ArticleTranslational vision science & technology2021
Reliability of Retinal Pathology Quantification in Age-Related Macular Degeneration: Implications for Clinical Trials and Machine Learning Applications.
Article in Translational vision science & technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Comparative efficacy of intravitreal anti-VEGF therapy for neovascular age-related macular degeneration: A systematic review with network meta-analysis.Acta ophthalmologica · 2025Pooled it
- Prognostic Ability of Automated RPE Sinuosity for Late AMD Supersedes Qualitative Outer Retinal Band Assessment.Investigative ophthalmology & visual science · 2026Article
- PAIR: Evaluating the Limits of Agreement Among Non-Retinal Specialist Using PathFinder Artificial Intelligence Tool for Retinal Disease Referrals: A Prospective Observational Study.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
- CLEAR report 1: a scoping review and meta-analysis for definitions, imaging metrics, and functional correlates of photoreceptor integrity in AMD.Frontiers in medicine · 2026Review
- Validation of a deep learning model for the automated detection and quantification of cystoid macular oedema on optical coherence tomography in patients with retinitis pigmentosa.Acta ophthalmologica · 2025Article
- Comparison of AI-based retinal fluid monitoring in neovascular age-related macular degeneration with manual assessment by different eye care professionals under optimized conditions.Acta ophthalmologica · 2025Article
- ADVANCES IN PHOTORECEPTOR AND RETINAL PIGMENT EPITHELIUM QUANTIFICATIONS IN INTERMEDIATE AGE-RELATED MACULAR DEGENERATION: High-Res Versus Standard SPECTRALIS Optical Coherence Tomography.Retina (Philadelphia, Pa.) · 2024Article
- Transformer enhanced autoencoder rendering cleaning of noisy optical coherence tomography images.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Denoising of Optical Coherence Tomography Images in Ophthalmology Using Deep Learning: A Systematic Review.Journal of imaging · 2024Review
- Lesion Detection in Optical Coherence Tomography with Transformer-Enhanced Detector.Journal of imaging · 2023Article
- A systematic evaluation of human expert agreement on optical coherence tomography biomarkers using multiple devices.Eye (London, England) · 2023Article
- Automated artificial intelligence-based system for clinical follow-up of patients with age-related macular degeneration.Acta ophthalmologica · 2022Article
- A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography.Translational vision science & technology · 2022Article
- Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice.Progress in retinal and eye research · 2022Review
- Intersession Repeatability of Structural Biomarkers in Early and Intermediate Age-Related Macular Degeneration: A MACUSTAR Study Report.Translational vision science & technology · 2022Article
- Challenges Associated With Ellipsoid Zone Intensity Measurements Using Optical Coherence Tomography.Translational vision science & technology · 2021Article
- Quantitative assessment of retinal fluid in neovascular age-related macular degeneration under anti-VEGF therapy.Therapeutic advances in ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 10 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To investigate the interreader agreement for grading of retinal alterations in age-related macular degeneration (AMD) using a reading center setting. Methods: In this cross-sectional case series, spectral-domain optical coherence tomography (OCT; Topcon 3D OCT, Tokyo, Japan) scans of 112 eyes of 112 patients with neovascular AMD (56 treatment naive, 56 after three anti-vascular endothelial growth factor injections) were analyzed by four independent readers. Imaging features specific for AMD were annotated using a novel custom-built annotation platform. Dice score, Bland-Altman plots, coefficients of repeatability, coefficients of variation, and intraclass correlation coefficients were assessed. Results: Loss of ellipsoid zone, pigment epithelium detachment, subretinal fluid, and drusen were the most abundant features in our cohort. Subretinal fluid, intraretinal fluid, hypertransmission, descent of the outer plexiform layer, and pigment epithelium detachment showed highest interreader agreement, while detection and measures of loss of ellipsoid zone and retinal pigment epithelium were more variable. The agreement on the size and location of the respective annotation was more consistent throughout all features. Conclusions: The interreader agreement depended on the respective OCT-based feature. A selection of reliable features might provide suitable surrogate markers for disease progression and possible treatment effects focusing on different disease stages. Translational Relevance: This might give opportunities for a more time- and cost-effective patient assessment and improved decision making as well as have implications for clinical trials and training machine learning algorithms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.