ArticleInvestigative ophthalmology & visual science2017
Dynamic Imaging of the Eye, Optic Nerve, and Extraocular Muscles With Golden Angle Radial MRI.
Article in Investigative ophthalmology & visual science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep orbital puncture of the superior ophthalmic vein for embolization of indirect carotid-cavernous fistula: a case report, technical note and review of the current literature.Neuroradiology · 2025Pooled it
- A-eye: Automated 3D MRI segmentation and morphometric feature extraction for eye and orbit atlas construction.PloS one · 2026Article
- Role of Structural, Metabolic, and Functional MRI in Monitoring Visual System Impairment and Recovery.Journal of magnetic resonance imaging : JMRI · 2021Review
- Influence of eye movement on lens dose and optic nerve target coverage during craniospinal irradiation.Clinical and translational radiation oncology · 2021Article
- Incorporating non-linear alignment and multi-compartmental modeling for improved human optic nerve diffusion imaging.NeuroImage · 2019Article
- Article
Corrections and comments
- Erratum issuedErratum.2017
Authors and funding
5 authors.
Funding
Abstract
Purpose: The eye and its accessory structures, the optic nerve and the extraocular muscles, form a complex dynamic system. In vivo magnetic resonance imaging (MRI) of this system in motion can have substantial benefits in understanding oculomotor functioning in health and disease, but has been restricted to date to imaging of static gazes only. The purpose of this work was to develop a technique to image the eye and its accessory visual structures in motion. Methods: Dynamic imaging of the eye was developed on a 3-Tesla MRI scanner, based on a golden angle radial sequence that allows freely selectable frame-rate and temporal-span image reconstructions from the same acquired data set. Retrospective image reconstructions at a chosen frame rate of 57 ms per image yielded high-quality in vivo movies of various eye motion tasks performed in the scanner. Motion analysis was performed for a left-right version task where motion paths, lengths, and strains/globe angle of the medial and lateral extraocular muscles and the optic nerves were estimated. Results: Offline image reconstructions resulted in dynamic images of bilateral visual structures of healthy adults in only ∼15-s imaging time. Qualitative and quantitative analyses of the motion enabled estimation of trajectories, lengths, and strains on the optic nerves and extraocular muscles at very high frame rates of ∼18 frames/s. Conclusions: This work presents an MRI technique that enables high-frame-rate dynamic imaging of the eyes and orbital structures. The presented sequence has the potential to be used in furthering the understanding of oculomotor mechanics in vivo, both in health and disease.
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What OpenQuestion holds
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.