Neovascular age‐related macular degeneration: A review of findings from the real‐world Fight Retinal Blindness! registry

Nguyen, Vuong; Barthelmes, Daniel; Gillies, Mark C

doi:10.1111/ceo.13949

Cited by 16 publications

(13 citation statements)

References 90 publications

(135 reference statements)

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“…Moreover, our analysis impressively demonstrates the overall high levels of exudative activity in nAMD disease: Half of the patients cannot be extended to 2 month intervals or beyond which is distinctly above the retreatment regimens in clinical practice globally ( 29 ). Obviously, the TREND study administered ranibizumab which used to be the most frequently applied substance in anti-VEGF therapy.…”

Section: Discussionmentioning

confidence: 90%

Predicting treat-and-extend outcomes and treatment intervals in neovascular age-related macular degeneration from retinal optical coherence tomography using artificial intelligence

et al. 2022

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PurposeTo predict visual outcomes and treatment needs in a treat & extend (T&E) regimen in neovascular age-related macular degeneration (nAMD) using a machine learning model based on quantitative optical coherence tomography (OCT) imaging biomarkers.Materials and methodsStudy eyes of 270 treatment-naïve subjects, randomized to receiving ranibizumab therapy in the T&E arm of a randomized clinical trial were considered. OCT volume scans were processed at baseline and at the first follow-up visit 4 weeks later. Automated image segmentation was performed, where intraretinal (IRF), subretinal (SRF) fluid, pigment epithelial detachment (PED), hyperreflective foci, and the photoreceptor layer were delineated using a convolutional neural network (CNN). A set of respective quantitative imaging biomarkers were computed across an Early Treatment Diabetic Retinopathy Study (ETDRS) grid to describe the retinal pathomorphology spatially and its change after the first injection. Lastly, using the computed set of OCT features and available clinical and demographic information, predictive models of outcomes and retreatment intervals were built using machine learning and their performance evaluated with a 10-fold cross-validation.ResultsData of 228 evaluable patients were included, as some had missing scans or were lost to follow-up. Of those patients, 55% reached and maintained long (8, 10, 12 weeks) and another 45% stayed at short (4, 6 weeks) treatment intervals. This provides further evidence for a high disease activity in a major proportion of patients. The model predicted the extendable treatment interval group with an AUROC of 0.71, and the visual outcome with an AUROC of up to 0.87 when utilizing both, clinical and imaging features. The volume of SRF and the volume of IRF, remaining at the first follow-up visit, were found to be the most important predictive markers for treatment intervals and visual outcomes, respectively, supporting the important role of quantitative fluid parameters on OCT.ConclusionThe proposed Artificial intelligence (AI) methodology was able to predict visual outcomes and retreatment intervals of a T&E regimen from a single injection. The result of this study is an urgently needed step toward AI-supported management of patients with active and progressive nAMD.

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Section: Discussionmentioning

confidence: 90%

Predicting treat-and-extend outcomes and treatment intervals in neovascular age-related macular degeneration from retinal optical coherence tomography using artificial intelligence

et al. 2022

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“…Although AMD is increasingly common as people age, if we can stop AMD from advancing to more severe forms, we can reduce the prevalence of blindness in the general population [14]. Age-related macular degeneration (AMD) with neovascularization is a prevalent cause of vision loss worldwide.…”

Section: Neovascular Age-related Macular Degenerationmentioning

confidence: 99%

Age-Related Macular Degeneration: Epidemiology, Pathophysiology, Diagnosis, and Treatment

Vyawahare¹,

Shinde²

2022

Cureus

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The greatest global root of irremediable amaurosis in the venerable is age-related macular degeneration (AMD), a complex eye condition. Clinically, AMD is characterized as being in an early stage to late stage and initially affects the macula, which is the center of the retina (advanced AMD). Age-related cellular and metabolic imbalance are made worse by the creation of excessive amounts of free radical species, which causes mitochondrial malfunction. As a result, in AMD-affected eyes, the deprivation of melanocytes, confection, and eventually atrophy within the retinal tissue are caused by the continued proliferation of oxidative stress caused by systemic antioxidant capacity depletion.In the urbanized, industrialized world, age-related macular degeneration (AMD) is one of the major causes of central vision loss in the older age group. Although several causes and mechanisms for the dysfunction and degeneration of the retinal pigment epithelium (RPE) have previously been identified, the condition's symptoms are still not fully understood. Etiopathogenesis is still not entirely understood. As a result, the RPE fails, allowing an accumulation of aberrant misfolded proteins, due to the loss of anatomical control over oppression, altered homeostasis, dysfunctional lipid homeostasis, and failure of mitochondria.Due to the multitude of interconnected processes, numerous complicated therapy combinations will probably be the best option to deliver the best visual outcomes; these combinations will vary depending on the kind and degree of the condition being treated. Undoubtedly, this will lead to the development of customized preventative medications and, hopefully, the revelation of a potential cure. All the mechanisms involved in the etiology of AMD should be continuously probed to create covariates for other contemporaneous or future problems.

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“…Despite the success of anti-VEGF drugs in the management of NV-AMD, many eyes do not gain or maintain useful vision. [ 95 96 ] Eyes with GA have no treatment currently available. Some researchers have reasoned that intervention at the iAMD stage may modify the natural history of the disease.…”

Section: Treatmentmentioning

confidence: 99%

Subretinal drusenoid deposits: An update

Monge

Araya²,

2022

Taiwan J Ophthalmol

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A wide spectrum of phenotypic manifestations characterizes age-related macular degeneration (AMD). Drusen is considered the hallmark of AMD and is located underneath the retinal pigment epithelium (RPE). In contrast, subretinal drusenoid deposits (SDDs), also known as reticular pseudodrusens, are located in the subretinal space, on top of the RPE. SDDs are poorly detected by clinical examination and color fundus photography. Multimodal imaging is required for their proper diagnosis. SDDs are topographically and functionally related to rods. SDDs cause a deep impairment in retinal sensitivity and dark adaptation. SDDs are dynamic structures that may grow, fuse with each other, or regress over time. An intermediate step in some eyes is the development of an acquired vitelliform lesion. The presence of SDD confers an eye a high risk for the development of late AMD. SDD leads to macular neovascularization, particularly type 3, geographic atrophy, and outer retinal atrophy.

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Neovascular age‐related macular degeneration: A review of findings from the real‐world Fight Retinal Blindness! registry

Cited by 16 publications

References 90 publications

Predicting treat-and-extend outcomes and treatment intervals in neovascular age-related macular degeneration from retinal optical coherence tomography using artificial intelligence

Predicting treat-and-extend outcomes and treatment intervals in neovascular age-related macular degeneration from retinal optical coherence tomography using artificial intelligence

Age-Related Macular Degeneration: Epidemiology, Pathophysiology, Diagnosis, and Treatment

Subretinal drusenoid deposits: An update

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