Predicting Topographic Disease Progression and Treatment Response of Pegcetacoplan in Geographic Atrophy Quantified by Deep Learning

OCT risk factors for 2-year foveal involvement in non-treated eyes with extrafoveal geographic atrophy and AMD

PURPOSE

To assess the relationship of optical coherence tomography (OCT) findings and progression to foveal atrophy in a cohort of eyes with extrafoveal geographic atrophy (GA) and age-related macular degeneration (AMD) at inclusion.

METHODS

We retrospectively analyzed 45 participants (45 eyes) with extrafoveal GA at baseline and with 2 years of regular follow-ups. Several OCT qualitative features (i.e., presence of foveal flat pigment epithelium detachment with a thin double layer sign [DLS] and reticular pseudodrusen, GA focality) and quantitative measurements (outer retinal layer thickness, retinal pigment epithelium [RPE] to Bruch's membrane [BM] volume, minimum distance from the central foveal circle, and untransformed GA lesion size area) were assessed at baseline. Logistic regression analyses were carried out to identify independent significant predictors and compute odds ratios (ORs) for the risk of the development of atrophy.

RESULTS

At month 24, 26 eyes (57.8%) developed atrophy in the foveal central circle, while 11 eyes (24.4%) developed atrophy in the foveal central point. Significant independent predictive features for the development of atrophy in the foveal central circle included foveal outer retinal thickness (OR, 0.867; p = 0.015), minimum distance from the foveal central circle (OR, 0.992; p = 0.022), and foveal thin DLS (OR, 0.044; p = 0.036). The only independent predictive feature for the development of atrophy in the foveal central point was the presence of foveal thin DLS (OR, 0.138; p = 0.017).

CONCLUSIONS

We identified OCT risk factors for 2-year foveal atrophy in eyes with untreated extrafoveal GA at baseline.

Geographic Atrophy Natural History Versus Treatment: Time to Fovea

BACKGROUND AND OBJECTIVE

The Food and Drug Administration recently approved treatments of geographic atrophy (GA). Our study aims to quantify the time for a lesion to reach the central fovea based on reduction of GA growth rates from therapeutics compared to the natural history.

PATIENTS AND METHODS

A previously published study calculates local border expansion rate of GA lesions at varying retinal eccentricities. In this study, we use these rates to model GA expansion toward the fovea and the effects of treatments that reduce growth in GA area by 15% to 45% on lesions of varying sizes with posterior margin 250, 500, 750, 1000, 1250, 1500, and 3000 µm from the fovea.

RESULTS

Lesions with an area 8 mm2 and posterior edge 500 µm from the fovea will reach the fovea in 5.08 years with no treatment, but the same lesions will reach the fovea in 5.85, 6.52, 7.36, and 8.46 years with a treatment that reduces growth in GA area by 15%, 25%, 35%, and 45%, respectively.

CONCLUSIONS

Distance of the posterior edge of the lesion was the primary factor in GA growth toward the fovea, and lesion size only minimally affects growth rates of GA. Based on the efficacy of current and future therapeutics and distance of GA to the fovea, our study provides the marginal time benefit of treatment to guide patients and clinicians, placing both the natural history of GA and the effects of current and future treatments into clinical context. [Ophthalmic Surg Lasers Imaging Retina 2024;55:XX-XX.].

Ophthalmologists' awareness of geographic atrophy: An Italian survey including 365 participants

PURPOSE

Geographic atrophy (GA) is a severe complication of age-related macular degeneration (AMD) and leads to irreversible visual decline. To date, no effective treatment is available for GA patients. However, a number of new therapies have recently been approved and several others are in the pipeline. This rapid evolution of prospects for GA patients requires constant updating of ophthalmologists' understanding of GA and its management so as to provide the appropriate treatment. For this reason, Società Italiana di Scienze Oftalmologiche (S.I.S.O.) has designed a specific survey to gauge the position of Italian ophthalmologists in this regard.

METHODS

The three hundred and sixty-five Italian ophthalmologists who agreed to take part received a seventeen-part questionnaire guaranteeing privacy and anonymity. The survey was compiled through an online portal and the results were sent directly to S.I.S.O. ETS. Two graders analyzed the data and recorded the results.

RESULTS

The results showed a high level of self-assessed awareness and understanding of GA, as well as considerable willingness to further improve knowledge of the disease. Most of the participants claimed to have effective rules of conduct in place for managing GA patients, including prompt response, involving a high prevalence of nutraceutical prescriptions and lifestyle recommendations.

CONCLUSIONS

This survey provided an overview of how GA patients are managed in Italy. The Italian ophthalmology community appears to be ready to adopt the upcoming treatments for GA.

Imaging geographic atrophy: integrating structure and function to better understand the effects of new treatments

Geographic atrophy (GA) is an advanced and irreversible form of age-related macular degeneration (AMD). Chronic low grade inflammation is thought to act as an initiator of this degenerative process, resulting in loss of photoreceptors (PRs), retinal pigment epithelium (RPE) and the underlying choriocapillaris. This review examined the challenges of clinical trials to date which have sought to treat GA, with particular reference to the successful outcome of C3 complement inhibition. Currently, optical coherence tomography (OCT) seems to be the most suitable method to detect GA and monitor the effect of treatment. In addition, the merits of using novel anatomical endpoints in detecting GA expansion are discussed. Although best-corrected visual acuity is commonly used to monitor disease in GA, other tests to determine visual function are explored. Although not widely available, microperimetry enables quantification of retinal sensitivity (RS) and macular fixation behaviour related to fundus characteristics. There is a spatial correlation between OCT/fundus autofluorescence evaluation of PR damage outside the area of RPE loss and RS on microperimetry, showing important associations with visual function. Standardisation of testing by microperimetry is necessary to enable this modality to detect AMD progression. Artificial intelligence (AI) analysis has shown PR layers integrity precedes and exceeds GA loss. Loss of the ellipsoid zone has been recognised as a primary outcome parameter in therapeutic trials for GA. The integrity of the PR layers imaged by OCT at baseline has been shown to be an important prognostic indicator. AI has the potential to be invaluable in personalising care and justifying treatment intervention.

Deep Learning Approaches for Detecting of Nascent Geographic Atrophy in Age-Related Macular Degeneration

Purpose

Nascent geographic atrophy (nGA) refers to specific features seen on OCT B-scans, which are strongly associated with the future development of geographic atrophy (GA). This study sought to develop a deep learning model to screen OCT B-scans for nGA that warrant further manual review (an artificial intelligence [AI]-assisted approach), and to determine the extent of reduction in OCT B-scan load requiring manual review while maintaining near-perfect nGA detection performance.

Design

Development and evaluation of a deep learning model.

Participants

One thousand eight hundred and eighty four OCT volume scans (49 B-scans per volume) without neovascular age-related macular degeneration from 280 eyes of 140 participants with bilateral large drusen at baseline, seen at 6-monthly intervals up to a 36-month period (from which 40 eyes developed nGA).

Methods

OCT volume and B-scans were labeled for the presence of nGA. Their presence at the volume scan level provided the ground truth for training a deep learning model to identify OCT B-scans that potentially showed nGA requiring manual review. Using a threshold that provided a sensitivity of 0.99, the B-scans identified were assigned the ground truth label with the AI-assisted approach. The performance of this approach for detecting nGA across all visits, or at the visit of nGA onset, was evaluated using fivefold cross-validation.

Main Outcome Measures

Sensitivity for detecting nGA, and proportion of OCT B-scans requiring manual review.

Results

The AI-assisted approach (utilizing outputs from the deep learning model to guide manual review) had a sensitivity of 0.97 (95% confidence interval [CI] = 0.93-1.00) and 0.95 (95% CI = 0.87-1.00) for detecting nGA across all visits and at the visit of nGA onset, respectively, when requiring manual review of only 2.7% and 1.9% of selected OCT B-scans, respectively.

Conclusions

A deep learning model could be used to enable near-perfect detection of nGA onset while reducing the number of OCT B-scans requiring manual review by over 50-fold. This AI-assisted approach shows promise for substantially reducing the current burden of manual review of OCT B-scans to detect this crucial feature that portends future development of GA.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

American Society of Retina Specialists Clinical Practice Guidelines on Multimodal Imaging for Retinal Disease

Purpose: Advancements in retinal imaging have augmented our understanding of the pathology and structure-function relationships of retinal disease. No single diagnostic test is sufficient; rather, diagnostic and management strategies increasingly involve the synthesis of multiple imaging modalities. Methods: This literature review and editorial offer practical clinical guidelines for how the retina specialist can use multimodal imaging to manage retinal conditions. Results: Various imaging modalities offer information on different aspects of retinal structure and function. For example, optical coherence tomography (OCT) and B-scan ultrasonography can provide insights into the microstructural anatomy; fluorescein angiography (FA), indocyanine green angiography (ICGA), and OCT angiography (OCTA) can reveal vascular integrity and perfusion status; and near-infrared reflectance and fundus autofluorescence (FAF) can characterize molecular components within tissues. Managing retinal vascular diseases often includes fundus photography, OCT, OCTA, and FA to evaluate for macular edema, retinal ischemia, and the secondary complications of neovascularization (NV). OCT and FAF play a key role in diagnosing and treating maculopathies. FA, OCTA, and ICGA can help identify macular NV, posterior uveitis, and choroidal venous insufficiency, which guides treatment strategies. Finally, OCT and B-scan ultrasonography can help with preoperative planning and prognostication in vitreoretinal surgical conditions. Conclusions: Today, the retina specialist has access to numerous retinal imaging modalities that can augment the clinical examination to help diagnose and manage retinal conditions. Understanding the capabilities and limitations of each modality is critical to maximizing its clinical utility.

Structural OCT and OCT angiography biomarkers associated with the development and progression of geographic atrophy in AMD

BACKGROUND

Geographic atrophy (GA) is an advanced, irreversible, and progressive form of age-related macular degeneration (AMD). Structural optical coherence tomography (OCT) and OCT angiography (OCTA) have been largely used to characterize this stage of AMD and, more importantly, to define biomarkers associated with the development and progression of GA in AMD.

METHODS

Articles pertaining to OCT and OCTA biomarkers related to the development and progression of GA with relevant key words were used to search in PubMed, Researchgate, and Google Scholar. The articles were selected based on their relevance, reliability, publication year, published journal, and accessibility.

RESULTS

Previous reports have highlighted various OCT and OCTA biomarkers linked to the onset and advancement of GA. These biomarkers encompass characteristics such as the size, volume, and subtype of drusen, the presence of hyperreflective foci, basal laminar deposits, incomplete retinal pigment epithelium and outer retinal atrophy (iRORA), persistent choroidal hypertransmission defects, and the existence of subretinal drusenoid deposits (also referred to as reticular pseudodrusen). Moreover, biomarkers associated with the progression of GA include thinning of the outer retina, photoreceptor degradation, the distance between retinal pigment epithelium and Bruch's membrane, and choriocapillaris loss.

CONCLUSION

The advent of novel treatment strategies for GA underscores the heightened need for prompt diagnosis and precise monitoring of individuals with this condition. The utilization of structural OCT and OCTA becomes essential for identifying distinct biomarkers associated with the initiation and progression of GA.

Quantitative Autofluorescence at AMD's Beginnings Highlights Retinal Topography and Grading System Differences: ALSTAR2 Baseline

INTRODUCTION

The aims of the study were to describe baseline quantitative (short-wavelength) autofluorescence (qAF) findings in a large pseudophakic cohort at age-related macular degeneration (AMD)'s beginnings and to assess qAF8 as an outcome measure and evaluate Age-Related Eye Disease Study (AREDS) and Beckman grading systems.

METHODS

In the ALSTAR2 baseline cohort (NCT04112667), 346 pseudophakic eyes of 188 persons (74.0 ± 5.5 years) were classified as normal (N = 160 by AREDS, 158 by Beckman), early AMD (eAMD) (N = 104, 66), and intermediate AMD (iAMD) (N = 82, 122). Groups were compared via mean qAF intensities in a 6°-8° annulus (qAF8) and maps of differences between observations and the overall mean, divided by standard deviation (Z-score).

RESULTS

qAF8 did not differ significantly among diagnostic groups by either stratification (p = 0.0869 AREDS; p = 0.0569 by Beckman). Notably, 45 eyes considered eAMD by AREDS became iAMD by Beckman. For AREDS-stratified eyes, Z-score maps showed higher centrally located qAF for normal, near the mean in eAMD, and lower values for iAMD. Maps deviated from this pattern for Beckman-stratified eyes.

CONCLUSIONS

In a large sample of pseudophakic eyes, qAF8 does not differ overall from normal aging to iAMD but also does not capture the earliest AMD activity in the macula lutea. AREDS classification gives results more consistent with a slow decline in histologic autofluorescence than Beckman classification.

Non-Neovascular Age-Related Macular Degeneration Assessment: Focus on Optical Coherence Tomography Biomarkers

The imagistic evaluation of non-neovascular age-related macular degeneration (AMD) is crucial for diagnosis, monitoring progression, and guiding management of the disease. Dry AMD, characterized primarily by the presence of drusen and retinal pigment epithelium atrophy, requires detailed visualization of the retinal structure to assess its severity and progression. Several imaging modalities are pivotal in the evaluation of non-neovascular AMD, including optical coherence tomography, fundus autofluorescence, or color fundus photography. In the context of emerging therapies for geographic atrophy, like pegcetacoplan, it is critical to establish the baseline status of the disease, monitor the development and expansion of geographic atrophy, and to evaluate the retina's response to potential treatments in clinical trials. The present review, while initially providing a comprehensive description of the pathophysiology involved in AMD, aims to offer an overview of the imaging modalities employed in the evaluation of non-neovascular AMD. Special emphasis is placed on the assessment of progression biomarkers as discerned through optical coherence tomography. As the landscape of AMD treatment continues to evolve, advanced imaging techniques will remain at the forefront, enabling clinicians to offer the most effective and tailored treatments to their patients.

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment

OBJECTIVE

To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on OCT (photoreceptor degeneration (PRD), retinal pigment epithelium (RPE) loss and hypertransmission); and the area of unaffected healthy macula.To identify OCT predictive biomarkers for GA growth.

METHODS

Post hoc analysis of the FILLY trial using a deep-learning model for spectral domain OCT (SD-OCT) autosegmentation. 246 patients were randomised 1:1:1 into pegcetacoplan monthly (PM), pegcetacoplan every other month (PEOM) and sham treatment (pooled) for 12 months of treatment and 6 months of therapy-free monitoring. Only participants with Heidelberg SD-OCT were included (n=197, single eye per participant).The primary efficacy endpoint was the square root transformed change in area of GA as complete RPE and outer retinal atrophy (cRORA) in each treatment arm at 12 months, with secondary endpoints including RPE loss, hypertransmission, PRD and intact macular area.

RESULTS

Eyes treated PM showed significantly slower mean change of cRORA progression at 12 and 18 months (0.151 and 0.277 mm, p=0.0039; 0.251 and 0.396 mm, p=0.039, respectively) and RPE loss (0.147 and 0.287 mm, p=0.0008; 0.242 and 0.410 mm, p=0.00809). PEOM showed significantly slower mean change of RPE loss compared with sham at 12 months (p=0.0313). Intact macular areas were preserved in PM compared with sham at 12 and 18 months (p=0.0095 and p=0.044). PRD in isolation and intact macula areas was predictive of reduced cRORA growth at 12 months (coefficient 0.0195, p=0.01 and 0.00752, p=0.02, respectively) CONCLUSION: The OCT evidence suggests that pegcetacoplan slows progression of cRORA overall and RPE loss specifically while protecting the remaining photoreceptors and slowing the progression of healthy retina to iRORA.

Multimodal imaging and deep learning in geographic atrophy secondary to age-related macular degeneration

Geographic atrophy (GA) secondary to age-related macular degeneration is among the most common causes of irreversible vision loss in industrialized countries. Recently, two therapies have been approved by the US FDA. However, given the nature of their treatment effect, which primarily involves a relative decrease in disease progression, discerning the individual treatment response at the individual level may not be readily apparent. Thus, clinical decision-making may have to rely on the quantification of the slope of GA progression before and during treatment. A panel of imaging modalities and artificial intelligence (AI)-based algorithms are available for such quantifications. This article aims to provide a comprehensive overview of the fundamentals of GA imaging, the procedures for diagnosis and classification using these images, and the cutting-edge role of AI algorithms in automatically deriving diagnostic and prognostic insights from imaging data.

Biomarkers for the Progression of Intermediate Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a leading cause of severe vision loss worldwide, with a global prevalence that is predicted to substantially increase. Identifying early biomarkers indicative of progression risk will improve our ability to assess which patients are at greatest risk of progressing from intermediate AMD (iAMD) to vision-threatening late-stage AMD. This is key to ensuring individualized management and timely intervention before substantial structural damage. Some structural biomarkers suggestive of AMD progression risk are well established, such as changes seen on color fundus photography and more recently optical coherence tomography (drusen volume, pigmentary abnormalities). Emerging biomarkers identified through multimodal imaging, including reticular pseudodrusen, hyperreflective foci, and drusen sub-phenotypes, are being intensively explored as risk factors for progression towards late-stage disease. Other structural biomarkers merit further research, such as ellipsoid zone reflectivity and choriocapillaris flow features. The measures of visual function that best detect change in iAMD and correlate with risk of progression remain under intense investigation, with tests such as dark adaptometry and cone-specific contrast tests being explored. Evidence on blood and plasma markers is preliminary, but there are indications that changes in levels of C-reactive protein and high-density lipoprotein cholesterol may be used to stratify patients and predict risk. With further research, some of these biomarkers may be used to monitor progression. Emerging artificial intelligence methods may help evaluate and validate these biomarkers; however, until we have large and well-curated longitudinal data sets, using artificial intelligence effectively to inform clinical trial design and detect outcomes will remain challenging. This is an exciting area of intense research, and further work is needed to establish the most promising biomarkers for disease progression and their use in clinical care and future trials. Ultimately, a multimodal approach may yield the most accurate means of monitoring and predicting future progression towards vision-threatening, late-stage AMD.

[Topical treatment for age-related macular degeneration: Where are we now?]

The therapeutic management of age-related macular degeneration (AMD) is a major public health issue. One of its two late forms, neovascular AMD, is currently treated by intravitreal injections of pharmaceutical active ingredients. Although it is very effective in treating pathologies of the posterior segment of the eye, the intravitreal route is not an ideal option for the long-term management of a chronic disease such as AMD. Indeed, in the literature, some authors even call it a "burden" for the practitioners, the patients and the healthcare system. Thus, consideration should be given to less invasive routes. Among the possible administration routes to reach the posterior segment of the eye, the most suitable for the patient with the least risk of systemic adverse effects is the topical route. Several research teams have attempted to formulate molecules for topical administration in the treatment of atrophic or neovascular AMD. In this review, we emphasize the importance of the pharmaceutical formulation to meet the challenge of targeting the posterior segment of the eye by a topical route.

Deep learning in optical coherence tomography: Where are the gaps?

Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid, high-resolution and cross-sectional morphology of macular area and optic nerve head for diagnosis and managing of different eye diseases. However, interpreting OCT images requires experts in both OCT images and eye diseases since many factors such as artefacts and concomitant diseases can affect the accuracy of quantitative measurements made by post-processing algorithms. Currently, there is a growing interest in applying deep learning (DL) methods to analyse OCT images automatically. This review summarises the trends in DL-based OCT image analysis in ophthalmology, discusses the current gaps, and provides potential research directions. DL in OCT analysis shows promising performance in several tasks: (1) layers and features segmentation and quantification; (2) disease classification; (3) disease progression and prognosis; and (4) referral triage level prediction. Different studies and trends in the development of DL-based OCT image analysis are described and the following challenges are identified and described: (1) public OCT data are scarce and scattered; (2) models show performance discrepancies in real-world settings; (3) models lack of transparency; (4) there is a lack of societal acceptance and regulatory standards; and (5) OCT is still not widely available in underprivileged areas. More work is needed to tackle the challenges and gaps, before DL is further applied in OCT image analysis for clinical use.

Treatment of dry age-related macular degeneration: A review

Age-related macular degeneration is a global disease with a significant societal impact. The advent of anti-vascular endothelial growth factor therapy (anti-VEGF) has revolutionised the treatment of neovascular age-related macular degeneration (nAMD). Dry age-related macular degeneration (dAMD) is being investigated for possible therapeutic options. The therapeutic categories undergoing clinical trials include complement pathway inhibitors, visual cycle modulators, reduction of toxic byproducts, antioxidative therapy, neuroprotective agents, laser therapy, surgical options, gene therapy, stem cell therapy, and miscellaneous treatments. Two intravitreal anti-complement factors (pegcetacoplan and avacincaptad pegol) have recently shown phase 3 clinical trial evidence of a reduction in the growth of geographic atrophy. In this review, we provide an update on treatment options currently undergoing clinical research trials for the management of dAMD and preventing the progression of Geographic Atrophy (GA).

[Monitoring of the progression of geographic atrophy with optical coherence tomography]

With the prospect of available therapy for geographic atrophy in the near future and consequently increasing patient numbers, appropriate management strategies for the clinical practice are needed. Optical coherence tomography (OCT) as well as automated OCT analysis using artificial intelligence algorithms provide optimal conditions for assessing disease activity as well as the treatment response for geographic atrophy through a rapid, precise and resource-efficient evaluation.

The impact of artificial intelligence on retinal disease management: Vision Academy retinal expert consensus

PURPOSE OF REVIEW

The aim of this review is to define the "state-of-the-art" in artificial intelligence (AI)-enabled devices that support the management of retinal conditions and to provide Vision Academy recommendations on the topic.

RECENT FINDINGS

Most of the AI models described in the literature have not been approved for disease management purposes by regulatory authorities. These new technologies are promising as they may be able to provide personalized treatments as well as a personalized risk score for various retinal diseases. However, several issues still need to be addressed, such as the lack of a common regulatory pathway and a lack of clarity regarding the applicability of AI-enabled medical devices in different populations.

SUMMARY

It is likely that current clinical practice will need to change following the application of AI-enabled medical devices. These devices are likely to have an impact on the management of retinal disease. However, a consensus needs to be reached to ensure they are safe and effective for the overall population.

Unleashing the power of optical attenuation coefficients to facilitate segmentation strategies in OCT imaging of age-related macular degeneration: perspective

The use of optical attenuation coefficients (OAC) in optical coherence tomography (OCT) imaging of the retina has improved the segmentation of anatomic layers compared with traditional intensity-based algorithms. Optical attenuation correction has improved our ability to measure the choroidal thickness and choroidal vascularity index using dense volume scans. Algorithms that combine conventional intensity-based segmentation with depth-resolved OAC OCT imaging have been used to detect elevations of the retinal pigment epithelium (RPE) due to drusen and basal laminar deposits, the location of hyperpigmentation within the retina and along the RPE, the identification of macular atrophy, the thickness of the outer retinal (photoreceptor) layer, and the presence of calcified drusen. OAC OCT algorithms can identify the risk-factors that predict disease progression in age-related macular degeneration.

Complement Inhibitors for Advanced Dry Age-Related Macular Degeneration (Geographic Atrophy): Some Light at the End of the Tunnel?

Geographic atrophy (GA) affects around 5 million individuals worldwide. Genome-wide, histopathologic, in vitro and animal studies have implicated the activation of the complement system and chronic local inflammation in the pathogenesis of GA. Recently, clinical trials have demonstrated that an intravitreal injection of pegcetacoplan, a C3 inhibitor, and avacincaptad pegol, a C5 inhibitor, both statistically significantly reduce the growth of GA up to 20% in a dose-dependent fashion. Furthermore, the protective effect of both pegcetacoplan and avacincaptad appear to increase with time. However, despite these anatomic outcomes, visual function has not improved as these drugs appear to only slow down the degenerative process. Unexpected adverse events included conversion to exudative NV-AMD with both drugs. Occlusive retinal vasculitis and anterior ischemic optic neuropathy have been reported in pegcetacoplan-treated eyes.

Complement inhibitors for age-related macular degeneration

BACKGROUND

Age-related macular degeneration (AMD) is a common eye disease and leading cause of sight loss worldwide. Despite its high prevalence and increasing incidence as populations age, AMD remains incurable and there are no treatments for most patients. Mounting genetic and molecular evidence implicates complement system overactivity as a key driver of AMD development and progression. The last decade has seen the development of several novel therapeutics targeting complement in the eye for the treatment of AMD. This review update encompasses the results of the first randomised controlled trials in this field.

OBJECTIVES

To assess the effects and safety of complement inhibitors in the prevention or treatment of AMD.

SEARCH METHODS

We searched CENTRAL on the Cochrane Library, MEDLINE, Embase, LILACS, Web of Science, ISRCTN registry, ClinicalTrials.gov, and the WHO ICTRP to 29 June 2022 with no language restrictions. We also contacted companies running clinical trials for unpublished data.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) with parallel groups and comparator arms that studied complement inhibition for advanced AMD prevention/treatment.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed search results and resolved discrepancies through discussion. Outcome measures evaluated at one year included change in best-corrected visual acuity (BCVA), untransformed and square root-transformed geographic atrophy (GA) lesion size progression, development of macular neovascularisation (MNV) or exudative AMD, development of endophthalmitis, loss of ≥ 15 letters of BCVA, change in low luminance visual acuity, and change in quality of life. We assessed risk of bias and evidence certainty using Cochrane risk of bias and GRADE tools.

MAIN RESULTS

Ten RCTs with 4052 participants and eyes with GA were included. Nine evaluated intravitreal (IVT) administrations against sham, and one investigated an intravenous agent against placebo. Seven studies excluded patients with prior MNV in the non-study eye, whereas the three pegcetacoplan studies did not. The risk of bias in the included studies was low overall. We also synthesised results of two intravitreal agents (lampalizumab, pegcetacoplan) at monthly and every-other-month (EOM) dosing intervals. Efficacy and safety of IVT lampalizumab versus sham for GA For 1932 participants in three studies, lampalizumab did not meaningfully change BCVA given monthly (+1.03 letters, 95% confidence interval (CI) -0.19 to 2.25) or EOM (+0.22 letters, 95% CI -1.00 to 1.44) (high-certainty evidence). For 1920 participants, lampalizumab did not meaningfully change GA lesion growth given monthly (+0.07 mm², 95% CI -0.09 to 0.23; moderate-certainty due to imprecision) or EOM (+0.07 mm², 95% CI -0.05 to 0.19; high-certainty). For 2000 participants, lampalizumab may have also increased MNV risk given monthly (RR 1.77, 95% CI 0.73 to 4.30) and EOM (RR 1.70, 95% CI 0.67 to 4.28), based on low-certainty evidence. The incidence of endophthalmitis in patients treated with monthly and EOM lampalizumab was 4 per 1000 (0 to 87) and 3 per 1000 (0 to 62), respectively, based on moderate-certainty evidence. Efficacy and safety of IVT pegcetacoplan versus sham for GA For 242 participants in one study, pegcetacoplan probably did not meaningfully change BCVA given monthly (+1.05 letters, 95% CI -2.71 to 4.81) or EOM (-1.42 letters, 95% CI -5.25 to 2.41), as supported by moderate-certainty evidence. In contrast, for 1208 participants across three studies, pegcetacoplan meaningfully reduced GA lesion growth when given monthly (-0.38 mm², 95% CI -0.57 to -0.19) and EOM (-0.29 mm², 95% CI -0.44 to -0.13), with high certainty. These reductions correspond to 19.2% and 14.8% versus sham, respectively. A post hoc analysis showed possibly greater benefits in 446 participants with extrafoveal GA given monthly (-0.67 mm², 95% CI -0.98 to -0.36) and EOM (-0.60 mm², 95% CI -0.91 to -0.30), representing 26.1% and 23.3% reductions, respectively. However, we did not have data on subfoveal GA growth to undertake a formal subgroup analysis. In 1502 participants, there is low-certainty evidence that pegcetacoplan may have increased MNV risk when given monthly (RR 4.47, 95% CI 0.41 to 48.98) or EOM (RR 2.29, 95% CI 0.46 to 11.35). The incidence of endophthalmitis in patients treated with monthly and EOM pegcetacoplan was 6 per 1000 (1 to 53) and 8 per 1000 (1 to 70) respectively, based on moderate-certainty evidence. Efficacy and safety of IVT avacincaptad pegol versus sham for GA In a study of 260 participants with extrafoveal or juxtafoveal GA, monthly avacincaptad pegol probably did not result in a clinically meaningful change in BCVA at 2 mg (+1.39 letters, 95% CI -5.89 to 8.67) or 4 mg (-0.28 letters, 95% CI -8.74 to 8.18), based on moderate-certainty evidence. Despite this, the drug was still found to have probably reduced GA lesion growth, with estimates of 30.5% reduction at 2 mg (-0.70 mm², 95% CI -1.99 to 0.59) and 25.6% reduction at 4 mg (-0.71 mm², 95% CI -1.92 to 0.51), based on moderate-certainty evidence. Avacincaptad pegol may have also increased the risk of developing MNV (RR 3.13, 95% CI 0.93 to 10.55), although this evidence is of low certainty. There were no cases of endophthalmitis reported in this study.

AUTHORS' CONCLUSIONS

Despite confirmation of the negative findings of intravitreal lampalizumab across all endpoints, local complement inhibition with intravitreal pegcetacoplan meaningfully reduces GA lesion growth relative to sham at one year. Inhibition of complement C5 with intravitreal avacincaptad pegol is also an emerging therapy with probable benefits on anatomical endpoints in the extrafoveal or juxtafoveal GA population. However, there is currently no evidence that complement inhibition with any agent improves functional endpoints in advanced AMD; further results from the phase 3 studies of pegcetacoplan and avacincaptad pegol are eagerly awaited. Progression to MNV or exudative AMD is a possible emergent adverse event of complement inhibition, requiring careful consideration should these agents be used clinically. Intravitreal administration of complement inhibitors is probably associated with a small risk of endophthalmitis, which may be higher than that of other intravitreal therapies. Further research is likely to have an important impact on our confidence in the estimates of adverse effects and may change these. The optimal dosing regimens, treatment duration, and cost-effectiveness of such therapies are yet to be established.

Geographic Atrophy in AMD: Prognostic Factors Based on Long-Term Follow-Up

INTRODUCTION

The aim of this large-scale long-term retrospective study was to show the enlargement rate (ER) of geographic atrophy (GA) in age-related macular degeneration (AMD), defined as complete retinal pigment epithelium and outer retinal atrophy (cRORA), to find predictors of progression in a clinical routine setting and to compare GA evaluation methods.

METHODS

All patients available in our database with follow-up of at least 24 months and cRORA in at least one eye, regardless of neovascular AMD being present, were included. SD-OCT and fundus autofluorescence (FAF) evaluations were performed according to a standardized protocol. The cRORA area ER, the cRORA square root area ER, the FAF GA area, and the condition of the outer retina (inner-/outer-segment [IS/OS] line and external limiting membrane [ELM] disruption scores) were determined.

RESULTS

204 eyes of 129 patients were included. Mean follow-up time was 4.2 ± 2.2 (range 2-10) years. 109 of 204 (53.4%) eyes were classified as MNV-associated GA in AMD (initially or during follow-up); 95 of 204 (46.6%) eyes were classified as pure GA in AMD. The primary lesion was unifocal in 146 (72%) eyes and multifocal in 58 (28%) eyes. A strong correlation was observed between the area of cRORA (SD-OCT) and the FAF GA area (r = 0.924; p < 0.001). Mean ER was 1.44 ± 1.2 mm2/year, mean square root ER 0.29 ± 0.19 mm/year. There was no significant difference in mean ER between eyes without (pure GA) and with intravitreal anti-VEGF injections (MNV-associated GA) (0.30 ± 0.19 mm/year vs. 0.28 ± 0.20 mm/year; p = 0.466). Eyes with multifocal atrophy pattern at baseline had a significantly higher mean ER compared to eyes with unifocal pattern (0.34 ± 0.19 mm/year vs. 0.27 ± 1.19 mm/year; p = 0.008). There were moderate significant correlations between ELM and IS/OS disruption scores and visual acuity at baseline, 5 and 7 years (all r values ca. -0.5; p < 0.001). In multivariate regression analysis, a multifocal cRORA pattern at baseline (p = 0.022) and a smaller baseline lesion size (p = 0.036) were associated with a higher mean ER.

CONCLUSION

SD-OCT-evaluated cRORA area might serve as a GA parameter comparable to traditional FAF measurement in clinical routine. The dispersion pattern and baseline lesion size might be predictors of ER, whereas anti-VEGF treatment seems not to be associated with ER.

Identifying geographic atrophy

PURPOSE OF REVIEW

Age-related macular degeneration (AMD) is one of the leading causes of blindness and can progress to geographic atrophy (GA) in late stages of disease. This review article highlights recent literature which assists in the accurate and timely identification of GA, and monitoring of GA progression.

RECENT FINDINGS

Technology for diagnosing and monitoring GA has made significant advances in recent years, particularly regarding the use of optical coherence tomography (OCT). Identification of imaging features which may herald the development of GA or its progression is critical. Deep learning applications for OCT in AMD have shown promising growth over the past several years, but more prospective studies are needed to demonstrate generalizability and clinical utility.

SUMMARY

Identification of GA and of risk factors for GA development or progression is essential when counseling AMD patients and discussing prognosis. With new therapies on the horizon for the treatment of GA, identification of risk factors for the development and progression of GA will become critical in determining the patients who would be appropriate candidates for new targeted therapies.

Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment

Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives, a strong need for automated GA segmentation has evolved. The main purpose of this study was the clinical validation of an artificial intelligence (AI)-based algorithm to segment a topographic 2D GA area on a 3D optical coherence tomography (OCT) volume, and to evaluate its potential for AI-based monitoring of GA progression under complement-targeted treatment. 100 GA patients from routine clinical care at the Medical University of Vienna for internal validation and 113 patients from the FILLY phase 2 clinical trial for external validation were included. Mean Dice Similarity Coefficient (DSC) was 0.86 ± 0.12 and 0.91 ± 0.05 for total GA area on the internal and external validation, respectively. Mean DSC for the GA growth area at month 12 on the external test set was 0.46 ± 0.16. Importantly, the automated segmentation by the algorithm corresponded to the outcome of the original FILLY trial measured manually on fundus autofluorescence. The proposed AI approach can reliably segment GA area on OCT with high accuracy. The availability of such tools represents an important step towards AI-based monitoring of GA progression under treatment on OCT for clinical management as well as regulatory trials.

Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD

BACKGROUND

The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD).

METHODS

Used in DL model training and testing were 341 subjects with nonexudative AMD with or without geographic atrophy (GA). An independent dataset of 120 subjects were used for testing model performance for prediction of GA progression. Accuracy, specificity, sensitivity, and intraclass correlation coefficient (ICC) for DL-based EZ At-Risk percentage area measurement was calculated. Random forest-based feature ranking of EZ At-Risk was compared to previously validated quantitative OCT-based biomarkers.

RESULTS

The model achieved a detection accuracy of 99% (sensitivity = 99%; specificity = 100%) for EZ At-Risk. Automatic EZ At-Risk measurement achieved an accuracy of 90% (sensitivity = 90%; specificity = 84%) and the ICC compared to ground truth was high (0.83). In the independent dataset, higher baseline mean EZ At-Risk correlated with higher progression to GA at year 5 (p < 0.001). EZ At-Risk was a top ranked feature in the random forest assessment for GA prediction.

CONCLUSIONS

This report describes a novel high performance DL-based model for the detection and measurement of EZ At-Risk. This biomarker showed promising results in predicting progression in nonexudative AMD patients.