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Retinal Physician

Article

Insightful Imaging for Geographic Atrophy

Maximize the effective use of tools for lesion detection and quantification.

By: Brian Solinsky, MD, Eliza Broadbent, BS, Elias Siltanen, BS, Monika Fleckenstein, MD, Steffen Schmitz-Valckenberg, MD
Retinal Physician January 1, 2024 Vol 21, Issue January/February 2024 Page(s): 19-22

Over the past decades, new imaging modalities have emerged for the diagnosis of geographic atrophy (GA) secondary to age-related macular degeneration (AMD) (Figure 1). These advances have the potential to improve disease monitoring, allowing clinicians to tailor care to individual patients more effectively than ever before. Yet the variety of imaging options introduces greater complexity into the selection of the most appropriate imaging technique for the clinical scenario. 

Figure 1. Geographic atrophy secondary to AMD (left eye of a 69-year-old patient). Color fundus photography, fundus autofluorescence, and optical coherence tomography with scan location indicated on near-infrared image.
Figure 1. Geographic atrophy secondary to AMD (left eye of a 69-year-old patient). Color fundus photography, fundus autofluorescence, and optical coherence tomography with scan location indicated on near-infrared image.

Background

Age-related macular degeneration represents a wide disease spectrum containing a complex interaction involving age, environmental risk factors, and genetic predisposition. It is characterized by extracellular deposition and accumulation of lipofuscin, specifically drusen, leading to photoreceptor and RPE loss, which thus results in subsequent central scotoma. Complete disease pathogenesis has yet to be fully unveiled, although strong implications have been found with chronic inflammation, lipid deposition, oxidative stress, and impaired extracellular matrix maintenance. Clinical classification of the disease is predominantly conducted via drusen size and the presence of GA and/or macular neovascularization (MNV). Geographic atrophy is represented through the concurrent and often progressive atrophy of retinal photoreceptors, RPE, and choriocapillaris.1,2

Color Fundus Photography

Historically, color fundus photography (CFP) has been the standard for imaging in AMD. CFP closely correlates with clinical ophthalmoscopy. It can detect a wide range of characteristic changes in AMD, including drusen, atrophy, fibrosis, and focal pigmentary changes. Although CFP is useful for identifying areas of atrophy and growth over time, it has limited precision in demarcating lesion margins given the lack of contrast. This is particularly true for small or multifocal lesions and limits its ability to quantify GA. Despite these shortcomings, CFP remains the standard validated imaging modality for detection of focal pigmentary changes and merits continued use as other imaging modalities are further validated.2,3 

Fundus Autofluorescence

Fundus autofluorescence (FAF) provides high-contrast retinal images, allowing for better visualization of atrophy margins. Fundus autofluorescence signal intensities are highest in lipofuscin-rich areas, because lipofuscin contains fluorophores responsible for FAF. Lipofuscin, along with retinal pigment epithelium (RPE), is lost in areas of atrophy with resultant low signal intensities. The contrast between low and high signal intensities at the border of lesions permits more precise quantification of atrophy than with CFP. This allows clinicians to closely track lesion growth across visits.2,4 To achieve reasonable quality FAF images, the patient’s pupils need to be dilated. 

The type of FAF imaging used most commonly relies on blue light excitation and is associated with some discomfort for patients.4 The quality of blue light signals can be affected by factors such as nuclear lens opacities, vitreous floaters, and pupil dilation. Further, macular pigment blocks blue light, meaning atrophic borders near the fovea may be more difficult to clearly visualize. Recent research has attempted to address this problem with longer wavelength (ie, green) light. Green light is less sensitive to optical medial opacities and macular pigment, theoretically minimizing the disadvantages of FAF imaging.5,6 More studies are needed to validate the use of green light in FAF. Overall, the ability of FAF to detect changes in atrophy makes it an essential component of dry AMD monitoring, and FAF should be included in regular follow up of patients.

RegionFinder, which is available on the Spectralis imaging platform (Heidelberg Engineering Inc.), allows for automated tracking of GA.7 RegionFinder provides semiautomatic quantification of the area of GA based on blue laser autofluorescence imaging that can be acquired through the Spectralis product family (Figure 2). The image processing software offers accurate, reproducible, and time-efficient identification and quantification of outer retinal atrophy and its progression over time.7 Alternative image analysis tools to segment GA areas and assess GA progression over time, along with additional features such as prediction of future GA enlargement, are currently under development (eg, RetinAI and Retinsight) but these have not yet become broadly available in the clinical setting. 

Figure 2. Geographic atrophy (GA) progression mapping using RegionFinder (Heidelberg Engineering). This figure depicts the progression of GA over approximately 13 years in a right eye. Moving from left to right, the first four columns display color fundus photography, fundus autofluorescence, and RegionFinder-based delineations of GA areas at 4 distinct time points. At the initial visit in January 2010, a small atrophic area superior to the fovea is visible, displaying gradual growth until January 2013. By February 2017, there is a marked increase in both the number and total size of atrophic regions. In May 2022, further enlargement is evident, while the fovea remains unaffected by atrophy. The fifth column, top row, features a graphical illustration revealing the initial slow growth, followed by exponential expansion, and later linear growth of the total atrophy size. The middle row of the fifth column presents a differential map, highlighting the expansion of atrophy. The increase in atrophy at the second time point is indicated in red, at the third time point in ocher, and at the fourth time point in light blue, illustrating the comparatively slower progression towards the fovea in contrast to the spread toward the peripheral regions of the macula. In the bottom row of the fifth column, an analysis summary table generated by the RegionFinder software displays numerical values for the number of atrophic regions, the total atrophy area, changes from the previous examination, and the rate of change per year.
Figure 2. Geographic atrophy (GA) progression mapping using RegionFinder (Heidelberg Engineering). This figure depicts the progression of GA over approximately 13 years in a right eye. Moving from left to right, the first four columns display color fundus photography, fundus autofluorescence, and RegionFinder-based delineations of GA areas at 4 distinct time points. At the initial visit in January 2010, a small atrophic area superior to the fovea is visible, displaying gradual growth until January 2013. By February 2017, there is a marked increase in both the number and total size of atrophic regions. In May 2022, further enlargement is evident, while the fovea remains unaffected by atrophy. The fifth column, top row, features a graphical illustration revealing the initial slow growth, followed by exponential expansion, and later linear growth of the total atrophy size. The middle row of the fifth column presents a differential map, highlighting the expansion of atrophy. The increase in atrophy at the second time point is indicated in red, at the third time point in ocher, and at the fourth time point in light blue, illustrating the comparatively slower progression towards the fovea in contrast to the spread toward the peripheral regions of the macula. In the bottom row of the fifth column, an analysis summary table generated by the RegionFinder software displays numerical values for the number of atrophic regions, the total atrophy area, changes from the previous examination, and the rate of change per year.

Optical Coherence Tomography

Optical coherence tomography (OCT) provides in vivo cross-sectional and en face visualization of the retina and RPE. Spectral-domain OCT (SD-OCT) is widely available and validated to assess and quantify phenotypes of AMD. Volume scans (SD-OCT or swept-source OCT) integrate a dense raster pattern of line-scans to display a representative image of macula topography. Spacing between line-scans can be modified to provide more or less detail within the image. It is important to select spacing sufficiently small to detect small areas of atrophy or subtle intraretinal or subretinal fluid. The level of detail desired must be balanced against time constraints, because denser scans require longer acquisition times. Although SD-OCT settings will be determined to some extent by the clinical question, SD-OCT should cover an area of at least 6 mm x 6 mm with distances between single line-scans no greater than 120 mm. An OCT should be completed at each visit and directly compared to prior images to monitor for progression of dry AMD/GA and for conversion to exudative AMD.2

Angiography

Fluorescein angiography (FA) has limited utility for monitoring dry AMD. A baseline FA can be considered to rule out the presence of MNV. Outside of this purpose, FA is not necessary for routine management of dry AMD.2,8 

Optical coherence tomography angiography (OCTA) detects blood flow using motion contrast (eg, Doppler). Unlike conventional dye-based angiography, OCTA is noninvasive and depth-resolved. It is primarily useful for visualizing MNV and can detect early, nonexudative MNV. As such, it does not have a role in regular monitoring of dry AMD. It can be used when there is a specific concern for MNV formation based on OCT imaging in patients being followed for dry AMD.2,9,10

Differential Diagnostics

Several distinct inherited retinal degenerations and toxic maculopathies can manifest at a similar age and exhibit shared characteristics with AMD.11 Clinicians should be mindful that the mere presence of well-defined macular atrophy lesions in individuals over the age of 55 does not automatically point to an AMD-related cause. Recent research suggests that common genetic variants linked to AMD rarely result in GA before the age of 70.12

For a precise differential diagnosis, retinal physicians, equipped with readily available multimodal imaging diagnostics in addition to clinical examination, should be vigilant for specific structural changes indicative of other retinal diseases. These include, but are not limited to, unusual FAF signal alterations around atrophic areas, such as flecks and focal regions with increased FAF, which are more characteristic of late-onset Stargardt disease (Figure 3). Drusen related to AMD typically do not lead to an elevated FAF signal. Therefore, when a clinician observes an increased signal precisely at the site of drusen or fails to detect drusen around atrophic regions, suspicion should arise regarding atrophy not attributed to AMD. Fundus autofluorescence imaging serves as a crucial tool in the process of differential diagnosis, because it can identify anomalous signal changes surrounding atrophic zones or even unusual distributions of atrophic areas themselves. 

 

Figure 3. Atrophy secondary to Stargardt macular dystrophy (70-year-old patient with biallelic pathogenic variants in the ABCA4 gene). Color fundus photography, fundus autofluorescence, and optical coherence tomography with scan location indicated on near-infrared image.
Figure 3. Atrophy secondary to Stargardt macular dystrophy (70-year-old patient with biallelic pathogenic variants in the ABCA4 gene). Color fundus photography, fundus autofluorescence, and optical coherence tomography with scan location indicated on near-infrared image.

Going beyond imaging diagnostics, several key factors should be considered. These include a positive family history, particularly when an individual is diagnosed with macular atrophy at a young age. Additionally, the presence of atypical symptoms such as deafness, diabetes, skin changes, and a high cardiovascular risk profile, especially when combined with heavy smoking or prior use of medications like hydroxychloroquine or pentosan polysulfate sodium, should lead to a reconsideration of the AMD diagnosis. These factors can have significant implications for patient management, particularly when it comes to initiating disease-specific therapeutic strategies.

Conclusion

Current options for imaging patients with dry AMD include a baseline CFP, OCT, and FAF. In all subsequent follow-ups, OCT can be repeated using the same reference point to enable direct image comparisons. Employing the RegionFinder technology with FAF images can facilitate the assessment of GA progression. These tests are straightforward and noninvasive, streamlining the monitoring process of patients with dry AMD.

For patients undergoing GA treatment, clinicians may also consider obtaining a baseline OCT retinal nerve fiber layer scan to evaluate optic nerve health. This baseline scan can serve as a foundation for future monitoring, particularly in the context of serial high-volume injections and the potential risk of ischemic retinopathy. RP

Brian Solinsky, MD, is with the University of Utah John A. Moran Eye Center in Salt Lake City, Utah. He reports no relevant disclosures.

Eliza Broadbent, BS, is with the University of Utah John A. Moran Eye Center in Salt Lake City, Utah. She reports no relevant disclosures.

Elias Siltanen, BS, is with the University of Utah John A. Moran Eye Center in Salt Lake City, Utah. He reports no relevant disclosures.

Monika Fleckenstein, MD, is with the University of Utah John A. Moran Eye Center in Salt Lake City, Utah. She reports no relevant disclosures. Reach Dr. Fleckenstein at monika.fleckenstein@hsc.utah.edu.

Steffen Schmitz-Valckenberg, MD, is with the University of Utah John A. Moran Eye Center in Salt Lake City, Utah. He reports grants and/or research funding from from AlphaRET, Apellis, Bayer, Formycon, Carl Zeiss MediTec, Galimedix, Katairo, Kubota Vision, Novartis, Perceive Therapeutics, Pixium, Roche/Genentech, and SparingVision; consulting fees from Apellis and Roche/Genentech; and nonfinancial support from Carl Zeiss Meditec and Heidelberg Engineering.

Editor's note: This work was supported by National Institutes of Health Core Grant (EY014800), and an unrestricted grant from Research to Prevent Blindness to the Department of Ophthalmology and Visual Sciences, University of Utah. 

This article is discussed on the Retina Podcast at www.retinapodcast.com.

References

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