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Analysis of brain structural covariance network in Cushing disease
Can-Xin Xu1, Linghan Kong2,3,4, Hong Jiang1
1Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Heliyon
|April 11, 2024
Summary
Cushing disease (CD) alters brain network organization, showing increased integration and segregation compared to healthy individuals. These findings illuminate the neurobiological underpinnings of CD, aiding in understanding its pathogenesis.
Area of Science:
- Neuroendocrinology
- Neuroimaging
- Graph Theory Analysis
Background:
- Cushing disease (CD) is a rare neuroendocrine disorder characterized by hypercortisolism due to pituitary adenomas.
- CD is associated with gray matter volume atrophy, but topographical organization alterations remain poorly understood.
Purpose of the Study:
- To investigate the structural covariance networks in individuals with Cushing disease using gray matter volume data.
- To analyze network properties and identify hub regions in CD patients.
Main Methods:
- Acquired high-resolution T1-weighted MRI scans from 61 CD patients and 53 healthy controls.
- Estimated gray matter volume and performed structural covariance network analysis using graph theory.
- Calculated network properties, including hub nodes based on degree centrality.
Main Results:
- Structural covariance networks in CD patients exhibited conserved small-world features, with higher global efficiency and modularity than controls.
- CD patients demonstrated increased network integration and segregation.
- Key hub nodes in CD were identified as the Short insular gyri, Anterior cingulate gyrus and sulcus, and Superior frontal gyrus.
Conclusions:
- Graph theory analysis revealed significant differences in the structural covariance network of Cushing disease patients.
- These findings offer insights into the pathogenesis of Cushing disease and its neurological impact.
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