Wen Chen, Hongru Zhao, Lingling Dai, Xing Xiong, Qifang Feng, Jun Ke, Chunhong Hu
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引用次数: 0
Abstract
Background
The high heterogeneity in vestibular migraine (VM) complicates understanding its precise pathophysiological mechanisms and identifying potential biomarkers. This study investigated the heterogeneity in VM using a newly proposed method called Individualized Differential Structural Covariance Network (IDSCN) analysis.
Methods
Structural T1-weighted MRI scans were performed on 55 patients with VM and 65 healthy controls, and an IDSCN was constructed for each patient. We studied the extent of heterogeneity in the IDSCNs, summarized the distribution of differential edges, and clustered the patients into subtypes with the shared differential edges. Imaging–clinical association analyses were conducted on both the subtype classification and the differential edges exhibiting significant inter-subtype differences.
Results
Patients with VM demonstrated notable heterogeneity in the number of significantly altered IDSCN edges, while sharing several common differential connections that were mainly distributed among the parietal, subcortical, and cerebellar regions. Two robust and distinct neuroanatomical subtypes of VM were identified, which were associated with headache frequency. The differential edge between the left paracentral lobule and right pallidum was associated with both headache frequency and occurrence.
Conclusions
These findings indicate the importance of considering individual differences in VM research and may offer insights for precise diagnosis and individualized treatment of the disease.
期刊介绍:
CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.