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

Ping-Hong Lai, Rui-Yang Hu, Xin Huang

Neuroreport August 7, 2024 DOI: 10.1097/wnr.0000000000002056 (opens in new tab)

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Study at a glance

AI-extracted from the abstract
Characteristics Case-control study Peer reviewed
Sample size 64
Population 32 patients with active thyroid-associated ophthalmopathy and 32 healthy controls
Measures dynamic regional homogeneity (dReHo), support vector machine (SVM) classification accuracy, area under the curve (AUC)
Topics Default mode network
Key findings Patients with active TAO showed significantly higher dynamic regional homogeneity in the right angular gyrus, left precuneus, right inferior parietal, and left superior parietal gyrus compared with healthy controls. A support vector machine using these dReHo maps classified TAO patients versus controls with 65.62–68.75% accuracy and an area under the curve of 0.70–0.76.

Abstract

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.

Comparable studies

Other observational and cohort studies on default mode network, most cited first.

Study Year Design Participants
A default mode of brain function Normal adult human brain 2001 Observational study
Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network Healthy subjects 2008 Observational cohort
Meditation experience is associated with increased cortical thickness Participants with extensive Insight meditation experience and matched controls 2005 Observational cohort n = 20
Meditation experience is associated with differences in default mode network activity and connectivity Experienced meditators and matched meditation-naive controls 2011 Observational cohort
The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis Healthy subjects 2008 Observational study

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