Local-to-Remote Brain Functional Connectivity in Patients with Thyroid-Associated Ophthalmopathy and Assessment of Its Predictive Value Using Machine Learning

Neuroimaging in thyroid eye disease: A systematic review

Thyroid eye disease (TED) is an organ-specific autoimmune disease secondary largely to hyperthyroid Graves' disease, which profoundly affects patients' visual function, appearance, and physical and mental well-being. Emerging neuroimaging studies have reported alterations in the brains of patients with TED, suggesting that the impact of this autoimmune disease may extend beyond the orbit. This systematic review aims to consolidate the neuroimaging evidence that describes the brain alterations of TED. We analyzed information from thirty-one related studies involving 1349 TED patients and 710 healthy controls, employing multimodal neuroimaging techniques such as structural magnetic resonance imaging (MRI), functional MRI, diffusion MRI, and metabolic MRI. These studies define the brain alterations in regions associated with vision, cognition, and emotion regulation, such as gray matter volume changes, altered functional connectivity and activity, and microstructural modifications, revealing the neurological impact of TED beyond the orbit. Notably, there was convergence across these studies indicating predominant abnormalities within the occipital and parietal lobes. This review underscores the critical role of advanced neuroimaging techniques in unraveling the complex neuropathological mechanism of TED, laying a foundation for future research and potential therapeutic targets.

Brain alteration of autoimmune thyroid disease: Neuropsychiatric impact, neuroimaging insights, and neurobiological implications

Autoimmune thyroid disease (AITD) is the most common organ-specific autoimmune disease, characterized by thyroid function disorder and autoimmune imbalance. Previous studies have demonstrated the decreased quality of life and neuropsychiatric manifestations in AITD patients, including anxiety, depression, cognitive impairment and affective disorder. These problems also plague the euthyroid AITD patients. Advanced neuroimaging techniques were well carried out and employed as an explanatory instrument for the above intriguing phenomenon. In recent years, an increasing number of neuroimaging studies have reported that these neuropsychiatric manifestations are accompanied by significant structural and functional brain alterations in AITD patients, mainly involved in neurocognitive and emotional regions, despite the underlying neurobiological mechanism is still unclear. The existing studies suggest that the potential pathogenesis of the neuropsychiatric manifestations and brain alterations does not depend on a single factor, but may result from a combination of thyroid function dysfunction, metabolic disorders, dysregulated autoimmune and trans-synaptic degeneration.

Specific static and dynamic functional network connectivity changes in thyroid-associated ophthalmopathy and it predictive values using machine learning

Background

Thyroid-associated ophthalmopathy (TAO) is a prevalent autoimmune disease characterized by ocular symptoms like eyelid retraction and exophthalmos. Prior neuroimaging studies have revealed structural and functional brain abnormalities in TAO patients, along with central nervous system symptoms such as cognitive deficits. Nonetheless, the changes in the static and dynamic functional network connectivity of the brain in TAO patients are currently unknown. This study delved into the modifications in static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) among thyroid-associated ophthalmopathy patients using independent component analysis (ICA).

Methods

Thirty-two patients diagnosed with thyroid-associated ophthalmopathy and 30 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. ICA method was utilized to extract the sFNC and dFNC changes of both groups.

Results

In comparison to the HC group, the TAO group exhibited significantly increased intra-network functional connectivity (FC) in the right inferior temporal gyrus of the executive control network (ECN) and the visual network (VN), along with significantly decreased intra-network FC in the dorsal attentional network (DAN), the default mode network (DMN), and the left middle cingulum of the ECN. On the other hand, FNC analysis revealed substantially reduced connectivity intra- VN and inter- cerebellum network (CN) and high-level cognitive networks (DAN, DMN, and ECN) in the TAO group compared to the HC group. Regarding dFNC, TAO patients displayed abnormal connectivity across all five states, characterized by notably reduced intra-VN connectivity and CN connectivity with high-level cognitive networks (DAN, DMN, and ECN), alongside compensatory increased connectivity between DMN and low-level perceptual networks (VN and basal ganglia network). No significant differences were observed between the two groups for the three dynamic temporal metrics. Furthermore, excluding the classification outcomes of FC within VN (with an accuracy of 51.61% and area under the curve of 0.35208), the FC-based support vector machine (SVM) model demonstrated improved performance in distinguishing between TAO and HC, achieving accuracies ranging from 69.35 to 77.42% and areas under the curve from 0.68229 to 0.81667. The FNC-based SVM classification yielded an accuracy of 61.29% and an area under the curve of 0.57292.

Conclusion

In summary, our study revealed that significant alterations in the visual network and high-level cognitive networks. These discoveries contribute to our understanding of the neural mechanisms in individuals with TAO, offering a valuable target for exploring future central nervous system changes in thyroid-associated eye diseases.

Alterations in dynamic regional homogeneity within default mode network in patients with thyroid-associated ophthalmopathy

Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Prior investigations have solely focused on static functional MRI (fMRI) scans of the brain in TAO patients, neglecting the assessment of temporal variations in local brain activity. This study aimed to characterize alterations in dynamic regional homogeneity (dReHo) in TAO patients and differentiate between TAO patients and healthy controls using support vector machine (SVM) classification. Thirty-two patients with TAO and 32 healthy controls underwent resting-state fMRI scans. We calculated dReHo using sliding-window methods to evaluate changes in regional brain activity and compared these findings between the two groups. Subsequently, we employed SVM, a machine learning algorithm, to investigate the potential use of dReHo maps as diagnostic markers for TAO. Compared to healthy controls, individuals with active TAO demonstrated significantly higher dReHo values in the right angular gyrus, left precuneus, right inferior parietal as well as the left superior parietal gyrus. The SVM model demonstrated an accuracy ranging from 65.62 to 68.75% in distinguishing between TAO patients and healthy controls based on dReHo variability in these identified brain regions, with an area under the curve of 0.70 to 0.76. TAO patients showed increased dReHo in default mode network-related brain regions. The accuracy of classifying TAO patients and healthy controls based on dReHo was notably high. These results offer new insights for investigating the pathogenesis and clinical diagnostic classification of individuals with TAO.

Altered Static and Dynamic Brain Functional Topological Organization in Patients With Dysthyroid Optic Neuropathy

CONTEXT

Dysthyroid optic neuropathy (DON) is a serious vision-threatening complication of thyroid-associated ophthalmopathy (TAO). Exploration of the underlying mechanisms of DON is critical for its timely clinical diagnosis.

OBJECTIVE

We hypothesized that TAO patients with DON may have altered brain functional networks. We aimed to explore the alterations of static and dynamic functional connectomes in patients with and without DON using resting-state functional magnetic resonance imaging with the graph theory method.

METHODS

A cross-sectional study was conducted at a grade A tertiary hospital with 66 TAO patients (28 DON and 38 non-DON) and 30 healthy controls (HCs). Main outcome measures included topological properties of functional networks.

RESULTS

For static properties, DON patients exhibited lower global efficiency (Eg), local efficiency, normalized clustering coefficient, small-worldness (σ), and higher characteristic path length (Lp) than HCs. DON and non-DON patients both exhibited varying degrees of abnormalities in nodal properties. Meanwhile, compared with non-DON, DON patients exhibited abnormalities in nodal properties in the orbitofrontal cortex and visual network (VN). For dynamic properties, the DON group exhibited higher variance in Eg and Lp than non-DON and HC groups. A strengthened subnetwork with VN as the core was identified in the DON cohort. Significant correlations were found between network properties and clinical variables. For distinguishing DON, the combination of static and dynamic network properties exhibited optimal diagnostic performance.

CONCLUSION

Functional network alterations were observed both in DON and non-DON patients, providing novel insights into the underlying neural mechanisms of disease. Functional network properties may be potential biomarkers for reflecting the progression of TAO from non-DON to DON.

Altered functional connectivity strength of primary visual cortex in subjects with thyroid-associated ophthalmopathy

Our objective was to explore the disparities in the intrinsic functional connectivity (FC) patterns of primary visual cortex (V1) between patients with thyroid-associated ophthalmopathy (TAO) and healthy controls (HCs) utilizing resting-state functional MRI. Twenty-one patients with TAO (14 males and 7 females; mean age: 54.17 ± 4.83 years) and 21 well-matched HCs (14 males and 7 females; mean age: 55.17 ± 5.37 years) underwent functional MRI scans in the resting-state. We assessed modifications in the intrinsic FC patterns of the V1 in TAO patients using the FC method. Subsequently, the identified alterations in FC regions in the analysis were selected as classification features to distinguish TAO patients from HCs through the support vector machine (SVM) method. The results indicated that, in comparison to HCs, patients with TAO exhibited notably reduced FC values between the left V1 and the bilateral calcarine (CAL), lingual gyrus (LING) and superior occipital gyrus, as well as between the right V1 and the bilateral CAL/LING and the right cerebellum. Furthermore, the SVM classification model based on FC maps demonstrated effective performance in distinguishing TAO patients from HCs, achieving an accuracy of 61.9% using the FC of the left V1 and 64.29% using the FC of the right V1. Our study revealed that patients with TAO manifested disruptions in FC between the V1 and higher visual regions during rest. This might indicate that TAO patients could present with impaired top-down modulations, visual imagery and vision-motor function. These insights could be valuable in understanding the underlying neurobiological mechanisms of vision impairment in individuals with TAO.

Machine Learning Analysis Classifies Patients with Primary Angle-Closure Glaucoma Using Abnormal Brain White Matter Function

Objective

Primary angle-closure glaucoma (PACG) is a globally prevalent, irreversible eye disease leading to blindness. Previous neuroimaging studies demonstrated that PACG patients were associated with gray matter function changes. However, whether the white matter(WM) function changes in PACG patients remains unknown. The purpose of the study is to investigate WM function changes in the PACG patients.

Methods

In total, 40 PACG patients and 40 well-matched HCs participated in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We compared between-group differences between PACG patients and HC in the WM function using amplitude of low-frequency fluctuations (ALFF). In addition, the SVM method was applied to the construction of the PACG classification model.

Results

Compared with the HC group, ALFF was attenuated in right posterior thalamic radiation (include optic radiation), splenium of corpus callosum, and left tapetum in the PACG group, the results are statistically significant (GRF correction, voxel-level P < 0.001, cluster-level P < 0.05). Furthermore, the SVM classification had an accuracy of 80.0% and an area under the curve (AUC) of 0.86 for distinguishing patients with PACG from HC.

Conclusion

The findings of our study uncover abnormal WM functional alterations in PACG patients and mainly involves vision-related regions. These findings provide new insights into widespread brain damage in PACG from an alternative WM functional perspective.

The insular cortex is not insular in thyroid eye disease: neuroimaging revelations of central-peripheral system interaction

BACKGROUND

Thyroid eye disease (TED) is highly correlated with dysregulated immunoendocrine status. The insular cortex was found to regulate peripheral inflammation and immunomodulation in mice. This study aimed to explore whether the insular cortex in patients with TED played a modulatory role including the aberrant brain functional alteration and its association with immunoendocrine status.

METHODS

This study included 34 active patients (AP), 30 inactive patients (IP) with TED, and 45 healthy controls (HC) matched for age, sex, and educational level. Comprehensive clinical details (especially immunoendocrine markers) and resting-state functional magnetic resonance imaging data were collected from each participant. The amplitude of low-frequency fluctuation (ALFF) was used to probe the aberrant alterations of local neural activity. The seed-based functional connectivity (FC) analysis was used to explore the relationship between the insular cortex and each voxel throughout the whole brain. The correlation analysis was conducted to assess the association between insular neurobiomarkers and immunoendocrine parameters.

RESULTS

When compared with the IP and HC groups, the AP group displayed significantly higher ALFF values in the right insular cortex (INS.R) and lower FC values between the INS.R and the bilateral cerebellum. None of the neurobiomarkers differed between the IP and HC groups. Besides, correlations between insular neurobiomarkers and immunoendocrine markers (free thyroxine, the proportion of T cells, and natural killer cells) were identified in both AP and IP groups.

CONCLUSIONS

This study was novel in reporting that the dysregulation of the insular cortex activity in TED was associated with abnormal peripheral immunoendocrine status. The insular cortex might play a key role in central-peripheral system interaction in TED. Further research is crucial to enhance our understanding of the central-peripheral system interaction mechanisms involved in autoimmune diseases.

Functional decoding and meta-analytic connectivity modeling in thyroid-associated ophthalmopathy

Background

Thyroid-associated ophthalmopathy (TAO) is an orbital disease closely related to thyroid disease with a long-lasting duration that can be blinding and disabling. Recently, structural and functional neuroimaging studies have been performed in TAO patients, but studies have reported inconsistent results. This quantitative meta-analysis was conducted to identify convergent patterns of abnormal brain function among different studies in TAO.

Methods

We searched PubMed, EMBASE, Cochrane, and Web of Science, performed reference tracking, and retrieved 15 eligible studies. Peak coordinates were extracted from these studies and subsequently tested for convergence using activation likelihood estimation (ALE).

Results

Compared to healthy subjects, resting-state brain activity in the whole brain of TAO patients was significantly increased in the left superior frontal gyrus (SFG) and decreased in the left cuneus/precuneus. Functional decoding analysis of the BrainMap database revealed that these regions are predominantly associated with cognitive and emotional impairment. In this study, task-related meta-analytic connectivity modeling (MACM) analysis was used to describe the connectivity and function of the two seed regions. Significant coactivation of these regions was found primarily in the bilateral superior parietal lobule, medial frontal gyrus, left fusiform gyrus, left cingulate gyrus, supplementary motor area and thalamus.

Conclusion

Our findings underscore the role of the SFG and the cuneus/precuneus in the pathophysiology of TAO, highlighting the crucial impact of working memory deficits.

Artificial Intelligence in Thyroidology: A Narrative Review of the Current Applications, Associated Challenges, and Future Directions

Background: The use of artificial intelligence (AI) in health care has grown exponentially with the promise of facilitating biomedical research and enhancing diagnosis, treatment, monitoring, disease prevention, and health care delivery. We aim to examine the current state, limitations, and future directions of AI in thyroidology. Summary: AI has been explored in thyroidology since the 1990s, and currently, there is an increasing interest in applying AI to improve the care of patients with thyroid nodules (TNODs), thyroid cancer, and functional or autoimmune thyroid disease. These applications aim to automate processes, improve the accuracy and consistency of diagnosis, personalize treatment, decrease the burden for health care professionals, improve access to specialized care in areas lacking expertise, deepen the understanding of subtle pathophysiologic patterns, and accelerate the learning curve of less experienced clinicians. There are promising results for many of these applications. Yet, most are in the validation or early clinical evaluation stages. Only a few are currently adopted for risk stratification of TNODs by ultrasound and determination of the malignant nature of indeterminate TNODs by molecular testing. Challenges of the currently available AI applications include the lack of prospective and multicenter validations and utility studies, small and low diversity of training data sets, differences in data sources, lack of explainability, unclear clinical impact, inadequate stakeholder engagement, and inability to use outside of the research setting, which might limit the value of their future adoption. Conclusions: AI has the potential to improve many aspects of thyroidology; however, addressing the limitations affecting the suitability of AI interventions in thyroidology is a prerequisite to ensure that AI provides added value for patients with thyroid disease.

Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy

Purpose: Thyroid-associated ophthalmopathy (TAO) is an autoimmune disease that affects the orbit and is the most prevalent extra-thyroidal complication of Graves' disease. Previous neuroimaging studies have focused on abnormal static regional activity and functional connectivity in patients with TAO. However, the characteristics of local brain activity over time are poorly understood. This study aimed to investigate alterations in the dynamic amplitude of low-frequency fluctuation (dALFF) in patients with active TAO and to distinguish patients with TAO from healthy controls (HCs) using a support vector machine (SVM) classifier. Methods: A total of 21 patients with TAO and 21 HCs underwent resting-state functional magnetic resonance imaging scans. dALFFs were calculated in conjunction with sliding window approaches to assess dynamic regional brain activity and to compare the groups. Then, we used SVM, a machine learning algorithm, to determine whether dALFF maps may be used as diagnostic indicators for TAO. Results: Compared with HCs, patients with active TAO showed decreased dALFF in the right calcarine, lingual gyrus, superior parietal lobule, and precuneus. The SVM model showed an accuracy of 45.24%-47.62% and area under the curve of 0.35-0.44 in distinguishing TAO from HCs. No correlation was found between clinical variables and regional dALFF. Conclusion: Patients with active TAO showed altered dALFF in the visual cortex and the ventral and dorsal visual pathways, providing further details on the pathogenesis of TAO.

Altered synchronous neural activities in retinal vein occlusion patients: A resting-state fMRI study

Objective

Retinal vein occlusion (RVO) is the second most common retinal vascular disorder after diabetic retinopathy, which is the main cause of vision loss. Retinal vein occlusion might lead to macular edema, causing severe vision loss. Previous neuroimaging studies of patients with RVO demonstrated that RVO was accompanied by cerebral changes, and was related to stroke. The purpose of the study is to investigate synchronous neural activity changes in patients with RVO.

Methods

A total of 50 patients with RVO and 48 healthy subjects with matched sex, age, and education were enrolled in the study. The ReHo method was applied to investigate synchronous neural activity changes in patients with RVO.

Results

Compared with HC, patients with RVO showed increased ReHo values in the bilateral cerebellum_4_5. On the contrary, patients with RVO had decreased ReHo values in the bilateral middle occipital gyrus, right cerebelum_crus1, and right inferior temporal gyrus.

Conclusion

Our study demonstrated that patients with RVO were associated with abnormal synchronous neural activities in the cerebellum, middle occipital gyrus, and inferior temporal gyrus. These findings shed new insight into neural mechanisms of vision loss in patients with RVO.