ArticleJournal of digital imaging2019
Assessment of Orbital Computed Tomography (CT) Imaging Biomarkers in Patients with Thyroid Eye Disease.
Article in Journal of digital imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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.
- Advancements in imaging research in thyroid-associated ophthalmopathy.Frontiers in endocrinology · 2025Review
- CT-based artificial intelligence prediction model for ocular motility score of thyroid eye disease.Endocrine · 2024Article
- Thyroid Eye Disease: Advancements in Orbital and Ocular Pathology Management.Journal of personalized medicine · 2024Review
- Artificial Intelligence Automation of Proptosis Measurement: An Indicator for Pediatric Orbital Abscess Surgery.Ophthalmology and therapy · 2023Article
- Computed tomography and magnetic resonance imaging approaches to Graves' ophthalmopathy: a narrative review.Frontiers in endocrinology · 2023Review
- Diagnostic Ability of Barrett's Index and Presence of Intracranial Fat Prolapse in Dysthyroid Optic Neuropathy.Clinical ophthalmology (Auckland, N.Z.) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
To understand potential orbital biomarkers generated from computed tomography (CT) imaging in patients with thyroid eye disease. This is a retrospective cohort study. From a database of an ongoing thyroid eye disease research study at our institution, we identified 85 subjects who had both clinical examination and laboratory records supporting the diagnosis of thyroid eye disease and concurrent imaging prior to any medical or surgical intervention. Patients were excluded if imaging quality or type was not amenable to segmentation. The images of 170 orbits were analyzed with the developed automated segmentation tool. The main outcome measure was to cross 25 CT structural metrics for each eye with nine clinical markers using a Kendall rank correlation test to identify significant relationships. The Kendall rank correlation test between automatically calculated CT metrics and clinical data demonstrated numerous correlations. Extraocular rectus muscle metrics, such as the average diameter of the superior, medial, and lateral rectus muscles, showed a strong correlation (p < 0.05) with loss of visual acuity and presence of ocular motility defects. Hertel measurements demonstrated a strong correlation (p < 0.05) with volumetric measurements of the optic nerve and other orbital metrics such as the crowding index and proptosis. Optic neuropathy was strongly correlated (p < 0.05) with an increase in the maximum diameter of the superior muscle. This novel method of automated imaging metrics may provide objective, rapid clinical information. This data may be useful for appreciation of severity of thyroid eye disease and recognition of risk factors of visual impairment from dysthyroid optic neuropathy from CT imaging.
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Registered trials
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