ArticleBMC medical imaging2025
Clinical value of dual-energy CT parameters combined with morphological features in predicting graves' ophthalmopathy.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundTo investigate the diagnostic value of dual-energy computed tomography (DECT)–derived quantitative parameters combined with morphological features for assessing subtle orbital tissue changes in Graves’ ophthalmopathy (GO), and to evaluate their feasibility as imaging biomarkers throughout the disease course.
methodsData from patients suspected of having GO were retrospectively collected. All these patients underwent DECT scans and had no history of thyroid function treatment or other medical history, which may have affected the measurement of orbital tissues. Three clinical features, four morphological features, and twenty-four DECT parameters were measured. The overall data were divided into training and test cohorts. Univariate and multivariate analyses were applied to select relevant parameters and construct a nomogram.
resultsAmong the 206 patients suspected of having GO, 134 patients were diagnosed as positive for GO (GO+), and 72 patients were diagnosed as negative (GO-) according to relevant diagnostic criteria. (1) The average thickness, average width, weighted average thickness and weighted average width of orbital muscles significantly differed between the GO + and GO- groups (p < 0.05). (2) The minimum and average values of electron density in orbital muscles and lacrimal glands were significantly different (p < 0.05). (3) A nomogram was constructed to predict the risk of GO, and the area under the curve, sensitivity, and specificity in the training and test cohorts were 0.812, 92.1%, and 59.5% and 0.825, 82.9%, and 71.9%, respectively.
conclusionsDECT parameters combined with morphological features not only can be used as robust predictive indicators for diagnosing GO but also represent promising novel biomarkers that may increase the precision and objectivity of clinical assessments.
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