ArticleJAMA ophthalmology2025
Proposed Nomenclature for Landmarks in Anterior-Segment OCT: The APOSTEL-AS Panel Consensus.
Article in JAMA ophthalmology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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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
2 citing papers in PubMed.
- Quantitative Ciliary Body Imaging Using Image-Registered Swept-Source AS-OCT and Ultrasound Biomicroscopy.Translational vision science & technology · 2026Article
- Anterior segment optical coherence tomography in uveitis: A comprehensive review of clinical applications, diagnostic insights, and future directions.Survey of ophthalmologyReview
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Authors and funding
19 authors.
Funding
Abstract
Importance: Anterior-segment optical coherence tomography (AS-OCT) has broad clinical and research utility. The utility of quantitative data derived from AS-OCT is, however, dependent on the quality and consistency of the cumulative evidence base. Objective: To develop consensus-based nomenclature that supports standardized reporting of AS-OCT image acquisition and analyses as a foundation to improve research reproducibility. Design, Setting, and Participants: A multistage consensus exercise was undertaken, in 2024, with an expert panel of ophthalmologists, optometrists, and vision scientists, informed by a scoping review to identify the range of AS-OCT applications and terminologies in use. Panel members were selected to represent the breadth of clinical areas identified within the review or key stakeholder groups (ie, ocular image acquisition, imaging analysis, consensus methodologies). Nominal group technique was used to seek consensus on existing and newly proposed terminologies for normal anatomical structures identifiable within cross-sectional swept-source and spectral-domain AS-OCT images. An ophthalmic histopathologist then reviewed the output for concordance with histological terminology. Data were analyzed from July 2024 to January 2025. Exposures: Expert consensus on nomenclature of ocular structures. Main Outcomes and Measures: Agreement on nomenclature of ocular structures, with consensus defined as at least 80% expert agreement. Results: A multinational group of 14 experts (mean [SD] age, 46.1 [7.8] years; 10 male [71%]) participated in the consensus process. Scoping review findings resulted in the generation of 45 terms for the annotation of identifiable structures. After presentation of multiple image annotations representing these structures, consensus was reached for 31 terms across 7 images. There was consensus on the use of standardized descriptive terms from the Federative Committee on Anatomical Terminology (FCAT) alongside established eponymous terms. There was absence of consensus on annotations and visualization of structures within less optically accessible areas, such as the episcleral and scleral vasculature. Conclusions and Relevance: Results of this survey study describe international, multidisciplinary consensus on terminology for ocular structures identifiable in AS-OCT images and present representative annotated images for reference use. Future expansion of nomenclature and annotation are anticipated, facilitated by advances in imaging technology. Follow-up consensus exercises should consider consensus-based terminology and annotations of pathological structural changes.
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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.