Aberrant Metabolic Patterns Networks in Insular Epilepsy

Baotian Zhao; Caio Seguin; Lin Ai; Tao Sun; Wenhan Hu; Chao Zhang; Xiu Wang; Chang Liu; Yao Wang; Jiajie Mo; Andrew Zalesky; Kai Zhang; Jianguo Zhang

doi:10.3389/fneur.2020.605256

Aberrant Metabolic Patterns Networks in Insular Epilepsy

Front Neurol. 2020 Dec 23:11:605256. doi: 10.3389/fneur.2020.605256. eCollection 2020.

Authors

Baotian Zhao^{1

2}, Caio Seguin³, Lin Ai⁴, Tao Sun⁵, Wenhan Hu^{1

2}, Chao Zhang^{1

2}, Xiu Wang^{1

2}, Chang Liu^{1

2}, Yao Wang^{1

2}, Jiajie Mo^{1

2}, Andrew Zalesky^{3

6}, Kai Zhang^{1

2}, Jianguo Zhang^{1

2}

Affiliations

¹ Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
² China National Clinical Research Center for Neurological Diseases, Beijing, China.
³ Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.
⁴ Department of Imaging and Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
⁵ Department of Neurosurgery, General Hospital of Ningxia Medical University, Yinchuan, China.
⁶ Department of Biomedical Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, VIC, Australia.

Abstract

Introduction: Insular epilepsy is clinically challenging. This study aimed to map cerebral metabolic networks in insular epilepsy and investigate their graph-theoretic properties, with the goal of elucidating altered metabolic network architectures that underlie interictal hypometabolism. Aims: Fluorine-18-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG-PET) imaging was performed in 17 individuals with a stereoelectroencephalography (SEEG) confirmed diagnosis of insula epilepsy and 14 age- and sex-matched healthy comparison individuals. Metabolic covariance networks were mapped for each group and graph theoretical analyses of these networks were undertaken. For each pair of regions comprising a whole-brain parcellation, regionally-averaged FDG uptake values were correlated across individuals to estimate connection weights. Results: Correlation in regionally-averaged FDG uptake values in the insular epilepsy group was substantially increased for several pairs of regions compared to the healthy comparison group, particularly for the opercular cortex and subcortical structures. This effect was less prominent in brainstem structures. Metabolic covariance networks in the epilepsy group showed reduced small-worldness as well as altered nodal properties in the ipsilateral hemisphere, compared to the healthy comparison group. Conclusions: Cerebral glucose metabolism in insular epilepsy is marked by a lack of normal regional heterogeneity in metabolic patterns, resulting in metabolic covariance networks that are more tightly coupled between regions than healthy comparison individuals. Metabolic networks in insular epilepsy exhibit altered topological properties and evidence of potentially compensatory formation of aberrant local connections. Taken together, these results demonstrate that insular epilepsy is a systemic neurological disorder with widespread disruption to cerebral metabolic networks.

Keywords: brainstem; insular epilepsy; metabolic covariance network; neocortical; subcortical.