Altered Structural Brain Network Topology in Patients With Primary Craniocervical Dystonia

Xiu Wang; Wenhan Hu; Huimin Wang; Dongmei Gao; Yuye Liu; Xin Zhang; Yin Jiang; Jiajie Mo; Fangang Meng; Kai Zhang; Jian-Guo Zhang

doi:10.3389/fneur.2022.763305

Altered Structural Brain Network Topology in Patients With Primary Craniocervical Dystonia

Front Neurol. 2022 Mar 30:13:763305. doi: 10.3389/fneur.2022.763305. eCollection 2022.

Authors

Xiu Wang^{1

2}, Wenhan Hu^{2

3}, Huimin Wang^{2

4}, Dongmei Gao^{1

2}, Yuye Liu^{1

2}, Xin Zhang^{2

3}, Yin Jiang^{2

3}, Jiajie Mo^{1

2}, Fangang Meng^{2

3}, Kai Zhang^{1

2}, Jian-Guo Zhang^{1

2

3}

Affiliations

¹ Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China.
² Beijing Key Laboratory of Neurostimulation, Beijing, China.
³ Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
⁴ Department of Functional Neurosurgery, Medical Alliance of Beijing Tian Tan Hospital, Peking University First Hospital Fengtai Hospital, Beijing, China.

Abstract

Purpose: Regional cortical thickness or volume analyses based upon structural MRI scans have been employed to study the pathophysiology of primary craniocervical dystonia (CCD). In the present study, brain connectivity network analyses based upon morphological distribution similarities among different brain areas were used to study the network disruption in individuals affected by CCD.

Methods: The T1 MRI scans were completed for 37 patients with CCD and 30 healthy controls, with individual brain structural networks being constructed based upon gray matter (GM) similarities in 90 regions within the brain. Area under the curve (AUC) values for each network parameter were determined, and the GRETNA program was used to conduct a graph theory-based measurement of nodal and global network properties. These properties were then compared between healthy controls and those with CCD. In addition, relationships between nodal properties and the severity of clinical dystonia were assessed through Spearman's correlation analyses.

Results: Relative to individuals in the control group, patients with CCD exhibited decreased local nodal properties in the right globus pallidus, right middle frontal gyrus, and right superior temporal pole. The degree of centrality as well as the node efficiency of the right globus pallidus were found to be significantly correlated with ocular dystonic symptom. The node efficiency of right middle frontal gyrus was significantly related to the total motor severity. No nodal properties were significantly correlated with oral dystonic motor scores. Among CCD patients, the right hemisphere exhibited more widespread decreases in connectivity associated with the motor related brain areas, associative cortex, and limbic system, particularly in the middle frontal gyrus, globus pallidus, and cingulate gyrus.

Conclusions: The assessment of morphological correlations between different areas in the brain may represent a sensitive approach for detecting alterations in brain structures and to understand the mechanistic basis for CCD at the network level. Based on the nodal properties identified in this study, the right middle frontal gyrus and globus pallidus were the most severely affected in patients with CCD. The widespread alterations in morphological connectivity, such as the cortico-cortical and cortico-subcortical networks, further support the network mechanism as a basis for CCD.

Keywords: morphological connectivity; network connectivity; primary craniocervical dystonia; similarity; structural MRI.