The radiological assessment of orbital fat in patients with thyroid eye disease.
Authors
Affiliations (3)
Affiliations (3)
- Department of Ophthalmology, The Sussex Eye Hospital, University Hospitals Sussex, Brighton, UK.
- Brighton and Sussex Medical School, University of Sussex, Brighton, UK.
- Department of Informatics, University of Sussex, Brighton, UK.
Abstract
To review the current literature on imaging modalities and segmentation techniques used to evaluate the orbital fat compartment in thyroid eye disease (TED), with particular emphasis on their role in assessing disease activity and improving diagnostic accuracy. A literature review was performed of studies using CT, MRI, ultrasound, and nuclear medicine imaging to evaluate orbital fat involvement in TED. Imaging findings were considered in the context of known histopathological changes, with particular focus on emerging MRI sequences and advances in segmentation methodology. There is currently no established gold-standard imaging modality for assessing changes in orbital fat volume or composition in TED. Fat-suppressed MRI techniques, particularly STIR and Dixon sequences, show promise for detecting inflammatory activity within the orbital fat compartment. Diffusion-weighted imaging (DWI) may enable identification of subclinical disease, while diffusion tensor imaging (DTI) demonstrates potential for quantitative assessment of disease activity. Multiparametric "whole-orbit" imaging approaches incorporating extraocular muscles, lacrimal gland, and orbital fat improve diagnostic performance compared with single-structure assessment. However, accurate anatomical delineation remains challenging, and although automated segmentation and deep-learning-based volumetric analysis offer important future opportunities, these techniques are currently largely confined to research settings. Orbital fat pathology represents a key component of TED pathogenesis, yet radiological assessment of the orbital fat compartment remains insufficiently standardized. Fat-suppressed MRI techniques - particularly DWI - show significant promise for improving detection of inflammatory activity and may support future development of multiparametric imaging-based disease‑activity assessment.