TY - JOUR
T1 - Callosal and subcortical white matter alterations in schizophrenia
T2 - A diffusion tensor imaging study at multiple levels
AU - Zhao, Wei
AU - Guo, Shuixia
AU - He, Ningning
AU - Yang, Albert C.
AU - Lin, Ching Po
AU - Tsai, Shih Jen
N1 - Publisher Copyright:
© 2018 The Authors
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Diffusion tensor imaging and its distinct capability to detect micro-structural changes in vivo allows the exploration of white matter (WM) abnormalities in patients who have been diagnosed with schizophrenia; however, the results regarding the anatomical positions and degree of abnormalities are inconsistent. In order to obtain more robust and stable findings, we conducted a multi-level analysis to investigate WM disruption in a relatively large sample size (142 schizophrenia patients and 163 healthy subjects). Specifically, we evaluated the univariate fractional anisotropy (FA) in voxel level; the bivariate pairwise structural connectivity between regions using deterministic tractography as the network node defined by the Human Brainnetome Atlas; and the multivariate network topological properties, including the network hub, efficiency, small-worldness, and strength. Our data demonstrated callosal and subcortical WM alterations in patients with schizophrenia. These disruptions were evident in both voxel and connectivity levels and further supported by associations between FA values and illness duration. Based on the findings regarding topological properties, the structural network showed weaker global integration in patients with schizophrenia than in healthy subjects, while brain network hubs showed decreased functionality. We replicated these findings using an automated anatomical labeling atlas to define the network node. Our study indicates that callosal and subcortical WM disruptions are biomarkers for chronic schizophrenia.
AB - Diffusion tensor imaging and its distinct capability to detect micro-structural changes in vivo allows the exploration of white matter (WM) abnormalities in patients who have been diagnosed with schizophrenia; however, the results regarding the anatomical positions and degree of abnormalities are inconsistent. In order to obtain more robust and stable findings, we conducted a multi-level analysis to investigate WM disruption in a relatively large sample size (142 schizophrenia patients and 163 healthy subjects). Specifically, we evaluated the univariate fractional anisotropy (FA) in voxel level; the bivariate pairwise structural connectivity between regions using deterministic tractography as the network node defined by the Human Brainnetome Atlas; and the multivariate network topological properties, including the network hub, efficiency, small-worldness, and strength. Our data demonstrated callosal and subcortical WM alterations in patients with schizophrenia. These disruptions were evident in both voxel and connectivity levels and further supported by associations between FA values and illness duration. Based on the findings regarding topological properties, the structural network showed weaker global integration in patients with schizophrenia than in healthy subjects, while brain network hubs showed decreased functionality. We replicated these findings using an automated anatomical labeling atlas to define the network node. Our study indicates that callosal and subcortical WM disruptions are biomarkers for chronic schizophrenia.
KW - Diffusion tensor imaging
KW - Fractional anisotropy
KW - Schizophrenia
KW - Structural network
KW - White matter
UR - http://www.scopus.com/inward/record.url?scp=85052468292&partnerID=8YFLogxK
U2 - 10.1016/j.nicl.2018.08.027
DO - 10.1016/j.nicl.2018.08.027
M3 - Article
C2 - 30186763
AN - SCOPUS:85052468292
SN - 2213-1582
VL - 20
SP - 594
EP - 602
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
ER -