Author:
Liu Ping,Luo Ban,Chen Lang,Wang Qiu-Xia,Yuan Gang,Jiang Gui-hua,Zhang Jing
Abstract
ObjectivePrediction of therapy response to intravenous methylprednisolone pulses (ivMP) is crucial for thyroid-associated ophthalmopathy (TAO). Image histograms may offer sensitive imaging biomarkers for therapy effect prediction. This study aimed to investigate whether pretherapeutic, multiparametric T2 relaxation time(T2RT) histogram features of extraocular muscles (EOMs) can be used to predict therapy response.Materials and MethodsForty-five active and moderate-severe TAO patients, who were treated with standard ivMP and underwent orbital MRI before therapy, were retrospectively included in this study. The patients were divided into responsive (n = 24, 48 eyes) and unresponsive group(n = 21, 42 eyes) according to clinical evaluation. Baseline clinical features of patients and histogram-derived T2RT parameters of the EOMs were analyzed and compared. Logistic regression model was conducted to determine independent predictors, and a histogram features nomogram was formulated for personalized prediction.ResultsResponsive group displayed lower values for 5th, 10th percentiles (P < 0.050, respectively), and higher values for 75th, 90th, and 95th percentiles, skewness, entropy, and inhomogeneity (P < 0.050, respectively) than unresponsive group. Multivariate logistic regression analysis showed that 95th percentile of >88.1 [odds ratio (OR) = 12.078; 95% confidence interval (CI) = 3.98–36.655, p < 0.001], skewness of >0.31 (OR = 3.935; 95% CI = 2.28–6.788, p < 0.001) and entropy of >3.41 (OR = 4.375; 95% CI = 2.604–7.351, p < 0.001) were independent predictors for favorable response. The nomogram integration of three independent predictors demonstrated optimal predictive efficiency, with a C-index of 0.792.ConclusionsPre-treatment volumetric T2RT histogram features of EOMs could function to predict the response to ivMP in patients with TAO. The nomogram based on histogram features facilitates the selection of patients who will derive maximal benefit from ivMP.
Funder
National Natural Science Foundation of China
Subject
Endocrinology, Diabetes and Metabolism
Cited by
10 articles.
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