Analysis of brain structural covariance network in Cushing disease.

BACKGROUND: Cushing disease (CD) is a rare clinical neuroendocrine disease. CD is characterized by abnormal hypercortisolism induced by a pituitary adenoma with the secretion of adrenocorticotropic hormone. Individuals with CD usually exhibit atrophy of gray matter volume. However, little is known about the alterations in topographical organization of individuals with CD. This study aimed to investigate the structural covariance networks of individuals with CD based on the gray matter volume using graph theory analysis.

METHODS: High-resolution T1-weighted images of 61 individuals with CD and 53 healthy controls were obtained. Gray matter volume was estimated and the structural covariance network was analyzed using graph theory. Network properties such as hubs of all participants were calculated based on degree centrality.

RESULTS: No significant differences were observed between individuals with CD and healthy controls in terms of age, gender, and education level. The small-world features were conserved in individuals with CD but were higher than those in healthy controls. The individuals with CD showed higher global efficiency and modularity, suggesting higher integration and segregation as compared to healthy controls. The hub nodes of the individuals with CD were Short insular gyri (G_insular_short_L), Anterior part of the cingulate gyrus and sulcus (G_and_S_cingul-Ant_R), and Superior frontal gyrus (G_front_sup_R).

CONCLUSIONS: Significant differences in the structural covariance network of patients with CD were found based on graph theory. These findings might help understanding the pathogenesis of individuals with CD and provide insight into the pathogenesis of this CD.