Name: quantitative fundus autofluorescence for the evaluation of retinal diseases
Uploaded: 2016-03-11T14:00:00.000+00:00
Duration: 7 min 22 s
Description: Watch this Scientific Journal Video about Quantitative Fundus Autofluorescence for the Evaluation of Retinal Diseases at JoVE.com

We would like to thank our collaborators, Francois Delori, Tomas Burke, and Tobias Duncker.
Research Support: NIH/NEI R01 EY015520 (RTS, JPG), and unrestricted funds from Research to Prevent Blindness (RTB).

Ethics Statement: All patients enrolled in these studies were done so in accordance with approved institutional review board oversight at New York University School of Medicine.
1. Patient Selection and Initial Preparation for Imaging
Note: The following materials are required: 0.5% tropicamide ophthalmic solution, 2.5% phenylephrine ophthalmic solution, cSLO equipped with spectral domain optical coherence tomography (SD-OCT), and internal fluorescence reference.
<ol>
	<li>Prior to imaging, appropriately set up cSLO for data acquisition according to manufacturer&#39;s instructions.</li>
	<li>Mount an internal fluorescent reference in the cSLO. Note: The internal fluorescent reference, as purchased from the manufacturer, is housed in a metal ring and is placed directly behind the camera lens. If a cSLO from another manufacturer is used, there may be a different configuration than that which is described in this protocol.
	<ol>
		<li>In order to insert the reference into the cSLO, twist the lens to remove it, unscrew the machine&#39;s metal ring, and replace it with the new metal ring containing the reference. 
		Note: the internal fluorescent reference is essential to the qAF technique, as it allows correction for variation in laser power and detector sensitivity/gain.</li>
	</ol>
	</li>
	<li>Have patients recruited for imaging undergo a routine dilated eye examination and obtain background information regarding past ocular history and underlying medical conditions that may manifest with ocular findings.</li>
	<li>Dilate pupils with 0.5% tropicamide and 2.5% phenylephrine. CRITICAL STEP: Dilate pupils to at least 6 mm. Note: This is essential for uninterrupted passage of light, and thus for optimal visualization and measurement of the fundus.</li>
	<li>Prior to imaging, position the patient properly on the cSLO, with chin resting on the chinrest, forehead placed against the forehead rest, and lateral canthi properly aligned with the indicators.</li>
</ol>
2. Baseline Imaging of the Ocular Fundus
<ol>
	<li>First, image the fundus with near infrared reflectance (IR) light (wavelength of 820 nm) in order to centralize the camera over the macula and obtain rough focus.
	<ol>
		<li>With patient properly positioned, switch the hardware setting on the control panel to IR imaging mode, position camera manually until the fundus is in full focus, and take an image</li>
		<li>Adjust the setting on the control panel to &#34;IR-OCT&#34;, which uses spectral-domain optical coherence tomography (SD-OCT) in conjunction with IR imaging to evaluate the macula for underlying disease.</li>
		<li>Use the guides present in the imaging window to correctly orient the OCT to the IR image of the fundus. To achieve optimal SD-OCT quality, position the camera such that the OCT image is in the top third of its imaging window. Acquire at least one horizontal line scan through the fovea and spanning the entire imaging field.</li>
	</ol>
	</li>
</ol>
3. Setting up qAF Imaging
<ol>
	<li>Use &#34;High speed&#34; image acquisition. Note: This setting allows for faster image acquisition, which decreases risk of signal loss due to patient movement and resulting blockage of light by the iris or eyelids.</li>
	<li>Use &#34;Mean of 9&#34; frames. Note: This setting allows for the rapid, sequential capture of 9 image frames, which can be subsequently &#34;averaged&#34; to reduce noise and artifact (see below).</li>
	<li>Use &#34;30 x 30 degree&#34; field. Note: This refers to the degrees of retinal area captured during image acquisition.</li>
	<li>Prior to imaging, warn patient about the blue light, as this can be alarming at first.</li>
	<li>Turn on the AF mode and align camera axis such that the screen is maximally &#34;filled&#34; with fundus AF (minimal darkening of the sides and corners of the image).
	<ol>
		<li>If patients have difficulty tolerating the bright blue light, start imaging with the camera further away from the eye and then bring the camera slowly toward the patient until the fundus is in full view. 
		CRITICAL STEP: If light entering into or exiting from the eye is obstructed, decreased signal will result. Localized decrease is visible as asymmetric darkening of an image side or corner. Generalized loss of signal is seen when eye movements alone obstruct light passage.</li>
	</ol>
	</li>
	<li>Align the camera such that the AF signal is at its highest level throughout the field. Aim for maximal signal rather than sharpest image, however they roughly correlate. Adjust the camera focus by moving the cSLO to reposition the camera either manually or with the ophthalmoscope joystick.</li>
	<li>Adjust the sensitivity/gain such that fundus AF is easily visible, but avoid over-saturation. During image acquisition, colored pixels visible in either the internal reference (located at the top of the image) or the fundus indicate over-saturation and thus loss of signal.</li>
</ol>
4. Image Acquisition
Note: CRITICAL STEP: The goal in image acquisition should be to obtain 2 high quality 9-frame image stacks per session to control for variability between images within a session. After repositioning the patient and camera, obtain a second session of two images to assess and control for variability. All images will ultimately be calibrated to the internal reference (described below).
<ol>
	<li>Acquire images only after at least 20 sec of &#34;bleaching&#34; (full exposure of retina to AF light) to minimize absorption of light by rhodopsin in the sensory retina 9.
	<ol>
		<li>Use this period to optimize camera alignment, focus and sensitivity.</li>
	</ol>
	</li>
	<li>Have the subjects blink before each image acquisition as a fresh tear film improves signal quality.</li>
	<li>Avoid eyelids in the plane of acquisition. 
	Note: It may be helpful to manually open eyelids for more challenging patients. The authors recommend that an assistant performs this task.</li>
	<li>Optimize alignment before each image acquisition to ensure that light is not obstructed by the iris resulting in decreased signal. 
	Note: As at least minor movement is very common, the authors recommend fine realignment as necessary before each image acquisition. Guiding and encouraging the patient while imaging helps decrease movement. The authors also recommend using the machine&#39;s foot-pedal as the &#34;acquisition button&#34; so as to minimize operator distraction.</li>
	<li>Perform post-image processing by computing the &#34;mean&#34; of the 9-frame stack to increase signal-to-noise ratio. Calculate the mean of a stack using the cSLO software by selecting the option to calculate the mean. 
	Note: There may be stacks where some frames are not of optimal quality (i.e., have localized or generalized decreased signal relative to the optimal frames), therefore carefully inspect each stack and deselect suboptimal frames before computation of the mean. 
	Note: Mean images with acceptable signal-to-noise ratios can be processed from at least 3 frames. It is normal for the sides and corners of each image to have lower signal than the central 20 degrees due to limitations within the cSLO itself.
	<ol>
		<li>If the software asks whether the operator would like to normalize the gray levels (i.e., stretch the histogram) between 0 and 255, select &#34;No&#34;. This maintains unaltered gray levels for analysis.</li>
	</ol>
	</li>
</ol>
5. Image Analysis
<ol>
	<li>Analyze AF images as previously described using image analysis software developed for the qAF technique (IGOR; 9). A brief description of a typical image analysis using this software is included below.
	<ol>
		<li>Load the qAF program in IGOR and import images (in .bmp format) exported from the cSLO software with pixel aspect ratio 768 x 768 (default output parameter).</li>
		<li>Select the image in the drop-down menu and initiate analysis.</li>
		<li>Reposition calibration indicators on the image such that the &#34;crosshairs&#34; overlie the fovea and the &#34;bracket&#34; abuts the optic disc (these indicators are used to scale and position the ROIs). When properly positioned, use software prompts then populate the image with circumferential ROIs surrounding the fovea (see Figures 1, 2).</li>
		<li>Select the option in IGOR to calibrate the overall gray levels of each image to those levels present in the internal fluorescent reference. Note: This step allows for calibration of machine-related factors, including the electronic zero level of each image and the internal reference calibration factor of each machine, as well as patient-related factors, including age, refraction and corneal curvature. 
		Note: The analysis software then displays the fixed regions on the resultant image and a qAF value is demonstrated within each region. qAF values are also automatically entered into a spreadsheet format in a separate window.&#34;</li>
		<li>Generate qAF &#34;heat maps&#34; by selecting the option within the command prompts. All images and data can be exported from the IGOR software in an excel spreadsheet by selecting the appropriate options.</li>
	</ol>
	</li>
</ol>

<ol>
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G., Group, F. A. M. 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G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inhibition+of+lysosomal+degradative+functions+in+RPE+cells+by+a+retinoid+component+of+lipofuscin.">Inhibition of lysosomal degradative functions in RPE cells by a retinoid component of lipofuscin.</a> Investigative ophthalmology &amp; visual science. 40, 737-743 (1999).</li><li>Sparrow, J. R., Nakanishi, K., Parish, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+lipofuscin+fluorophore+A2E+mediates+blue+light-induced+damage+to+retinal+pigmented+epithelial+cells.">The lipofuscin fluorophore A2E mediates blue light-induced damage to retinal pigmented epithelial cells.</a> Investigative ophthalmology &amp; visual science. 41, 1981-1989 (2000).</li><li>Smith, R. 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P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+fundus+autofluorescence+in+healthy+eyes.">Quantitative fundus autofluorescence in healthy eyes.</a> Investigative ophthalmology &amp; visual science. 54, 5684-5693 (2013).</li><li>Delori, F. C., Goger, D. G., Dorey, C. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Age-related+accumulation+and+spatial+distribution+of+lipofuscin+in+RPE+of+normal+subjects.">Age-related accumulation and spatial distribution of lipofuscin in RPE of normal subjects.</a> Investigative ophthalmology &amp; visual science. 42, 1855-1866 (2001).</li><li>Sparrow, J. 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A, Optics, image science, and vision. 24, 1250-1265 (2007).</li></ol>

STA: no disclosures, JPG: no disclosures, RTS: consultant, Ocata Therapeutics.

Abnormal RPE lipofuscin distribution, whether increased or decreased, is a sensitive marker of retinal disease and is generally associated with loss of sensory retina function. Here, we describe application of qAF for the evaluation of RPE lipofuscin. Incorporation of an internal fluorescent reference to correct for variable laser power and detector sensitivity9 alongside our standardized imaging technique allows for reliable quantitation of AF levels. It is our goal that this method will aid in the diagnosis ...

The retinal pigment epithelium (RPE) supports the function of the sensory retina through numerous processes 1. Age-related macular degeneration (AMD) is the most important cause of untreatable blindness in industrialized countries and is characterized by changes in the RPE, including loss of pigment, loss of function and atrophy. In AMD and in normal aging, the RPE accumulates fluorescent, lysosome-derived organelles containing phagocytosed photoreceptor fragments, referred to as lipofuscin granules. The accumulation of RPE lipofuscin has been thought to indicate oxidative dysfunction 1, but recent studies have shown that the RPE morphology remains normal in aged eyes with high lipofuscin levels 2. However, abnormal patterns of lipofuscin distribution, in particular loss of lipofuscin, are documented markers for AMD and AMD progression, both histologically and clinically 3,4
Defective processing of RPE lipofuscin has also been shown to occur in certain inherited retinal degenerations. Patients suffering from Stargardt disease (STGD) accumulate lipofuscin in the RPE at a young age, eventually developing vision loss similar to that seen in AMD 5. These findings suggested that lipofuscin accumulation may itself be toxic and drive RPE dysfunction 6,7. However, a detailed imaging study of subjects with STGD over time did not confirm that focal lipofuscin accumulation led to subsequent RPE loss 8. Hence, although lipofuscin abnormalities are markers for retinal degenerations, a role for direct toxicity of lipofuscin remains unproven.
The RPE is the most posterior cell layer of the retina, but generates the majority of fluorescent signal from the ocular fundus. Generation and detection of autofluorescence (AF) derived from the RPE can be performed using confocal scanning laser ophthalmoscopy (cSLO), which allows for visualization of the spatial distribution of fundus AF. Certain retinal degenerations demonstrate distinctive patterns of fundus AF, and AF imaging aids in the diagnosis and monitoring of these conditions. Although standard AF imaging is clinically important, quantitative AF (qAF) has become an important means of assessing RPE health. We and others have developed a standardized approach that can reliably determine qAF levels at specific retinal locations 9. qAF has potential applications in the diagnosis and monitoring of retinal conditions, and may also have utility in prognosis and risk stratification. In addition, the diagnostic capabilities of qAF have also been described for certain retinal disorders 10-12. Here, we provide step-wise details for performing our technique accompanied by a visual demonstration of its application in the evaluation of healthy and diseased eyes.

<table><tbody><tr><td>Spectralis HRA + OCT</td><td>Heidelberg Engineering</td><td></td><td></td></tr><tr><td>0.5% tropicamide ophthalmic solution</td><td></td><td></td><td>Any brand can be used</td></tr><tr><td>2.5% phenylephrine ophthalmic solution</td><td></td><td></td><td>Any brand can be used</td></tr><tr><td>Internal fluorescent reference</td><td>Heidelberg Engineering</td><td></td><td></td></tr><tr><td>IGOR Pro software</td><td>WaveMetrics</td><td></td><td></td></tr></tbody></table>

quantitative fundus autofluorescence for the evaluation of retinal diseases

The retinal pigment epithelium (RPE) is juxtaposed to the overlying sensory retina, and supports the function of the visual system. Among the tasks performed by the RPE are phagocytosis and processing of outer photoreceptor segments through lysosome-derived organelles. These degradation products, stored and referred to as lipofuscin granules, are composed partially of bisretinoids, which have broad fluorescence absorption and emission spectra that can be detected clinically as fundus autofluorescence with confocal scanning laser ophthalmoscopy (cSLO). Lipofuscin accumulation is associated with increasing age, but is also found in various patterns in both acquired and inherited degenerative diseases of the retina. Thus, studying its pattern of accumulation and correlating such patterns with changes in the overlying sensory retina are essential to understanding the pathophysiology and progression of retinal disease. Here, we describe a technique employed by our lab and others that uses cSLO in order to quantify the level of RPE lipofuscin in both healthy and diseased eyes.

This technique was used to study qAF in both healthy 13 and disease states 10-12. In healthy eyes (Figure 1), AF emitted from the RPE is distributed relatively uniformly throughout the fundus (Figure 1A). Reduced intensity is seen in the central macular region due to blocking of light by macular pigment, and at the sides and corners of the image due to the optics of the eye and camera. Vessels appear dark and should be in clear focus...

Watch this Scientific Journal Video about Quantitative Fundus Autofluorescence for the Evaluation of Retinal Diseases at JoVE.com

Quantitative Fundus Autofluorescence for the Evaluation of Retinal Diseases

The retinal pigment epithelium (RPE) supports the sensory retina through recycling visual cycle byproducts, which accumulate as lipofuscin. These products are autofluorescent and can be qualitatively imaged in vivo. Here, we describe a method to quantitatively image RPE lipofuscin using confocal scanning laser ophthalmoscopy.

The retinal pigment epithelium (RPE) is juxtaposed to the overlying sensory retina, and supports the function of the visual system. Among the tasks ...

quantitative-fundus-autofluorescence-for-evaluation-retinal

Universidad de Cartagena UDEC

Research

JoVE Journal

Medicine

11.4K Views.  NYU School of Medicine. The retinal pigment epithelium (RPE) supports the sensory retina through recycling visual cycle byproducts, which accumulate as lipofuscin. These products are autofluorescent and can be qualitatively imaged in vivo. Here, we describe a method to quantitatively image RPE lipofuscin using confocal scanning laser ophthalmoscopy. 

Video: Quantitative Fundus Autofluorescence for the Evaluation of Retinal Diseases

A Protocol to Evaluate and Quantify Retinal Pigmented Epithelium Pathologies in Mouse Models of Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a debilitating retinal disorder in aging populations. It is widely believed that dysfunction of the retinal pigmented epithelium (RPE) is a key pathobiological event in AMD. To understand the mechanisms that lead to RPE dysfunction, mouse models can be utilized by researchers. It has been established by previous studies that mice can develop RPE pathologies, some of which are observed in the eyes of individuals diagnosed with AMD. Here, we describe a phenotyping protocol to assess RPE pathologies in mice. This protocol includes the preparation and evaluation of retinal cross-sections using light microscopy and transmission electron microscopy, as well as that of RPE flat mounts by confocal microscopy. We detail the common types of murine RPE pathologies observed by these techniques and ways to quantify them through unbiased methods for statistical testing. As proof of concept, we use this RPE phenotyping protocol to quantify the RPE pathologies observed in mice overexpressing transmembrane protein 135 (Tmem135) and aged wild-type C57BL/6J mice. The main goal of this protocol is to present standard RPE phenotyping methods with unbiased quantitative assessments for scientists using mouse models of AMD.

Mouse models can be useful tools for investigating the biology of the retinal pigmented epithelium (RPE). It has been established that mice can develop an array of RPE pathologies. Here, we describe a phenotyping protocol to elucidate and quantify RPE pathologies in mice using light, transmission electron, and confocal microscopy.

Age-related macular degeneration (AMD) is a debilitating retinal disorder in aging populations. It is widely believed that dysfunction of the retinal ...

Genetics

Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies

The microcirculation consists of blood vessels with diameters less than 150 &#181;m. It makes up a large part of the circulatory system and plays an important role in maintaining cardiovascular health. The retina is a tissue that lines the interior of the eye and it is the only tissue that allows for a non-invasive analysis of the microvasculature. Nowadays, high-quality fundus images can be acquired using digital cameras. Retinal images can be collected in 5 min or less, even without dilatation of the pupils. This unobtrusive and fast procedure for visualizing the microcirculation is attractive to apply in epidemiological studies and to monitor cardiovascular health from early age up to old age.
Systemic diseases that affect the circulation can result in progressive morphological changes in the retinal vasculature. For example, changes in the vessel calibers of retinal arteries and veins have been associated with hypertension, atherosclerosis, and increased risk of stroke and myocardial infarction. The vessel widths are derived using image analysis software and the width of the six largest arteries and veins are summarized in the Central Retinal Arteriolar Equivalent (CRAE) and the Central Retinal Venular Equivalent (CRVE). The latter features have been shown useful to study the impact of modifiable lifestyle and environmental cardiovascular disease risk factors.
The procedures to acquire fundus images and the analysis steps to obtain CRAE and CRVE are described. Coefficients of variation of repeated measures of CRAE and CRVE are less than 2% and within-rater reliability is very high. Using a panel study, the rapid response of the retinal vessel calibers to short-term changes in particulate air pollution, a known risk factor for cardiovascular mortality and morbidity, is reported. In conclusion, retinal imaging is proposed as a convenient and instrumental tool for epidemiological studies to study microvascular responses to cardiovascular disease risk factors.

Retinal image analysis is an unobtrusive procedure for visualizing the microcirculation. The impact of cardiovascular disease risk factors can result in changes of retinal vessel calibers. The procedures to acquire fundus images and the steps for calculating the vessel calibers are described.

The microcirculation consists of blood vessels with diameters less than 150 &#181;m. It makes up a large part of the circulatory system and plays an ...

Using Retinal Imaging to Study Dementia

The retina offers a unique &#8220;window&#8221; to study pathophysiological processes of dementia in the brain, as it is an extension of the central nervous system (CNS) and shares prominent similarities with the brain in terms of embryological origin, anatomical features and physiological properties.&#160; The vascular and neuronal structure in the retina can now be visualized easily and non-invasively using retinal imaging techniques, including fundus photography and optical coherence tomography (OCT), and quantified semi-automatically using computer-assisted analysis programs. Studying the associations between vascular and neuronal changes in the retina and dementia could improve our understanding of dementia and, potentially, aid in diagnosis and risk assessment.&#160; This protocol aims to describe a method of quantifying and analyzing retinal vasculature and neuronal structure, which are potentially associated with dementia. This protocol also provides examples of retinal changes in subjects with dementia, and discusses technical issues and current limitations of retinal imaging.

The retina shares prominent similarities with the brain and thus represents a unique window to study vasculature and neuronal structure in the brain non-invasively. This protocol describes a method to study dementia using retinal imaging techniques. This method can potentially aid in diagnosis and risk assessment of dementia.

The retina offers a unique &#8220;window&#8221; to study pathophysiological processes of dementia in the brain, as it is an extension of the central ...

Experimental Autoimmune Uveitis: An Intraocular Inflammatory Mouse Model

Experimental Autoimmune Uveitis (EAU) is driven by immune cells responding to self-antigens. Many features of this non-infectious, intraocular inflammatory disease model recapitulate the clinical phenotype of posterior uveitis affecting humans. EAU has been used reliably to study the efficacy of novel inflammatory therapeutics, their mode of action and to further investigate the mechanisms that underpin disease progression of intraocular disorders. Here, we provide a detailed protocol on EAU induction in the C57BL/6J mouse - the most widely used model organism with susceptibility to this disease. Clinical assessment of disease severity and progression will be demonstrated using fundoscopy, histological examination and fluorescein angiography. The induction procedure involves subcutaneous&#160;injection of an emulsion containing a peptide (IRBP1-20) from the ocular protein interphotoreceptor retinoid binding protein (also known as retinol binding protein 3), Complete Freund&#39;s Adjuvant (CFA) and supplemented with killed Mycobacterium tuberculosis. Injection of this viscous emulsion on the back of the neck is followed by a single intraperitoneal injection of Bordetella pertussis toxin. At the onset of symptoms (day 12-14) and under general anesthesia, fundoscopic images are taken to assess disease progression through clinical examination. These data can be directly compared with those at later timepoints and peak disease (day 20-22) with differences analyzed. At the same time, this protocol allows the investigator to assess potential differences in vessel permeability and damage using fluorescein angiography. EAU can be induced in other mouse strains - both wildtype or genetically modified - and combined with novel therapies offering flexibility for studying drug efficacy and/or disease mechanisms.

In this report we present a protocol that allows the investigator to generate a mouse model of intraocular uveitis. More commonly referred to as experimental autoimmune uveitis (EAU), this established model captures many aspects of human disease. Herein, we will describe how to induce and monitor disease progression using several readouts.

Experimental Autoimmune Uveitis (EAU) is driven by immune cells responding to self-antigens. Many features of this non-infectious, intraocular ...

Immunology and Infection

OCT-Based Multimodal Imaging of Human Donor Eyes for AMD Research

Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration

A progression sequence for age-related macular degeneration (AMD) learned from optical coherence tomography (OCT)-based multimodal (MMI) clinical imaging could add prognostic value to laboratory findings. In this work, ex vivo OCT and MMI were applied to human donor eyes prior to retinal tissue sectioning. The eyes were recovered from non-diabetic white donors aged &#8805;80 years old, with a death-to-preservation time (DtoP) of &#8804;6 h. The globes were recovered on-site, scored with an 18 mm trephine to facilitate cornea removal, and immersed in buffered 4% paraformaldehyde. Color fundus images were acquired after anterior segment removal with a dissecting scope and an SLR camera using trans-, epi-, and flash illumination at three magnifications. The globes were placed in a buffer within a custom-designed chamber with a 60 diopter lens. They were imaged with spectral domain OCT (30&#176; macula cube, 30 &#181;m spacing, averaging = 25), near-infrared reflectance, 488 nm autofluorescence, and 787 nm autofluorescence. The AMD eyes showed a change in the retinal pigment epithelium (RPE), with drusen or subretinal drusenoid deposits (SDDs), with or without neovascularization, and without evidence of other causes. Between June 2016 and September 2017, 94 right eyes and 90 left eyes were recovered (DtoP: 3.9 &plusmn; 1.0 h). Of the 184 eyes, 40.2% had AMD, including early intermediate (22.8%), atrophic (7.6%), and neovascular (9.8%) AMD, and 39.7% had unremarkable maculas. Drusen, SDDs, hyper-reflective foci, atrophy, and fibrovascular scars were identified using OCT. Artifacts included tissue opacification, detachments (bacillary, retinal, RPE, choroidal), foveal cystic change, an undulating RPE, and mechanical damage. To guide the cryo-sectioning, OCT volumes were used to find the fovea and optic nerve head landmarks and specific pathologies. The ex vivo volumes were registered with the in vivo volumes by selecting the reference function for eye tracking. The ex vivo visibility of the pathology seen in vivo depends on the preservation quality. Within 16 months, 75 rapid DtoP donor eyes at all stages of AMD were recovered and staged using clinical MMI methods.

Author Spotlight: Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration  

Laboratory assays can leverage prognostic value from the longitudinal optical coherence tomography (OCT)-based multimodal imaging of age-related macular degeneration (AMD). Human donor eyes with and without AMD are imaged using OCT, color, near-infrared reflectance scanning laser ophthalmoscopy, and autofluorescence at two excitation wavelengths prior to tissue sectioning.

A progression sequence for age-related macular degeneration (AMD) learned from optical coherence tomography (OCT)-based multimodal (MMI) clinical imaging ...

Neuroscience

Retinal Pathophysiological Evaluation in a Rat Model

A posterior segment eye disease like diabetic retinopathy alters the physiology of the retina. Diabetic retinopathy is characterized by a retinal detachment, breakdown of the blood-retinal barrier (BRB), and retinal angiogenesis. An in vivo rat model is a valuable experimental tool to examine the changes in the structure and function of the retina. We propose three different experimental techniques in the rat model to identify morphological changes of retinal cells, retinal vasculature, and compromised BRB. Retinal histology is used to study the morphology of various retinal cells. Also, quantitative measurement is performed by retinal cell count and thickness measurement of different retinal layers. A BRB breakdown assay is used to determine the leakage of extraocular proteins from the plasma to vitreous tissue due to the breakdown of BRB. Fluorescence angiography is used to study angiogenesis and leakage of blood vessels by visualizing retinal vasculature using FITC-dextran dye.

Diabetic retinopathy is one of the leading causes of blindness. Histology, blood-retinal barrier breakdown assay, and fluorescence angiography are valuable techniques to understand the pathophysiology of the retina, which could further enhance the efficient drug screening against diabetic retinopathy.

A posterior segment eye disease like diabetic retinopathy alters the physiology of the retina. Diabetic retinopathy is characterized by a retinal ...

Image-Guided Optical Coherence Tomography to Assess Structural Changes in Rodent Retinas

Ocular diseases, such as age-related macular degeneration, glaucoma, retinitis pigmentosa, and uveitis, are always accompanied by retinal structural changes. These diseases affecting the fundus always exhibit typical abnormalities in certain cell types in the retina, including photoreceptor cells, retinal ganglion cells, cells in the retinal blood vessels, and cells in the choroidal vascular cells. Noninvasive, highly efficient, and adaptable imaging techniques are required for both clinical practice and basic research. Image-guided optical coherence tomography (OCT) satisfies these requirements because it combines fundus photography and high-resolution OCT, providing an accurate diagnosis of tiny lesions as well as important changes in the retinal architecture. This study details the procedures of data collection and data analysis for image-guided OCT and demonstrates its application in rodent models of choroidal neovascularization (CNV), optic nerve crush (ONC), light-induced retinal degeneration, and experimental autoimmune uveitis (EAU). This technique helps researchers in the eye field to identify rodent retinal structural changes conveniently, reliably, and tractably.

The protocol presented here details the procedures of data collection and data analysis for image-guided optical coherence tomography (OCT) and demonstrates its application in multiple rodent models of ocular diseases.

Ocular diseases, such as age-related macular degeneration, glaucoma, retinitis pigmentosa, and uveitis, are always accompanied by retinal structural ...

Exploring Quantitative Autofluorescence in Age-Related Macular Degeneration

A Workflow to Quantitatively Determine Age-Related Macular Degeneration Lesion-Specific Variations in Fundus Autofluorescence

Fundus autofluorescence (FAF) imaging allows the noninvasive mapping of intrinsic fluorophores of the ocular fundus, particularly the retinal pigment epithelium (RPE), now quantifiable with the advent of confocal scanning laser ophthalmoscopy-based quantitative autofluorescence (QAF). QAF has been shown to be generally decreased at the posterior pole in age-related macular degeneration (AMD). The relationship between QAF and various AMD lesions (drusen, subretinal drusenoid deposits) is still unclear.
This paper describes a workflow to determine lesion-specific QAF in AMD. A multimodal in vivo imaging approach is used, including but not limited to spectral domain optical coherence tomography (SD-OCT) macular volume scanning and QAF. Using customized FIJI plug-ins, the corresponding QAF image is aligned with the near-infrared image from the SD-OCT scan (characteristic landmarks; i.e., vessel bifurcations). The foveola and the edge of the optic nerve head are marked in the OCT images (and transferred to the registered QAF image) for accurate positioning of the analysis grids.
AMD-specific lesions can then be marked on individual OCT BScans or the QAF image itself. Normative QAF maps are created to account for the varying mean and standard deviation of QAF values throughout the fundus (QAF images from a representative AMD group were averaged to build normative standard retinal QAF AMD maps). The plug-ins record the X and Y coordinates, z-score (a numerical measurement that describes the QAF value in relation to the mean of AF maps in terms of standard deviation from the mean), mean intensity value, standard deviation, and number of pixels marked. The tools also determine z-scores from the border zone of marked lesions.&#160;This workflow and the analysis tools will improve the understanding of the pathophysiology and clinical AF image interpretation in AMD.

Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow 

This research describes a workflow to determine and compare autofluorescence levels from individual regions of interest (e.g., drusen and subretinal drusenoid deposits in age-related macular degeneration [AMD]) while accounting for varying autofluorescence levels throughout the fundus.

Fundus autofluorescence (FAF) imaging allows the noninvasive mapping of intrinsic fluorophores of the ocular fundus, particularly the retinal pigment ...

Measuring Retinal Vessel Diameter from Mouse Fluorescent Angiography Images

It is important to study the development of retinal vasculature in retinopathies in which abnormal vessel growth can ultimately lead to vision loss. Mutations in the microphthalmia-associated transcription factor (Mitf) gene show hypopigmentation, microphthalmia, retinal degeneration, and in some cases, blindness. In vivo imaging of the mouse retina by noninvasive means is vital for eye research. However, given its small size, mouse fundus imaging is difficult and might require specialized tools, maintenance, and training. In this study, we have developed a unique software enabling analysis of the retinal vessel diameter in mice with an automated program written in MATLAB. Fundus photographs were obtained with a commercial fundus camera system following an intraperitoneal injection of a fluorescein salt solution. Images were altered to enhance contrast, and the MATLAB program permitted extracting the mean vascular diameter automatically at a predefined distance from the optic disk. The vascular changes were examined in wild-type mice and mice with various mutations in the Mitf gene by analyzing the retinal vessel diameter. The custom-written MATLAB program developed here is practical, easy to use, and allows researchers to analyze the mean diameter and mean total diameter, as well as the number of vessels from the mouse retinal vasculature, conveniently and reliably.

Mouse retinal vasculature is particularly interesting in understanding the mechanisms of vascular pattern formation. This protocol automatically measures the diameter of mouse retinal vessels from fluorescent angiography fundus images at a fixed distance from the optic disk.

It is important to study the development of retinal vasculature in retinopathies in which abnormal vessel growth can ultimately lead to vision loss. ...

Quantifying Retinal Pigment Epithelial Phagocytosis and Lipofuscin Accumulation

Improved Lipofuscin Models and Quantification of Outer Segment Phagocytosis Capacity in Highly Polarized Human Retinal Pigment Epithelial Cultures

The daily phagocytosis of photoreceptor outer segments by the retinal pigment epithelium (RPE) contributes to the accumulation of an intracellular aging pigment termed lipofuscin. The toxicity of lipofuscin is well established in Stargardt's disease, the most common inherited retinal degeneration, but is more controversial in age-related macular degeneration (AMD), the leading cause of irreversible blindness in the developed world. Determining lipofuscin toxicity in humans has been difficult, and animal models of Stargardt's have limited toxicity. Thus, in vitro models that mimic human RPE in vivo are needed to better understand lipofuscin generation, clearance, and toxicity. The majority of cell culture lipofuscin models to date have been in cell lines or have involved feeding RPE a single component of the complex lipofuscin mixture rather than fragments/tips of the entire photoreceptor outer segment, which generates a more complete and physiologic lipofuscin model. Described here is a method to induce the accumulation of lipofuscin-like material (termed undigestible autofluorescence material, or UAM) in highly differentiated primary human pre-natal RPE (hfRPE) and induced pluripotent stem cell (iPSC) derived RPE. UAM accumulated in cultures by repeated feedings of ultraviolet light-treated OS fragments taken up by the RPE via phagocytosis. The key ways that UAM approximates and differs from lipofuscin in vivo are also discussed. Accompanying this model of lipofuscin-like accumulation, imaging methods to distinguish the broad autofluorescence spectrum of UAM granules from concurrent antibody staining are introduced. Finally, to assess the impact of UAM on RPE phagocytosis capacity, a new method for quantifying outer segment fragment/tips uptake and breakdown has been introduced. Termed "Total Consumptive Capacity", this method overcomes potential misinterpretations of RPE phagocytosis capacity inherent in classic outer segment "pulse-chase" assays. The models and techniques introduced here can be used to study lipofuscin generation and clearance pathways and putative toxicity.

Author Spotlight: Improved Lipofuscin Models and Quantification of Outer Segment Phagocytosis Capacity in Highly Polarized Human Retinal Pigment Epithelial Cultures  

This protocol describes a lipofuscin accumulation model in highly differentiated and polarized human retinal pigment epithelial (RPE) cultures and an improved outer segment (OS) phagocytosis assay to detect the total OS consumption/degradation capacity of the RPE. These methods overcome the limitations of previous lipofuscin models and classical pulse-chase outer segment phagocytosis assays.

The daily phagocytosis of photoreceptor outer segments by the retinal pigment epithelium (RPE) contributes to the accumulation of an intracellular aging ...