ArticleFrontiers in medicine2022
Risk prediction of dysthyroid optic neuropathy based on CT imaging features combined the bony orbit with the soft tissue structures.
Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Orbital CT scan parameters in dysthyroid optic neuropathy: a systematic review and meta-analysis.Eye (London, England) · 2024Pooled it
- Teprotumumab for thyroid eye disease-associated superior ophthalmic vein periphlebitis: a case series.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Interpretable machine learning for severity classification of thyroid eye disease using orbital anatomical features.Frontiers in medicine · 2026Article
- Orbital anatomical variations between the Southern China and the Kashi populations based on 3D-CT analysis.International journal of ophthalmology · 2026Article
- A novel nomogram based on orbital MRI parameters for early prediction of dysthyroid optic neuropathy in thyroid-associated ophthalmopathy.BMC ophthalmology · 2025Article
- Radiological Activity Score (RAS)-MRI Characteristics in Dysthyroid Optic Neuropathy in a Multi-Ethnic Thyroid Eye Disease Population.Clinical endocrinology · 2025Article
- Retinal and Choroidal Alterations in Thyroid-Associated Ophthalmopathy: A Systematic Review.Life (Basel, Switzerland) · 2025Review
- Correlation between orbital imaging features of thyroid-associated ophthalmopathy and pupillary light reflex measurement.Frontiers in medicine · 2025Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To analyze computed tomographic (CT) imaging features of patients with dysthyroid optic neuropathy (DON) retrospectively and deduce a more appropriate predictive model. Methods: The CT scans and medical records of 60 patients with clinically proven Graves' ophthalmopathy (GO) with (26 women and 10 men) and without DON (16 women and 8 men) were retrospectively reviewed, and 20 age- and sex-matched control participants (12 women and 8 men) were enrolled consecutively. The bony orbit [orbital rim angle (ORA), medial and lateral orbital wall angles (MWA and LWA), orbital apex angle (OAA), and length of the lateral orbital wall (LWL)], and the soft tissue structures [maximum extraocular muscle diameters (Max EOMD), muscle diameter index (MDI), medial and lateral rectus bulk from inter-zygomatic line (MRIZL and LRIZL), proptosis, intraorbital optic nerve stretching length (IONSL), superior ophthalmic vein diameter (SOVD), apical crowding, and presence of intracranial fat prolapse] were assessed on a clinical workstation. The CT features among groups were compared, and a multivariate logistic regression analysis was performed to evaluate the predictive features of DON. Results: All bony orbital angle indicators, except ORA ( Conclusion: Bone and soft tissue CT features are useful in the risk prediction of DON, especially the MWA, MDI, and SOVD were the independent factors predictive of DON.
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