ArticleQuantitative imaging in medicine and surgery2025
Quantitative analysis of orbital soft tissue for the detection of dysthyroid optic neuropathy in patients with thyroid-associated ophthalmopathy, based on three-dimensional cube fast spin-echo Flex.
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Dysthyroid optic neuropathy (DON) is a vision-threatening complication of thyroid-associated ophthalmopathy (TAO). The underlying pathophysiology is believed to involve compression of the optic nerve at the orbital apex, primarily due to edema and volumetric expansion of orbital soft tissues. Early detection of DON is crucial to prevent irreversible visual loss. However, reliable imaging biomarkers for early diagnosis remain limited. This study aimed to investigate whether orbital soft tissue volume and water fraction (WF), derived from three-dimensional cube fast spin-echo Flex (3D Cube FSE-Flex) magnetic resonance imaging (MRI), can serve as predictive markers for DON in TAO patients. Methods: In this retrospective study, 3D Cube FSE-Flex MRI images and clinical data were analyzed from 60 patients with TAO (27 with DON, 33 without). A total of 116 orbits (53 with DON, 63 without) were included. Quantitative measurements of extraocular muscle volume (EOMV), water fraction of extraocular muscles (EOM-WF), and orbital fat (OF-WF) were obtained using semi-automated segmentation. Group comparisons were performed using appropriate statistical tests. Logistic regression was used to identify risk factors for DON, and receiver operating characteristic (ROC) curve analysis was employed to evaluate diagnostic performance. Correlation analysis was conducted to assess relationships between imaging parameters and clinical activity scores (CAS). Results: DON orbits showed significantly higher EOMV, EOM-WF, and OF-WF compared to non-DON orbits (all P<0.001). Logistic regression revealed that increased EOMV [odds ratio (OR) =1.555; 95% confidence interval (CI): 1.250-1.934] and higher OF-WF (OR =1.190; 95% CI: 1.064-1.332) were independent risk factors for DON. A combined model incorporating EOMV and OF-WF demonstrated good diagnostic performance [area under the curve (AUC) =0.843]. Additionally, both EOMV (P=0.015, r=0.333) and OF-WF (P=0.025, r=0.308) were positively correlated with CAS. Conclusions: Quantitative MRI analysis using 3D Cube FSE-Flex reveals that enlargement and edema of orbital soft tissues-specifically EOMV and OF-WF-are significant risk factors for DON. The combination of these parameters provides a robust imaging biomarker for early identification of DON in TAO patients, with potential clinical utility in risk stratification and treatment planning.
Indexed as
Identifiers
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.