •8.3.1.2 Occult Choroidal Neovascularization
- •8.3.1.4 Mixed-Type Choroidal Neovascularization
- •8.3.1.5 Retinal Angiomatous Proliferation
- •8.3.3 Fibrovascular Scar
- •8.5 Conclusions
- •References
- •Chapter 9
- •9.1 Fundus Cameras
- •9.1.1 Standard Images
- •9.1.2 Wide-Angle Images
- •9.1.2.1 Pomerantzeff Equator Plus
- •9.1.2.2 RetCam™
- •RetCam™ Camera Description
- •RetCam™ Technique of Image Capture
- •RetCam™ Problems
- •9.1.2.3 Panoret™
- •9.1.2.4 Optos™
- •9.2.1 Retinal Tumors
- •9.2.1.1 Retinoblastoma
- •9.2.1.2 Astrocytic Hamartoma
- •9.2.1.4 Retinal Cavernous Hemangioma
- •9.2.1.5 Retinal Racemose Hemangioma
- •9.2.1.6 Vasoproliferative Tumor
- •9.2.2 Retinal Pigment Epithelium Tumors
- •9.2.3 Choroidal Tumors
- •9.2.3.1 Choroidal Nevus
- •9.2.3.2 Choroidal Melanoma
- •9.2.4 Anterior Segment Lesions
- •9.2.4.1 Iris Lesions
- •References
- •Chapter 10
- •Metabolic Mapping
- •10.1 Aspects of Metabolism
- •10.4.1 Technical Solution
- •10.5 Clinical Results
- •10.5.1 Age-Related Macular Degeneration
- •10.5.1.1 Detection of Alterations in Early AMD
- •10.5.1.2 Lifetime Images in Late AMD
- •Non-Exudative AMD and Geographic Atrophy
- •Exudative AMD
- •10.5.2.1 Arterial Branch Occlusion
- •10.5.3 Metabolic Alteration in Diabetes Mellitus
- •10.5.3.1 Detection of Fields of Reduced Metabolism
- •References
- •Chapter 11
- •11.1 Diabetic Macular Edema
- •11.2 Examinations in Diabetic Macular Edema
- •11.3 Treatment of Diabetic Macular Edema
- •References
- •Chapter 12
- •12.1.1 Incidence and Natural History
- •12.2 Investigation of Diagnostic Accuracy of OCT for Detection of DME
- •12.2.2 Diagnostic Accuracy of OCT for Detection of DME: Are Photography or Biomicroscopy a Valid Gold Standard?
- •12.2.3 Diagnostic Accuracy of OCT to Detect CSME Using Time-Domain OCTs: How to Use OCT Retinal Thickness Cut-Offs?
- •12.3 Use of OCT When Compared with Photography: Beyond Diagnostic Accuracy
- •12.4 Appendix: Reproducibility of OCT Retinal-Thickness Measurement in Patients with DME
- •12.4.1 How Reproducibility is Reported
- •12.4.3 Spectral-Domain OCTs Reproducibility
- •References
- •Chapter 13
- •13.2 Clinical Features
- •13.3 Examination
- •13.4 Natural History
- •13.5 Ultra-High Resolution OCT and Spectral OCT Findings in Macular Holes
- •13.6 Macular Hole Formation
- •13.7 Postoperative Appearance
- •13.8 Theory of Macular Hole Closure After Vitrectomy
- •13.9 Surgical Considerations
- •13.11 Clinical Features
- •13.12 Treatment
- •References
- •Chapter 14
- •14.1 Introduction
- •14.2 Vitreous Biochemistry
- •14.3 Vitreo-Retinal Interface Anatomy
- •14.4 Anomalous Posterior Vitreous Detachment (PVD)
- •14.5 Spectral-Domain OCT (SD-OCT)
- •14.6 Vitreo-Maculopathies
- •14.6.1 Macular Pucker (MP)
- •14.6.2 Macular Hole (MH)
- •14.6.2.1 Lamellar Hole (LH)
- •14.6.3 Age-Related Macular Degeneration (AMD)
- •14.6.4 Vitreo-Macular Traction Syndrome (VMTS)
- •14.7 Conclusion
- •References
- •Chapter 15
- •15.3 Imaging the Choroid
- •15.4 Age-Related Choroidal Atrophy
- •15.5 Choroid in High Myopia
- •15.8 Volume Rendering
- •15.9 Summary
- •References
- •Chapter 16
- •16.1 Introduction
- •16.2 Optical Coherence Tomography
- •16.3 Role of Optical Coherence Tomography
- •References
- •Chapter 17
- •17.1 Background and Motivation
- •17.2 Three-Dimensional Imaging of the Choroid
- •17.3 In Vivo Cellular Resolution Retinal Imaging
- •17.4 Polarization Sensitive Retinal OCT
- •17.5 Doppler (Blood Flow) Retinal OCT
- •References
- •Chapter 18
- •Toward Molecular Imaging
- •Summaries for the Clinician
- •References
- •Index
6.2 Measurement Techniques |
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Fig. 6.6 Autofluorescence excitation spectra for the fovea (F, open circles) and for a site at 7° temporal to the fovea (P, open squares) in a 32-year old man. Excitation spectra represent the mean fluorescence intensity in 620–650 nm band as a function of the excitation wavelength λ (430, 450, 470, 490, 510, 530, and 550 nm); only emission spectra at the fovea (F´) and perifovea (P´) for both Λ = 470 nm (thick lines) and Λ = 550 nm (thin lines) excitation are shown for clarity. Fluorescence is expressed in nJnm-1sr-1/J. Top left: log-ratio spectrum of perifoveal to foveal fluorescence (filled circles) and fitted MP spectrum. Reprinted with permission of Archives of Biochemistry and Biophysics
found no age effect. Bone et al., in another study comparing donor eyes with and without AMD, found a slight increase with age in 56 donor eyes of healthy subjects, aged 58–98 years [43].
Studies using Raman spectroscopy initially showed a strong decrease with age [124–126]. This seemed strange in view of the results from all other methods. A number of possible causes like aberrations, scatter, and fixation were discussed extensively in eLetters and their replies [127– 130]. In the end, the most important parameter seems to be pupil size. If eyes for which pupil diameter smaller than 7 mm are excluded, the age-related decline vanishes to nonsignificance [131]. Taken together, most studies found no age effect; a few found either a slight decrease or a slight increase. This makes us to conclude that the relationship between age and MPOD, if any, is marginal.
Summary for the Clinician
■The yellow spot, or macula lutea, in the center of the retina is caused by the presence of the socalled macula pigment (MP). Its absorption has its peak at the center of the fovea and decreases rapidly with eccentricity.
■The MP consists of the carotenoids lutein and zeaxanthin. In the central 0–2.3 mm region, zeaxanthin predominates over lutein, whereas for eccentricities beyond this region, lutein is the major carotenoid.
■Many benefits have been ascribed to the MP like reducing the consequences of chromatic aberration, minimize stray light, preservation of visual sensitivity, improving glare disability, and photostress recovery. However, from a clinical point of view, the most important is its possible role in the prevention of age-related macular degeneration.
■Plausible arguments to assume that MP indeed exerts a protective effect in the retinal area are:
●MP acts as a blue light filter, thereby decreasing chances for photochemical light damage.
●MP is capable of scavenging free radicals.
●Lutein is capable of suppressing inflammation.
■The MP optical density (MPOD) seems to be independent of age, but can be increased by dietary modification or supplementation with lutein or zeaxanthin.
6.2 Measurement Techniques
There are several ways to determine the MPOD. The most widespread are the psychophysical techniques, where the subject adjusts color or luminosity, generally through a minimum flicker, or a minimum motion task [132–134]. The second, more objective approach is through analysis of light returning from the retina. It relies either on spectral analysis [121, 135], autofluorescence [136], or on Raman spectroscopy [124].
6.2.1 Heterochromatic Flickerphotometry
The most common method is heterochromatic flickerphotometry (HFP). Here, measurement of the MPOD is accomplished using a stimulus that alternates between a test wavelength that is absorbed by the MP (blue, around 460 nm) and a reference wavelength that is not absorbed (green, around 540 nm). Flicker observed by the subject is reduced to a null point by adjusting the intensity of the
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6 Imaging the Macular Pigment |
former, while viewing the stimulus centrally, and then peripherally, where the MP is assumed to be absent. A higher intensity of the blue component of the stimulus is needed under central viewing conditions owing to attenua-
6 tion by the MP. The MPOD is then derived by taking the logarithm of the ratio between blue and green luminance measured centrally and peripherally. Bone et al. [137] noted that the luminosity function may differ between fovea and parafovea. Therefore, one should probably account for an additional (small) correction factor when determining MPOD with flicker-based methods. The psychophysical approach has the advantage of requiring no special measures like pupil dilatation or head fixation. However, a complete measurement is rather time consuming, and the task, in particular, when making a match in the peripheral retina, is not trivial. Nevertheless, it has been proven to be a reliable method [134, 138, 139], also in the elderly, if a proper setup and measurement protocol is employed [140].
6.2.2Fundus reflectance
Using fundus reflectance spectroscopy, MPOD can be determined either through comparison of the reflection at the macular region and peripheral region, where the MPOD can be assumed to be negligible [111], or by a spectral analysis of the reflected light [121].
Figure 6.7 is an example of a comparison between a foveal and a peripheral site. At the bottom of the graph, the log ratio of these two spectra is drawn, clearly
showing the macular pigment fingerprint. Using the known spectral absorption of the macular pigment, the solid line shows a best fit to this Log ratio spectrum to the MPOD on an offset. Figure 6.8 shows the spectral distribution of the foveal reflection for a young subject (age 20, upper panel) and a middle-aged subject (age 55, middle panel). Using known spectral characteristics of the different absorbers within the eye, the densities of the pigments and the percent reflectance at the interfaces were optimized to fit the measured data at all wavelengths. The solid lines in Fig. 6.8 result from this model analysis. Also shown is a model spectrum with the MPOD set to zero and all other parameters identical as in the fit. A big hurdle in fundus reflectance spectroscopy is the presence of stray-light may. Reflectance at the cornea and lens greatly exceed the reflectance of the fundus, due to the rather large changes in refractive indices [141]. In most of the experimental setups, this problem is alleviated by careful separation of entrance pupil and exit pupil. Although reflectance at the nerve fiber layer, in principle, may be rather high [142–144], in the fovea this layer is nearly absent, and its reflectance can be neglected. A final, small contribution to the stray light caused by vitreous backscatter and reflectance at the inner limiting membrane is hard to avoid. Rather low-mean MPOD compared with others found by Bour et al. [145], Wüstemeyer et al. [146], and Chen et al. [118] were probably caused by this pre-retinal
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Fig. 6.7 Macular pigment optical density as a function of age obtained in three different studies using fundus reflectance spectroscopy. Reprinted with permission of Archives of Biochemistry and Biophysics
Fig. 6.8 Mean macular pigment optical density (MPOD) as a function of eccentricity for 19 patients with age related macular degeneration (AMD), determined with heterochromatic flickerphotometry (HFP). At 7º eccentricity MP is assumed to be absent. This point is taken as a reference. The smooth line is a least-squares fit with an exponential decaying function with eccentricity. Error bars represent standard error of the mean. Reprinted with permission of Experimental Eye Research
and intra-retinal scatter. Delori et al. also had some remaining stray light that could explain his somewhat lower MPOD results. The use of the model analysis described earlier has the advantage that stray light can be incorporated. An elegant way to fully circumvent the latter sources of stray light is to only use the directional component of the reflected light [147, 148], since it will not show a directional dependence. Another advantage of the spectral analysis, compared with the comparison method and also with psychophysical methods, is the absence of a reference spectrum at a peripheral retinal location. The spatial extent of the macular pigment may exceed the 6° or even 8° eccentricity commonly used, which leads to an underestimate of the MPOD if these sites are used as a zero reference. For a detailed discussion on the spectral analysis, see van de Kraats et al. [149, 150]. Most setups for fundus reflectance require pupil dilation. However, the Macular Pigment Reflectometer can do without it [151]. A very recent improvement has been the ability to measure in vivo lutein and zeaxanthin separately [61], based on the fact that between 500 and 520 nm the parallel slopes of the extinction spectra of lutein and zeaxanthin differ about 10 nm (see Fig. 6.2).
6.2 Measurement Techniques |
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6.2.3 Autofluorescence
Noninvasive measurement of the optical density of the human macular pigment by the autofluorescence (AF) method takes advantage of the fluorescence of lipofuscin in the human retinal pigment epithelium (RPE) cells [111]. Fundus AF is dominated by the AF of lipofuscin that accumulates throughout life in the RPE, as a result of phagocytosis of the photoreceptors’ outer membranes [152]. The AF is emitted in the 520–800 nm spectral range and can be excited in the 400 and 590 nm spectral range [153]. This excitation range is broader than the absorption range of MP [6, 34], which makes it possible to excite lipofuscin without substantial absorption by MP. Thus, measuring the intensity of fluorescence above 550 nm, where macular pigment has essentially zero absorption, and stimulating the fluorescence with two wavelengths, one well absorbed by macular pigment and the other minimally absorbed by macular pigment, provides a single-pass measurement of the macular pigment optical density [136]. Figure 6.9 shows AF excitation spectra for the fovea and for a site at 7° temporal to the fovea and the MPOD spectrum, determined by the log-ratio of perifoveal to foveal AF.
Fig. 6.9 Reflectance (left) and autofluorescence maps (right) at a wavelength of 488 nm (top) and 514 nm (middle). The lower images show the corresponding color coded macular pigment optical density (MPOD) maps. Reprinted with permission of Investigative Ophthalmology and Visual Science
