Consensus Definition for Atrophy Associated with Age-Related Macular Degeneration on OCT: Classification of Atrophy Report 3.
Srinivas R. Sadda,Robyn H. Guymer,Frank G. Holz,Steffen Schmitz-Valckenberg,Christine A. Curcio,Alan C Bird,Barbara A Blodi,Ferdinando Bottoni,Usha Chakravarthy,Emily Y. Chew,Karl G. Csaky,Ronald P. Danis,Monika Fleckenstein,K. Bailey Freund,Juan E. Grunwald,Carel B. Hoyng,Glenn J. Jaffe,Sandra Liakopoulos,Jordi Monés,Daniel Pauleikhoff,Philip J. Rosenfeld,David Sarraf,Richard F. Spaide,Ramin Tadayoni,Adnan Tufail,Adnan Tufail,Sebastian Wolf,Giovanni Staurenghi +27 more
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TLDR
A classification system and criteria for OCT-defined atrophy in the setting of AMD has been proposed based on an international consensus and is a more complete representation of changes that occur in AMD than can be detected using color fundus photography alone.Citations
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Optical coherence tomography angiography.
TL;DR: The integration of OCTA in multimodal imaging in the evaluation of retinal vascular occlusive diseases, diabetic retinopathy, uveitis, inherited diseases, age-related macular degeneration, and disorders of the optic nerve is presented.
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Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data: Consensus on Neovascular Age-Related Macular Degeneration Nomenclature Study Group
Richard F. Spaide,Glenn J. Jaffe,David Sarraf,K. Bailey Freund,Srinivas R. Sadda,Giovanni Staurenghi,Nadia K. Waheed,Usha Chakravarthy,Philip J. Rosenfeld,Frank G. Holz,Eric H. Souied,Salomon Y. Cohen,Giuseppe Querques,Kyoko Ohno-Matsui,David S. Boyer,Alain Gaudric,Barbara A Blodi,Caroline R. Baumal,Xiaoxin Li,Gabriel Coscas,Alexander J. Brucker,Lawrence J. Singerman,Phil Luthert,Steffen Schmitz-Valckenberg,Ursula Schmidt-Erfurth,Hans E. Grossniklaus,David J. Wilson,Robyn H. Guymer,Lawrence A. Yannuzzi,Emily Y. Chew,Karl G. Csaky,Jordi Monés,Daniel Pauleikhoff,Ramin Tadayoni,James G. Fujimoto +34 more
TL;DR: The study group suggests that the consensus standards outlined in this article be used in future reported studies of neovascular AMD and clinical practice.
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Subretinal drusenoid deposits AKA pseudodrusen.
TL;DR: Advances in imaging technology have enabled many insights into this condition, including associated photoreceptor, retinal pigment epithelium, and underlying choroidal changes, and many studies reported that SDDs are strong independent risk factors for late age-related macular degeneration.
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A systems biology approach towards understanding and treating non-neovascular age-related macular degeneration
James T. Handa,Catherine Bowes Rickman,Andrew D. Dick,Andrew D. Dick,Michael B. Gorin,Joan W. Miller,Cynthia A. Toth,Marius Ueffing,Marco A. Zarbin,Lindsay A. Farrer +9 more
TL;DR: The authors propose that research should emphasize system biology approaches that integrate various ‘omics’ data into mathematical models to establish pathogenic mechanisms on which to design novel treatments, and identify biomarkers that predict disease progression and therapeutic response.
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Predicting conversion to wet age-related macular degeneration using deep learning
Jason Yim,Reena Chopra,Terry Spitz,Jim Winkens,Annette Obika,Christopher Kelly,Harry Askham,Marko Lukic,Josef Huemer,Katrin Fasler,Gabriella Moraes,Clemens Meyer,Marc Wilson,Jonathan Mark Dixon,Cian Hughes,Geraint Rees,Peng T. Khaw,Alan Karthikesalingam,Dominic King,Demis Hassabis,Mustafa Suleyman,Trevor Back,Joseph R. Ledsam,Pearse A. Keane,Jeffrey De Fauw +24 more
TL;DR: In individuals diagnosed with age-related macular degeneration in one eye, a deep learning model can predict progression to the ‘wet’, sight-threatening form of the disease in the second eye within a 6-month time frame, and demonstrates the potential of using AI to predict disease progression.
References
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An international classification and grading system for age-related maculopathy and age-related macular degeneration
Alan C. Bird,Neil M. Bressler,Susan B. Bressler,I H Chisholm,Gabriel Coscas,M.D. Davis,P.T.V.M. de Jong,Caroline C W Klaver,Barbara E.K. Klein,Ronald Klein,Philip B. Mitchell,J.P. Sarks,S.H. Sarks,Gisèle Soubrane,Hugh R. Taylor,Johannes R. Vingerling +15 more
TL;DR: A common detection and classification system is needed for epidemiologic studies of age-related maculopathy (ARM) and such a grading scheme for ARM is described in this paper.
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The Wisconsin age-related maculopathy grading system.
Ronald Klein,Matthew D. Davis,Yvonne L. Magli,Paul Segal,Barbara E.K. Klein,Larry D. Hubbard +5 more
TL;DR: A new system for grading age-related maculopathy using stereoscopic 30 degrees color fundus photographs, standard circles printed on plastic to assess size and area, and a specially designed lightbox to allow better discrimination of subtle drusen is described and measures of reliability are reported.
Journal ArticleDOI
Clinical Classification of Age-related Macular Degeneration
Frederick L. Ferris,Charles P. Wilkinson,Alan C. Bird,Usha Chakravarthy,Emily Y. Chew,Karl G. Csaky,Srinivas R. Sadda +6 more
TL;DR: The proposed basic clinical classification scale seems to be of value in predicting the risk of late AMD, and incorporating consistent nomenclature into the practice patterns of all eye care providers may improve communication and patient care.
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Prevalence of Age-related Maculopathy in Australia: The Blue Mountains Eye Study
TL;DR: Detailed prevalence rates for most components of ARM in an Australian population are provided and reinforce the Beaver Dam Eye Study findings for the relative age-specific frequency of age-related macular degeneration components.
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Evolution of geographic atrophy of the retinal pigment epithelium.
TL;DR: The rate of progression slowed once GA had involved all the retina affected by incipient atrophy and the risk of choroidal neovascularization appeared to decline and an estimate of the percentage of fovea involved proving a more useful clinical parameter.