Baseline Volumetric T2 Relaxation Time Histogram Analysis: Can It Be Used to Predict the Response to Intravenous Methylprednisolone Therapy in Patients With Thyroid-Associated Ophthalmopathy?

Application of Quantitative MRI in Thyroid Eye Disease: Imaging Techniques and Clinical Practices

Thyroid eye disease (TED) is a complex autoimmune disorder that impairs various orbital structures, leading to cosmetic damage and vision loss. Magnetic resonance imaging (MRI) is a fundamental diagnostic tool utilized in clinical settings of TED, for its accurate demonstration of orbital lesions and indication of disease conditions. The application of quantitative MRI has brought a new prospect to the management and research of TED, offering more detailed information on morphological and functional changes in the orbit. Therefore, many researchers concentrated on the implementation of different quantitative MRI techniques on TED for the exploration of clinical practices. Despite the abundance of studies utilizing quantitative MRI in TED, there remain considerable barriers and disputes on the best exploitation of this tool. This could possibly be attributed to the complexity of TED and the fast development of MRI techniques. It is necessary that clinical and radiological aspects of quantitative MRI in TED be better integrated into comprehensive insights. Hence, this review traces back 30 years of publications regarding quantitative MRI utilized in TED and elucidates this promising application in the facets of imaging techniques and clinical practices. We believe that a deeper understanding of the application of quantitative MRI in TED will enhance the efficacy of the multidisciplinary management of TED. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Fat-suppression T2 relaxation time and water fraction predict response to intravenous glucocorticoid therapy for thyroid-associated ophthalmopathy

OBJECTIVE

To investigate the value of fat-suppression (FS) T2 relaxation time (T2RT) derived from FS T2 mapping and water fraction (WF) derived from T2 IDEAL to predict the treatment response to intravenous glucocorticoids (IVGC) in patients with thyroid-associated ophthalmopathy (TAO) based on texture analysis.

MATERIALS AND METHODS

In this study, 89 patients clinically diagnosed with active and moderate-to-severe TAO were enroled (responsive group, 48 patients; unresponsive group, 41 patients). The baseline clinical characteristics and texture features were compared between the two groups. Multivariate analysis was performed to identify the independent predictors of treatment response to IVGC. ROC analysis and the DeLong test were used to assess and compare the predictive performance of different models.

RESULTS

The responsive group exhibited significantly shorter disease duration and higher 90th percentile of FS T2RT and kurtosis of WF in the extraocular muscle (EOM) and 95th percentile of WF in the orbital fat (OF) than the unresponsive group. Model 2 (disease duration + WF; AUC, 0.816) and model 3 (disease duration + FS T2RT + WF; AUC, 0.823) demonstrated superior predictive efficacy compared to model 1 (disease duration + FS T2RT; AUC, 0.756), while there was no significant difference between models 2 and 3.

CONCLUSIONS

The orbital tissues of responders exhibited more oedema and heterogeneity. Furthermore, OF is as valuable as EOM for assessing the therapeutic efficacy of IVGC. Finally, WF derived from T2 IDEAL processed by texture analysis can provide valuable information for predicting the treatment response to IVGC in patients with active and moderate-to-severe TAO.

CLINICAL RELEVANCE STATEMENT

The texture features of FS T2RT and WF are different between responders and non-responders, which can be the predictive tool for treatment response to IVGC.

KEY POINTS

Texture analysis can be used for predicting response to IVGC in TAO patients. TAO patients responsive to IVGC show more oedema and heterogeneity in the orbital tissues. WF from T2 IDEAL is a tool to predict the therapeutic response of TAO.

Assessing the relationship between levator palpebrae superioris and thyroid-associated ophthalmopathy using the Dixon-T2WI sequence

Background

The current clinical practice lacks sufficient objective indicators for evaluating thyroid-associated ophthalmopathy (TAO). This study aims to quantitatively assess TAO by evaluating levator palpebrae superioris (LPS) using Dixon-T2WI.

Methods

The retrospective study included 231 eyes (119 patients) in the TAO group and 78 eyes (39 volunteers) in the normal group. Dixon-T2WI provided data on maximum thickness of LPS (LPS_T) and signal intensity ratio (LPS_SIR) between the muscle and ipsilateral brain white matter. TAO diagnosis and assessment of its activity and severity were quantitatively determined using LPS_T and LPS_SIR.

Results

In the TAO group, LPS_T and LPS_SIR were higher than those in the normal group (p < 2.2e-16). The upper lid retraction (ULR) ≥ 2 mm group exhibited higher LPS_T and LPS_SIR compared to the ULR < 2 mm and normal groups. Optimal diagnostic performance was achieved with an AUC of 0.91 for LPS_T (cutoff: 1.505 mm) and 0.81 for LPS_SIR (cutoff: 1.170). LPS_T (p = 2.8e-07) and LPS_SIR (p = 3.9e-12) in the active phase were higher than in the inactive phase. LPS_T and LPS_SIR showed differences among the mild, moderate-to-severe, and sight-threatening groups (p < 0.05). ROC showed an AUC of 0.70 for LPS_T (cutoff: 2.095 mm) in judging the active phase, and 0.78 for LPS_SIR (cutoff: 1.129). For judging the moderate-to-severe and above, AUC was 0.76 for LPS_T (cutoff: 2.095 mm) and 0.78 for LPS_SIR (cutoff: 1.197).

Conclusion

The maximum thickness and SIR of LPS provide imaging indicators for assisting in the diagnosis and quantitative evaluation of TAO.

Predicting glucocorticoid effectiveness in thyroid eye disease: combined value from serological lipid metabolism and an orbital MRI parameter

Purpose

The aim was to determine the combined value of serological lipid metabolism and an orbital MRI quantitative parameter in predicting the effectiveness of glucocorticoid (GC) therapy in patients with thyroid eye disease (TED).

Methods

This study retrospectively enrolled 46 patients with active and moderate-to-severe TED (GC-effective group, n = 29; GC-ineffective group, n = 17). Serological lipid metabolism, the orbital MRI-based minimum signal intensity ratio of extraocular muscles (EOM-SIRmin), as well as other clinical parameters before GC therapy were collected and compared between the two groups. Multivariate logistic regression and receiver operating characteristic curve analysis were adopted to identify independent predictable variables and assess their predictive performances.

Results

Compared to the GC-ineffective group, the GC-effective group showed lower serum total cholesterol levels (P = 0.006), lower serum low-density lipoprotein cholesterol levels (P = 0.019), higher EOM-SIRmin values (P = 0.005), and shorter disease durations (P = 0.017). Serum total cholesterol and EOM-SIRmin were found to be independent predictors of GC-effective TED through multivariate analysis (odds ratios = 0.253 and 2.036 per 0.1 units, respectively) (both P < 0.05). The integration of serum total cholesterol ≤4.8 mmol/L and EOM-SIRmin ≥ 1.12 had a better predictive efficacy (area under the curve, 0.834) than EOM-SIRmin alone, with a sensitivity of 75.9% and a specificity of 82.4% (P = 0.031).

Conclusion

Serological lipid metabolism, combined with an orbital MRI-derived parameter, was a useful marker for predicting the effectiveness of GCs in patients with active and moderate-to-severe TED.

Whole-orbit radiomics: machine learning-based multi- and fused- region radiomics signatures for intravenous glucocorticoid response prediction in thyroid eye disease

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.

Predictive markers for anti-inflammatory treatment response in thyroid eye disease

Anti-inflammatory treatment is the primary and vital therapeutic approach for active, moderate-to-severe thyroid eye disease (TED). Accurate pretreatment prediction of treatment response is of paramount importance for the prognosis of patients. However, relying solely on the clinical activity score asa determinant of activity has led to unsatisfactory treatment outcomes. In recent years, significant advancements have been made in identifying predictive markers for anti-inflammatory treatment response in TED, clinical markers, body fluid biomarkers and imaging biomarkers. Several clinical studies have developed prediction models based on these markers. However, there is still a lack of comprehensive elucidation or comparison between the different markers. Therefore, this review aims to provide a detailed analysis of the definition, characteristics, and application of predictive markers for anti-inflammatory treatment response in TED. Through detailed literature search, 26 articles applying anti-inflammatory treatment effect prediction with a total of 1948 TED patients were used for analysis and discussion. By gaining a better understanding of the current research on predictive markers, we can accelerate and guide the exploration of treatment prediction strategies, leading us towards an era of precise therapy for TED.

Extraocular muscle enlargement

Extraocular muscle enlargement can occur secondary to a range of orbital and systemic diseases. Although the most common cause of extraocular muscle enlargement is thyroid eye disease, a range of other inflammatory, infective, neoplastic, and vascular conditions can alter the size and shape of the extraocular muscles. Imaging with computed tomography and magnetic resonance imaging plays an essential role in the workup of these conditions. This article provides an image-rich review of the wide range of pathology that can cause enlargement of the extraocular muscles.

T2 -Weighted MR Imaging-Derived Radiomics for Pretreatment Determination of Therapeutic Response to Glucocorticoid in Patients With Thyroid-Associated Ophthalmopathy: Comparison With Semiquantitative Evaluation

BACKGROUND

MR imaging has been applied to determine therapeutic response to glucocorticoid (GC) before treatment in thyroid-associated ophthalmopathy (TAO), while the performance was still poor.

PURPOSE

To investigate the value of T₂ -weighted imaging (T₂ WI)-derived radiomics for pretreatment determination of therapeutic response to GC in TAO patients, and compare its diagnostic performance with that of semiquantitative parameters.

STUDY TYPE

Retrospective.

POPULATION

A total of 110 patients (49 ± 12 years; male/female, n = 48/62; responsive/unresponsive, n = 62/48), divided into training (n = 78) and validation (n = 32) cohorts.

FIELD STRENGTH/SEQUENCE

3.0 T, T₂ -weighted fast spin echo.

ASSESSMENT

W.C. and H.H. (6 and 10 years of experience, respectively) performed the measurements. Maximum, mean, and minimum signal intensity ratios (SIRs) of extraocular muscle (EOM) bellies were collected to construct a semiquantitative imaging model. Radiomics features from volumes of interest covering EOM bellies were extracted and three machine learning-based (logistic regression [LR]; decision tree [DT]; support vector machine [SVM]) models were built.

STATISTICAL TESTS

The diagnostic performances of models were evaluated using receiver operating characteristic curve analyses, and compared using DeLong test. Two-sided P < 0.05 was considered statistically significant.

RESULTS

The responsive group showed higher minimum signal intensity ratio (SIR_min ) of EOMs than the unresponsive group (training: 1.46 ± 0.34 vs. 1.18 ± 0.39; validation: 1.44 ± 0.33 vs. 1.19 ± 0.20). In both cohorts, LR-based radiomics model demonstrated good diagnostic performance (area under the curve [AUC] = 0.968, 0.916), followed by DT-based (AUC = 0.933, 0.857) and SVM-based models (AUC = 0.919, 0.855). All three radiomics models outperformed semiquantitative imaging model (SIR_min : AUC = 0.805) in training cohort. In validation cohort, only LR-based radiomics model outperformed that of SIR_min (AUC = 0.745). The nomogram integrating LR-based radiomics signature and disease duration further elevated the diagnostic performance in validation cohort (AUC: 0.952 vs. 0.916, P = 0.063).

DATA CONCLUSION

T₂ WI-derived radiomics of EOMs, together with disease duration, provides a promising noninvasive approach for determining therapeutic response before GC administration in TAO patients.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 4.

T2 Mapping with and without Fat-Suppression to Predict Treatment Response to Intravenous Glucocorticoid Therapy for Thyroid-Associated Ophthalmopathy

Objective

To evaluate the performance of baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping of the extraocular muscles (EOMs) in the prediction of treatment response to intravenous glucocorticoid (IVGC) therapy for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO) and to investigate the effect of fat-suppression (FS) in T2 mapping in this prediction.

Materials and Methods

A total of 79 patients clinically diagnosed with active, moderate-to-severe TAO (47 female, 32 male; mean age ± standard deviation, 46.1 ± 10 years), including 43 patients with a total of 86 orbits in the responsive group and 36 patients with a total of 72 orbits in the unresponsive group, were enrolled. Baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping with FS (i.e., FS T2 mapping) or without FS (i.e., conventional T2 mapping) of EOMs were compared between the two groups. Independent predictors of treatment response to IVGC were identified using multivariable analysis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the prediction models. Differences between the models were examined using the DeLong test.

Results

Compared to the unresponsive group, the responsive group had a shorter disease duration, lower kurtosis (FS-kurtosis), lower standard deviation, larger 75th, 90th, and 95th (FS-95th) T2 relaxation times in FS mapping and lower kurtosis in conventional T2 mapping. Multivariable analysis revealed that disease duration, FS-95th percentile, and FS-kurtosis were independent predictors of treatment response. The combined model, integrating all identified predictors, had an optimized area under the ROC curve of 0.797, 88.4% sensitivity, and 62.5% specificity, which were significantly superior to those of the imaging model (p = 0.013).

Conclusion

An integrated combination of disease duration, FS-95th percentile, and FS-kurtosis was a potential predictor of treatment response to IVGC in patients with active and moderate-to-severe TAO. FS T2 mapping was superior to conventional T2 mapping in terms of prediction.