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Abstract Background Radiomics analysis of orbital magnetic resonance imaging (MRI) shows preliminary potential for intravenous glucocorticoid (IVGC) response prediction of thyroid eye disease (TED). The current region of interest segmentation contains only a single organ as extraocular muscles (EOMs). It would be of great value to consider all orbital soft tissues and construct a better prediction model. Methods In this retrospective study, we enrolled 127 patients with TED that received 4·5 g IVGC therapy and had complete follow-up examinations. Pre-treatment orbital T2-weighted imaging (T2WI) was acquired for all subjects. Using multi-organ segmentation (MOS) strategy, we contoured the EOMs, lacrimal gland (LG), orbital fat (OF), and optic nerve (ON), respectively. By fused-organ segmentation (FOS), we contoured the aforementioned structures as a cohesive unit. Whole-orbit radiomics (WOR) models consisting of a multi-regional radiomics (MRR) model and a fused-regional radiomics (FRR) model were further constructed using six machine learning (ML) algorithms. Results The support vector machine (SVM) classifier had the best performance on the MRR model (AUC = 0·961). The MRR model outperformed the single-regional radiomics (SRR) models (highest AUC = 0·766, XGBoost on EOMs, or LR on OF) and conventional semiquantitative imaging model (highest AUC = 0·760, NaiveBayes). The application of different ML algorithms for the comparison between the MRR model and the FRR model (highest AUC = 0·916, LR) led to different conclusions. Conclusions The WOR models achieved a satisfactory result in IVGC response prediction of TED. It would be beneficial to include more orbital structures and implement ML algorithms while constructing radiomics models. The selection of separate or overall segmentation of orbital soft tissues has not yet attained its final optimal result.

Background: Radiomics analysis of orbital magnetic resonance imaging (MRI) shows preliminary potential for intravenous glucocorticoid (IVGC) response prediction of thyroid eye disease (TED). The current region of interest segmentation contains only a single organ as extraocular muscles (EOMs). It would be of great value to consider all orbital soft tissues and construct a better prediction model. Methods: In this retrospective study, we enrolled 127 patients with TED that received 4·5 g IVGC therapy and had complete follow-up examinations. Pre-treatment orbital T2-weighted imaging (T2WI) was acquired for all subjects. Using multi-organ segmentation (MOS) strategy, we contoured the EOMs, lacrimal gland (LG), orbital fat (OF), and optic nerve (ON), respectively. By fused-organ segmentation (FOS), we contoured the aforementioned structures as a cohesive unit. Whole-orbit radiomics (WOR) models consisting of a multi-regional radiomics (MRR) model and a fused-regional radiomics (FRR) model were further constructed using six machine learning (ML) algorithms. Results: The support vector machine (SVM) classifier had the best performance on the MRR model (AUC = 0·961). The MRR model outperformed the single-regional radiomics (SRR) models (highest AUC = 0·766, XGBoost on EOMs, or LR on OF) and conventional semiquantitative imaging model (highest AUC = 0·760, NaiveBayes). The application of different ML algorithms for the comparison between the MRR model and the FRR model (highest AUC = 0·916, LR) led to different conclusions. Conclusions: The WOR models achieved a satisfactory result in IVGC response prediction of TED. It would be beneficial to include more orbital structures and implement ML algorithms while constructing radiomics models. The selection of separate or overall segmentation of orbital soft tissues has not yet attained its final optimal result. [ABSTRACT FROM AUTHOR]

Intravenous glucocorticoid (IVGC) remains the main treatment for moderate-to-severe and active thyroid-associated ophthalmopathy (TAO). However, a substantial number (20–30%) of active moderate-to-severe TAO patients may not respond to IVGC. Some patients may have disease progression despite IVGC treatment or relapse after steroid withdrawal. To analyze risk factors for clinical activity and predictive factors for clinical outcomes of 4.5 g IVGC therapy in patients with moderate-to-severe TAO. Our study was performed in two steps: step 1 involved 110 moderate-to-severe TAO patients and analyzed risk factors for TAO activity; step 2 involved 53 active moderate-to-severe TAO patients from step 1 who were treated with 4.5 g IVGC therapy and analyzed predictive factors for clinical outcomes of IVGC therapy. Multivariate logistic regression analysis was used to identify the independent predictors and establish the predictive model. Abnormal TRAb (OR = 4.717; P = 0.019) and the percentage of CD3+CD4+ T cell (OR = 1.092; P = 0.028) were independently associated with the activity of moderate-to-severe TAO patients. The pretreatment CAS-max in both eyes (OR = 7.221; P = 0.013) and the percentage of pretreatment CD3+T cell (OR = 0.718; P = 0.037) were independently associated with therapeutic efficacy. The pretreatment CAS-max in both eyes (OR = 156.53; P = 0.028) and the percentage of post-treatment CD3+T cell (OR = 0.554; P = 0.043) were independently associated with therapeutic efficacy. Besides, multivariable prediction models were established, which were better in the forecasting aspect than single-variable prediction models. Based on the findings of this study, we should monitor the peripheral blood T cell subsets for TAO, which could be helpful to timely judge the condition of clinical manifestation and effect of treatment for TAO patients. Multivariable prediction models have been established, which have great significance for clinical work. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the performance of combined T2 mapping and T2 iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) in orbital tissues to predict the therapeutic efficacy of intravenous glucocorticoids (IVGCs) for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO).Method: Sixty-three active and moderate-to-severe TAO patients (responsive group, n = 35; unresponsive group, n = 28) who underwent orbital MRI before receiving IVGCs were retrospectively enrolled. Baseline clinical characteristics and imaging parameters were analyzed and compared between the two groups of different therapeutic efficacy. Binary logistic regression analysis was conducted to determine the independent predictors, the predictive performance of which was evaluated using receiver operating characteristic curve analysis.Results: The mean T2 relaxation time of extraocular muscle (EOM-T2RTmean) (P = 0.001), maximum T2RT of EOM (EOM-T2RTmax) (P = 0.001), mean water fraction of EOM (EOM-WFmean) (P < 0.001), maximum WF of EOM (EOM-WFmax) (P < 0.001) and exophthalmos (P = 0.007) were significantly higher in the responsive group than in the unresponsive group. EOM-T2RTmean (P < 0.001) and EOM-WFmax (P < 0.001) were determined as independent predictors for responsive patients with TAO in the multivariable analysis. Combining EOM-T2RTmean ≥ 77.1 and EOM-WFmax ≥ 91.52 demonstrated optimal efficiency for prediction (area under the curve = 0.844) and optimal predictive sensitivity (77.1%). Setting EOM-WFmax ≥ 91.52 achieved the optimal predictive specificity (89.3%).Conclusions: Pretherapeutic quantitative measurements, based on combining T2 mapping and T2 IDEAL in orbital tissues, are valuable for predicting IVGC treatment response in active and moderate-to-severe TAO. EOM-T2RTmean and EOM-WFmax may become promising IVGC treatment response predictors. [ABSTRACT FROM AUTHOR]