Characterizing White Matter and Structural Brain Network Alterations in Children with Growth Hormone Deficiency Using Diffusion Tensor Imaging
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Published on: September 12, 2011
Xuewen Wang1, Hui Tan1, Donglong Lin2
1Department of Radiology, the Second Affiliated Hospital of Shantou University Medical College, Shantou 515041, Guangdong, China.
Purpose:
To characterize white matter microstructure and structural brain network topology in children with growth hormone deficiency (GHD) using diffusion tensor imaging and explore their associations with clinical indicators.
Methods:
A total of 77 short-stature children (GHD = 50, idiopathic short stature [ISS] = 27) and 40 healthy controls (HC) underwent 3D-T1WI and DTI. Nineteen participants were excluded due to poor data quality (10 in the GHD group, 4 in the ISS group, and 5 in the HC group), yielding a final analytical cohort of 40 children with GHD, 23 with ISS, and 35 healthy controls. Tract-Based Spatial Statistics and graph-theoretical analysis were applied to characterize white matter microstructure and network topological properties. Clinical metrics including bone age and pituitary volume were collected.
Results:
Children with GHD showed reduced fractional anisotropy together with elevated mean and radial diffusivity relative to controls. Children with ISS showed elevated mean and radial diffusivity without a reduction in fractional anisotropy, and their diffusivity elevations exceeded those observed in the GHD group. Graph-theoretical analysis revealed that the GHD group had significantly higher global efficiency and lower characteristic path length than the HC group, as well as lower clustering coefficient than the ISS group. Rich-club findings were contingent on both the method used to define core nodes and the connection retention thresholds applied to backbone networks. Nodal analysis identified significantly higher betweenness centrality of the left insula in ISS compared with both the GHD and HC groups. Significant associations were observed between white matter microstructural properties, network connectivity, and clinical variables, including age, bone age, and bone age delay.
Conclusion:
Children with GHD exhibit altered white matter microstructure and global organization of the structural brain network, which differed from the pattern observed in ISS, and these imaging measures were associated with age, bone age, and bone age delay; given the cross-sectional design, causal inference remains unwarranted.
