Metabolic Imaging of Deep Brain Stimulation in Meige Syndrome

Liu, Jiayu; Li, Lei; Li, Yuan; Wang, Qian; Liu, Ruen; Ding, Hu

doi:10.3389/fnagi.2022.848100

Cited by 3 publications

(1 citation statement)

References 35 publications

(51 reference statements)

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“…Local injection of botulinum toxin type A might bring about a dependency effect and possible facial paralysis [6]. Deep brain stimulation surgery is also a relatively effective treatment option for patients with ineffective responses to drug treatment [7]. However, surgical treatment is not effective.…”

Section: Introductionmentioning

confidence: 99%

Higher betweenness and degree centrality in the frontal and cerebellum cortex of Meige’s syndrome patients than hemifacial spasm patients

et al. 2022

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Meige’s syndrome and hemifacial spasm (HFS) are two different forms of dystonic movement disorder, but their difference in terms of resting state functional connectivity (rsFC) remains unclear. The present study applied resting state fMRI on the patients and quantified their functional connectivity with graph theoretical measures, including the degree centrality and the betweenness centrality. Fifteen Meige’s syndrome patients and 19 HFS patients matched in age and gender were recruited and their MRI data were collected. To analyze the rsFC, we adopted the Anatomical Automatic Labeling (AAL) template, a brain atlas system including 90 regions of interest (ROIs) covering all the brain regions of cerebral cortex. For each participant, the time-course of each ROI was extracted, and the corresponding degree centrality and betweenness centrality of each ROI were computed. These measures were then compared between the Meige’s syndrome patients and the HFS patients. Meige’s syndrome patients showed higher betweenness centrality and degree centrality of bilateral superior medial frontal cortex, the left cerebellum cortex, etc. than the HFS patients. Our results suggest that the rsFC pattern in Meige’s syndrome patients might become more centralized toward the prefrontal and vestibular cerebellar systems, indicating less flexibility in their functional connections. These results preliminarily revealed the characteristic abnormality in the functional connection of Meige’s patients and may help to explore better treatment.

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Section: Introductionmentioning

confidence: 99%

Higher betweenness and degree centrality in the frontal and cerebellum cortex of Meige’s syndrome patients than hemifacial spasm patients

et al. 2022

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Closed-Loop Reinforcement Learning Based Deep Brain Stimulation Using SpikerNet: A Computational Model

Coventry

Bartlett

2023

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)

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Development and Validation of a Nomogram Based on Inflammatory Markers for Risk Prediction in Meige Syndrome Patients

Fu,

Lian,

Zhang

et al. 2024

JIR

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Purpose Inflammatory markers are known to be associated with many diseases, but their role in Meige syndrome (MS) remains unclear. This study aimed to develop and validate a nomogram for the risk prediction of MS based on inflammatory markers. Patient Data and Methods Data from 448 consecutive patients with MS at the Third People’s Hospital of Henan Province between January 2022 and December 2023 were retrospectively reviewed. The MS cohort was randomly divided into separate training and validation sets. A nomogram was constructed using a multivariate logistic regression model based on data from the training set. The model’s performance was validated through cross-validation, receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA). Results A total of five predictors, including red blood cell distribution width (RDW), hemoglobin (HGB), high-density lipoprotein cholesterol (HDL-C), the lymphocyte-to-monocyte ratio (LMR), and the systemic immune‐inflammation index (SII), were identified using multivariate logistic regression from a total of 11 variables. The cross-validation results indicated the stability of the model constructed with the above five predictors. The model showed moderate predictive ability, with an area under the ROC curve of 0.767 in the training set and 0.735 in the validation set. The calibration curve and DCA results indicate that the model has strong consistency and significant potential for clinical application. Conclusion We constructed a nomogram based on five risk predictors, RDW, HGB, HDL-C, the LMR and the SII, to predict MS and enhance the predictive accuracy for identifying MS risk.

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Metabolic Imaging of Deep Brain Stimulation in Meige Syndrome

Cited by 3 publications

References 35 publications

Higher betweenness and degree centrality in the frontal and cerebellum cortex of Meige’s syndrome patients than hemifacial spasm patients

Higher betweenness and degree centrality in the frontal and cerebellum cortex of Meige’s syndrome patients than hemifacial spasm patients

Closed-Loop Reinforcement Learning Based Deep Brain Stimulation Using SpikerNet: A Computational Model

Development and Validation of a Nomogram Based on Inflammatory Markers for Risk Prediction in Meige Syndrome Patients

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